notebook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "39a27611",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:12.108786Z",
     "start_time": "2022-05-24T08:22:08.368734Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython.display import display\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a2bffcdb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:12.592839Z",
     "start_time": "2022-05-24T08:22:12.111928Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.metrics import mutual_info_score\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.metrics import roc_curve"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99d6bdea",
   "metadata": {},
   "source": [
    "#  1. Initial data cleaning procedures"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b33b2311",
   "metadata": {},
   "source": [
    "## 1.1 Normalizing strings on initial data load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2095d3f2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:12.610896Z",
     "start_time": "2022-05-24T08:22:12.602870Z"
    }
   },
   "outputs": [],
   "source": [
    "def load_dataset(filename):\n",
    "    df = pd.read_csv(filename)\n",
    "    df.columns = df.columns.str.lower().str.replace(' ', '_', regex=False)\n",
    "    string_columns = list(df.dtypes[df.dtypes == 'object'].index)\n",
    "    numerical_columns = list(df.dtypes[df.dtypes != 'object'].index)\n",
    "    \n",
    "    for col in string_columns:\n",
    "        df[col] = df[col].str.lower().str.replace(' ', '_', regex=False)\n",
    "    \n",
    "    df.asymmetrique_activity_index = df.asymmetrique_activity_index.str.split('.', n = 1, expand = True)[1]\n",
    "    df.asymmetrique_profile_index = df.asymmetrique_profile_index.str.split('.', n = 1, expand = True)[1]\n",
    "    \n",
    "    return df, string_columns, numerical_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2fc7455c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.172611Z",
     "start_time": "2022-05-24T08:22:12.614741Z"
    }
   },
   "outputs": [],
   "source": [
    "df, string_columns, numerical_columns = load_dataset('leads.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da3f78eb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.199693Z",
     "start_time": "2022-05-24T08:22:13.175259Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>prospect_id</th>\n",
       "      <td>7927b2df-8bba-4d29-b9a2-b6e0beafe620</td>\n",
       "      <td>2a272436-5132-4136-86fa-dcc88c88f482</td>\n",
       "      <td>8cc8c611-a219-4f35-ad23-fdfd2656bd8a</td>\n",
       "      <td>0cc2df48-7cf4-4e39-9de9-19797f9b38cc</td>\n",
       "      <td>3256f628-e534-4826-9d63-4a8b88782852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_number</th>\n",
       "      <td>660737</td>\n",
       "      <td>660728</td>\n",
       "      <td>660727</td>\n",
       "      <td>660719</td>\n",
       "      <td>660681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_origin</th>\n",
       "      <td>api</td>\n",
       "      <td>api</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_source</th>\n",
       "      <td>olark_chat</td>\n",
       "      <td>organic_search</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>google</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_email</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_call</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>converted</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalvisits</th>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_time_spent_on_website</th>\n",
       "      <td>0</td>\n",
       "      <td>674</td>\n",
       "      <td>1532</td>\n",
       "      <td>305</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_views_per_visit</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_activity</th>\n",
       "      <td>page_visited_on_website</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>unreachable</td>\n",
       "      <td>converted_to_lead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <td>NaN</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>specialization</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>business_administration</td>\n",
       "      <td>media_and_advertising</td>\n",
       "      <td>select</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>how_did_you_hear_about_x_education</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>word_of_mouth</td>\n",
       "      <td>other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_is_your_current_occupation</th>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>student</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_matters_most_to_you_in_choosing_a_course</th>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>search</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>magazine</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper_article</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x_education_forums</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>digital_advertisement</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>through_recommendations</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>receive_more_updates_about_our_courses</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>interested_in_other_courses</td>\n",
       "      <td>ringing</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>ringing</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_quality</th>\n",
       "      <td>low_in_relevance</td>\n",
       "      <td>NaN</td>\n",
       "      <td>might_be</td>\n",
       "      <td>not_sure</td>\n",
       "      <td>might_be</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>update_me_on_supply_chain_content</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>get_updates_on_dm_content</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_profile</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_activity_index</th>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_profile_index</th>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_activity_score</th>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_profile_score</th>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i_agree_to_pay_the_amount_through_cheque</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a_free_copy_of_mastering_the_interview</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_notable_activity</th>\n",
       "      <td>modified</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>modified</td>\n",
       "      <td>modified</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                  0  \\\n",
       "prospect_id                                    7927b2df-8bba-4d29-b9a2-b6e0beafe620   \n",
       "lead_number                                                                  660737   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                              olark_chat   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                         0   \n",
       "totalvisits                                                                     0.0   \n",
       "total_time_spent_on_website                                                       0   \n",
       "page_views_per_visit                                                            0.0   \n",
       "last_activity                                               page_visited_on_website   \n",
       "country                                                                         NaN   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "magazine                                                                         no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "receive_more_updates_about_our_courses                                           no   \n",
       "tags                                                    interested_in_other_courses   \n",
       "lead_quality                                                       low_in_relevance   \n",
       "update_me_on_supply_chain_content                                                no   \n",
       "get_updates_on_dm_content                                                        no   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         select   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "i_agree_to_pay_the_amount_through_cheque                                         no   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                                  1  \\\n",
       "prospect_id                                    2a272436-5132-4136-86fa-dcc88c88f482   \n",
       "lead_number                                                                  660728   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                          organic_search   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                         0   \n",
       "totalvisits                                                                     5.0   \n",
       "total_time_spent_on_website                                                     674   \n",
       "page_views_per_visit                                                            2.5   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "magazine                                                                         no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "receive_more_updates_about_our_courses                                           no   \n",
       "tags                                                                        ringing   \n",
       "lead_quality                                                                    NaN   \n",
       "update_me_on_supply_chain_content                                                no   \n",
       "get_updates_on_dm_content                                                        no   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         select   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "i_agree_to_pay_the_amount_through_cheque                                         no   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                                  2  \\\n",
       "prospect_id                                    8cc8c611-a219-4f35-ad23-fdfd2656bd8a   \n",
       "lead_number                                                                  660727   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                         1   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                    1532   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                              business_administration   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                             student   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "magazine                                                                         no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "receive_more_updates_about_our_courses                                           no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "update_me_on_supply_chain_content                                                no   \n",
       "get_updates_on_dm_content                                                        no   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "i_agree_to_pay_the_amount_through_cheque                                         no   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                                  3  \\\n",
       "prospect_id                                    0cc2df48-7cf4-4e39-9de9-19797f9b38cc   \n",
       "lead_number                                                                  660719   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                         0   \n",
       "totalvisits                                                                     1.0   \n",
       "total_time_spent_on_website                                                     305   \n",
       "page_views_per_visit                                                            1.0   \n",
       "last_activity                                                           unreachable   \n",
       "country                                                                       india   \n",
       "specialization                                                media_and_advertising   \n",
       "how_did_you_hear_about_x_education                                    word_of_mouth   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "magazine                                                                         no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "receive_more_updates_about_our_courses                                           no   \n",
       "tags                                                                        ringing   \n",
       "lead_quality                                                               not_sure   \n",
       "update_me_on_supply_chain_content                                                no   \n",
       "get_updates_on_dm_content                                                        no   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    13.0   \n",
       "asymmetrique_profile_score                                                     17.0   \n",
       "i_agree_to_pay_the_amount_through_cheque                                         no   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                                  4  \n",
       "prospect_id                                    3256f628-e534-4826-9d63-4a8b88782852  \n",
       "lead_number                                                                  660681  \n",
       "lead_origin                                                 landing_page_submission  \n",
       "lead_source                                                                  google  \n",
       "do_not_email                                                                     no  \n",
       "do_not_call                                                                      no  \n",
       "converted                                                                         1  \n",
       "totalvisits                                                                     2.0  \n",
       "total_time_spent_on_website                                                    1428  \n",
       "page_views_per_visit                                                            1.0  \n",
       "last_activity                                                     converted_to_lead  \n",
       "country                                                                       india  \n",
       "specialization                                                               select  \n",
       "how_did_you_hear_about_x_education                                            other  \n",
       "what_is_your_current_occupation                                          unemployed  \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects  \n",
       "search                                                                           no  \n",
       "magazine                                                                         no  \n",
       "newspaper_article                                                                no  \n",
       "x_education_forums                                                               no  \n",
       "newspaper                                                                        no  \n",
       "digital_advertisement                                                            no  \n",
       "through_recommendations                                                          no  \n",
       "receive_more_updates_about_our_courses                                           no  \n",
       "tags                                            will_revert_after_reading_the_email  \n",
       "lead_quality                                                               might_be  \n",
       "update_me_on_supply_chain_content                                                no  \n",
       "get_updates_on_dm_content                                                        no  \n",
       "lead_profile                                                                 select  \n",
       "city                                                                         mumbai  \n",
       "asymmetrique_activity_index                                                  medium  \n",
       "asymmetrique_profile_index                                                     high  \n",
       "asymmetrique_activity_score                                                    15.0  \n",
       "asymmetrique_profile_score                                                     18.0  \n",
       "i_agree_to_pay_the_amount_through_cheque                                         no  \n",
       "a_free_copy_of_mastering_the_interview                                           no  \n",
       "last_notable_activity                                                      modified  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "88f93c3f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.236826Z",
     "start_time": "2022-05-24T08:22:13.209167Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9240, 37)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "093a035d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.249730Z",
     "start_time": "2022-05-24T08:22:13.239880Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prospect_id                                       object\n",
       "lead_number                                        int64\n",
       "lead_origin                                       object\n",
       "lead_source                                       object\n",
       "do_not_email                                      object\n",
       "do_not_call                                       object\n",
       "converted                                          int64\n",
       "totalvisits                                      float64\n",
       "total_time_spent_on_website                        int64\n",
       "page_views_per_visit                             float64\n",
       "last_activity                                     object\n",
       "country                                           object\n",
       "specialization                                    object\n",
       "how_did_you_hear_about_x_education                object\n",
       "what_is_your_current_occupation                   object\n",
       "what_matters_most_to_you_in_choosing_a_course     object\n",
       "search                                            object\n",
       "magazine                                          object\n",
       "newspaper_article                                 object\n",
       "x_education_forums                                object\n",
       "newspaper                                         object\n",
       "digital_advertisement                             object\n",
       "through_recommendations                           object\n",
       "receive_more_updates_about_our_courses            object\n",
       "tags                                              object\n",
       "lead_quality                                      object\n",
       "update_me_on_supply_chain_content                 object\n",
       "get_updates_on_dm_content                         object\n",
       "lead_profile                                      object\n",
       "city                                              object\n",
       "asymmetrique_activity_index                       object\n",
       "asymmetrique_profile_index                        object\n",
       "asymmetrique_activity_score                      float64\n",
       "asymmetrique_profile_score                       float64\n",
       "i_agree_to_pay_the_amount_through_cheque          object\n",
       "a_free_copy_of_mastering_the_interview            object\n",
       "last_notable_activity                             object\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b2b25fc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-21T21:15:14.020514Z",
     "start_time": "2022-05-21T21:15:14.016999Z"
    }
   },
   "source": [
    "## 1.2 Converting int -> float records on 'total time spent' column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8bca02c1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.260868Z",
     "start_time": "2022-05-24T08:22:13.253863Z"
    }
   },
   "outputs": [],
   "source": [
    "df.total_time_spent_on_website = df.total_time_spent_on_website.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "56616cdc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.324022Z",
     "start_time": "2022-05-24T08:22:13.266794Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9240 entries, 0 to 9239\n",
      "Data columns (total 37 columns):\n",
      " #   Column                                         Non-Null Count  Dtype  \n",
      "---  ------                                         --------------  -----  \n",
      " 0   prospect_id                                    9240 non-null   object \n",
      " 1   lead_number                                    9240 non-null   int64  \n",
      " 2   lead_origin                                    9240 non-null   object \n",
      " 3   lead_source                                    9204 non-null   object \n",
      " 4   do_not_email                                   9240 non-null   object \n",
      " 5   do_not_call                                    9240 non-null   object \n",
      " 6   converted                                      9240 non-null   int64  \n",
      " 7   totalvisits                                    9103 non-null   float64\n",
      " 8   total_time_spent_on_website                    9240 non-null   float64\n",
      " 9   page_views_per_visit                           9103 non-null   float64\n",
      " 10  last_activity                                  9137 non-null   object \n",
      " 11  country                                        6779 non-null   object \n",
      " 12  specialization                                 7802 non-null   object \n",
      " 13  how_did_you_hear_about_x_education             7033 non-null   object \n",
      " 14  what_is_your_current_occupation                6550 non-null   object \n",
      " 15  what_matters_most_to_you_in_choosing_a_course  6531 non-null   object \n",
      " 16  search                                         9240 non-null   object \n",
      " 17  magazine                                       9240 non-null   object \n",
      " 18  newspaper_article                              9240 non-null   object \n",
      " 19  x_education_forums                             9240 non-null   object \n",
      " 20  newspaper                                      9240 non-null   object \n",
      " 21  digital_advertisement                          9240 non-null   object \n",
      " 22  through_recommendations                        9240 non-null   object \n",
      " 23  receive_more_updates_about_our_courses         9240 non-null   object \n",
      " 24  tags                                           5887 non-null   object \n",
      " 25  lead_quality                                   4473 non-null   object \n",
      " 26  update_me_on_supply_chain_content              9240 non-null   object \n",
      " 27  get_updates_on_dm_content                      9240 non-null   object \n",
      " 28  lead_profile                                   6531 non-null   object \n",
      " 29  city                                           7820 non-null   object \n",
      " 30  asymmetrique_activity_index                    5022 non-null   object \n",
      " 31  asymmetrique_profile_index                     5022 non-null   object \n",
      " 32  asymmetrique_activity_score                    5022 non-null   float64\n",
      " 33  asymmetrique_profile_score                     5022 non-null   float64\n",
      " 34  i_agree_to_pay_the_amount_through_cheque       9240 non-null   object \n",
      " 35  a_free_copy_of_mastering_the_interview         9240 non-null   object \n",
      " 36  last_notable_activity                          9240 non-null   object \n",
      "dtypes: float64(5), int64(2), object(30)\n",
      "memory usage: 2.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0f89c9a1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.383532Z",
     "start_time": "2022-05-24T08:22:13.327320Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>lead_number</th>\n",
       "      <th>converted</th>\n",
       "      <th>totalvisits</th>\n",
       "      <th>total_time_spent_on_website</th>\n",
       "      <th>page_views_per_visit</th>\n",
       "      <th>asymmetrique_activity_score</th>\n",
       "      <th>asymmetrique_profile_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9240.000000</td>\n",
       "      <td>9240.000000</td>\n",
       "      <td>9103.000000</td>\n",
       "      <td>9240.000000</td>\n",
       "      <td>9103.000000</td>\n",
       "      <td>5022.000000</td>\n",
       "      <td>5022.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>617188.435606</td>\n",
       "      <td>0.385390</td>\n",
       "      <td>3.445238</td>\n",
       "      <td>487.698268</td>\n",
       "      <td>2.362820</td>\n",
       "      <td>14.306252</td>\n",
       "      <td>16.344883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>23405.995698</td>\n",
       "      <td>0.486714</td>\n",
       "      <td>4.854853</td>\n",
       "      <td>548.021466</td>\n",
       "      <td>2.161418</td>\n",
       "      <td>1.386694</td>\n",
       "      <td>1.811395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>579533.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>11.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>596484.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>615479.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>248.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>637387.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>936.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>18.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>660737.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>251.000000</td>\n",
       "      <td>2272.000000</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         lead_number    converted  totalvisits  total_time_spent_on_website  \\\n",
       "count    9240.000000  9240.000000  9103.000000                  9240.000000   \n",
       "mean   617188.435606     0.385390     3.445238                   487.698268   \n",
       "std     23405.995698     0.486714     4.854853                   548.021466   \n",
       "min    579533.000000     0.000000     0.000000                     0.000000   \n",
       "25%    596484.500000     0.000000     1.000000                    12.000000   \n",
       "50%    615479.000000     0.000000     3.000000                   248.000000   \n",
       "75%    637387.250000     1.000000     5.000000                   936.000000   \n",
       "max    660737.000000     1.000000   251.000000                  2272.000000   \n",
       "\n",
       "       page_views_per_visit  asymmetrique_activity_score  \\\n",
       "count           9103.000000                  5022.000000   \n",
       "mean               2.362820                    14.306252   \n",
       "std                2.161418                     1.386694   \n",
       "min                0.000000                     7.000000   \n",
       "25%                1.000000                    14.000000   \n",
       "50%                2.000000                    14.000000   \n",
       "75%                3.000000                    15.000000   \n",
       "max               55.000000                    18.000000   \n",
       "\n",
       "       asymmetrique_profile_score  \n",
       "count                 5022.000000  \n",
       "mean                    16.344883  \n",
       "std                      1.811395  \n",
       "min                     11.000000  \n",
       "25%                     15.000000  \n",
       "50%                     16.000000  \n",
       "75%                     18.000000  \n",
       "max                     20.000000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a0e2d71",
   "metadata": {},
   "source": [
    "## 1.3 Dealing with missing values in the DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9dfed4d1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.498824Z",
     "start_time": "2022-05-24T08:22:13.393074Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prospect_id                                         0\n",
       "lead_number                                         0\n",
       "lead_origin                                         0\n",
       "lead_source                                        36\n",
       "do_not_email                                        0\n",
       "do_not_call                                         0\n",
       "converted                                           0\n",
       "totalvisits                                       137\n",
       "total_time_spent_on_website                         0\n",
       "page_views_per_visit                              137\n",
       "last_activity                                     103\n",
       "country                                          2461\n",
       "specialization                                   1438\n",
       "how_did_you_hear_about_x_education               2207\n",
       "what_is_your_current_occupation                  2690\n",
       "what_matters_most_to_you_in_choosing_a_course    2709\n",
       "search                                              0\n",
       "magazine                                            0\n",
       "newspaper_article                                   0\n",
       "x_education_forums                                  0\n",
       "newspaper                                           0\n",
       "digital_advertisement                               0\n",
       "through_recommendations                             0\n",
       "receive_more_updates_about_our_courses              0\n",
       "tags                                             3353\n",
       "lead_quality                                     4767\n",
       "update_me_on_supply_chain_content                   0\n",
       "get_updates_on_dm_content                           0\n",
       "lead_profile                                     2709\n",
       "city                                             1420\n",
       "asymmetrique_activity_index                      4218\n",
       "asymmetrique_profile_index                       4218\n",
       "asymmetrique_activity_score                      4218\n",
       "asymmetrique_profile_score                       4218\n",
       "i_agree_to_pay_the_amount_through_cheque            0\n",
       "a_free_copy_of_mastering_the_interview              0\n",
       "last_notable_activity                               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e2c6971",
   "metadata": {},
   "source": [
    "## 1.4 Filling null values in DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3c15ab6f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.516265Z",
     "start_time": "2022-05-24T08:22:13.509238Z"
    }
   },
   "outputs": [],
   "source": [
    "def filling_null_values(df, fill_strategy, column_type):\n",
    "    imputer = SimpleImputer(strategy=fill_strategy)\n",
    "\n",
    "    for col in column_type:\n",
    "        df[col] = imputer.fit_transform(df[col].values.reshape(-1,1))[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c2deb355",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.668561Z",
     "start_time": "2022-05-24T08:22:13.519327Z"
    }
   },
   "outputs": [],
   "source": [
    "filling_null_values(df, 'most_frequent', string_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ead79557",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.683807Z",
     "start_time": "2022-05-24T08:22:13.671810Z"
    }
   },
   "outputs": [],
   "source": [
    "filling_null_values(df, 'mean', numerical_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "58c45df1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.738677Z",
     "start_time": "2022-05-24T08:22:13.686311Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prospect_id                                      0\n",
       "lead_number                                      0\n",
       "lead_origin                                      0\n",
       "lead_source                                      0\n",
       "do_not_email                                     0\n",
       "do_not_call                                      0\n",
       "converted                                        0\n",
       "totalvisits                                      0\n",
       "total_time_spent_on_website                      0\n",
       "page_views_per_visit                             0\n",
       "last_activity                                    0\n",
       "country                                          0\n",
       "specialization                                   0\n",
       "how_did_you_hear_about_x_education               0\n",
       "what_is_your_current_occupation                  0\n",
       "what_matters_most_to_you_in_choosing_a_course    0\n",
       "search                                           0\n",
       "magazine                                         0\n",
       "newspaper_article                                0\n",
       "x_education_forums                               0\n",
       "newspaper                                        0\n",
       "digital_advertisement                            0\n",
       "through_recommendations                          0\n",
       "receive_more_updates_about_our_courses           0\n",
       "tags                                             0\n",
       "lead_quality                                     0\n",
       "update_me_on_supply_chain_content                0\n",
       "get_updates_on_dm_content                        0\n",
       "lead_profile                                     0\n",
       "city                                             0\n",
       "asymmetrique_activity_index                      0\n",
       "asymmetrique_profile_index                       0\n",
       "asymmetrique_activity_score                      0\n",
       "asymmetrique_profile_score                       0\n",
       "i_agree_to_pay_the_amount_through_cheque         0\n",
       "a_free_copy_of_mastering_the_interview           0\n",
       "last_notable_activity                            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d082d6d8",
   "metadata": {},
   "source": [
    "# 2. Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bf9c9cd",
   "metadata": {},
   "source": [
    "## 2.1 Distribution of values in the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9388c6f8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.751119Z",
     "start_time": "2022-05-24T08:22:13.742752Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    5679\n",
       "1.0    3561\n",
       "Name: converted, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.converted.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "63ae40a0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.888407Z",
     "start_time": "2022-05-24T08:22:13.754220Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='converted', ylabel='count'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEGCAYAAACUzrmNAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAARvUlEQVR4nO3df7DldV3H8edL1h/lrwXZCHehZXT7gf0g2hDNGoNpWejHMg4SlbEhM9sUOTpTllYTijFpWgSWFBMrC1MBWcZWFu6AppYIu6jIj4gbSOwOuiu7okboLL7743yuHpa9+zkL95x7d+/zMXPmfL/v7+f7Pe+7c/e+5vvzpKqQJGlfnjbXDUiS5j/DQpLUZVhIkroMC0lSl2EhSepaNNcNjMPhhx9ey5cvn+s2JOmAsmXLli9U1ZK9LTsow2L58uVs3rx5rtuQpANKkvtnWuZhKElSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUtdBeQf3bPihN1451y1oHtryzrPnugVpTrhnIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdY01LJJ8NslnknwqyeZWOyzJpiT3tPdDWz1JLkkyleS2JMcPbWdtG39PkrXj7FmS9EST2LP48ao6rqpWtvk3ATdU1QrghjYPcCqwor3WAZfCIFyA84GXAicA508HjCRpMubiMNQaYEOb3gCcPlS/sgZuAhYnORI4BdhUVTurahewCVg94Z4laUEbd1gU8MEkW5Ksa7UjqurBNv054Ig2vRR4YGjdra02U/1xkqxLsjnJ5h07dszmzyBJC96iMW//FVW1Lcm3AZuS/OfwwqqqJDUbH1RVlwGXAaxcuXJWtilJGhjrnkVVbWvv24H3Mzjn8Pl2eIn2vr0N3wYcNbT6slabqS5JmpCxhUWSZyd57vQ0sAq4HdgITF/RtBa4rk1vBM5uV0WdCDzcDlddD6xKcmg7sb2q1SRJEzLOw1BHAO9PMv05f11V/5rkFuDaJOcC9wNntvEfAE4DpoBHgHMAqmpnkrcBt7RxF1TVzjH2LUnaw9jCoqruBX5gL/WHgJP3Ui/gvBm2tR5YP9s9SpJG4x3ckqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUtfYwyLJIUk+meSf2vwxST6RZCrJNUme0erPbPNTbfnyoW28udXvTnLKuHuWJD3eJPYsXg/cNTT/DuCiqnoxsAs4t9XPBXa1+kVtHEmOBc4CXgKsBt6T5JAJ9C1JasYaFkmWAT8J/GWbD3AS8L42ZANwepte0+Zpy09u49cAV1fVV6vqPmAKOGGcfUuSHm/cexZ/Avwm8PU2/wLgi1W1u81vBZa26aXAAwBt+cNt/Dfqe1nnG5KsS7I5yeYdO3bM8o8hSQvb2MIiyU8B26tqy7g+Y1hVXVZVK6tq5ZIlSybxkZK0YCwa47Z/BPiZJKcBzwKeB1wMLE6yqO09LAO2tfHbgKOArUkWAc8HHhqqTxteR5I0AWPbs6iqN1fVsqpazuAE9Y1V9QvAh4Az2rC1wHVtemObpy2/saqq1c9qV0sdA6wAbh5X35KkJxrnnsVMfgu4OsnvA58ELm/1y4GrkkwBOxkEDFV1R5JrgTuB3cB5VfXY5NuWpIVrImFRVR8GPtym72UvVzNV1aPAq2dY/0LgwvF1KEnaF+/gliR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqSuuXg2lKSn4H8u+L65bkHz0NG/95mxbt89C0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUtdIYZHkhlFqkqSD0z4f95HkWcC3AocnORRIW/Q8YOmYe5MkzRO9Z0P9MvAG4IXAFr4ZFl8C/nR8bUmS5pN9hkVVXQxcnOR1VfXuCfUkSZpnRnrqbFW9O8nLgeXD61TVlWPqS5I0j4wUFkmuAl4EfAp4rJULMCwkaQEY9fssVgLHVlWNsxlJ0vw06n0WtwPfvj8bTvKsJDcn+XSSO5K8tdWPSfKJJFNJrknyjFZ/ZpufasuXD23rza1+d5JT9qcPSdJTN2pYHA7cmeT6JBunX511vgqcVFU/ABwHrE5yIvAO4KKqejGwCzi3jT8X2NXqF7VxJDkWOAt4CbAaeE+SQ0b+CSVJT9moh6Hesr8bboesvtJmn95eBZwE/Hyrb2jbvhRYM/Q57wP+NEla/eqq+ipwX5Ip4ATg4/vbkyTpyRn1aqh/ezIbb3sAW4AXA38G/Dfwxara3YZs5Zs39y0FHmiftzvJw8ALWv2moc0OrzP8WeuAdQBHH330k2lXkjSDUR/38eUkX2qvR5M8luRLvfWq6rGqOg5YxmBv4LufWrv7/KzLqmplVa1csmTJuD5GkhakUfcsnjs9PXRo6MRRP6SqvpjkQ8DLgMVJFrW9i2XAtjZsG3AUsDXJIuD5wEND9WnD60iSJmC/nzpbA/8A7POqpCRLkixu098C/ARwF/Ah4Iw2bC1wXZve2OZpy29s5z02Ame1q6WOAVYAN+9v35KkJ2/Um/JeNTT7NAb3XTzaWe1IYEM7b/E04Nqq+qckdwJXJ/l94JPA5W385cBV7QT2TgZXQFFVdyS5FrgT2A2cV1WPIUmamFGvhvrpoendwGcZHIqaUVXdBvzgXur3Mjh/sWf9UeDVM2zrQuDCEXuVJM2yUc9ZnDPuRiRJ89eoV0MtS/L+JNvb6++SLBt3c5Kk+WHUE9zvZXCi+YXt9Y+tJklaAEYNiyVV9d6q2t1eVwDezCBJC8SoYfFQktckOaS9XsPgHghJ0gIwali8FjgT+BzwIIP7IH5pTD1JkuaZUS+dvQBYW1W7AJIcBryLQYhIkg5yo+5ZfP90UABU1U72cg+FJOngNGpYPC3JodMzbc9i1L0SSdIBbtQ/+H8EfDzJ37b5V+Md1ZK0YIx6B/eVSTYz+OIigFdV1Z3ja0uSNJ+MfCiphYMBIUkL0H4/olyStPAYFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKlrbGGR5KgkH0pyZ5I7kry+1Q9LsinJPe390FZPkkuSTCW5LcnxQ9ta28bfk2TtuHqWJO3dOPcsdgO/XlXHAicC5yU5FngTcENVrQBuaPMApwIr2msdcCkMwgU4H3gpcAJw/nTASJImY2xhUVUPVtWtbfrLwF3AUmANsKEN2wCc3qbXAFfWwE3A4iRHAqcAm6pqZ1XtAjYBq8fVtyTpiSZyziLJcuAHgU8AR1TVg23R54Aj2vRS4IGh1ba22kz1PT9jXZLNSTbv2LFjdn8ASVrgxh4WSZ4D/B3whqr60vCyqiqgZuNzquqyqlpZVSuXLFkyG5uUJDVjDYskT2cQFH9VVX/fyp9vh5do79tbfRtw1NDqy1ptprokaULGeTVUgMuBu6rqj4cWbQSmr2haC1w3VD+7XRV1IvBwO1x1PbAqyaHtxPaqVpMkTciiMW77R4BfBD6T5FOt9tvA24Frk5wL3A+c2ZZ9ADgNmAIeAc4BqKqdSd4G3NLGXVBVO8fYtyRpD2MLi6r6GJAZFp+8l/EFnDfDttYD62evO0nS/vAObklSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXWMLiyTrk2xPcvtQ7bAkm5Lc094PbfUkuSTJVJLbkhw/tM7aNv6eJGvH1a8kaWbj3LO4Ali9R+1NwA1VtQK4oc0DnAqsaK91wKUwCBfgfOClwAnA+dMBI0manLGFRVV9BNi5R3kNsKFNbwBOH6pfWQM3AYuTHAmcAmyqqp1VtQvYxBMDSJI0ZpM+Z3FEVT3Ypj8HHNGmlwIPDI3b2moz1Z8gybokm5Ns3rFjx+x2LUkL3Jyd4K6qAmoWt3dZVa2sqpVLliyZrc1Kkph8WHy+HV6ivW9v9W3AUUPjlrXaTHVJ0gRNOiw2AtNXNK0Frhuqn92uijoReLgdrroeWJXk0HZie1WrSZImaNG4Npzkb4BXAocn2crgqqa3A9cmORe4HzizDf8AcBowBTwCnANQVTuTvA24pY27oKr2PGkuSRqzsYVFVf3cDItO3svYAs6bYTvrgfWz2JokaT95B7ckqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUdcCERZLVSe5OMpXkTXPdjyQtJAdEWCQ5BPgz4FTgWODnkhw7t11J0sJxQIQFcAIwVVX3VtXXgKuBNXPckyQtGIvmuoERLQUeGJrfCrx0eECSdcC6NvuVJHdPqLeF4HDgC3PdxHyQd62d6xb0eP5uTjs/s7GV75hpwYESFl1VdRlw2Vz3cTBKsrmqVs51H9Ke/N2cnAPlMNQ24Kih+WWtJkmagAMlLG4BViQ5JskzgLOAjXPckyQtGAfEYaiq2p3k14DrgUOA9VV1xxy3tZB4eE/zlb+bE5KqmuseJEnz3IFyGEqSNIcMC0lSl2Ghb+g9UiXJM5Nc05Z/IsnyOWhTC1CS9Um2J7l9huVJckn73bwtyfGT7vFgZ1gIGPmRKucCu6rqxcBFwDsm26UWsCuA1ftYfiqwor3WAZdOoKcFxbDQtFEeqbIG2NCm3wecnGRWbhuV9qWqPgLs3MeQNcCVNXATsDjJkZPpbmEwLDRtb49UWTrTmKraDTwMvGAi3Un7Nsrvr54Cw0KS1GVYaNooj1T5xpgki4DnAw9NpDtp33wk0JgZFpo2yiNVNgLTj109A7ixvKtT88NG4Ox2VdSJwMNV9eBcN3UwOSAe96Hxm+mRKkkuADZX1UbgcuCqJFMMTjaeNXcdayFJ8jfAK4HDk2wFzgeeDlBVfw58ADgNmAIeAc6Zm04PXj7uQ5LU5WEoSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRbSPJNkcZJffRLrvSXJb4yjJ8mwkOaRdmf8YmC/w0IaJ8NC2kOSs9t3Inw6yVVJlie5sdVuSHJ0G3dF+w6F/0hyb5IzWv3qJD85tL0rkpyR5JAk70xyS9vWL7flr0zy0SQbgTuBtwMvSvKpJO9sY944tN5bh7b9O0n+K8nHgO+a3L+SFhrv4JaGJHkJ8LvAy6vqC0kOY/BY9g1VtSHJa4FLgNPbKkcCrwC+m8EjJ94HXAOcCfxze3TKycCvMPg+kIer6oeTPBP49yQfbNs5HvjeqrqvfanU91bVca2nVQy+p+EEIMDGJD8G/C+Du+iPY/B/+VZgyzj+XSTDQnq8k4C/raovAFTVziQvA17Vll8F/OHQ+H+oqq8DdyY5otX+Bbi4BcJq4CNV9X/tj/73T++BMHgQ4wrga8DNVXXfDD2taq9PtvnntPWeC7y/qh4BaHsm0lgYFtJT89Wh6QBU1aNJPgycAvwsgy+Sml7+uqq6fngDSV7JYC9hJgH+oKr+Yo/13vAU+pb2i+cspMe7EXh1khcAtMNQ/8E3H5r4C8BHR9jONQweZvejwL+22vXAryR5etv2dyZ59l7W/TKDvQaG1nttkue09ZYm+TbgI8DpSb4lyXOBnx79x5T2j3sW0pD2pN0LgX9L8hiDQz+vA96b5I3ADkZ7oukHGRyyuq59TS3AXwLLgVvb19Hu4JvnPoZ7eCjJvye5HfiXqnpjku8BPt6+xfYrwGuq6tYk1wCfBrYzeMy8NBY+dVaS1OVhKElSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1PX/+72S0LCZysIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"converted\", data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4efdcfc0",
   "metadata": {},
   "source": [
    "## 2.2 Global lead convertion rate"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a8204f6",
   "metadata": {},
   "source": [
    "### 2.2.1 We can see that the data set is unbalanced, because the distribution of leads that converted and that who didn't are different. Non-converted lead class dominates converted lead class and it's about 1.6 times higher"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "77e6d821",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.912238Z",
     "start_time": "2022-05-24T08:22:13.897009Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.39"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_mean = df.converted.mean()\n",
    "round(global_mean,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0b02773f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.943752Z",
     "start_time": "2022-05-24T08:22:13.920455Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.61, 1.564102564102564)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imbalance_ratio = 1 - round(global_mean,2) \n",
    "imbalance_percentage = imbalance_ratio / round(global_mean,2)\n",
    "\n",
    "imbalance_ratio, imbalance_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4c8930aa",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:13.986630Z",
     "start_time": "2022-05-24T08:22:13.946839Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "prospect_id                                      9240\n",
       "lead_number                                      9240\n",
       "lead_origin                                         5\n",
       "lead_source                                        20\n",
       "do_not_email                                        2\n",
       "do_not_call                                         2\n",
       "converted                                           2\n",
       "totalvisits                                        42\n",
       "total_time_spent_on_website                      1731\n",
       "page_views_per_visit                              115\n",
       "last_activity                                      17\n",
       "country                                            38\n",
       "specialization                                     19\n",
       "how_did_you_hear_about_x_education                 10\n",
       "what_is_your_current_occupation                     6\n",
       "what_matters_most_to_you_in_choosing_a_course       3\n",
       "search                                              2\n",
       "magazine                                            1\n",
       "newspaper_article                                   2\n",
       "x_education_forums                                  2\n",
       "newspaper                                           2\n",
       "digital_advertisement                               2\n",
       "through_recommendations                             2\n",
       "receive_more_updates_about_our_courses              1\n",
       "tags                                               26\n",
       "lead_quality                                        5\n",
       "update_me_on_supply_chain_content                   1\n",
       "get_updates_on_dm_content                           1\n",
       "lead_profile                                        6\n",
       "city                                                7\n",
       "asymmetrique_activity_index                         3\n",
       "asymmetrique_profile_index                          3\n",
       "asymmetrique_activity_score                        13\n",
       "asymmetrique_profile_score                         11\n",
       "i_agree_to_pay_the_amount_through_cheque            1\n",
       "a_free_copy_of_mastering_the_interview              2\n",
       "last_notable_activity                              16\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "94c63865",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:14.000803Z",
     "start_time": "2022-05-24T08:22:13.990119Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mumbai                         4642\n",
       "select                         2249\n",
       "thane_&_outskirts               752\n",
       "other_cities                    686\n",
       "other_cities_of_maharashtra     457\n",
       "other_metro_cities              380\n",
       "tier_ii_cities                   74\n",
       "Name: city, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.city.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f3048b4c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:14.270804Z",
     "start_time": "2022-05-24T08:22:14.005013Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lsLv/KcmF1xg+PMmJw+MTkzxq3fire+YjSW5ZVbdN8tAk7+7uC7v7K0nenf9cLAEAANhOG31P4G26+4vD439Lcpvh8T5J/nXd8z4/jF3bOAAAADfCaAvDdHcn6Xl9v6o6qqq2VtXWCy64YF7fFgAAYKVsdAn892GaZ4bPXxrGz0+y37rn7TuMXdv4f9LdL+/uQ7r7kC1btsw9OAAAwCrY6BJ4UpK1FT6PSPLWdeNPHFYJPSzJRcO00XcleUhV7TUsCPOQYQwAAIAbYZdFfeOqen2SByTZu6o+n9kqny9K8saqOjLJ55I8dnj6O5L8eJLzknwjyZOTpLsvrKrfTfKx4Xm/093XXGwGAACA7bSwEtjdj7uWUw/axnM7ydOv5fu8Mskr5xgNAABgskZbGAYAAICNpwQCAABMiBIIAAAwIUogAADAhCiBAAAAE6IEAgAATIgSCAAAMCFKIAAAwIQogQAAABOiBAIAAEyIEggAADAhSiAAAMCE7DJ2AIAb6/lbjx47wqT99iHHjR0BALgRXAkEAACYECUQAABgQpRAAACACXFPIACw4Y7+q61jR5is455yyNgRgJG5EggAADAhSiAAAMCEKIEAAAATogQCAABMiBIIAAAwIUogAADAhCiBAAAAE6IEAgAATIgSCAAAMCFKIAAAwIQogQAAABOiBAIAAEyIEggAADAhSiAAAMCE7DJ2AAAAVscfHr117AiT9ivHHTJ2BJaAK4EAAAATogQCAABMiBIIAAAwIUogAADAhFgYBoBN6eitrx87wqQdd8jjxo4AwIK4EggAADAhSiAAAMCEKIEAAAATogQCAABMiBIIAAAwIUogAADAhCiBAAAAE6IEAgAATIgSCAAAMCFKIAAAwIQogQAAABOiBAIAAEyIEggAADAhSiAAAMCEKIEAAAATogQCAABMiBIIAAAwIUogAADAhCiBAAAAE6IEAgAATMguYwcAAACWw9aj3zl2hMk65LiHze17Lc2VwKp6WFWdW1XnVdVzx84DAACwjJaiBFbVzkn+PMnDkxyU5HFVddC4qQAAAJbPUpTAJIcmOa+7P93dlyf5mySHj5wJAABg6SxLCdwnyb+uO/78MAYAAMANUN09dobrVVWPTvKw7v7F4fgJSe7d3f913XOOSnLUcHinJOdueNDx7J3kP8YOwcJ4fVeX13a1eX1Xl9d2tXl9V9uUXt87dPeWbZ1YltVBz0+y37rjfYex7+julyd5+UaG2iyqamt3HzJ2DhbD67u6vLarzeu7ury2q83ru9q8vjPLMh30Y0kOrKo7VtVuSX42yUkjZwIAAFg6S3ElsLuvqKr/muRdSXZO8sruPnvkWAAAAEtnKUpgknT3O5K8Y+wcm9Qkp8FOiNd3dXltV5vXd3V5bVeb13e1eX2zJAvDAAAAMB/Lck8gAAAAc6AEAgAATIgSCAAAMCFK4JKqqmO2ZwzYXKrqflV18+Hx46vqJVV1h7FzAdetqg6oqpsMjx9QVc+sqluOHAvgRlECl9cR2xh70kaHYL6q6gPD54ur6mvrPi6uqq+NnY+5+Msk36iquyf5b0k+leTV40ZiXqrqD6pqz6ratareU1UXVNXjx87FXLw5yZVV9X2ZrS64X5K/HjcS81JVh1XVx6rq61V1eVVd6f/d1VBVj6mqPYbHv1FVb6mqg8fONTYlcMlU1eOq6m1J7lhVJ637eG+SC8fOx47p7vsPn/fo7j3XfezR3XuOnY+5uKJnyzIfnuTPuvvPk+wxcibm5yHd/bUk/yXJZ5N8X5JfGTUR8/Lt7r4iyU8mOba7fyXJbUfOxPz8WZLHJflkkpsm+cUkfz5qIublN7v74qq6f5IfS3J8Zm/ITtrS7BPId3woyReT7J3kj9eNX5zkzFESsTBV9d1Jdl877u7/N2Ic5uPiqnpekscn+eGq2inJriNnYn7W/l99RJI3dfdFVTVmHubnW1X1uMxm4vzEMObf7grp7vOqaufuvjLJCVV1epLnjZ2LHXbl8PkRSV7e3f+nqn5vzECbgRK4ZLr7c0k+V1U/n+QL3X1pklTVTZPsm9k7zyy5qnpkZiX/dkm+lOQOST6R5C5j5mIufibJzyU5srv/rapun+QPR87E/Ly9qv4lyTeTPLWqtiS5dORMzMeTkxyd5AXd/ZmqumOS14ycifn5RlXtluSMqvqDzN5wN2NuNZxfVf8zyYOTvHi4t3fyr63N4pdUVW1Nct/uvnw43i3JB7v7XuMmYx6q6p+TPDDJ33f3PavqR5M8vruPHDkaO6iqXtzdz7m+MZZXVd0qyUXdfeWwCNAe3f1vY+dixw1vuN6+u88dOwvzNSzQ9e9Jdkvyy0lukeQvuvu8UYOxw6rqZkkeluSs7v5kVd02yV27++9GjjaqybfgJbbLWgFMkuHxbiPmYb6+1d1fTrJTVe3U3e9NcsjYoZiLB29j7OEbnoKFGH7ZeFquut/kdvFvdyVU1U8kOSPJO4fje1TVSaOGYi6qauckv9/dl3b317r7t7v72Qrgaujub2Q2q+r+w9AVmd37OWlK4PK6YJgymCSpqsOT/MeIeZivr1bVdyV5f5LXVdXLklwyciZ2QFU9tarOSnLnqjpz3cdn4n7eVXJCksuT3Hc4Pj/J5O89WRG/leTQJF9Nku4+I8n3jheHeRnuAbzDMKuKFVNVz0/ynFx1f+euSV47XqLNwT2By+vozMrBnyfpJJ9P8sRxIzFHh2d2H9Gzkvx8ZtNSfmfMQOywv05ycpIXJnnuuvGLu9vKvqvjgO7+mWEBkXT3N8rKMKviW9tY6OfbY4Vh7j6d5IPD1d3vvOna3S8ZLxJz8pNJ7pnktCTp7i+sbRkxZUrgkuruTyU5bLhalO7++siRmKPuvqSqviezd50vTPKuYXooS2r45fHrSe45LPDEarp8uG+sk9kG40kuGzcSc3J2Vf1ckp2r6sAkz8xsxW5Ww6eGj51y1bY9Fs5YDZd3d1fV2s/lm48daDMwHXRJVdVtqur4zJYg/3pVHVRVFg1ZEVX1i0lOSfJTSR6d5CNV9QvjpmJHDVOOzh1WBGU1PT+ze8b2q6rXJXlPkl8dNxJz8ozMVmi+LMnrk3wts9karIZzhnsBv/OR2arcLL83DquD3rKqnpLk75P81ciZRmd10CVVVSdndu/Jr3f33atqlySnd/ddR47GHFTVuZmt/vrl4fjWST7U3XcaNxk7qqr+KbNpKafk6lOOHnmtX8RSGf69Hpakknyku92vDZtcVZ3W3Qdf3xjLqaoenOQhmf1cfld3v3vkSKMzHXR57d3dbxw2nU53X1FVV17fF7E0vpzk4nXHFw9jLL/fHDsA81dVd+7uf6mqtV8Yvzh8vn1V3b67TxsrGzumqv6ku59VVW/LNqYHegNnuVXVw5P8eJJ9qupP153aM7NVJFkBQ+mbfPFbTwlcXpcM7zavzW8+LMlF40ZiR1XVs4eH5yX5aFW9NbPX+PBYQXIldPf7xs7AQjw7yVFJ/ngb5zqzfT9ZTmsbwv/RqClYlC8k2ZrkkUlOXTd+cWb7BbKkquoD3X3/qro4V38Dp5J0d+85UrRNwXTQJTW823xskh9I8vEkW5I8ursVhSU2LGN8rYZ7FFhC/jOahqravbsvvb4xlk9VHdPdL7u+MZZTVe3a3d8aOwdsFCVwiQ33Ad4ps18iz/XDC2Bc7itaXdfy2p7e3fccKxPzU1X3y2wvyDtkNlNu7Q06e0Euuap6TXc/4frGpsZ00CVTVT91Lae+v6rS3W/Z0EAsRFUdkuTXc9V/RkmS7r7baKGYi6o6sruPv8bYi7r7udf2NWx+w5Yu+yS5aVXdM7NfIJPZfUU3Gy0YO2zY8/Hnktxx2ENuzR6ZbeHDajg+s+mfpyaxxsJqucv6g+Eiyg+OlGXTUAKXz09cx7lOogSuhtcl+ZUkZ8VmxKvmp6vq0u5+XZJU1Z8nuenImdhxD03ypCT7Jlm/ufTFSX5tjEDMzYcyW+hn71z9ns+L417tVXJRd588dgjmZ1g88dcye3Pua2vDSS5P8vLRgm0SpoPCJrR2/9jYOZi/YSPxk5K8MsnDkny1u48ZNxXzUlU/3d1vHjsHsH3Wrej72CQ7Z/Zm+mVr563su/yq6oXd/byxc2w2SuCSqqrbJPn9JLfr7odX1UFJ7nPNaWYsp6p6UJLHZbbR9Pr/jFzpXVJVdat1h3sk+d9JPpjkfyRJd5tWtsSq6vHd/dqq+m/Z9jYCL9nGl7EELOq02qrqvddxurvbyr5Lahtb91zN1Au+6aDL61UZNosfjv9vkjdkNqed5ffkJHdOsmuumg5quu9yOzWz17DWfX7E8NFJLD6w3G4+fP6uUVMwd2uzMrp7j7GzMH/d/aNjZ2BhbN1zHVwJXFJV9bHuvtf6lcmq6ozuvsfI0ZiDqjq3u+80dg4AZob9eM/u7ouH4z2SHNTdHx03GfNQVcdk9ub6xUn+KsnBSZ7b3X83ajBYkJ3GDsCNZrP41fahYYovK6aqHjP88piq+o2qesuwmiQroKpOrKpbrjveq6peOWIk5ucvk3x93fElwxir4Re6+2tJHpLk1kmekORF40ZiHqrq6dv4ufy0ESNtCkrg8np2ZotLHFBVH0zy6iTPGDcSc3RYkjOq6tyqOrOqzqoqq9Ctht/s7our6v5JfiyzKdzHjZyJ+blbd3917aC7v5JEyV8N1eumT3X3t+O2mlWytq3Ljyd5dXefvW6M5faUbfxcfsp4cTYHP7yW1wFJHp5kvyQ/neTe8XqukoeNHYCFWdt/6hFJXt7d/6eqfm/MQMzVTlW11/BLxtqCQH42r4ZPV9Uzc9XVv6cl+fSIeZivU6vq75LcMcnzhhkbtmhaDTtX1XfexKmqnZPsNnKm0bkSuLx+c5i2sFeSH03yFzEtZZX0tXyw/M6vqv+Z5GeSvKOqbhI/i1fJHyf5cFX9blX9bmZ7zP3ByJmYj6OT3DfJ+Uk+n9mbr0eNmoh5OjLJc5Pcq7u/kVlJePK4kZiTdyZ5Q1U9aFh9/fXD2KRZGGZJrS0IU1UvTHJWd//1+kViWG5VdVauWkFy98zemTy3u+8yajB2WFXdLLMrvWd19yer6rZJ7mrxgdUx3M+7turcP3T3OevOfecqIaulqp7X3S8cOwc3XlXtleTAzP7fTZJ09z+Nl4h5qKqdMnvD5seGoXcneUV3X3ntX7X6lMAlVVVvz+zdyAdntoLVN5Oc0t13HzUYCzHscfO07v7FsbOwY6rqNd39hOsbYzVV1Wndvc09q1huXtvlVlW/mOSYJPsmOSOze/M/bJ/A1VdVb+7unx47x0YzBWl5PTbJu5I8dLjZ9VZJfmXURCzMsKHpvcfOwVxc7WrucG/CD46UhY1noYnV5bVdbsckuVeSzw17B94zyVdHTcRGmeQ+vW5WX1LDfPW3rDv+YpIvjpeIeaqqZ6873CmzkvCFkeIwB1X1vCS/luSmVfW1XPUL4+VJXj5aMDaa6Tery2u73C7t7kurKlV1k+7+l6qyX+80TPLfrhIIm9MeueqH0hVJ3pbkzePFYUcN9wq9sKpe2N3PGzsPMHeuBC63zw97yf3vJO+uqq8k+dyoiWCB3BMIm1BV3Suzq0b756o3a7q77zZaKOaiqn54W+MWH5gGC3gtp2Ha9jO7+6XX8Zxf6+7f38BYLEhV/UiSWyR5Z3dfPnYeFmuqP5eVQNiEqurcJP89ycezbp+i7vau5JKrqretO9w9yaFJTrX4wOqoqrsn+aHh8P3d/c/rzt2quy8cJxk7oqpO6e5Dx87B/A0l/+zuvvPYWdh4VfWQKa7QrQTCJlRVH+ju+4+dg8Wrqv2S/MkUVyZbRVV1TJKn5Kp7tn8yycu7+9jxUjEPVfXSJLsmeUOSS9bGh4W7WHJV9dYkz+ju/zd2Fuajqt7Y3Y9dt+3Wd07F7ColEDajYTPTxyV5T5LL1sa7+y3X+kUspaqqzN6BPmjsLOy4qjozyX26+5Lh+OaZLTM/6V82VkFVvXcbw+0q/mqoqn/KbEXQU3L1kv/I0UKxQ6rqtt39xaq6w7bOT312lYVhYHN6cpI7Z/au89p00M66FWFZTlV1bK56R3KnJPdI4krC6qgk6zcgvjIWDFkJw7YBrK7fHDsA8zWsnD/5sndtlEDYnO7V3ZamXk1b1z2+Isnru/uDY4Vh7k5I8tGq+tvh+FFJjh8vDvNSVbdJ8vtJbtfdD6+qgzK76uv1XQHd/b6xMzBfa7fWVNXF2fZ00D1HirYpmA4Km1BVnZDkD7v7nLGzMH9VtVuS7x8Oz+3ub42Zh/moqp2SHJbk0iRr9/S+v7tPHy8V81JVJ2dW8n+9u+9eVbskOb277zpyNOagqg5LcmyS/y/Jbkl2TnLJ1IvCFFTVXt39lbFzbDQlEDahqvpEkgOSfCazewLdxLwiquoBSU5M8tnMXtf9khxhi4jVMNWlxqegqj7W3fda/xpX1RndfY+RozEHVbU1yc8meVOSQ5I8Mcn329d19VXVad198Ng5NprpoLA5PWzsACzMHyd5SHefmyRV9f1JXp/kB0dNxby8p6p+Oslb2rusq+aSqrp1hmllw5Wji8aNxDx193lVtXN3X5nkhKo6PYkSuPomed+2EgibkJuYV9quawUwSbr7/1bVrmMGYq5+Kcmzk1xRVZfGvSer5NlJTkpyQFV9MMmWJI8eNxJz9I1hqv4ZVfUHSb6Y2eJdrL5JvmFnOijABqqqV2a24utrh6GfT7Jzd//CeKmA7THcB3inzMq9+3lXyLCNwL9ndj/gLye5RZK/6O7zRg3Gwk11OqgSCLCBquomSZ6edQuHZPaLxmXX/lUsi6p6T3c/6PrGWE5Vdd8k+2fdTKrufvVogYAdNtV7uZVAgE2kqt7c3T89dg5umKraPcnNkrw3yQNy1T0meyZ5Z3ffeaRozElVvSazBbvOyFV7QXZ3P3O0UMxNVd0vyW8luUOuXvK/d6xM7Liq2jnJ2df1M7iqbtXdF25grE3BPYEAm4tfOJbTLyV5VpLbJTlt3fjXkvzZGIGYu0OSHGTBn5V1fGbTQE/NVSWfJdfdV1bVuVV1++7+f9fynMkVwEQJBNhs/IK5hLr7ZUleVlXP6O5jx87DQnw8yfdktmAIq+ei7j557BAsxF5Jzq6qU5JcsjbY3Y8cL9L4TAcF2ESmeoP6qqiqm2d2NeH23X1UVR2Y5E7d/faRo3EjVdXbMntzZo8k90hySmb7tybxi+Syq6q1n7ePzWyD+Lfk6q/vadv6OpZHVf3Itsa7+30bnWUzUQIBNpGp3qC+KqrqDZlNJ3tid/9AVd0syYdsKL68ru0XyDVT/0Vy2VXVe6/jdHf3AzcsDAszrP56YHf//fBzeefuvnjsXGMyHRRgZFV16+7+8nD4nFHDsKMO6O6fqarHJUl3f6OqJrkR8apYK3lV9eLuvtq/z6p6cRIlcIl194+OnYHFqqqnJDkqya0yW9xpnyTHJZn0qs02wQQYQVV9qqr+tKoOzWybiCRJd//diLHYcZdX1U0z3NtZVQdk3dQyltqDtzH28A1PwcJU1SOq6ler6n+sfYydibl4epL7ZbZQV7r7k0m+e9REm4ArgQAj6O4DquqXk3w4yZPHzsPcPD/JO5PsV1Wvy+wXjyeNmogdUlVPTfK0JAdU1ZnrTu2R5EPjpGLequq4zLZ5+dEkr0jy6Mzu/2T5Xdbdl69NyqiqXWIRNvcEAmyEqvq7JE/p7s8Nx4clOTHJHyZ5SHc/dsx8zE9V3TrJYZntFfiR7v6PkSOxA6rqFpmtLvjCJC9K8sPDqQ909+mjBWOuqurM7r7bus/fleTk7v6hsbOxY6rqD5J8NckTkzwjszd1zunuXx8z19hMBwXYGN+9rgA+Iskrk/xEd78iyR1HTca87ZPZKoO7JfnhqvqpkfOwA7r7ou7+bJKPJHltkr2TbElyYlU9Y8xszNU3h8/fqKrbJflWktuOmIf5eW6SC5Kcldmeru9I8hujJtoETAcF2BiXVdURSfbL7J3Ie3b3F6pqzyQ3Hzca81JVr0xytyRnJ/n2MNyZLTvPcjsyyWHdfUnynUVhPpzEvpCr4e1VdcvMZmecltm/21eMmoi56O5vJ/mr4YOB6aAAG6Cqvi+zdyMvT/KpzBaZ+FCSw5O8trtfOmI85qSqzunug8bOwfxV1VlJ7tXdlw7Huyf5WHffddxkzFtV3STJ7t190dhZuPGq6o3d/djh3+5/KjzdfbcRYm0argQCbIDuPi/JL64dV9U/JPmxJM/p7r8fLRjz9uGqOqi7zxk7CHN3QpKPVtXfDsePSnL8eHGYp6raOckjkuyf4ffjqkp3v2TMXOyQY4bPn0jyK+vGK8kfbHyczcWVQIBNpKo+3N33GTsHN86wsfhJSf4ts60hKrMNpyf9jvOqqKqDk9x/OHy/hWFWR1W9I8mlmd03tjaVO93926OFYi6q6rTuPvgaY2dO/eeyK4EAm8vuYwdghxyf5Am5xi+SrIbuPi2z+8VYPftOvRSsmnXbu3zvNrZ3+eA4qTYPJRBgczE9Y7ld0N0njR0CuMFOrqqHdPffjR2EufnrJCdntr3Lc9eNX9zdF44TafNQAgFgfk6vqr9O8rbMpoMmSbrb6qCwuX0kyd9W1U6ZbQ+xNpV7z3FjcWMNC/tclORxY2fZjJRAgM2lxg7ADrlpZuXvIevGbBEBm99LktwnyVltwQwmwMIwABusqu6Q5MDu/vuqummSXbr74uHcD3T3x8dNyKJU1fO6+4Vj5wCurqr+KckDhj3lYOUpgQAbqKqekuSoJLfq7gOq6sAkx3X3g0aOxgbY1ip1wPiq6lVJvjeze8jWT+W2RQQryXRQgI319CSHJvloknT3J6vqu8eNxAYy3Rc2p88MH7sNH7DSlECAjXVZd19eNesCVbVLrAg6JV5r2ISubz/Aqjq2u5+xUXlg0XYaOwDAxLyvqn4tyU2r6sFJ3pTZSpJMgyuBsJzuN3YAmCclEGBjPTfJBZltJv5LSd6R5DdGTcRcVNXOVfXL1/O0N21IGAC4DhaGAYA5qapTuvvQsXMA82VRJ1aNewIBNlBV3S/JbyW5Q2Y/g9c2JP7eMXMxNx+sqj9L8oYkl6wNdvdp40UC5sBUblaKK4EAG6iq/iXJLyc5NcmVa+Pd/eXRQjE3VfXebQx3dz9ww8MA16uqXtPdT6iqY7r7ZdfxvCd196s2MBoslBIIsIGq6qPdfe+xcwCQVNU5SX4ss/0BH5BrXPHr7gtHiAULpwQCbKCqelGSnZO8JVffkNh0wRVQVbdJ8vtJbtfdD6+qg5Lcp7uPHzkasA1V9cwkT81so/jzc/USaKo+K0sJBNhApguutqo6OckJSX69u+8+7AN5enffdeRowHWoqr/s7qeOnQM2ihIIAHNSVR/r7ntV1endfc9h7IzuvsfI0YDrUVV3T/JDw+E/dfeZY+aBRbI6KMAGq6pHJLlLkt3Xxrr7d8ZLxBxdUlW3TtJJUlWHJblo3EjA9RmmhR6V2VT9JHldVb28u48dMRYsjCuBABuoqo5LcrMkP5rkFUkeneSU7j5y1GDMRVUdnOTYJD+Q5ONJtiR5tCsKsLlV1ZmZ3b97yXB88yQf7u67jZsMFkMJBNhAVXVmd99t3efvSnJyd//Q9X4xS2G4D/BOmS0wcW53f2vkSMD1qKqzktyruy8djndP8jH387KqTAcF2FjfHD5/o6pul+TLSW47Yh7m79Ak+2f2f+zBVZXufvW4kYDrcUKSj1bV3w7Hj0piVV9WlhIIsLHeXlW3TPKHSU7L7N6xV4yaiLmpqtckOSDJGUmuHIY7iRIIm1h3v6Sq/jHJ/YehJ3f36Wvnq2qv7v7KKOFgAUwHBRhJVd0kye7dbeGQFVFVn0hyUPvPFVZKVZ3W3QePnQPmxZVAgA1WVffNVdMFY7rgSvl4ku9J8sWxgwBzVdf/FFgeSiDABjJdcDVV1dsyex33SHJOVZ2S5LK18939yLGyAXPh6j4rRQkE2FiHxHTBVfRHYwcAgO2lBAJsLNMFV1B3vy9JqurF3f2c9eeq6sVJ3jdKMGBeTAdlpVgYBmADXGO64D2SmC64gra1eMTanpBjZQKuX1UdkOTz3X1ZVT0gyd2SvLq7vzqcv1V3XzheQpgvJRBgA1TVj2T2TvKLk/zq+lNJXtzd9x4lGHNRVU9N8rTM7vc8b92pPZJ8qLt/fpRgwHapqjMym66/f5J3JHlrkrt094+PGAsWxnRQgA2wbrrgrmuP11TVTcdJxRz9dZKTk7wwyYuS/PAw/oH1e40Bm9a3u/uKqvrJJMd297FV5d8uK2unsQMATEFVPbWqzkpyp6o6c93HZ5KcOXY+dkx3X9Tdn03ykSSvTbJ3ki1JTqyqZ4yZDdgu36qqxyU5Isnbh7FdR8wDC2U6KMAGqKpbJNkrsytFz1136mL3mayOqjozyX26+5Lh+OZJPuyeQNjcquqgJEdn9u/19VV1xySP7e4XjxwNFkIJBIA5Ga723qu7Lx2Od0/yse6+67jJgOszTM2/fXefO3YWWDTTQQFgfk5I8tGq+q2q+q3MpoceP24k4PpU1U8kOSPJO4fje1TVSaOGggVyJRAA5qiqDk5y/+Hw/RaGgc2vqk5N8sAk/9jd9xzGPt7dPzBuMlgMq4MCwBx192lJThs7B3CDfKu7L6q62p7w3x4rDCyaEggAwNSdXVU/l2TnqjowyTOTfGjkTLAw7gkEAGDqnpHkLkkuS/L6JF9L8qwxA8EiuScQAABgQkwHBQBgkqrqT7r7WVX1tiT/6cpIdz9yhFiwcEogAABT9Zrh8x+NmgI2mBIIAMAkdfepw8N7dPfL1p+rqmOSvG/jU8HiWRgGAICpO2IbY0/a6BCwUVwJBABgkqrqcUl+Lskdq+qkdaf2SHLhOKlg8ZRAAACm6kNJvphk7yR/vG784iRnjpIINoAtIgAAACbElUAAACapqj7Q3fevqotz9S0iKkl3954jRYOFciUQAABgQqwOCgDApFXVYVW1x7rjParq3mNmgkVyJRAAgEmrqtOTHNzDL8ZVtVOSrd198LjJYDFcCQQAYOqq110Z6e5vx9oZrDAlEACAqft0VT2zqnYdPo5J8umxQ8GiKIEAAEzd0Unum+T8JJ9Pcu8kR42aCBbIPYEAAHAdqup53f3CsXPAvLgSCAAA1+0xYweAeVICAQDgutXYAWCelEAAALhu7p9ipSiBAABw3VwJZKUogQAATFZV7VxVv3w9T3vThoSBDWJ1UAAAJq2qTunuQ8fOARtFCQQAYNKq6qVJdk3yhiSXrI1392mjhYIFUgIBAJi0qnrvNoa7ux+44WFgAyiBAAAAE2JhGAAAJq2qblNVx1fVycPxQVV15Ni5YFGUQAAApu5VSd6V5HbD8f9N8qyxwsCiKYEAAEzd3t39xiTfTpLuviLJleNGgsVRAgEAmLpLqurWSTpJquqwJBeNGwkWZ5exAwAAwMieneSkJAdU1QeTbEny6HEjweJYHRQAgMmrql2S3ClJJTm3u781ciRYGCUQAIDJq6r7Jtk/62bKdferRwsEC2Q6KAAAk1ZVr0lyQJIzctWCMJ1ECWQluRIIAMCkVdUnkhzUfjFmIqwOCgDA1H08yfeMHQI2iumgAABMUlW9LbNpn3skOaeqTkly2dr57n7kWNlgkZRAAACm6o/GDgBjcE8gAACTVlUv7u7nXN8YrAr3BAIAMHUP3sbYwzc8BWwQ00EBAJikqnpqkqclOaCqzlx3ao8kHxonFSye6aAAAExSVd0iyV5JXpjkRUl+eDj1ge4+fbRgsGCmgwIAMEndfVF3fzbJR5K8NsneSbYkObGqnjFmNlgkVwIBAJi0YSrofbr7kuH45kk+3N13GzcZLIYrgQAATF0luXLd8ZXDGKwkC8MAADB1JyT5aFX97XD8qCTHjxcHFst0UAAAJq+qDk5y/+Hw/RaGYZUpgQAAABPinkAAAIAJUQIBAAAmRAkEgDmoqqOr6onD4ydV1e3GzgQA2+KeQACYs6r6xyT/vbu3jp0FAK5JCQSAG2G46vffk3SSM5N8KsnXk3w2yauSnJ/km0l+PclTuvtRw9c9OMnTuvsnNzw0AMR0UAC4warqLkl+I8kDu/vuSY5ZO9fd/yvJ1iQ/3933SPKOJHeuqi3DU56c5JUbmxgArqIEAsAN98Akb+ru/0iS7r7w2p7Ysyk3r0ny+Kq6ZZL7JDl5I0ICwLbsMnYAAJiAE5K8LcmlmZXHK0bOA8CEuRIIADfcPyR5TFXdOkmq6lbXOH9xkj3WDrr7C0m+kNkU0hM2KiQAbIsrgQBwA3X32VX1giTvq6ork5ye2YIwa16V5Liq+maS+3T3N5O8LsmW7v7ERucFgPWsDgoAG6Cq/izJ6d19/NhZAJg2JRAAFqyqTk1ySZIHd/dlY+cBYNqUQAAAgAmxMAwAAMCEKIEAAAATogQCAABMiBIIAAAwIUogAADAhCiBAAAAE/L/A/nc/Q+z6CEqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "sns.countplot('city', data = df, palette='hls') \n",
    "plt.xticks(rotation = 90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1568eb2e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:14.283771Z",
     "start_time": "2022-05-24T08:22:14.272978Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "india                   8953\n",
       "united_states             69\n",
       "united_arab_emirates      53\n",
       "singapore                 24\n",
       "saudi_arabia              21\n",
       "united_kingdom            15\n",
       "australia                 13\n",
       "qatar                     10\n",
       "hong_kong                  7\n",
       "bahrain                    7\n",
       "oman                       6\n",
       "france                     6\n",
       "unknown                    5\n",
       "south_africa               4\n",
       "nigeria                    4\n",
       "germany                    4\n",
       "kuwait                     4\n",
       "canada                     4\n",
       "sweden                     3\n",
       "china                      2\n",
       "asia/pacific_region        2\n",
       "uganda                     2\n",
       "bangladesh                 2\n",
       "italy                      2\n",
       "belgium                    2\n",
       "netherlands                2\n",
       "ghana                      2\n",
       "philippines                2\n",
       "russia                     1\n",
       "switzerland                1\n",
       "vietnam                    1\n",
       "denmark                    1\n",
       "tanzania                   1\n",
       "liberia                    1\n",
       "malaysia                   1\n",
       "kenya                      1\n",
       "sri_lanka                  1\n",
       "indonesia                  1\n",
       "Name: country, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.country.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "57ad5d86",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.015295Z",
     "start_time": "2022-05-24T08:22:14.286645Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUIyaBkiRJktQjJoGSJEmS1CMmgZIkSZLUI50lgRHx0Ig4MyKuiogrI2K/enztiDg9In5RP69Vj0dEfCoiro2IyyNi66FYr6jf/4uIeEVXbZYkSZKkpV2XI4H3Am/PzM2B7YA3RcTmwHuAMzJzE+CMehtgN2CT+vFa4DAoSSNwAPAE4PHAAYPEUZIkSZK0eDpLAjPz95l5cf36TuBqYD3gecDR9duOBvaoXz8POCaL84A1I+LBwDOB0zPzlsy8FTgd2LWrdkuSJEnS0myJrAmMiA2BxwLnA+tm5u/rXX8A1q1frwf8dujHrq/HpjsuSZIkSVpMnSeBEbEq8A1g/8y8Y/i+zEwgW/o9r42ICyPiwptuuqmNkJIkSZK01Ok0CYyI5SkJ4LGZeUI9/Mc6zZP6+cZ6/AbgoUM/vn49Nt3xCTLziMzcNjO3XWedddr9QyRJkiRpKdFlddAAjgSuzsz/GrrrW8CgwucrgJOGjr+8VgndDri9Ths9FXhGRKxVC8I8ox6TJEmSJC2m5TqMvSPwMuCKiLi0HvsX4D+B4yJiX+DXwAvrfd8FngVcC9wFvAogM2+JiA8CP63fd1Bm3tJhuyVJkiRpqdVZEpiZPwJimrufOsX3J/CmaWJ9AfhCe62TJEmSpH5aItVBJUmSJEmzg0mgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9YhJoCRJkiT1iEmgJEmSJPWISaAkSZIk9cicSQIjYteI+HlEXBsR7xl3eyRJkiRpLpoTSWBELAv8N7AbsDmwd0RsPt5WSZIkSdLcs9y4GzBDjweuzczrACLiq8DzgKvG2ipx4Tde3zjGtv94+IJxz2gh7lMXjCtJkiT13VxJAtcDfjt0+3rgCWNqi6RpfPzC5sn7O7Zdcsn7m1to76FLsL2SJEltiMwcdxsWKSL2BHbNzNfU2y8DnpCZ/zz0Pa8FXltvbgr8fIbhHwD8qcXmGte4Szq2cY1rXOMa17jGNa5xjTvZBpm5zlR3zJWRwBuAhw7dXr8emyczjwCOWNzAEXFhZm7brHnGNe74YhvXuMY1rnGNa1zjGte4i2NOFIYBfgpsEhEbRcQKwIuBb425TZIkSZI058yJkcDMvDci/hk4FVgW+EJmXjnmZkmSJEnSnDMnkkCAzPwu8N0OQi/2FFLjGneWxTaucY1rXOMa17jGNa5xZ2xOFIaRJEmSJLVjrqwJlCRJkiS1wCRQkiRJknrEJFCSJEmSesQksAMR8cCIeNjgo4V4H5nJsRFjrxcRO0TEkwYfbcSd9DvWiogt246r/oqIZSPi4+Nux2wRERtExNPq1ytHxGrjbtPSJCI2jogV69dPiYi3RMSaY27WUiEi7t9x/M7f42a7iHj0uNuwuNq+jlL3ImLtKY5tNI62zAYRsXpErD34GHd7ptLLwjARsQ7wbmBzYKXB8czcpWHc5wIHAw8BbgQ2AK7OzEc1jHtxZm496djlmdkosaqJ5IuAq4D76uHMzOc2iVtjnwU8l1KB9iLK43FuZr6tYdyPAh8C/g/4HrAl8NbM/J8GMTcB/oMFnw8Pb9LWGntN4OXAhgxV483MtzSMu8MUMY9pErPGfTbwKCY+Dgc1jLkK8HbgYZn5T/Xx3jQzv90w7nmZuV2TGAuJ3dU5YiPgzSz4vxv5NRcR/wS8Flg7Mzeuj+/hmfnUJm0dit/Fc2ILFnxsGz1/u/qf1diXAttS/m/fBU4CHpWZz2oQc0XgH1nwudDosa2xtwMOBf4BWIGytdJfMnP1hnFfMMXh24ErMvPGEWP+ArgUOAo4JVu8KOnqPa6r94wO/2/nACsCXwSOzczbm8SbFLvV13JX11E1dievua7+bzV2a4/vNK/feTLzhFHiDsU/F9gtM++otzcHjsvMLRrG3Y9yfrgT+DzwWOA9mXlak7g1duvXUhHxOuADwN3A4HyWLV1Ttvp+PGe2iGjZscDXgGcDrwdeAdzUQtwPAtsB38/Mx0bEzsBLRw0WEW8A3gg8PCIuH7prNeDcRi0t9qBcjN/TQqzJ1sjMOyLiNcAxmXnApL9hVM/IzHdFxPOB/wVeAPwQGDkJpJxcDgA+AewMvIr2Rsm/C5wHXAH8vY2AEfElYGPKhdO8Cxug6YnrcGAVymPweWBP4IImMaujKB0B29fbNwDHA42SQOCSiPhWjfWXwcGmb2RVV+eIE4EjgZNp6fkAvAl4PHA+QGb+IiIe2EbgLp4TEXEA8BTKhc13gd2AH9Hw+Ut3/zOAv9f9ap8PHJqZh0bEJQ1jnkRJoC4C2j4Hfxp4MeW1sS2lI+qRLcTdl/I6PrPefgql/RtFxEGZ+aURYj4SeBrwauBTEXEc8MXM/H8ttHcPunmP6+o9o5P/W2Y+sSaurwYuiogLgKMy8/QmcTt6Lbd6HTVJV6+5Tv5vHTy+z6mfHwjsAPyg3t4Z+DHQ9L3z34GTa6KyKaWd+zSMCfDqzDwkIp4JrAW8DPgS0CgJ7OpaCngHsEVm/qlhnAk6uUbLzN59ABfVz5cPHftpC3EvrJ8vA5YZfN0g3hqUHoqvUHrDBh9rt/Q4nAKs2tFjfAXwYMqL9HGTH+8GcX9WP38e2LXpYzzp+XDF5GMttPfiDh7bq6mj+C3HvXzS51WBc1qIO3hdXDJ0rNH/rMY4aoqPL7T0WHR1jji/g//b+cOPL6Vzr/FrravnRD03LDN4DgDrAqfP1v/Z4DEG9gZ+BmxUj/2sYcxGP7+I2IPX3PBjcUkLcU8F1h26vW49tnYbfw/l4uYG4DbgbGD7hvE6eY/r6j2jq//bUKxlKSNhN9T3kWuAFzSI1/prmZavoybF7uQ11+Hrratz5WnAg4duPxg4taXHYg9KQnkF8MiWYg7efw4Bnt/i49vVtdT3gFU6iNv6+3FfRwL/Vj//vvZY/I7yJtbUbRGxKmVk6tiIuJGhEYoRZGb+b0S8afIdEbF2Zt7SIDbAXcClEXEGQ71i2XCqYnUQ5eLg3Mz8aUQ8HPhFC3G/HRHXUKaDvqFOAbu7Ycx7ImIZ4BcR8c+UN8hVG8Yc+FKdrvdtJj7GTf53PwMeBPy+Ydsm+7/6+a6IeAhwM+XNoam/RsTK1GkREbExLfTCZuarmsZYiK7OEYfU3t3TmPh8uLhBzLMj4l+AlSPi6ZTZAyc3a+Y8XTwn/i8z/x4R90bE6pQpXw9tGBO6+59BGel5PfDhzPxVndY7yqjXsB9HxKMz84rmzVvAXRGxAuX8/lHKuaKNkaqHZuYfh27fWI/dEhF/m+6HFqauCXwppXf/j5Tp0t8CHkMZWWmypqir97iu3jM6+b9FWZP/Ksoo+enAczLz4vqa/gmjjwB18Vpu+zpqWFevua5eb12dKx+amcPXD38ERl53GRGHMn/aI5QBjF8C/xwRbbzeLoqI0yjngvdGWfPexkyarq6l3kt5rp1Pu+ed1t+P+5oEfigi1qCsUzoUWB14awtxn0dJSN5KGQJfg5IMjerLwO6UqQsJxNB9CTSdX/yt+tG6zDye8gY+uH0dpQeyadz31JPs7Zl5X0TcRXncm9iPMsT+FspUlF0oU8na8FfgY8C/MjQ3nGb/uwcAV9UpPcMnmKZrOb9d1zB+DLiY0s7PN4wJZdrU94CHRsSxwI7AK5sGjYiVKNPTJs+Pf3XT2HR3jng05WJ3F+a/iWW9Par3UB6HK4DXUaYNtfF/g26eExfWmJ+jnNv+TLkQbaqr/xmZeRXl/DC4/SugaXGunYBXRsSvKK/jKKGbrfWuXkYZ9flnymPwUFo4/wJnRcS3mX9u/8d67H6U0btR/ISSUO+RmdcPHb+wTn9qoqv3uK7eM15GSR7a/r8dSpmG/i+ZObiQJDN/FxHvaxC3i9dy29dRw7p6zXX1euvqXHlGRJxKmWUGZd3s9xvEu3DS7YsaxJrKvpROoesy867acTRyJ3BEnEx5L1uNbq6lPkuZatvaMqCq9ffjXhaGUfci4pHAYZSpQ1vUnsjnZuaHGsZdBXgbpcjIa6OlIiNdiYjrgMdni3PDI+LJUx3PzLNb/B0rAitlwwICtbd8T+AMyjqPAM5r4/GIiOMp05leQrlI2IdSQGC/prG7EhHXAptn5l9bjHk/4O7MvK/eXhZYMTPvaiH2ilnXUw2eE8CyLcxCGMTfEFg9M9tYL9y6iLiCiT3cEzS5eIyIDaaJ+etRY3YtIoJycbtjPXQu8I1scCEREdHk52cQfwXmr8/6eWaONGK5JETEc4DvZGabF45LxGx/LcPcfM0NtP34RikS88R684eZ+c2G8Zal1H9oYw3g5NhBeX9/eGYeFKVa7IMyc6T1cNNdQw00vZaKiEsy87FNYszgd7RzjdanJDAi3pWZH51i6BoYfag2In6UmTtFxJ2T4g56mdqoELUWsAkTRzx+2DBml1UxzwbeCXx28GKIiJ9l8ypRX6P0Mr28JperAD/OzMeMEOuTmbn/UK/QBC30BlGnMOzRxgX5khDdVMq6MDO3bdi0qeJekqVwwOWZuWVELE+ZHz9yxdCuzhFD8U8EXpsjVlKcJuZ5wNMy88/19qrAaZm5Qwuxv0N5/v6t3n4Q5SJ1m4Zx16Osbx5+no10PpvufzUUd+T/2dBF42BK/mAK6EtL6HzPqLFr/J2ATTLzqChT21eto4yjxjsuM184XfLa0ihjq2qH4TtY8LzTRlXXpwBHU4qIBWWE5hUNnmtTvlcMNH3PiIj/oRTe+QZlffM1DeNN14nRyghYlEJJPxhciNZRiqdk5okjxFoS11EfpEwz/XFmNp5i2tXrLSI2y8xrImLrqe5vuHygMxHxI2CXNjs5a9zDKCNqu2TmP9Tr4dMy83EN496P+VNuHwlsRqlQ3KijKCL+nXLOOZkWlgFFxC6Z+YOYprprNiiG17fpoFfXz5OHrhvJzJ3q50725opSYXM/YH1KFaPtKFMCmr5JHkV3VTFXycwLSgfOPPe2EHfjzHxRROwNUKcGxKJ+aBqDC7ou95v7C2WdwJk0nBve9ZtkdFcp6/sR8Q5K5cbhKp5NR5MGJ+rbopTR/gOl6lkTnZwjhqwJXBMRP6W96ScrDRLAGuvPtXOkDScCx0XEnpQL6G9RLthHFtOU7adcnI1i8L/akdKh9bV6e6/6O0Y2GCGIiKdP6tl9d0RcTJmKO5Ioa0O3pVTROwpYnlLleMeF/dwiDEbBd28QY1r1IuQjlNdZ0M6553jgcMq0pvsW8b2L62BKRemfw7yE8yvAqJ0Yg/eKF1DWEg2qUu9NWVfVSGa+NMrar72BL0ZEUp4bX8nMO0cI2cnzYMgBwyNImXlbfV6fuLiBur6Oqq6jPLafqu+j51BGwU4aMV5Xr7e3Ubb9OXiK+5ouH+jqdQzl8T03StXu4ff6/2oY9wmZuXXUisyZeWsd4W/qh8ATB0kl8FPKe1PT0cy96+f3Dh1rsgzoyZTppc+Z4r6kQVXXXiWBmXly/Xx0F/GjFLy4PjPvqT2QW1KGx29rGHo/4HGUaXQ7R8RmlFK8Ta2cmWfU6Ti/Bg6MiIuAf2sh9p/q4zEoBrIn7Sy+ba3ISGZeVD+3No1yCicywhviVJbAm+S2lKmKbU8PeFH9PFzgqI01rUfUk/f7KMnJqsD7mwScfI6oF2Q54gXYVA5oKc6wv0TE1oPe4YjYhvkLyBvJzM/VN9sTKSM1r8vMHzcMuwctlu0f+l+9AdgpM++ttw+nXOS1ISJix8w8t97YgeYdZs+n7Hd1Mcxbn9XotZ2Zv6/Tsr6YmTs3bN9UPkopKnL1Ir9z5u7NzMNajDds+UECCJCZ/6/OGBjJ4L0iIg6eNLvh5IhopeMoy9ZKXwdWBvanPE/eGRGfysxDFzNW19Mcp3oNNL6urM/hdZk4MvybpnEz8yjgqDqj4YWUDq3XUtaGjRJvcE3zJ6YYUWrQztdGWUrxvsE5p2VdvI6hFIP5JeV50eZ1yt/qc2Jw3bcO7ay1izqQsC/wmToL6LKmQTOzSTGrqeIdUD+3XgyvV0lg11M5KFM4to2IRwBHUPak+TIw8obC1d2ZeXdEDNboXBMRmzaMCd1WxXwT5THYLCJuAH5FO/vFHMiCRUZGemEsZKoM0M7Uqcw8OjpakxJlL7jhabxN3yQ7qZTV9glxyBmZeSulN+/hAFGqNjYWEdtSeuBXKzfjNspeRY0WvHfU4bA/cHxE/I7So/sg5ifeI4mItw3fpFSOuxTYLiK2a9izex1l1KvtvdvWohSDGYwwr1qPtWFf4AtRCs8EcCtlz7Um/pqZWUd7BlOTGstSMOvvEbFGtrgpePXHDi4cT46INwLfpL0KygMXRsTnmT9itw/tjPLfLyIenqXg2eC80/j/F2Wj9FcBj6DMwHh8Zt5YR/avohR4GSVuV5uZXxgR/wX8d739JhoWBYmIN1M6y/7IxOJZjd+P63Nh8xr7HMp69TamVrY+olQTyk9TOora1sXrmMz8QNsxq09Rzg8PjIgPU/5vTQoaDUREbE/5P+1bj7UyG67OTpq81Krp0pr9KNcld1KKBW0NvCczR94vsVdJIB1P5aCbDYUBrq9z7U8ETo+IW4E2evi6rIqZmfm0emGzTGbe2cYFemaeVkcrB0VG9svRi4x0PVVmyjUpEfGKbLCes14oHAw8hFIyegPKNMZHNWxuJ1VHa8/7G4An1UNnUdaKNk2Gv0E5CQ77OqNP9Rr2BeCNmXkOzFu7dRQNL0QmTeVdgZIMNboYy7IFy2aUaYXQTkfD5F7cE6Y5Poquyvb/J3BJnXodlOfbgQ1jAvNmDWxVk0BaSq6Oi4jPAmtG2Ubm1ZQ39jb8GbgiIk5n4rSspo/xhVHWZZ/IxP9dk02mB+857xw61sZMASjnnTcxv7LrOcBnWoj7VkpV1Osoz7UNKJV5m/pH4BOT3x+GRitG1clm5pTtPN7P/CnYpzNxxsco9qPMFLi5YZyp3J+SAN9G6Sz602DmQENTjShd2kLcMyLiH4ETWp6h08XreDBC9y4WrNjdaPpqZh5br/ueSnm97dFSErs/ZcrmNzPzyihbmZ3ZNGidEv0UShL4XWA34Ec0X1rz6sw8JCKeSXkuv4yyrGnkJLBXhWEGYopCFVMdGyHu+cAnKdsBPCfLflKNi6FM+h1PppRM/l62vPi2TRFxcWZuPenYRdm8oMQZmfnURR2bLeqJ6yU5aU1Kk8ehTlfYBfh+lsIoOwMvzcwmFwnTVsxqOnpVe1+XpyTDUE5c92Xma0aMtxnlTeajTLxwXB14Z2Y2TYanrO411XO64e8ISjn07bJ5gZHWC/p0JSKm7GjKFqbp12leT6g3z8/MPzSNWeOuSLlA35CJj3Gj0vVR9nV8BuXC5tTMPL1JvKG4nTzGEXHU1GFb2ZZlTqnPic3qzWvamt7chcH1TdQiWvXYAue42aB24jy9peRsut/xD8AzKcn8spm5fsN4l1D2Z/0EsG9NKK7IzEc3jHsnZYT5PsoU/7bW/3fyOo5SCO9rlGm2r6d08NyUme9uErfG7mSKcI29SrZYvK/OMtuKsqH9VhGxLvA/mfn0hnEHRfAOAc7KzG82fR33bSRwoJOpHHSzofDkilZtbgOwLSVhnVylr0nZ88EF+hoxsZLR6gz1DI0QdyXKqOUD6pSLQTGY1YH1Ro1bY3c1VQZaXpNS/S0zb46IZSJimcw8MyI+2TBml2sjH5eZWw3d/kE0m3e/KWUUd00mLpS+E/inBnGJ+dXYzq6jNF+hjEq8iDKC2Zras3ti7TVsUmCkq4I+nVRubCPZW4h7KNOZVwIeGRGPbDLqPuQk4HbKVLfWLvZr0tdK4jcp7tFR1k4/bPj800Lc1tekQPtTp2LJVEndhvmvi62ibIrddLpXVwU7Wt3MPLqtrH0dZZT1O0wcpWpaXISI2J2yLcKTKO8fP6CddcP70cGIUna0/r+r1zFw/8w8MiL2q9cTZ0cpgtbIpCnC91FfFzSfmbM9Zf/MVYGHRcRWlHXvb2zW4nnrQ++NUlfgRkphtaYuqon2RsB7o6whb7Q2sq9JYCdTOXJoQ+GaqKyWmU03FIb2K1oNHEsZSWlzQ8uuLtBfRxm6fwjlQmyQBN5BmerSRFdTZaCbNSm3RdkG4IfAsRFxI0NTvkbVYTJ8X0RsnJm/rL/n4TSoAlif9ydFxPaZ2cbGucMmV2MbLuTSeNrEpI6RZSjPt7sbhu2qoA+0WLmx6wvz6K6KMsD6mblrC3EmTwleQBudT1H2m/s45XW8UUQ8Bjio4cU5EbE+5RwxqGB6DmVK/vXT/9QiY3YxdarrKqlddbx0VbBjqk3opyw3P0NdVtb+Tf1YoX60aVfKc/aQzPxdi3FvHX5t1QGGplOvB7NF9gE2yswPRsRDgQfniPvjDcVdibIGbvK0zaYj+oNlCL+PiGcDvwPWbhgTupsi/EnKiPC3ADLzsoh40kJ/YmYujLKE63OU69U/U96LmtoXeAxwXZ1+fH9GrIkxT2b28gNYkTJcuxVlY+U2Yp5FGZlam1II5Xzgv1ps84MoJ5bfAHe2EO9HHT6+23cU980dxLywfr586NglLcVekVLu+YT68damzzfKqPUylE6cV9TnxP3beBwoBQkuoSSArwL+o4W4T63P2bOAsynrI3duIe5KlPUnn6Gs4fsCZW+t1p93LT7Xjhr6+BxlJP6BDWMeT7kw6KK9F7UY68H18wZTfbQQ/4r6nLi03t6MspamjbYfATy65cf2g5QpZKvV9403UBK1Vv5vlGUDlwwd+1kLcU+v54Xl6scrgdNb+L8tA1xWb6/bNGbXH5Q12NFB3HM7au9+Mzm2mDGXBY4d9/9ihHavS+kc2L3puXco5jnABfX1vEaLbT2MUnTn6np7LeCnLcQ9vp5/flmvIU6jJMZN4+5ezztbUEZCLwKe20LcM4HlOngunF8/XzJ07LKWf8eGwJYtxQrKHrX/Vm8/jFI8auSYvVwTCN2soYn5m1e/BnhoZh4wPAe/QdzJFa1+BFycDefMR8RTKSOMkws0NFocXGN31dPUxdShHwJPo4x2/IEyVeaVOXEK46xQ58V/Pzso/97lupG6fma4cEnjKXURcTxwDfAS4CBKj+nVmbnfQn9w5vGfzYLP30ZrwLpQ19A8hnIR0lpBnxr7QMpUli4qN7YqIn6amY+LUpDhCVm26rky21kjehWlg+RXlMeh8WbbEXHZ5HPMVMdGjH1eZm43/Ppt6b3o0sx8zKKOLWbMCzLz8VHWT+9MmTVydWZutogfnUnsqUZdb6d0eL0965KQEeIeD7wl528R0Iq61udBtF+wY6o1+o3P7dHB5uDRUXGRGnsvyujlWZTX8BMp68i/3kLsR1I6SPainIu/mA2qNtaYF2fdH2/oddz4HDF0rTpYY7Y8cE5mbtckblci4kjK9UOrU4SjbMXyX5TZYE+gjDhum5kvbhK3xl6PBZdaNVqaEBGHUWbt7ZKZ/1BnHJ6WmY8bNWYvp4N2OJVjuYh4MGX/mX9tGGtYVxWtXkXpLV+eiaWYGyeBlOki11CG2uddoDcN2tHUoammyvxjw3Z2sv1Edlv+vdV1IwO1Q+CNwE6Ux+SciDg8M5tOg3xEZu4VEc/Lsgbqy7S0L1yUPeZWoVyUfp5SknrkKTgR8a4sFeMOZeqpkE2mDh3Y4GcXpfXKjR2ue+qqijKU80zb/hIR+wBfpTyme9PCtO7qyoh4CbBsRGxCmS3QdH9HgJsj4qWUtbJQ2tx0ilZXU6egTPe6nrJVU1Cm/W9M2RbgC5T3klF0UkmZMiJ8F6VY0LywjPieHBF7UzrJNoqygffAaszfSqWJLjYHP5ZSXGR3hoqLNGnkkPdR1qjfCPMSzu9Tqko3kmW9//soHQyfAh5bp3P+S4Mkvqv98QbTNm+rnep/oJyPG4lSB+PNLDjA0vR10dUU4dcDh1DqStxAGRFtWt2WiPgIpY7AVUzMMZquT3/CoFMAIDNvrddsI+vlSGBEXE0Ha2hqL9P7KdMs31jXPn0sMxslFEPx265o9fPMbGO/walid9LTFC1XXaon2GMys409DIfjblC/HJxQBmsoXkq54G1SCOQkyt5BrZZ/r23+I+Uk+1bKtI7PZOa1DeMeR+ndH6yLfAmwZmbu1TDuYAThh5Qk8w/ABZnZuLT80PN28HlV4JTMfOKI8Z6TmSdHh5Ux54qIuJZu1j0N/44n00EV5Whxb86I2JByAbIj5QLhXGD/zPzfZq0s1e4oHZHzKo8CH2za8VLPEYcC21Pa/GPKFP3fNmvxvPgbAqtn5uUtxZtqtPXSzHxMkxGV6KiSctvq/2sj4D+YWHzqTsryh6aziQ6Y6ng22C8uahXxSTNSftpktGMo9oSKnVH2Sb4sm1fx3JLSqf5syvvykZl5cUQ8BPhJZm6w0ADTx92HkkxsA3yRuj9eZh7fsL2voWyxtCVlacKqlCmGhzeMexml0MqEOhOz7XXRtYj4OWUKaKsVg6PsQLADZUrw1rVT4LQmI/q9HAmku02xj6fMtR7cvo6GI0rQaUWrH0fE5lkK2rStk54mWq66VEfWNoiIFdq8WMzMXwNExNMnvUDfHREX06AaJPPXF7Zq0GZKoZI2N33dIjM3H7p9ZpTpdU0dUadDvI+ysHtVSidMGwYXy3fVN/KbgQePGiwzT66fW0/2otvqtq1Pv6ajjYphXqfOupRpm1DO843LiEcHe3PWZO95Tds2Tey7KElgmzNSoHSeTujVj4jXU4oHjaxeRG9IvSaJiEc0nQJZ3RURL2T+SM+ezH9tj9wJ3NVFbZ1SeBiwbmZuUR+X52bmh0aJV8/pv6Yk7a2JiC9l5suA2zLzkDZj011xEYDvRcSpzB/JfhFlRlFTh1JmjPxLZv7f4GBm/q6ODo4kJ+6PBy3tj5eZn69fnk07+3EO3J2Zn2orWHRUhXa6GTlDcZsW9bmOMsOu7W1jPkVZmvHAiPgwtVOgScC+JoFdbYp9FFM/UZuug+uqotV2wGVRqqS2ss5lSFcX6F1MHepiSstARMSOmXluvbEDDadYdjVqFBE7UqYWTp7H3vRN4uKI2C4zz6u/5wk0r5AKZaRnUBnrv+vn+0XE26Dx/+/k+jz7GGXqWNLCRt7TvJkN1ih9dsSRms6q20aL069jfmXUrjYqHi4jPjy9vY3z2Qcp58sJe3M2Cdj2Bf+k2F08zwDeHxH3ZOYP6u95J6X66shJYER8gfI/upL2lyXsQxlt/UyNeR7w0ijbZ/zzqEE77Hj5HGXq9WcBMvPyKNPcR3pORMSPMnOnWHBtZNMp2NvUzrFXR8QxNd482WzN8IciYg3g7ZTHeHXKzJTGMvOdUTZfH1S3PSIzv9lC3ClHhut9TbcJW4Xy/Epg5SaBBu+N02nhmueQ+p5xGhPP7RePGK+rKrSD648dKe9tX6u396JM4WzqLsqymsn1Nholl5M6BYIWOgX6Oh20k6kc9eQysBLwfOB3LfQqdKJOFVmLMsoIZb7ybUMjQqPGXQbYMzOPa9jERf2eDWlh6tA0U1oyWygCEhHbUNaerEF50d4KvLrBSXGqZG3wht4oWYuIayhvthcxtB1ANizLHGX69abMH5F5GPBz4F4adDrUi6PHUcs7U7YkuQD4BYw+Jak+f7fLzB/X2ysCK2ULazCjFH5Yh4k90XdQ3uBXr73rixuzy4I+rU2/jvkbFCeTLhopz4OmGxVfS1kz0XYZ8eHH+DLgsXU2QqMCDRFxNvWCP+cXffhZZm7RQntbf57VuA8Avl3bvStlTfneTWZRRMRVk2YKzHoRcSFTdLxk5nsbxh0UN7pk6DnRqPBOFyLiLZRqtg+nrKUafj03ei+KiIfmpOnFEfGgzPzDqDG7FmXd7X+w4IyJpu/J/0ZJTL5BvegHjh+1o2i66bsDTabx1vj/Qamx8EuGOnSynaI+K1DON0kpLtd45lZEnAfslHVadLS3bGmqZR/ZcAbNIPZgtstwR/3os12y5ZKrfkwo57oMZYP3pnHupLyB30GZynIfcEcLcfejzN3+AKV4y+W0tAUDdduFDh7TM2ZybDFj7jWTYw1/xxq0VDqaUnBnN8r02vsPPlqIe35H/7MNFvbRIO4PKXtxDm6vRtk/s402X9LRY7FAee/BMeDKBo/DCpTRuY9SEvlWylxT1lhC6RhYnXIhck3DmEdT1oQObq9FC1t70FEZ8Rr7+5TZDIdSEqtDmp7bh/7vlwwdu3S2Ps+G4jywvlccBc23SaCsIdq8o//bIynVr39Wb29JWVPVNG4n2woBp1AL19Tbe1LWIrf+2LT0+B7WQcx762tslaFjF7cU+wWUTsLbKddTd9LOtdSPKKMzl9f3tQNpYbsXSmfpSkO3V6YkQE1iLgu8taPnw7XACh3EfTbwW+ZvM/UbYLeWHt+1h26v1fTxrXH2m8mxEeK+GfgTZdbE5ZTr98ubxOzVdNAOp0ZMZxNaWAeXmasNvo6IoKwjaaOU776UEY+/1NgfoUytPLSF2N+PiHdQhtmHp1iONE0kSoXJVYAH1Gmmg57H1SmVnZp4L0NrORdybLFNnn5R/n3cTtl/7dIRw96emac0bNpwmwalw8+MiI9RpmG1MZVj8POD9ZGtFdWo1gWGewP/Wo+14Yw6sn9C1rNvS1aNiIcN/vaIeBgluYCJf8viaL267ZAupl9vmZm3DW5kqXDWeNSSMq37rIhotYx49TxKB9xbKVMM16B0nDXxp4jYmPmV//akvXXqrT7PpnjPXIEyCrRnRDR97zwG+ElE/IH2lyW0Or1ySCeVlCnTmT8LbBYRN1DWtn5t4T8yPpn5Bmj93H4FdSusiNgrM3/JgjMHRvVRuilKtXJmnhHlxfBr4MA6be/fGsb9HeVxHUzfXpEy8jqyLHUQ9gY+0bBtU/kZpW7FjS3HPRjYOWuRunre/A6l06SJ/wQuibLNUlDqbhzYMCaUiraT18q+copji2s/YNNscbZLr5LAzNypfl5tUd+7uGpydh/lImngD8C72/w99YL0xDqs36S4CJQn/X1Dt++jvZPti+rn4XK7yeiLkF8H7E8pzHAR89t5B2VN1GKLiN2AZwHrRcTwYubVKb2Rbdi2fpxcb+9O6cF5fUQcn5kfXYz2dpWsHTzp9jaDX0n5nzWayhEdFNWojgEuiIjBmo49KBXU2vA64G3AvRFxN+11FL2dcnEzuLDZCHhjRNyPMkK2WOrUkH/PUt227YI+ZOYb65eHR8T3aKdy4zIRsVZm3goQEWvTzntRV2XEGXSUVW2tyX0TZRP64Qv+tqoUt/o8m+l7ZkQ8KjOvXMzwR1I6MiZUFGzJKpl5Qe18G2jj3P4yyohK2x0vh1MuIK+jJJW7U9732uiYbV1EPIeyz1qb5/bMzM/UqdcnR8S7aVDEZ5KuilLdU5cR/CIi/pmSqK26iJ+ZVswvXHI7ZbuX0+vtp9Ngq6Ih50bEp1mwk75Rhy8lAbwmIn5Ku1un3JkTq5RfRxnFbSQzj4qIUyh7BAK8OxtMO47ut2T5LeU50ZpergnsSlvrOaaI+4Khm8tQkoonZ2ajil91lOoVlGpDUC+iM/OTTeJ2KSLenJmtvCFGxFaUTbYPYmKP3Z3AmYOL1Ia/44fAszLzz/X2qpQerF0po4EzXgtTe6umk9lw3n1EvJ2J67WSkmRf2GDUclA2ehcmFdXIzH2btLfG3pqhNa2ZeUnTmF2rawwHG2H/PJuX7e9iw+atF3Z/k4uFiHg58C/MH2nfC/hwNi+g0LqhEbBBh8i8u2hp9khNzJbJzMYXNZPitvo8m+HvXGBT8hn8zE+avpctJPYplETt+Cwl1fcE9s3MLvZ9bCzKtlLHUy4kn0hZa/icbH9P2FZ0cW6ftB7ywcBxwDaZuUoL7T2EUjH4RNotSvU4SvK7JqWI1BrAR7MWQxsh3lRryubJhsXhprmWaOMaoqt6G4dROhiOo5yH96J0+H2/xh/5/1dnlm3CxJHskfbzi+63ZDmSUl+htdkuJoEtioijgU9n5k9bjvtt5m+Wei/wv8Bv2rhoqhd7O9Wb5zS9iI6IXTLzB5MS13laONnuRdn7684opZe3Bj7U8KJ0+cz8W/16LeChLYx2DGJfAzx6KP6KlPVam0VLxTvaUqdJbUsptBLMH7XckHIRNeNRy0lxWy+qsSS0/OYw5ethKG6TN7FjKFUKW6tuuwQ6HDZn/gjzD7KFbWqi7Jn0LsooxPD/rHFRgi7UUbrzKFPfzhlhBG2qmJ2ef2fw+xf7nBYRn6FcPJ9MixfmNfbDKaOtO1CKcv0K2CebFz+7gumrr36oyXStKFVjT6Rc5D4/h7YcmG26OLdHxIMz8/dDt5cDdhj13Dsp9lFTHM5sXsFdHZrm/zYw8v8vyn6J+wHrA5dSlln9pI33jJoQbpKZ349SjXi5ph190cG+nL2aDroEPAHYJyJ+TbkYa2ttw0OA92bmFTBvyHl/5pfPHVlNnppOARj2ZMo+hs+Z6tfRvOz3+zPz+IjYCXgapYT/Ycwfzh/F6XXK4nKUqaY3RsSPM7ONstTHAudH2eAdyuPy5dr7P/KFb5T9kyZf7DZdo7Q+sPXQqOUBlB6nJ1Eel5GSQMpekatSCpgcGxE3MpSszEbTvTkw+tTYqV4PAyO9LmL+Xl3PpazvWIYy7aSxzNx5hm14emaePkL8q2inFPewYynTm3YHXk+Z5XDTQn9iBuqU2yszc7NFfvPi2Zxy3noi8LGI2JTSW/z8BjEnn38HicpgJLPTJJAFE6OZWJmS/D1jUpymHYbLAm/MzKd1MNp6CmX5xJfr7RdT1qz/gTIlfWGv96naOjmpXJsy3fT8iKCFa4iudHFuvyUiXsLQvpFV4yQQeHtOqksQERuNGiym2b9uYNRpkBFxXGa+cJrOhsbPhyhVnv8deEhm7lY75bbPzCMbxn0B8BFKLYygpRkTmfmqRX/XSPajVBg/LzN3jojNKI9LIxHxT8BrKa/jjSnXEYczf7/HkQySvfqaY3Ct1oQjgS2qmf8CWuh1HJ4i8iTKFJHdZ+sUkS4NepqjlCK+IjO/3HREbSjmayijgAfEULn9Ftr8OEpPNMC5mdloj7yIOJxywbEzZYPaPSlVHBtNr+xq1LJegA3W1Q2KahzbpLe8a/XNd/Dm8JjBm0NmLnREb0mKiKsoHSHfo+zlN8Hki52O2rDY0/+6EhEXZeY2MXGrjJ9m5uNaiH0SpXJy443nh2IuR3mOPZkyG+P+lCTwdS3EXomyRm1D5l9IZwsdRYv6vYv1fKiJ2kcy8x0dtee8bFjufZq4C/ydg2MRcUVmPnox40157TDQ9BqiK/Xc/n+UDqhWzu1R1h7fzoJbFU1euz5K7HMpVSXvqLf/gTLLZaRlPNNNfxwYdRrkYDS0w2vKUyjVff81y9Y/y1Gq2y7W83aKuNfSQeGdeg18CKUzNikdsm/NzOsaxh1syXIpZXuheyLiysxsVK+gxns8peL6YGrzYp8Xpoi7BWXwZ+166E/Ay5vMInEksEVdnagz87o6+nciZYrIM2bzFBGAKBUFX86k3rxsvmfiDRHxWcoC6Y/URKVpVbbloqw9eCHwrw1jTeViykLx5QBiqGrfiHbIzC3rxe4HIuJgmlfJgo5GLbObohpduzsz744IImLFzLymjtQ00nIP7OGU8vcbMX/zW5g/6tNoj6oZaquQVBv+Vj//vo6U/475b5ZNrUUp0HABE6fcNil4cAelGMp/AZ9ruVPkROA2yrlnsBZwSfT4Lta61CyVCndc9HeO7JIoBRqOZ+L/remI6LIR8fjMvAAgIh5PGbmDEQrPzNYkb1GGzu1/Z4pze4y23nP9zNy1ceOm9u+UYjPPpqytOoYGxZhGTfJmEPf39XNXz4sHZOZxEfHe+nvujYj7FvVDM9BV4Z0vA/9N2Xsbysj7V2g2Awzg+nqteiJlRtitQBuP+T2Z+deoBalqkt3G+fcI4G2ZeWaN+xRKBeQdFvIzC2USOIvN4SkiAN+lrHdpu+LbCylFVT6embfV5O2dgztjqOrgYjgIOBX4UWb+tPY6/aKNxkbEmyllv//I/OqrSdmvalSDDoC7IuIhwM3Ag5u0EyAzP1h7CAcXZa8fGrUc+Y0yFiwvD/PXz7y9aW9eR7p6c/gitQe23v5/lCmMi50EZuangE9FxGFZS7WPwWyaSvKhiFiDUhnzUEqV3/1biv3+luIM25syAvhG4DUR8WNKcaMzWojdyYV0TF0w6Hbg15l574ijbpd2lKhBmS5/MxOncbcxLXZf4KjBtCxK4Yd9a4fZfzSMvTRZadHfsoAfR8SjB8tf2pSZ34myIfhplKnzz8/M/9c0brS8Wfw075nQXkGqv0TE/Qe/IyK2o52qkxdGxNdoufAOpcrv8PKn/4mId0773TM0NPX+wCjr4NegzKxp6uyI+Bdg5Yh4OuUcf/IifmYm7jdIAAEy86x6zhmZ00Fnsbk6RQTGN01sNk1Pg3nTI57QZi9/RLyfcpG7C6V3DODzmdnFhWpjEfFB4HpKb15QevE2poxSvCEznzK+1i1anfKzBqUg0V/rsVE6G4ann8ybXhsRl2bmY1pt9BIym15vUQpz7Zd1D8IoW098PFsq+hATF/qvAiybLawxq1ONd6MkrA/MzJVbiHkEcGjbF9IRcR6lGNfllNfyFpSNi9egvJZPGyHm2Ip1RMR7M3Oxk7aI+DfK379mPXQbS2C67VwzyvmhTnN/BKWITyv7Rsb8LRcGngr8klJkr/EMpSgVmg+grM1+DvAqyhrUpvsEdiIitgE+RXn9/gxYB9grMy9rGLeT13KUPaxvBb5K+T++iDI742P1FyzW0of63jCtpkspomwXsi9lnXNQBhk+nw0TrijbYV3M/HogL6VUzh15HblJoDoREW+l7Jn4bSb2CHW6TilGq053FFMvvm58EVJ7l56eDUsDT4q5MvAGSkGJpFQXPCyXQAn4UcQU1eIGic9U980FoyY/EXEWZa3W6XX90HaUNVELXVsyW0XECTlL1klO9dof5XwwTex5C/0zc+Pa8394Zo680D8ivgFsRbkY/SHldXxBG6/jLi6ka9wTKMW5rqy3N6fMpHgXcMJc68xo8Dp++9DNlSjFiK5eEonrXDJiEtj6OrjofsuFwXrkeeu+BseaxO1SnaK4KeXc8POstQBmo4j41ULuzsUdca3xhrfDahRvSYlSsfwDDFX0Bw4cpUN6wOmg6spfKb00/8r8BGtJrFMapVfj20Nfr0SZd/67dprDdcBZEdHavi6UtRd3UnryoBQMOoYyVXY2uisiXgh8vd7ekyW7TqkLo66FextlK4eHRylSsA7l8ZhVYoZbDcyWBLDqahN6KBu7Px44HyAzfxERD2wY83zgVZl5Rx3d35+yx1gbe112tQ/eI3OoCEFmXhURm2VZtz5SwChbIhwGrJuZW0TElsBzM/ND7TR54b9+lB/KSUVKIuLjlN5+TbTYj+8g2auvr1Gmk04Vs+u16K1uFt+1KNvTfCwzDx869u3M3L1h3E5ey5k5cgXXJRFvIDqu6lrf25rW1ZjAJFBdeTvwiMz807gbsiiZ+Y3h2xHxFeBHLYX/Tf1YoX60YYucuMn8mbXnf7bah1LZ6zOUE+N5wEvriOY/j7NhDYyavF4FfBO4i5LIn0hZFzjbdL3VSxcOBn4SERM2oW8pdhcL/V+amR+Nst3NLsDHKcV+mhY76HKpwJVRNm7+ar39IuCqKAW6Rh1J+BxlXfdnATLz8ih7li6JJLCtTqhVKGXgNdHLFvcHomzXdDBla6wbKZuEX03ZEqmRKEWIDqwxl2P+CHnTzun9KM+Bt1A6cnamFMabrf4G7BwRTwBeV5c5rNdC3FZfyzPtjBzVotY4jxByv/r5i5TrnOtHbNoE0dFWJGASqO5cS7nQXdLaqFa4CWWfm8aywSaeC3FxRGyXmecB1BN5o20nupSl8Mt0+2a1lWzPFcdQqkIO9iJ6CWV+/15ja9EUsmyTsgxwSmYeN+72zERmHhMRFzK/CMgLsoVN6KsuFvoPqvE9m1Id9DsRsSQSnyZeSfnb96+3zwXeQb2oHDHmKpl5waSRxNamzy/CSO8Xk3r6l6WM6PduPWAsYl+4zPzZCGE/SNkK4PtZtm7ambL2qQ1HAm9l0vYTLUjKeXwDYPl67HM0KwDXpbsy80UR8S7gnIjYi3Y6RNp+LXfdGfkZJq5xfjRljeQaEbHYa5yzVnWljAIfAdxCKfx2fGb+sUE7P14/vwB4EPA/9fbelKKDIzMJVFf+Qqn6diYTp0GONJS9GAt5F3uNTkysxJWUF9W7FjfOpJifzMz9p+vBGaXnZujCY3lKBbXf1NsbANc0aW+XImId4J9YcLuQubx+ZtTOhjkzipuZf68XCXMiCYTONqEHeA9lof8VwOso1Y8/3zBmF9vddCrL1kQH14/JRt24+E8RsTHzKxXuCfx+4T/SmuMX/S1TGp42dy+lNP6SSlxnk4/S/r5wf8vMmyNimYhYJjPPjIhPthT79sxsYzulyY6ljIC1XQ29KwFQZyJcTKmW2sZ2Oq2+ljPzgPq5q83ifwfsO90aZ8rjsthq5/8H6nTYF1E6Ea/PzKeNGO/s2r6DM3PbobtOrh2fIzMJVFdOrB9tuYj5C3kfRqkUNajO9hvKXmkjFZ7JzNVqkrkJ89cgNO0VG1Rv+vhCv2vxNJqvP0YnURYwf592e19bFxGr1zVaU74hNulsqObUKC7w/Yh4B6U3c7h8f+cb0c8mmfl3Ss/+51oMu9DtbmajKabTAaOXwq/eROk13ywibqAUsxl5S5phsWDF2LWAgwcdUJn57wv58Wl1ON12ruliX7jbomy98UPg2Ii4kdE7GCY7MyI+RrnAH+6cvrhh3Jsy81sNYyxJ86qWZql2/ExgocVzZqjV13JEvG1h9zesrQAdrHGe5EbgD5RtatqYXXa/iHh4nV1FRGwEuEWEZqe65uthmfnzFmN+DvhmZn633t4N2CMzX9cg5msoc7nXBy6lTEX5SWbusrCfm2HsbTLzoknHds/Mb0/3M0ubmENbIAwWx09TPWzktSOTRnE3pXRczBvFnTQ6OGtMqso2781itlZP60qHa4nmlIi4himm02WDLXCGLvRWpoyE/oWyLueizLx05MbSbcXYPhtao/VkyvS0E2lpX7iIOJjSGbIMJYFYA9gqM/cdNeZQ7MEea4Nz2eB13Oi9PiKeSpmadwbt7o/XiYg4IydVNp7q2GLEm5ysDb+WR07WIuKAhd3fdLlNlD0Nb2HiGucHUNay/igzHzdi3DdSOvnWocw2OK6NpQkRsSslyb6O8tzdgLKmc+SiVI4EqhMR8RzKKNgKwEYR8RjgoCYLWKvtMvOfBjcy85SI+GjDmPsBjwPOy8ydo+zbNVIP8RQ+FxEvH6yNiIi9KetpepMEAt+OiGcNEvfZbFAdrYPqYXN1FPfdlP0RBxUst6as2embrtYSzTVdTKfbtn58i3Jh81LKGp3XR8Txmdnk/N5lxdg+G16jdRdlP7SBpmu1dq4j73+nVMImIi5vEG/YWVMca2Mk5FXAZpROvsF00FlXQCsiVqIUsHlAHRUfdHKuTrPCMKvVz5tSrqVOqrFfBlwwatCOaioMeyXtr3EGeCiwf9NOrMky83tRtifarB66JjPvWdjPLIojgepERFxEKdBwVs7fFPtnmblFw7inUqYWDhbG7gM8KTOf2SDmYAPvSykbu98TEVdmZhvVyB5O2RrhJZR9/V4O7J6ZtzeNPVfUNZf3o/SQ/o1JxQNmk2mqhc3TwrShOSUiLs/MLaNUsPwgpWPn3zKzcQXLuSQizu/b3zyViPhPSiGU1qbTRcQPgWdl5p/r7VWB71Cmyl7UZJQ8Il4O/AulNz4o27F8ODO/tNAf1IxExI6Zee6ijs0w1hsoF+QbUwrLDawGnJuZjYvDREf7O0bEzzNz00aNWwIiYj9KwvMQJm6DdQelONWnG8b/IfDszLyz3l4N+E5mPmnEeO+q6xYPZeraCq1ulzAXRMQOLFhf4ZhR49kjpq78LTNvnzSvuo0F03sDB1DK7Cdl3cDeDWNeHxFrUqa0nB4RtwKtrPmoc8tfXGP/BnhGLa7QG5m52qK/a9YYFLxYiTI6cRnl4nFLytq97cfUrnGZixUsWzPUKdDVWqK5ZpAIDxcnSOZXZB3FAxl6TCkdRetm5v9FRKNe7uy2YqzgUMrsgEUdm4kvA6cA/0EpxDRwZ1trkLO7/R1/HBGbz/bnVmYeAhwSEW/OzEM7+BXrUvaIHvhrPTaqwXrTTtbNd7TGuTMR8SVKJ8mlzH9vTkrV8ZGYBKorV0bES4Bl6/D1W4AfNw1a3wz2i4j7ZeZfFvkDM4v5/PrlgXXNwBrA95rEjAU3C12b0oN+fkQ03jR0LqgLrK+ZbnRtNl5AZ+bOABFxArB1Zl5Rb29BebPomzlXwbJlk6tgtpn8zDmD10fLjqWcF0+qt58DfDki7seIlV4nFXj6AyXBGNy3dt8KG7UtIrYHdgDWmbQebHXK+9xiq7Njbqd5p+7iaGt/x+0o1dB/RenQGMx2mVXv81H33aOc1xfYe6+FNYzHABdExDfr7T0oe+aNJDNPrp+Pbtiu6cy1af7bAptni1M4nQ6qTkTEKsC/Mn+twKnAhzLz7oZxd6CUZl81Mx8WEVtRFsa+sVGDWxYRGyzs/qzV5YbXqyxtIuKIzHzt0GJ8mFhcZNZeQE81HbitKcJzSX0d7wpckZm/iFLB8tG5mPsnzXXDFdkWdmxpFxFrUGZiDKZ3nU1Z691oentEbAvsWG+em5mNev6nKPA07y56WNCnbRHxZOApwOuBw4fuuhM4OTN/MY52LUpMs79jC9Mgp3y/z1lWRTYiPpBlD9ijprg7m06Lrb9ja8rSF4AfZuYlLcR8JGWt3oZMHLFrWtBnTk3zj4jjgbfk/P0Im8c0CdQ4RMShmfnmEX7ufMq6jm+1udZwXCLi4swcZerMnBERL2SK4iKzcSRwICK+QqlsNrz2dNXMXJK91JolpnqdRsRFmbnNuNo0DhHxDcpmyoOe+ZdRKjcuMKowThGxU2b+KCJWatrxqOlFxAazLdFZmEnJWp/3d5xTIuIySmfD5KrEF037QzOL2/oa5y7VDvXHUIrtDLd35IKLTgfVuOy46G+ZWmb+dtJaw7kwjD+dVjajmeXel5nH1eIiu1CKixzG/PVFs9GrgDdQKsdCWXt62Piao3GolYIfBawxafrU6szfU7RPNs7Mfxy6/YFaUGu2OQTYhrIEYanuZBuzL0bEVAU7ZuUsj7mUsHYpIn4JnEcpsndODu2VN0vdm5ldvP92sca5Swe2HdAkUHPNb+uU0IyI5SkX6W1vVrsk9WEofs4VF6mjB5+oH+qvTSkVBNdkYln8O4F/muoHlnL/Nxhlg3mFFWZjoau/RcQRwPoR8anJd/axqmBH3jH09UrAP1JG2DS7bU5JgJ4IfCwiNgUuH6qPMCvUNb0AJ0fEm1hwxK7R2t6O1jh3JjPPbjumSaDmmtdTennXA24ATqOUldbsNeeKi0yxlgiYvVXD1I3MPAk4KSK2z8yfjLs9s8AbgKPr2kCAW4FXjLE909kdeBrwTMoUMnVgiul450bEyPvCaYm5j1KF9z5K1fYb68dscxHlfXgwY+rtk+5v/H4cEc+mzPaYN7MjMw9qGrdNEfGjzNwpynZbU61xHnm7LZNAjcuo0yA3zcx9JgQqvdGLvS/RLNGH6aAvpBQX+Xhm3laLi7xzzG1alOHpISsBe1EqvKqfbo6IMyhbF2wREVsCz83MWT2i3YGrgY9SypSvSanmuAdlc/dZIzP/BHw1Iq7OzMvG3Z6l1dBIDZSOvW0o1bU1u90BXAH8F2V2zs1jbs+UMnMjgIhYmdLZvxMlCTqHiQWJRhIRh1MqxO5MKTi4Jw02t+9KZu5UP7e+3ZaFYdSpiFid0lNx56Tjr8zML44Qb6oCDbOuuMqkN8cFDKYxWK587uhjIRAVEXE2pePis0tDQapRRcT3gNuAi5lYoGHyVhpjFW4yvUQMzZgIyjTQX1Gqbf5orA3TQkXE8ygJ1eMpe/n9mFLJ84yxNmwaEXEcJXE9th56CbBGZr6wYdzLM3PLoc+rAqdk5hMX+cNLCUcC1YmIeBzwBWC1cjNuA149mD6yuAlgF/sSdWx4GsPDKNOmgtJ7/htgI2g+p13dmLS34TKUkUHPl/21SmZeMKkgVR/XPq2fmbuOuxEz0Okm0yoGIzWaW4amuW8G7AbsD7wLWHmc7VqILTJz86HbZ0bESHuITjJYz3xXRDwEuBl4cAtx5wwvatSVI4E3ZuY5UEp2A0cBo26eugKwKuU5OzwkfgdlCH9WGZrG8Dngm5n53Xp7N8r0Kc1uwyMb9wL/S5nWqn76U0RsTB1Viog9gdb2appDfhwRj87MK8bdkIVZAptMC6jF2d7A/H0jz6KMlv9tbI3SItWtXrYCfkmpfP0yZuE0yCEXR8R2mXkeQEQ8gXY6eL4dEWtSprgP1rd+voW4c4bTQdWJiLhkMG1q6FjjaZtzcF+iKzLz0Ys6Jmn2ioiHA0dQZiPcSpn2ts9cOhc1MbTJ9nLAJsB1lCp9g8IEo3budSoiTgf2yszb6u21gK9m5jPH2rClRER8HlieiftG3peZrxlfq7QoEfEu4PChvXsfS9m7t/HG7l2IiKsplZp/Uw89DPg5pYN25PNPXWv4BkqV1MFaw8P6tLeoSaBaNTSN7uWUqQVfoby4XgTcnZlvm+5nFxH3k5m5f0SczNRrPEbeLLNLEXEq5cQyvOn4k7wImf3mQtUwLRm1ou2ewIaUAkF3UC4+evF8mLTJ9gJmazIcEZdm5mMmHVugg1KjiYjLMnOrRR3T7DK0Bm4n4IOUvXv/LTNn5d69XZ1/6lrDO5l/fdbKWsO5xOmgatvkAgEHDH3dpMfhS/XzxxvEGIe9KY/BNyl//w/rMc1ic6VqmJaYk5hfEOV3423Kkjdbk7wZuC8iHpaZv4F5F5P2fLfnvojYODN/CfNGzO9bxM9o/ObU3r0dnn+6Wms4ZzgSKC0BEXG/zPzLuNuhmbFqmIb1sRLo0iAidqVM4z2bMnX1icBrM/PUsTZsKRERuwBfpEwPhjJS/qrMPHNcbdKiRcS3KfssPx3YmlIg5YK+jeBGxP8An5601vBNmfny8bZsyXEkUJ3pYjpd3RPwQGADyvN3sCZlVm7iHRE7UEaSVgUeFhFbAa/LTDe4n90GawIGVcNuoWdVwzTBnCiIooky83t1icJ29dD+dQ9BteP+wBaU5G8PYHvK3pGa3ebi3r2tGVrjvDzl3P6bensD4Jpxtm1JMwlUJzqcTnck8FZKJae5MO3kE8AzgW8BZOZlEfGkhf+IZoGTa9Wwj1GmACbwubG2SOO0E/DKui/arC+IognuA26kdEZuHhFk5g/H3Kalxfsz8/i6H/DOlOUahwGzcm2Zisy8Czhh6Pbv6Ve1493H3YDZwiRQXdlhaDrdByLiYOCUFuLenpltxFliMvO3k/YXmwvJa99dQ6ly942I2JwyZebE8TZJY7TbuBugxRcRrwH2A9YHLqWMCP4E2GWMzVqazKm1ZRLM6TXOrVtm3A3QUmvydLq/0c50ujMj4mMRsX1EbD34aCFuV35bp4RmRCwfEe9g/kbGmr3en5l31uppu1BGsw8bc5s0Jpn566k+xt0uLdJ+wOOAX2fmzpRS+LeNtUVLlxsi4rOU6t/frVV0va6U5ghHAtWVrqbTDaaZbFM/R409W3t2Xw8cAqxHWYh9GuB6wNnPHm5p7rs7M++OCCJixcy8JiI2HXejliK9XlsmzXUmgWpdRCwDnFE36P1GrUS1Uma2sWD8rCmOzeYSt5tm5j7DB2pxm3PH1B7NzKCH++nAR+zhluak62tn5InA6RFxK+AIbktcWybNbW4RoU50tSFvRLx96OZKlAW+V2fmq9v+XW2IiIszc+tFHdPsEhGrUHq4r8jMX9Qe7kdn5mljbpqkEUTEk4E1gO9l5l/H3R5JGjeTQHUiIj5OWYB/Qnb4JKsjNKdm5lO6+h2jiIjtgR2A/SkVQgdWB57ft/14JGkc6prxnSgzRs7NzIvH3CRJmhWc3qSuvA44HrgnIu6IiDsj4o4Ofs8qlMpvs80KlL0BlwNWG/q4g7JdhiSpQxHxb8DRlP3sHgAcFRHvG2+rJGl2cCRQc8rQJp8AywLrAAdl5qfH16rpRcQGVhGUpCUvIn4ObJWZd9fbKwOXZqbFYST1noVh1JmIWAvYhLJ2D6CNTXqHN/m8F/hjZt7bMGbrIuKTmbk/8OmIWKCnJTOfu+RbJUm98jvK+89gy6IVKVWaJan3HAlUJ6bbpDczZ+tWDq2KiG0y86JajGABmXn2km6TJPVJRJxI2SfwdMoMkqcDFwDXA2TmW8bWOEkaM5NAdaJO23wccF5mPiYiNgP+PTNfMOamSZJ6ICJesbD7M/PoJdUWSZptnA6qrrhJL/P2BDwQ2IDyegsgM/Ph42yXJC2tIuII4BRKdeo7x90eSZqNTALVFTfpLY4E3gpcBNw35rZIUh8cCewGvC0i/gqcRtkf8LLxNkuSZg+ng6pzU23SGxFrZeat421Z9yLi/Mx8wrjbIUl9FBH3B55BSQq3BC6mvBcdN9aGSdKYmQRqLCLi4szcetzt6FpE/CdlK4sTgHsGx92wWJKWvIjYBtg1Mz887rZI0jg5HVTjEuNuwBIyGAXcpn4OSpW6XlRJlaRxiohnA49i4lZFB42vRZI0O5gEalz6MgR91hTH+vK3S9LYRMThwCrAzsDngT0pW0RIUu8tM+4GSEu5Pw993AvsCmw4zgZJUk/skJkvB27NzA8A2wOPHHObJGlWcCRQ49KL6aCZefDw7Yj4OHDqmJojSX3yf/XzXRHxEOBm4MFjbI8kzRomgWpVRKy9sPsz85b65VOXQHNmo1WA9cfdCEnqgW/XrYo+RqkKmpRpoZLUe1YHVasi4leUN9oAHgbcWr9eE/hNZm40vtYteRFxBfPXAC4LrAMclJmfHl+rJKlfImJFYKXMvH3cbZGk2cCRQLVqkORFxOeAb2bmd+vt3YA9xti0cdl96Ot7gT9m5r3jaowkLe0iYpfM/EFEvGCK+8jME8bRLkmaTRwJVCci4orMfPSijkmS1KaI+EBmHhARR01xd2bmq5d4oyRpljEJVCci4lTgHOB/6qF9gCdl5jPH1ypJkiRJbhGhruxNWf/2TeCE+vXeY22RJKk3ImK/iFg9is9HxMUR8Yxxt0uSZgNHAtWpiLhfZv5l3O2QJPVLRFyWmVtFxDOB1wPvA76UmVuPuWmSNHaOBKoTEbFDRFwFXF1vbxURnxlzsyRJ/THYj/ZZwDGZeSU92aNWkhbFJFBd+QTwTMrmvGTmZcCTxtoiSVKfXBQRp1GSwFMjYjXg72NukyTNCm4Roc5k5m8jJnS63jeutkiSemdf4DHA8sC2wAOAL46xPZI0a5gEqiu/jYgdgIyI5YH9qFNDJUlaAl5Nee9ZH7gU2A74CXDoGNskSbOC00HVldcDbwLWA26g9Ma+cZwNkiT1yn7A44BfZ+bOwGOB28baIkmaJRwJVFc2zcx9hg9ExI7AuWNqjySpX+7OzLsjgohYMTOviYhNx90oSZoNHAlUV6aabuMUHEnSknJ9RKwJnAicHhEnAb8ea4skaZZwJFCtiojtgR2AdSLibUN3rQ4sO55WSZL6JjOfX788MCLOBNYAvjfGJknSrGESqLatAKxKeW6tNnT8DmDPsbRIktRrmXn2uNsgSbNJZOa426ClUERskJlOu5EkSZJmGZNAtSoiPpmZ+0fEycACT67MfO4YmiVJkiSpcjqo2val+vnjY22FJEmSpCk5EihJkiRJPeJIoDpR9wQ8ENiA8jwLIDPz4eNslyRJktR3jgSqExFxDfBW4CLgvsHxzLx5bI2SJEmS5EigOnN7Zp4y7kZIkiRJmsiRQHUiIv6Tsjn8CcA9g+OZefHYGiVJkiTJJFDdiIgz65eDJ9hgTeAuY2qSJEmSJJwOqu6cNcUxexwkSZKkMTMJVFf+PPT1SsDuwNVjaoskSZKkyumgWiIiYkXg1Mx8yrjbIkmSJPXZMuNugHpjFWD9cTdCkiRJ6jung6oTEXEF89cALgusAxw0vhZJkiRJAqeDqiMRscHQzXuBP2bmveNqjyRJkqTCJFCSJEmSesQ1gZIkSZLUIyaBkiRJktQjJoGSJC0hEbF/RKwy7nZIkvrNNYGSJC0hEfG/wLaZ+acp7ls2M+9b8q2SJPWNI4GSJA2JiJdHxOURcVlEfCkiNoyIH9RjZ0TEw+r3fTEi9hz6uT/Xz0+JiLMi4usRcU1EHBvFW4CHAGdGxJmDn4mIgyPiMuBfI+LEoXhPj4hvLsm/XZLUD+4TKElSFRGPAt4H7JCZf4qItYGjgaMz8+iIeDXwKWCPRYR6LPAo4HfAucCOmfmpiHgbsPPQSOD9gPMz8+0REcDVEbFOZt4EvAr4Qtt/oyRJjgRKkjTfLsDxgyQtM28Btge+XO//ErDTDOJckJnXZ+bfgUuBDaf5vvuAb9TflTX+SyNizfp7Txnpr5AkaSEcCZQkaTT3UjtTI2IZYIWh++4Z+vo+pn+/vXvSOsCjgJOBuynJ6L3tNVeSpMKRQEmS5vsBsFdE3B+gTgf9MfDiev8+wDn16/8FtqlfPxdYfgbx7wRWm+7OzPwdZQrp+ygJoSRJrXMkUJKkKjOvjIgPA2dHxH3AJcCbgaMi4p3AYK0ewOeAk2pRl+8Bf5nBrzgC+F5E/C4zd57me44F1snMq5v8LZIkTcctIiRJmkUi4tPAJZl55LjbIklaOpkESpI0S0TERZQRxadn5j2L+n5JkkZhEihJkiRJPWJhGEmSJEnqEZNASZIkSeoRk0BJkiRJ6hGTQEmSJEnqEZNASZIkSeoRk0BJkiRJ6pH/DzjeL3RQbNj9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "sns.countplot('country', data = df, palette='hls') \n",
    "plt.xticks(rotation = 90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "46e5697e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.028134Z",
     "start_time": "2022-05-24T08:22:15.018646Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "select                               3380\n",
       "finance_management                    976\n",
       "human_resource_management             848\n",
       "marketing_management                  838\n",
       "operations_management                 503\n",
       "business_administration               403\n",
       "it_projects_management                366\n",
       "supply_chain_management               349\n",
       "banking,_investment_and_insurance     338\n",
       "travel_and_tourism                    203\n",
       "media_and_advertising                 203\n",
       "international_business                178\n",
       "healthcare_management                 159\n",
       "hospitality_management                114\n",
       "e-commerce                            112\n",
       "retail_management                     100\n",
       "rural_and_agribusiness                 73\n",
       "e-business                             57\n",
       "services_excellence                    40\n",
       "Name: specialization, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.specialization.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5c1eddb4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.583899Z",
     "start_time": "2022-05-24T08:22:15.031743Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rtoVhDgeOBtarX9+pYxEREREREdEjs00C17F9uO1b69dngXXmMK6IiIiIiIiYA7NNAq+V9AJJy9evFwDXzmVgERERERERsezNNgl8KfBs4CrgSuCZwIvnKKaIiIiIiIiYI7NtEbEvsJvtPwNIWgv4b0pyGBERERERET0x25nALQcJIIDtPwHbzE1IERERERERMVdmmwQuJ2nNwY06EzjbWcSIiIiIiIhoxGwTuQ8BP5P01Xr7WcD75iakiIiIiIiImCuzSgJtf07SQuBRdejpti+cu7AiIiIiIiJiLsx6SWdN+pL4RURERERE9Nhs9wRGRERERETECEgSGBERERERMUaSBEZERERERIyRJIERERERERFjJElgRERERETEGEkSGBERERERMUbmLAmU9BlJV0s6f2hsH0lXSDq7fj1+6L63S7pE0i8kPXZofJc6domkt81VvBEREREREeNgLmcCPwvsMsn4R2xvXb+OBZC0BfAc4AH1dz4haXlJywMfBx4HbAE8tz42IiIiIiIi7oBZN4tfWrZ/LGnjWT78KcCXbd8M/FrSJcD29b5LbF8KIOnL9bFpWh8REREREXEHdLEn8DWSzq3LRdesY+sDvx16zO/q2FTjS5C0u6SFkhZec801cxF3RERERERE7813EngwsCmwNXAl8KFl9YdtH2p7ge0F66yzzrL6sxERERERESNlzpaDTsb2HwY/S/oUcEy9eQWw4dBDN6hjTDMeERERERERS2leZwIlrTt082nAoHLo0cBzJN1Z0ibAZsBpwOnAZpI2kXQnSvGYo+cz5oiIiIiIiFEyZzOBkr4EPAJYW9LvgL2BR0jaGjBwGfBKANsXSDqKUvDlVmBP27fVv/Ma4PvA8sBnbF8wVzFHRERERESMurmsDvrcSYYPm+bx7wPeN8n4scCxyzC0iIiIiIiIsdVFddCIiIiIiIjoSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSJLAiIiIiIiIMZIkMCIiIiIiYowkCYyIiIiIiBgjc5YESvqMpKslnT80tpak4yX9sn5fs45L0kclXSLpXEnbDv3ObvXxv5S021zFGxERERERMQ7mcibws8AuE8beBpxgezPghHob4HHAZvVrd+BgKEkjsDewA7A9sPcgcYyIiIiIiIilN2dJoO0fA3+aMPwU4Ij68xHAU4fGP+fiVGANSesCjwWOt/0n238GjmfJxDIiIiIiIiJmab73BN7D9pX156uAe9Sf1wd+O/S439WxqcYjIiIiIiLiDuisMIxtA15Wf0/S7pIWSlp4zTXXLKs/GxERERERMVLmOwn8Q13mSf1+dR2/Athw6HEb1LGpxpdg+1DbC2wvWGeddZZ54BEREREREaNghXn+944GdgM+UL9/e2j8NZK+TCkCc53tKyV9H/ivoWIwjwHePs8xR8RS+u+Fe3Qdwu3etOCQrkOIiIiIaMqcJYGSvgQ8Alhb0u8oVT4/ABwl6WXA5cCz68OPBR4PXALcCLwEwPafJO0HnF4ft6/ticVmIiIiIiIiYpbmLAm0/dwp7nr0JI81sOcUf+czwGeWYWgRERERERFjq7PCMBERERERETH/kgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGVug6gIiIWDp7LNyv6xBud8iC/+w6hIiIiFhKSQIjImJO7bHw812HsJhDFryw6xAiIiI6leWgERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBhJEhgRERERETFGkgRGRERERESMkSSBERERERERYyRJYERERERExBjpJAmUdJmk8ySdLWlhHVtL0vGSflm/r1nHJemjki6RdK6kbbuIOSIiIiIiYhR0ORP4SNtb215Qb78NOMH2ZsAJ9TbA44DN6tfuwMHzHmlERERERMSIaGk56FOAI+rPRwBPHRr/nItTgTUkrdtBfBEREREREb3XVRJo4DhJZ0javY7dw/aV9eergHvUn9cHfjv0u7+rYxEREREREbGUVujo332o7Ssk3R04XtLFw3fatiQvzR+syeTuABtttNGyizQiIiLG1h5vXdh1CIs5ZP8FMz8oImIGncwE2r6ifr8a+CawPfCHwTLP+v3q+vArgA2Hfn2DOjbxbx5qe4HtBeuss85chh8REREREdFb854ESrqLpLsOfgYeA5wPHA3sVh+2G/Dt+vPRwItqldAdgeuGlo1GRERERETEUuhiOeg9gG9KGvz7X7T9PUmnA0dJehlwOfDs+vhjgccDlwA3Ai+Z/5AjIiIiIiJGw7wngbYvBbaaZPxa4NGTjBvYcx5Ci4iIiIiIGHkttYiIiIiIiIiIOZYkMCIiIiIiYowkCYyIiIiIiBgjSQIjIiIiIiLGSFfN4mMGCz+8R9ch3G7BGw7pOoSIiIiIiFhGMhMYERERERExRpIERkREREREjJEkgREREREREWMkewIjeuBrC9vZI/rMBdkjGhEREdFnSQJjLJ3eUFK1XZKqiIiIiJhHSQIjIiKG7LHwx12HsJhDFjys6xAiImLEZE9gRERERETEGEkSGBERERERMUaSBEZERERERIyRJIERERERERFjJElgRERERETEGEkSGBERERERMUaSBEZERERERIyRJIERERERERFjJElgRERERETEGEkSGBERERERMUaSBEZERERERIyRJIERERERERFjZIWuA4jRsPDre3Qdwu0WPOOQrkOInnntwnaevwctyPM3IiIi5lZmAiMiIiIiIsZIZgIjIiJ6bI9jF3YdwmIOefyCrkOIiIgZZCYwIiIiIiJijGQmMCIiIiIimrBwjyO6DuF2Cw7ZresQ5kxmAiMiIiIiIsZIksCIiIiIiIgxkiQwIiIiIiJijGRPYERERMybPQ5urJrpq1LNNJbO9/Zo5zm8yyF5/sYdkyQwIiIiYoS8vaEk5f1JUiKalOWgERERERERYyQzgRERERERI2rhHid1HcLtFhzy8K5DiCozgREREREREWMkM4ERERERERF3wMI99u06hNstOOTds35sb5JASbsABwLLA5+2/YGOQ4qIiIiIf9EhDRWy2SOFbGJM9GI5qKTlgY8DjwO2AJ4raYtuo4qIiIiIiOifXiSBwPbAJbYvtf0P4MvAUzqOKSIiIiIionf6kgSuD/x26Pbv6lhEREREREQsBdnuOoYZSXomsIvtl9fbLwR2sP2aocfsDuxeb94P+MUchLI28Mc5+LtzqW8xJ965lXjnVuKdW4l3biXeuZV451binVuJd27NVbz3sr3OZHf0pTDMFcCGQ7c3qGO3s30ocOhcBiFpoe1e7RjuW8yJd24l3rmVeOdW4p1biXduJd65lXjnVuKdW13E25floKcDm0naRNKdgOcAR3ccU0RERERERO/0YibQ9q2SXgN8n9Ii4jO2L+g4rIiIiIiIiN7pRRIIYPtY4NiOw5jT5aZzpG8xJ965lXjnVuKdW4l3biXeuZV451binVuJd27Ne7y9KAwTERERERERy0Zf9gRGRERERETEMpAkMCIiIiIiYowkCYyIiIiIiBgjSQJnIGmv2YzF+JC0/2zGWiHpzrMZa0EfX2+S1pS0paRtB19dxzSdvh1jSc+azVhrJK3SdQxLS9JyklbrOo7pqHiBpHfX2xtJ2r7ruKbSw9fbQ2YzFnecpM/PZqxFg8+7ruOYjqQTZjMWSQJnY7dJxl4830EsDUnrSHqHpEMlfWbw1XVcU5H09Em+Hi3p7l3HNoWdJxl73LxHMXs/m+VYC3r1epO0H3Au8FHgQ/XrvzsNama9OsbA22c51gRJD5Z0IXBxvb2VpE90HNaUJH1R0mqS7gKcD1wo6c1dxzWNTwA7Ac+tt28APt5dODPq2+vtoFmONUHSPSQdJum79fYWkl7WdVwzeMDwDUnLA//WUSwzkvSj+h6xFnAm8ClJH+46rokkrVRjXLsmq2vVr42B9TsOb1KSDqjHdkVJJ0i6RtIL5uvf702LiPkm6bnA84BNJA03pr8r8Kduopq1bwM/AX4A3NZxLLPxMsqH+on19iOAMyjHfl/bTVwhk/Qq4NXAvSWdO3TXXYGTu4lqapLuSXnjW1nSNoDqXasBTc1S9Pj19mxgU9v/6DqQmfTtGEt6HPB4YH1JHx26azXg1m6impWPAI8FjgawfY6kh3Ub0rS2sH29pOcD3wXeRnn//WC3YU1pB9vbSjoLwPafJd2p66Am6uHrbSfgwcA6kt4wdNdqlP7MrfoscDjwznr7/4CvAId1FdBUJL0deAflM/n6wTDwD9puZ7B6fY94OfA523tPOAdqxSuB/wDWo7yHDc55rgc+1lFMM3mM7bdIehpwGfB04MfAF+bjH08SOLVTgCuBtSlX9wduoFz5b9kqtt/adRBLYQXg/rb/AOXKHvA5YAfKi6GJJBD4IuUk6f2UE6WBG2w396FOORF9MbABMHzV7gbKB1FL+vp6Ox9YA7i64zhmo2/H+PfAQuDJlA/0gRuA13cS0SzZ/q2k4aGWL8atKGlF4KnAx2zfIqnl3lG31JkTQ1n5Avyz25Am1bfX252AVSmfx3cdGr8eeGYnEc3O2raPqgkWtm+V1OTrzfb7gfdLer/tZlczTGIFSetSLnq+c6YHd8X2gcCBkl5ru9nZ6wkGedgTgK/avm7CZ8e8/OMxge3Lgcvr1dHf274JQNLKlJPqyzoMbybHSHq87WO7DmSWNhwkgNXVdexPkm7pKqiJbF8HXAc8t56E3IPyGlpV0qq2f9NpgBPYPgI4QtIzbH+963imM3i9UWaE++T9wFmSzgduHgzafnJ3IU2ub8fY9jnAOZK+aLuZ94FZ+K2kBwOuydVewEUdxzSdT1I+z84BfizpXpQT/1Z9FPgmcHdJ76MkKO/qNqQl9fD1dhJwkqTP1tj74m+S7saiiwI7Uj6nm2X77ZLWB+7F0Hm47R93F9W09gW+D/zU9umS7g38suOYpmT7oPoevDGLH9/PdRbU1I6RdDHwd+BV9aLWTfP1j6dZ/AwkLQQePFjuVZednGx7u24jm5qkG4C7UJYYDE6ebLvJDf91v8xGwFfr0DOA3wFvBo6x/ciuYpuMpNcA+wB/YNEVaNtucrO0ShGYZ7DkG+K+XcU0FUlPB/YH7k5ZyiHafu5eQDmJPo+h2Yh6QtWkHh7jh1Beb4MTpkG89+4yrqlIWhs4EPh3SqzHAXvZvrbTwJaCpBVsN7vkVtLmwKMpx/cE280m2T18vd0XeBNLfl48qquYpqNSiOsg4IGUlRnrAM+03eJsKwCSPgA8B7iQRasE3OLFwz5SKbKzKXA2ix/f13UW1DTqPsbrbN+mUlBsNdtXzcu/nSRwepLOtr31hLFzbG/VUUgjR2Xu+xnAoALZycDX3eiTU9IllH0pvTipk/Q9ypXRMxhalmb7Q1P+UkfqsX1Syyd1wySd3vIFocn08BhfTFn+OfH524vXX+tUKlUeTlmm+GlgG+Btto/rNLAp1JmeC2zfUG+vRtlO8PNuI5tcD19v5wCHsOTr7Ywpf6ljklYA7kdJsH/R+soBSb8AtrR984wPboCkA4D3UmarvgdsCbze9rzsW1taki6i7HVu8hxymEql6+/ZvkHSu4BtgffaPnM+/v0sB53ZNZKebPtoAElPAf7YcUwzkvRkYFCM4Ee2j+kynunUF+rX6lcf/JbGl5tMsIHtXboOYpb+0JeTpeonkt5PKQIyvBx0Xt7A76C+HePrbH+36yBmS9IRlJm/v9TbawIfsv3STgOb2kttHyjpscCawAsp+7CbTAKBgyknSgN/nWSsJX17vd1q++Cug5gtSXsCR9q+oN5eU9JzbTdbkRe4FFiRoc+MxnVavOQOOB+4J2VPbuv+0/ZXJT2Usnrkg5T3sx3m4x9PEjizPYAjJX2csub8d8CLug1penWpwXbAkXVoL0kPaXUjct+Wy1DewH8k6X9Z/MS/uZLJ1SmSHmT7vK4DmYWFkr4CfIvFj+03OotoetvU7zsOjRloculU1bdjfKKkDwLfoB+J9paDBBBur165zTSP79qgCsHjgc/bvkDzWZlg6Wn4Cr/tf9aZoFb17fX2HUmvpuy7HI63xeJnAK+wfXuLkPp6ewWllUirbgTOVuldN3yMm1yuSMfFS+6AtSmtbk6j8b36LJptfwJwqO3/lfTe+frHW37jbILtXwE7Slq13v5rxyHNxuOBrW3/E26/Mn0W7fbWOoAeLZcBflO/7lS/WvdQ4MWSfk15Qxwk2S3uYVyN8gH5mKExUxKA5rS2X3WWenWMWXRFdMHQWMuJ9nKS1rT9Z7h9v0fLn7VnSDoO2AR4u6S70ma1zYFLJb2OcrUcStueSzuMZyZ9e70N+hoO94o00OQeXGB5SbdfGKhF21r/XD66fvVFp8VL7oB9ug5gKVwh6ZOU/tP71xoO89bDPXsCZ6DSruC/gPVsP07SFsBOtpvrQTOg0r/lEYMrd/Uk5EeNnvQj6WTbD5n5kW2RtIrtG7uOYya12t8SelYBrkkT9lN9irIkrdn9VDH3JL2I0oLlq5QLLs8E3udG+p1OJGk5YGvgUtt/qZUW12+1sIaku1MqhD6KkpycAPyH7T60aYllrK4SuBelQBeUXnG/tf3G7qKaWa00v5HtX3Qdy2xMKF5yF+Cu81W85I6o5z2b2f5BLbay/GAfcUtqbLsA59n+pUorjgfN1znEvGWbPfZZSmnc9ert/6M0o2zZoGz9Z+ss4BnA+zqOaToLJX1F0nMlPX3w1XVQU5G0k6QLgYvr7a1qhdMm1WRvQ+BR9ecbafS1L+m+kk5QabmApC3rZulWvdT29ZSr/Hej7Kf6QLchTa9vx1jSPSQdJum79fYWkl7WdVxTcSlD/gxK9eCrgKe3mgBWBrYABkvR7gKs1F04U6uzPB+x/Rzbd7d9D9vPazkB7OHrbRVJ75J0aL29maQndh3XNN4KnAi8qn6dALyl04hmIOlJlMqV36u3t5bU7MxgTVRezaLZ9/VYfGVGU+py4K+x6MLA+pTl2M2pEwlXU1ZsAdzKPLbfaPJEsDFr2z6Kujymls1ushHpgO0vUfYofQP4OmXm8ivdRjWt4eUyT6pfLX/o/A+lEfu1cHs/s4dN9wtdkrQ35YNysBx4Rdrd0P0pSpy3ANTZiOd0GtH0hvdTfa4WJ2h6swT9O8afpX8X4i6mvP8eDfxV0kYdxzOdT1B62T233r4B+PjUD++O7duAe6m0auqLvr3eDqe0l3pwvX0FpTJkk2z/0/bBtp9Zvz5Znyct2wfYHvgLgO2zaXe5LfTsOQHsSak2fz2A7V9Sak40p+vzs5b3KbSiN41IJW1u+2KVvjlQitgArCdpvVYLKdh+SdcxLC3bv52wMbrlD52nUQqYnAlg+/d130+LVrF92oRj22y/Mvq3nwr6d4zXtn2UpLdDuRAnqdnXm6TXAntTZgJvo+7BpZRVb9EOtreVdBbcXlij5STrUuDkOnPyt8Fgw4W5+vZ629T2rpKeC2WmouVCQepZH9HqlkmKq7T8udGr5wRws+1/DEKshaNa3fvW6flZksCZvYFyNXdTSSdTG5F2G9KU3gDsDkzW/625QgqS3mL7AEkHMckLtOFKWb+V9GDAklYE9gJaLmrzD9uWNLiQcZeuA5rGHyVtyqKLLs+k7TLPL2PRfqob6wWj1i9q9O0Y9+ZCXLUXcD/3p4/hLXWZ5eD4rkPbJ6S/ql/LAa1ezBrWt9fbP+p+tUG8m9J2K4PDmKSPaOMukPQ8SlGbzShLsU/pOKbp9O05cZKkdwArS9qZspT1Ox3HNJVOz8+SBM7A9pmSHk4PGpHa3r3++Djbi1VuktTiHo9B4rSw0yiW3h7AgZR15ldQ+mnt2WlE0ztKpfrUGnWt/EspS5RatCdwKLC5pCuAXwMv6DakJQ1m3SkJIMC9274wupheHOMhfboQB/3rI/pRSjuAu0t6H+XYNrtnzfZ7oD+Fuejf621vyl61DSUdSVlW9+JOI5per/qIVq8F3klJpL5EWe6+X6cRTa9vz4m3US7QnkcpFHQs8OlOI5pap+dnqQ46hZkKkzTc4wdJZ9redqaxFqlUqlu1FtuIZaReDXsM5ULG920f33FI06pXw5ZrsZoXgKRDbe8u6cRJ7rbtpmbdJ9P6MR5Wl/M0fyEOQNJhlFj70kcUSZsDj6Yc3xNabtcjaSfK7M+qtjeStBXwStuv7ji0afXs9XY3Sl0BAafa/mPHIU1JpS/y8vSnj2gv9ek50Tddnp8lCZyCpMOnudu2XzpvwcySpHtSZqe+ADyPRQUqVgMOsb15V7FNR9IXKbNrtwGnU+I90PYHOw1sCpI2oVzJ25ih2fRGG5HeTtJqLB5vc81/Ja0BvIglj21zS4PrBYudbJ/cdSxLo0/HGG6vCPkEloy3yaSqbvRfwmAGq0X1GN+DxY/vb7qLaGqSfk6ZrTza9jZ17HzbD+w2ssn17fUGpYIpS8bb5IXvPl6Ik7SA0kZmYxY/xq3uG0bS+izadwmA7R93F9HUajXb/Vhyn+hqnQbWoCwHnUIfi5VQKla+GNgAGD5BuoHyhtOqLWxfL+n5wHcpU/lnAE0mgZRSw4dR1pi3vHcGAEmvBN5Dae76TxYVqmhx4/yxwKmUZRxNH1vb/5T0Mcqm7j7pzTGuvkN57vYi3paTvcn0sJBN3wpz9er1JukzlP/3F7Ao3mab29t+ZNcx3AFHAm+mP8+J/YFdWfI50WQSSKng/nRK772mZ7rqqsP9KdVLxTwnrEkCZ6AeNYu3fQRwhKRn2P561/EshRVrgZWnAh+zfctgk2yjbrL90a6DWApvAh7Yk+UbK9l+Q9dBLIUTJD0D+EbrHzZD+naMN2j5CvlEtbDKW4AHMNRvr+GZib4VsulbYa6+vd52tL1F10HMVp/O0YZcY7vZvoCTeCrlPaLlYjDDfguc35PP5AOAJ3W1BD9J4Mw+S+mR8s56+/+Ar1Bmgppk++uSnsCSJyH7dhfVtD4JXAacA/xY0r2o/V0adWBd8nUc/diD8CtKH8Y++HzdHH0Mix/b5pauVq+kFC65VdJN9GPZSd+O8XclPcb2cV0HMktHUj4jnkhZ5r4bcE2nEU2vb4Vs+laYq2+vt59J2sL2hV0HMkufpWfnaMDekj5NaWw//JxocraV0pZlRdquCDrsLcCxkk6i/X3Zf+hyD3aSwJn1qkcVgKRDgFWAR1IqIj0TOK3ToKZRZ9WGZ9Yul9TyEo8HAS+ktNwYXhrR6pX+twOn1L00w2+ILe5J+QdlGfA7WdQ2pNWlq9juQ4n6iXp1jClL6b5Z92DeQvuJ9t1sHyZpL9snUcqVn951UNO4FPiRpF4UsqkrGp7fdRxLoW+vt89REsGrKM+Hweut1dn43p2jUdoIbU5JrJpfcku5iHy2pIlJa4vnEADvA/5KmQRpuecpwEJJX6FsM5r3CwJJAmfWtx5VAA+2vaWkc22/R9KHKHvtmiLpBba/IGmqpTJNnoQAzwLubfsfXQcyS58Efkg/9h+8EbhPT5auIulhk423umG+6tUxprwP7EQP9ndUg8qlV9YVGb8H1uownpn8pn7difZPmPpYmKtvr7fDKBc5+/B5Af08R9vO9v26DmIpHF2/+mK9VgtFTWI1SpL9mKGxebsgkCRwZn3rUQWliALAjZLWA64F1u0wnqkMmmJONpvS8sne+cAawNUdxzFbK/ZoT8ol9GfpKpTN/QMrAdtTihq1OisM/TvGfdrfAfBeSatTTv4PonzIv77bkKbWt0I29KwwF/17vfVtv1ofz9FO6dOS21pvok+O7csWgq6LUCYJnNmmwOOADYFnADvQ/nH7Ti1L/UHgTEpC1VxzcNufrD/+YGKZfUkP6SCk2VoDuLgu8Rqevm/1SvR3Je1OOWlqfU/K3yjLTk6kB8tObD9p+LakDSmVyVrWq2PMouWK36Xx5Yq11cJmto+hzEY0u6xd0v/Y/g9J32GSi24Nv5/1rTBX315vZ9W2TRM/L5pcqmj7TEkPpyd9RKsdKc+JX9PwkltJR9l+tqTzWPw9osl4h7wKeJOkf1CWYze3hUDSW2wfIOkgJn//nZf3h/QJnEFdUrmlpIdS+o78N/Bu2zt0HNqk6r6ZHW2fUm/fmVKdrNnlEX1rbl8/cJZQ9/80p37QTGTbze1JkbTbZON9uRKpUrf+gpar6/XtGPet756k02xv33UcM5H0b7bP6OH72fOAzehJYa4evt4m65FsN9YbuZbWn1KrSStALX63BNuXz3cs05G0ru0r+xJvn0h6ku3vdP3+kCRwBpLOsr2NpPdT9qR8cTDWdWxTaT2+AUk7AQ8G/gP4yNBdqwFPs71VF3HNRn1T3Mz2DyStAixv+4au4xoFklYGNrL9i65jmcmEq3jLAVsDl9l+QWdBzUKfjvGApFVsN7+sTtJHKAUfvkKZBQLaTVKGSVoT2ND2uV3HMpX6WfxCStXj24tquN0WHL18vbVuimR1oLmkdaI6sbCZ7cNrW5lVbU92wbZzku4C/N2lN+59KUVtvtvqjGu9GPt8YBPb+9UVOuvabrZAItw+ibOq7Xmrjp8kcAaSjqGUod4Z2Bb4O3Ba4wnKfwM/o/HeZfUK9CMoJb8PGbrrBuA7tn/ZRVwzqeW+dwfWsr2ppM2AQ2w/uuPQJlWT1DdQTkJ2r/Hery5Za4qkJ1Fm2+9kexNJWwP7tro0bcJVvFspCeDJUz2+BT08xjtR9oCtansjSVsBr7T96o5Dm1Rd9jdRs0mKpB8BT6ZscziDstf55Fb3EUu6BNiiL4W5evh6uy9wMHAP2w+UtCXwZNvv7Ti0kVFXNyygfA7ft9Zu+KrtJrfBSDoD+H/AmsDJwOnAP2w3WaVX0sGUC0SPsn3/enHrONvbdRzaEurS6z2A2yjHdTXgQNsfnJd/v+EcoQn1BHoXyizgLyWtCzyo5Q2nkm6gFF25lVIkprn10AN1D81Rtp/RdSyzJelsSgGQnw9mXCWdZ/tBnQY2hVp++AzgRfVDfRXgFNtbdxvZkuqHzaOAHw0d2/PdcKUvSXcC7ltvNr8fpW/HWKW1yTOBo/sQb98MrXZ5OWUWcO/BNoiuY5uMpG8Bu9vuRWGuHr7eTqIUvPpky/Fq6qriQJt7hgfqOcQ2wJlDx7jl19yZtreV9Fpg5bqX7ewWzyFgsXjPGjq+57Q4eTM4jpKeT5loehtwxnw9F1ovcNK5uvzoG0O3rwSu7C6imblHvcts31avgvXJzbb/UVYcgKQVaLua6aa2d5X0XCjPaQ2Cb88ttq+bEF6zFQAlPQI4AriMcrFlQ0m7ue0WEb06xgC2fzsh3mb7gEl692Tjtved71hmaYV6cfPZLGq43bI16Fdhrr693laxfdqEeG/tKphp9OY8ZxL/sG1Jg7YWd5npFzqmuiLj+cDL6tjyHcYzk1vqBMPg+K5Du6+5FSWtCDwV+JjtWwbPi/mQJHAESTph4tLEycYacrako4GvsvgemlY3dp8k6R3AypJ2Bl5NqaTWqn/UPSmDN8RNGTp5aswFKoUflq/LVl8HnNJxTNP5EPCYwV6fupTqS8C/dRrV9Pp2jH8r6cGA64flXsBFHcc0nb8N/bwS8ETajndf4PvAT22fLuneQJNL8atJCwU1rG+vtz/Wz4jB58UzafDCtxstDDVLR0n6JLBG3V7yUhqs4D7kP4C3A9+0fUF9j5hs2XsrPgp8E7i7pPdRVpK8q9uQpvRJykXkc4Afq9SbyJ7AWHqSVgJWobw4H0GZmYCyxvh7tjfvKLRpTbHBu9mN3XXz7ssozT1FOYH6dKv7L2ui+i5gC0pFvYcAL7b9oy7jmkxdqvpOFj+2+9m+adpf7MhkS3haXtYDvTzGawMHAv9Oifc4YC/b13Ya2CypVGj+vu1HdB3LKJG0Gos3i2+x5U0fX2/3Bg6lFG37M/Br4AW2L+syrqn0dQ9j/Vy+/Tlh+/iOQxopkjYHHk05vifYbvlC3GIkrWB7XmbfkwSOEEl7Ua7YrEcpZjNIAq8HPmX7Yx2FFh2TdDdKbyIBp9r+Y8chjQRJn6EsM/lCHXo+pVJskxcwYv7VogSn275P17FMpl6Em6xPVZPPYZWep/tS9rv/k0V73ptredNndYnicm686nVf9jD2WS12Ndl7RKvFrtaaZPiGFvfrd719IMtBR4jtA4EDJb3W9kFdxzNbfbuSpyUbp0JpDL0QeG9rMxSSBv0WB0t6NpK0OnD5fF1tmi1N3rh6cGw/2eDV81cBe1KWeAH8BPh4d+HMrG/HWNJkjcGvAxba/vZ8xzOTCe8PywPrUJKWVg1XCV4JeBrw+45imY03Aw/sy4WsHr7e3jDhNpR4z7B9dhcxzaAvexhvp1K8b6rnxBttXzr/UU3rTUM/rwQ8g7aP8ZnAhpSZbFH2EV8l6Q/AK2yf0WFsE3W6fSAzgSNI0rMoyz9vkPQuSsWh97rRPlV9u5In6QBKYYov1qHnUJbhXgU81PaTuoptMpJOpTwHzqW8IT4QuABYHXhVS5VuJR1IOWn+Uh3alTKTbWA12y/sKrbJSNqrXnyZdqwlPTzGh1L6Un21Dj2DskTtbsCltv+jo9AmpcUbK98K/KG1iy3Tqcvdf2r7wV3HMhlJ3wOe7h70jIRevt6+SGlfMNjn/kTKZ8fGlDYGB3QU2qQkfRd4DSW2besexpfZflzHoU1J0n7A7yjnEKKcQ2xKSV5e1Yel45JOs71913FMRtKngK/Z/n69/RjK58bhlPYLO3QZ33TmffuA7XyN2Bdwbv3+UOBHwBMo7Qw6j22KeE+v388aGju767imiffMqcYorUQ6j3FCbN8AHjB0ewvga8C9WzvOg+fCFM+PC7qOb5bPhbO6jmvEjvGplCW2g9srUPqgLg9c2HV8k8S7KXDn+vMjKLPEa3Qd11LEfz/gkq7jmCa+bYCzKQUVPjr46jquaeLt2+vtx5SenIPbqwInASs3+nq7N/AD4EbKNpifAht3HdcMMZ8zydjZU93X9Rew1tDX2sBjKe2QOo9tiniXOA8bOi8+u+v4Zoh9zfl8/81y0NE0KJ/+BOBQ2/8rqcmllVUvqpENWV7S9rZPA5C0HYvKJbd4xf++ti8Y3LB9oaTNbV/aYKeIVSVtZPs3AJI2opyEADTTHLq223gesEmtbDtwV6DJAhVDenGMh6xJie+6evsuwFou7WVarHL7dWCBpPtQCmx8m3LF//GdRjWFoaVpqt+vAt7aaVDT+yTwQ+A82i37Pqxvr7e7s3j16FsoWzX+3uLrzWXp5L/3ZQ9jdaOkZ1MuxkKpXjlYFtzi8rwzWPQecStlJcbLpv2Nbl0p6a3Al+vtXYE/1LYRTb1ndL19IEngaLqilh/eGdi/Ti8v13FM09mTcrK0uaQrKG8wz+82pGm9HPiMpFUpb4rXAy+vH0Lv7zSyyV0g6WAWf0O8sD4vWtso/Ubgp5J+RTm2mwCvrsf2iE4jW9wplAsVa1PaRAzcQFk61bK+HOOBAyhtZH5EifdhwH/VeH/QZWBT+KftWyU9HTjI9kGSzuo6qKm4R31lqxVtT9sovDF9e70dCfxc0mC/7ZOAL9Z4L+wurMlJ+i/gANt/qbfXpOyra7UlAJTzmwOBT1ASgFOBF6i0cnpNl4FNxvYmXcewlJ5HaSXzrXr75Dq2PKUfakueOPTzvG8fyJ7AEVRLUu9CmRL/pUoj4Ae5ob1fwyQtX6/q9+lKHrW4Cravm+mxXaofLK+mLA+G8ob4CcqVx1Vs/7Wr2CZTk9NBO5NfuLHCCUtD0s9s79R1HBP17RjX97DB/pPTbTdbuETSz4H/obQFeJLtX7e8xxmgJqwPpZyQ/sT2t7qNaGr1pP8yyp614Wbxzc7A9/D1th2lRQTAybYXdhnPdCSd5VpLYGjsTNvbTvU7sXRU2o8NziFMKYB2SOvP476oxfsGx/antuftomGSwBEiaTXb109RHrfZD0lJvwG+B3wF+KF78KSU9ATgAZRqTsD8lfQddZIeSNm3OHxsP9ddRHfcZCcoLejbMa5X9zdj8Xh/3F1EU5O0BbAH8DPbX5K0CfBs2/t3HNqkJH0CuA+LFy75le09u4tqapJ+Pcmw3XCLiL693gAk3Z3F4/1Nh+FMSdK5wHa2b663V6ZUDn5At5FNrSZVL2PJc4hW27IcRVnlMmiF9DzKPudndRfV1CStA7yFJY9vcy0taouIZ1FqNwA8lVLkaF62cCUJHCGSjrH9xPohOVi/PdDsh2SduXwipULWtpSS5V+2/dNOA5uCpEMo1UAfCXyasp7/NNtNrpGXtBllmerEk5Dmng+S9qYU09gCOBZ4HOXK2DO7jOuOavGKdN+OsaSXA3sBG1AKguxISbCa+0DvI0kXA/cfXHyr1UEvsH3/biMbDT18vT2ZssR9PeBqYCPg4laTqrr360mUyo8ALwG+0+pFFwBJXwUupiRT+1KWh15ke69OA5uCpAttbzHTWCskHUeZVHgT5YLcbsA1tpvb6yzpF8BWg1nVehHjbNv3m49/v+V9YrGUbD+xft/E9r3r98FXcyf8A7ZvtH2U7adTKr+tRqlG1qoH234R8Gfb7wF2Au7bcUzTOZzSh/FWSuL6ORZd0WvNM4FHA1fZfgmwFaWVRSw7fTvGewHbUfpaPpLyHvGXTiOahqSHSDpe0v9JulTSryW11vdr2CWUE/2BDetYkyStKOl1kr5Wv14jacWu45pG315v+1EutPxf3Qv275Q9a02qyd77gPvXr/1aTgCr+9j+T+Bvto+gFPFrtm0BcKakHQc3JO1A6WnYqrvZPgy4xfZJdYa11YuGv2fo4jxwZ0qV23mRwjAjStL6wL0Y+n/c6vIpAEkPpyxD2oXy5tLa5t1hf6/fb5S0HnAtsG6H8cxkZdsnSJLty4F9JJ0BvLvrwCbxd9v/lHSrpNUoV6I37Dqof0Fz5Vfp3zG+yfZNkpB0Z9sXS5qXq6R30GHA6ykV9W6b4bGd0aIm5ncFLpJ0Wr29A3Bal7HN4GBgRcq+ZoAX1rGXdxbR9Pr2ervF9rWSlpO0nO0TJf1P10FNRdK/2/4u8N2hsd1qctWqQUG2v9SlwldRqrI2Zahy5YrAKXXrjinnlhd3GdsMBsf3yrp15/eU9hbNkHQQ5VheRyned3y9vTPz+P6bJHAESdqfWgGSRSchpvT/aY6ky4CzgKOAN9v+W7cRzegYSWsAH6Q0dzVlWWirbq5LvH4p6TWUq0yrzvA7XVlYj+2nKCfRf6X0hOurphpBV307xr+r8X4LOF7Sn4HLO41oetfVk9LW/XfXAdxB29neauj2DyWd01k0M+vb6+0vKpWvfwwcKelqoOXP5HdLegalCutdKZ/FN9Nm5dWBQ+s+5/8EjqZ8Hrd4UfaJMz+kSe+thfveCBxEWV32+m5DWsJgJvUM4JtD4z+azyCyJ3AE1TXGWw42SrduUNCm6zjuiFr1baWWK4TWSm8XAWtQlvqsTimp3ewSHwBJGwOr2W6u5YIW9VablO3V5jGcO6zlYzyZumJgdeB7tlvssYakD1BKkX+DxatXntlZUP+C1ircSjoTeJbtX9Xb9wa+1tre28n04fVWq3TfRFnF8HzK6+1I29d2GtgUJIlysv/KOvRu21+a5ldilvpabLCvJG07358TSQJHkKTvUj4kmyr9P9HQdPikbL9uHsNZKpIeDGzM4sttm6721hd9WsosaT9Kv8DPs+ikaV3bLV7VvV2fjjGUNjLAPVg83larFZ44ybD7WsimtQq3kh5N2ed8KeU1dy/gJbYnO+5N6NvrrU9qgnIIZbZnA8p+9/1brjJeLx4/gyXPIZqqMN7jYoPrAK9gyePbZPXVgS4KyWU56Gi6kdJc+QQWvxLdWlI1mA5/CKVy2lfq7WfRYFPaAUmfBzalVCocXm7bZBIo6b7Am1nyJKS5k9K+LWUGnjxhadrBdWlas0lg346xpNdSGv/+AfhnHTawZWdBTaMWrxklTZ1M1/3NmwGDfaG/aHnVSw9fb08H9qfsUVP9csOrG04FPmD7M7Wy4v6UXrgPnv7XOvVtyl6wMxg6R2tNTQAFPLzVi25T+Dall+EPaHhf9iTmvYZAZgJHkKTdJhtvdaO0pFOBh9q+td5ekdKweMfpf7Mbki4Ctmj5SuOwmpQcwoRCFbbP6CyoKfRwKfMpwMeBL1NO7J4L7Gm72ROQHh7jS4AdWl2ONiDpBba/IOkNk91v+8PzHdOy0MXV6elI2pOyPPEv9faawHNtf2LaX+xIT19vT7J9UdexzIakjSYmKJIe1vJMq6TzbT+w6zhmS9J5th/UdRyzJels21t3Hcds1CT7+cC9gXMp52nr2p6X4jCZCRxBrSZ701iTspRjsL581TrWqvOBe1KWAfbBrbYP7jqIWbqUUomsFydMlD5PB9YvU65AP6/TiGbWt2P8W8pV89bdpX6/a6dRLHutVbh9he2PD27Y/rOkV7CoWmhr+vZ6+0NfEsDqj5L+E9jI9ivqLHGrs5YDp0h6kO3zug5kls6UtJ3t07sOZJaOkfR428d2HcgsfIKywuVRtvetF7U+TmmLNOeSBI4QSUfZfvZQWd/F2G5y+RTwAeCsupdGwMOAfTqNaHprAxfWkurDy22f3F1I0/qOpFdTKlANx9vipu6+LGUGwPZlwFO6jmMp9eoYU06ifyTpf1k83qZm1mx/sn5/z3SPk/R22++fn6iWidYq3C4vSYOVGHW/6J06jmk6fXu9LZT0FUo13uF4v9FZRNM7nDJ7MihedAXwVeCYziKa2UOBF9e9djezaMltq+doOwDPl3Q5pVJs6/HuBbxD0s2UdhEtL2newfa2ks6C2y9qzdv7WZLA0bJX/d6rsr62D6/FbAbNUt9q+6ouY5rBPl0HsJQGy4PfPDRmyvKD1hxdv3qhpxvQe3WMgd/UrzvR9sn+bD0L6DwJnKbC7WInTLbPn9fAZvY94CuSPllvv7KOtapvr7fVKInrY4bGTKl226JNbe8q6bkAtm+sS+xa9riuA1hKj+06gKVhu0+rMW6pF7IGF7XWYdHe9zmXPYEjTKUx7fCJaYszP8Dt+zo2A1YajLW8pj8Cbt8T+BOW3G/59c6Ciqa1Vm2zb2rP092Bf69DxwOftt2nAhCxjNT34EcDJ9cZlU2BL9nevuPQZiTp7ix+ztNk8ZUpWkTcYPuWScab0JdzSknPpxSO2pbS2/KZwLtsf3Ve/v0kgaNH0iuB91B6/Qz+B7dczvfllFnMDSgVN3cEftZi9UoASTtSGpDenzIzsTzwt0aXGgAg6YGUCqzDb4jNVTOt+znez5Kxtvrc7c0G9IEeHuN1gLcAD2DxeJt8f5hJa4VWBvpyQjqsi75aS6uHr7eVgJex5OutydUNknYG3kU5vsdRqo2/2PaPuoxrOpKeDHwIWA+4mlK5+yLbD+g0sClIugzYEPgzZaXAGsBVlIrNr2ityFwPzyk3p1zIEHDCfO7JXW6+/qGYV28CHmh7Y9ub1K8mP3CqvSibYC+v5dW3Af7SaUTT+xilCuQvgZWBl1M28jZJ0t6UpPUg4JHAAUCr+xcPBw4GbqXE+jlK36dWHSPp8V0HsZT6doyPBC4GNqFc3LoM6EuBgsk0tVRN0pMl/RL4NXAS5fh+t9OgZu/TXQcwC317vX2eUvjssZTnwwbADZ1GNA3bxwNPB14MfAlYMJwASmoxsdqPkpj8n+1NKAnAqd2GNK3jgcfbXtv23SjLWY8BXk2bBZl6dU5p+2LbH7f9sfkuypQkcDT9irKmvy9usn0TlCaqti9mUQ+oJtm+BFje9m22Dwd26TqmaTyT8iFzle2XAFsBq3cb0pRWtn0CZZXC5bb3AZ7QcUzT2YuSCP5d0vWSbpB0fddBzaBvx/hutg8DbrF9Up2RaPKK7izNyzKfpdC3E9JhTSXUU+jb6+0+tv+TsrrlCEqsO8zwO52yfa3t/7V9jO0/Trj7850ENb1bXFreLCdpOdsnAgu6DmoaO9r+/uCG7eOAnWyfCty5u7Cm1Ltzyq6kMMxoejulBPHP6Uc1st9JWoNSjex4SX8GLu80oundWKs3nS3pAEqriJYvqPzd9j8l3Vr3iV5NWdrRopvrnp9fSnoNpdLbqh3HNKWebUAf6NUxplR3A7hS0hOA3wOT7VHplKSDmKax+uD91/Z/zVtQs3OL7Wsl3X5CKul/ug5qKhP6ar1H0obMY1+tO6Cvr7e/1G0EV1Eax/dVixcK/iJpVeDHwJGSrqZU3WzVlZLeSumHC2UP2x9qQZN5K2KyFPp2TtmZ7AkcQbV1wU+B8xh6gboH/QMlPZwyS/U92/+oY2va/nO3kS0i6V6URGpF4PWUeD9RZwebI+kTwDuA5wBvBP4KnF1nBZsiaTvgIsqeg/0ox/aAesWxSX3ZgD7Qt2Ms6YmU4jsbUpY0rwa8x3ZTFRclDarwPoSyP+kr9fazgAtt79FJYDOQ9APgqZR9a2tT3tu2s/3gLuOaiqSDWdRX6/719Xec7Xnpq7W0evh6eznwdWBLylLWVYF32z6k08DuoBb34Eq6C6Vmw+CCxurAkXV2sDmS1gb2prS2gNIP9z2U/q0btXruA5OfU8YiSQJH0KhVn2vxTbyvJG0MrGb73K5jGQV924Aec0/SqcBDbd9ab68I/MT2jt1GNrkenpCeOeirNfick3SO7a26ji3a0/L5Q58quPdNvTi0IYsf36aLSHUhy0FH03cl7Q58h/abg89GU8s56szEfpSKXivQdiNSACRtyVAvO0n3cYPNfyUtAN7JomMLgNtuSrsdcKrtR9YqX60t91tM346xpE2A17JkL8ZWixutSZmtHLzfrlrHmmR7eBla86tF6Liv1tLq4ettDeBFLPl6a3U7yUyam/2ZUMH9n9RzCNrs3du7Cs2S9qMUCrqURe8Npt97yedEksDR9Nz6/e1DY82+wcxCa9PV/0OpRnaeezCVLukzlKU9F7D4G2JzSSClEuSbmbCUuWE32b5J0u0b0CW1vgG9b8f4W8BhlItafYj3A8BZkk6knNw9DNin04imIenpwP6UfV+i/YtaHwW+Cdxd0vuofbW6DWlafXu9HUspDNSLeCU9hLK94W+SXkDpt3ag7csBGp2BH1Rwn1jEplVHUpa3PxHYA9gNuKbTiKb3bGDTLP+cWZLAEVQrvMXc+S1wfh8SwGpH21t0HcQsXdPaXq8Z9HEDet+O8U22P9p1ELNl+3BJ32VRRcW32r6qy5hmcADwpPkuTX5H2T5S0hks6qv11MZj79vrbSXbb+g6iKVwMLCVpK0oe94/TWnD8fBOo5pe3yq43832YZL2sn0ScJKkltv0nE/Zg3t1x3E0L3sCR0i9ojulFpf/zUZrexzrRv/9KD2UhpfbfrizoKYh6TDgQ7Yv7DqWmUh6NGUm+wQWP7bNP3f7UNQI+neMJT2PUnjnOBaPt9n9HZLWZ8nlf00WC5J0su2HdB3HqOrh6+31lOJhx9CD7SRDe0TfDVxRk5Vm9wECSNqGUnSnFxXcJZ1qe0dJ36fMxP8e+JrtTTsObVJ1Cfa3Kcng8PFtdQtBZzITOFqeVL/fHXgw8MN6+5HAKTS2/E/StGXehz50Hj0P4SyN91E+JFcC7tRxLLPxOeBnkq6ivCEOlnu1uCflJcDmlMqrrS9dXUy9QjrRCZTlSS3p2zF+EPBCyn6O5vd3SNqfUkJ94vLrJpNAYKGkr1Bms5tPUnqob6+3fwAfpOxjHMwStLyd5AZJb6e8R/y/2o5jxY5jmsknKednvVhyC7xX0uqUmdZBhebXdxvStI6gLHHvy/HtTGYCR5Ck44DdbF9Zb68LfNb2Y7uNbHGSfk35cBGwEfDn+vMawG9aXdYq6XzbD+w6jtmSdAnwBpZsGdLcskVJv7Dd+p66WWttFhv6d4zr83eLvuzvkPQLYEvbN8/44AZIOnySYdt+6bwHM4J6+Hq7FNi+L/vVJN0TeB5wuu2fSNoIeITtz3Uc2pRa/Fz4V0h6u+33dx3HgKTTW20Z05rMBI6mDQcJYPUHSpLVlEGSJ+lTwDdtH1tvP47St6pVx0p6jO3jug5klvq0J+UUSVv0YenqLLV4la1vx7hv+zsupcxE9CIJdIP9QkdM315vl9Cj/Wq2r5L0dcqScYA/UgoHtWzUKrg/i9JntBU/kfR+4Gh6soWgK5kJHEGSPkZ5Q/xSHdoVuMT2a7uLamqSzrP9oJnGWiHpBuAulDeXW2i8ml5tFr8GS37gNLccSdJFwKbAr2l/6eqMWtyb0rdjLOlHlOq2p9OD/R31hHQrltwD1up+nw0oS7wG+wJ/Auxl+3fdRTU6evh6+yalFcCJ9OP5+wpgd2At25tK2gw4xHZr20huV1dBTWTbrS65nVZrM5u1MvNEbrWlRZcyEziCbL+mFon5f3XoUNstXxn7vaR3AV+ot59P2XjcJNt3ne5+SQ+wfcF8xTMLK1M+zB8zNNbqnpRdpruzxUIrM2iqx2XVt2O8d9cBLKWj61dfHA58kXI1H+AFdWznziIaLX17vX2rfvXFnsD2lCIr2P6lpLt3G9L0ZtrqImln28fPVzzLQFOzSbYfOd39knaz3YeeqHMuM4HRuVogZm9KPy0oBRTe09elES3O/kyntfX802nl2M62qJGktfr2PG7lGM+WpJ/Z3qnrOPpK0tm2t55pLOZGD19vX7f9jK7jGJD0c9s7DGajJK0AnNnqTOts9PA50dRM4Ez6dnznUmYCR5CkHSnLe+5PqV65PPC3Vpcr1pPkvbqOYxlqcfZnOq2t559OK8f2DBYVNZro9kp6fUsAq1aO8Wyt1HUAw+pytPcDWzAUW8NLva6tTbYH2weeC1zbYTzjpm+vt9aexydJegewsqSdgVdTtj70Wd+eE1/tOoCl1LfjO2eSBI6mjwHPobwwFwAvAu7baUTTkHRf4E3AxizeV6uv67f7Nr3epzfEJo5tq5Vrl5EmjvFSaC3ewykrGz5Cac/zEmC5TiOa3kspFw0/QjmWp1BijvnR2vN3Jq3F+zbgZZTq168EjqU0jO+zJo6xpIOYJpbBPlHb/zVvQS0bTRzfFiQJHFG2L5G0vO3bgMMlnQW8veu4pvBV4BDKG/dtHccyjvKGeAdJEmUP6ya296vlye9p+7SOQ4vurGz7BEmqbVj2kXQG8O6uA5tMjbHJIjsRs7Ay8BnbnwKQtHwd602F04YtrN8fQlnZ8JV6+1lAX6rdTqZPF77nVJLA0XSjpDsBZ0s6ALiStq9E32r74K6DWIZ60c9sSJ/eEFuL9ROU3ouPAvYDbgC+DvS5R1Frx3gmrcV7c21Y/UtJrwGuAFbtOKYlSHqL7QOmutrfajXIEdTa83cmrcV7AvDvwF/r7ZWB44AHdxbRv+6yrgMAGBRPkfQq4KG2b623D6FUEe6rk7sOoBUtJwZxx72Q8v/2NcDfgA2BZjZyT+I7kl4taV1Jaw2+ug5qOpLWl/RgSQ8bfA3us71jl7HdAU2t55f0UEkvqT+vI2l46WVrZb93sL0ncBNArfJ3p25DmlnPjvFMXth1ABPsBawCvA74N0q1zd06jWhyF9XvCyl7XCd+xTIgaVNJd64/P0LS6yStMfSQvr3e3tp1ABOsZHuQAFJ/XqXDeGYk6QxJe0pac7L7bT99vmOawZrAcE2JVetYkyTdQ9Jhkr5bb28h6WWD+22/prvo2pLqoGOowepeveqZI2l/Su/FC1m0fNUN9y07AHgv8Hfge5Sea6+3/YVpf7EDkvam7GO9n+37SloP+Krth8zwq52Q9HPKFefTbW8raR3guJYrpfXwGN/AkjNV11GSlzfavnT+o7rjJB3UUs9WSc+y/dWZxuKOkXQ25fW2MWW/2reBB9h+fIdhLUHSeUy+NaD1voYnA68dNAKX9G/Ax1quGCzpPpR9t7tS3scOp3xuNHlCXi8Y7kPpHSlKJfd9Wm2zUJO/w4F32t6qVow9q9Xe011KEjiG+lbOtzWSfgFsafvmGR/cgEG5d0lPA54IvAH4se2tOg5tCfWEaRtKie9t6ti5DZ+APJ/yQb4tcATwTOBdLZ9A9/AY7wf8jtLLTpSiV5sCZwKvsv2I7qJbeq2VJ58sntZi7LPBsZT0ZuAm2we1+Bks6V7T3V/3jjZH0nbAlym9hQXcE9jVdvOz2XXZ+BOBgykXlA8HDmyxqrSkewI71Js/t31Vl/FMR9Lptrcbfp2l7c3ksidwPDWX+Ut6IEuWVP9cdxFN61JgRUoD9j5YsX5/AmXG57pSz6RJ/7BtSQaQdJeuA5qO7SNr0Y9HU05Anmr7ohl+rWu9OsbAkydcsDi0fqC/tZaGjztA0uOAxwPrS/ro0F2rAbd2E9VIukXScylLgp9Ux1ac5vGdaDXJm4nt0yVtDtyvDv3C9i1dxjQbkrakzAY+nrKP/EjgocAPga27i2xKywPXUPKG+0q6r+0fdxzTVP4m6W7Uc93aNu26bkNqU5LA6FxdnvYIShJ4LPA44KdAq0ngjZSiOycwlAg2XEjhO5IupiwHfVVdsnhTxzFN5ShJnwTWkPQKSvn6T3Uc05TqyfOXbX+861iWQq+OMaXQ1bOBr9Xbz2TR87e5C1o98nvKUrQns/gewBuA13cS0Wh6CbAH8D7bv677bz/fcUxLkPRT2w+dZPn1YDloU32GJT3K9g8lTdw/d19J2P5GJ4HNQr1w+BfgMOBtQ6uKfi6puWX5Q1tgLqAUQoPyHGk1CXwDcDSwaV0uvA7lcyMmyHLQMdTaUpS6F2EryprtrSTdA/iC7Z07Dm1SkiYt8tDw+vg7A3cBrrN9W535WdX2HzoObVIqDX8fQzn5+L7t4zsOaUr1ubAr5Sr0NykJ4cLpf6t7PTvG9wYOBHainHicSklSrgD+zfZPOwxvqTX4/rtiH2ZOIoZJeo/tvSUdPsndtv3SeQ9qliTde+JeZkmb2J6sPkLn+rQFRqVFyOsovU/vR/mM68XscBeSBI64Wn1qQ9vnDo09xvZxHYa1GEmn2d6+Xh17JOVK9EW2N+84tJHQpz0/9Sr5lbZvqrdXBu5h+7JOA5uBSjXbZ1D2q21ke7OOQ5pSX49xX8xUaEXSi21/tpPgJiFpM+D9LLkcv8nCXH1TZ3b2Ae5FWX01mFlr+vhKujuLPx9+02E4U9Kifsi9McVn8hm2/62rmKZTC608a7gKa8sG55Rdx9EHWQ46giT9iLLEZwXKMp+rJZ1s+w0ALSWA1UKVktmfosT7V+BnnUY0CUlH2X72VFXUWiusUTdyrw+sLGkbFvV3Wo12S2h/lcX7O91Wx1rvu3cfYHPKiV7rewJ7dYzr8uVXUKor3v6Z1fCV/rezZNuV28daSgCrw4G9gY9QLsK9hLSPWpYOo8xcn8GiatLNkvRk4EPAesDVLHpPe0CXcU3j15K+R2lk/sNWK2wC1L2LDwBWn7CMdTWGEu4G9W0LzMmSPkZ5TvxtMDioIBuLJAkcTavbvl7Sy4HP1SUT5874Wx2x/er64yH1zXy1CTOXD7B9QTfRLWav+v2JnUYxe48FXgxsAHx4aPx6oNWCGivY/sfghu1/SGq2755K+42nAb+ifODsZ/svnQY1s14dY0pJ/Z8AP6Dhk+geF1pZ2fYJklSLg+xTV2W8u+vARsR1tr/bdRBLYT9gR+AHtreR9EhKr8tWbU75TN4TOEzSMZRl+S0uE78fJdY1WFQkCMrqp1d0EdAsHV2/+mLr+n3foTEDj5r/UNqWJHA0rSBpXeDZwDu7DmZpTLEk7fOUEvydsn1l/d6LKmp1j+IRkp5h++tdxzNL10h6su2jASQ9BfhjxzFN51fATrZbjnGivh3jVWy31qB6Mn0ttHJzLVX/S0mvoey1XLXjmEbJiZI+CHyDxWdRWp2VuMX2tZKWk7Sc7RMl/U/XQU3F9o3AUZSCV2tS9g+fRKlm2RTb3wa+LWkn282tdppKq/UOpmL7kV3H0BdJAkfTvsD3gZ/W8sn3Bn7ZcUz/iqb6GdRywwcB9wfuRPmw+Vtr1dOG/JukEwYzVPWD8o2239VtWJPaAziyLuUQ8FvgRd2GNDXbn5S0pqTtWXz/TKtV02DxYwylB98LO4xnJsdIerztY7sOZDq2zwHOkfTFnhUh2IuyPPx1lFmgR1HaGcSyMeittmBorOVZib9IWpVS+fFISVcztKSuRZIeTinQtQvlQsyzu41ocpLeYvsA4Hm1bchiWl1e2cd9w5KeQFl6OxzvvlP/xnhKYZhoXmtFTCQtpBQA+Srlg/1FwH1tv73TwKYwWTXC1o7pRPUkhNY3otcl13tRltyeTVlG9TPbTZ7g1cpp+9t+U4+O8Q2U6rY3A7fQaMn6gb4WAomA2/uG/p2yL/T5wOqUat3NNTAHkHQZcBZlNvBo280mrJKeZPs7Paww/lMW7Rt+EnXfsO0ml4xLOoRyYeuRwKcp7SFOs/2yTgNrUJLAEVT3Kb2X8kb+PWBL4PW2v9BpYHdQawmLpIW2F0g6d1AMprWy78PqftDtBuWdazXIhbab2+hf21k8gyWLgDR5Ba8WCdoOONX21nXj/3/Znti7qhmSTrW9Y9dxjCqVnpxLFAKxfW1nQU1D0n2BN7MoaQWg1QsZfSNpdcoJ9MPq0EnAvrabbF4taf+Jy68nG2tBvaj1zlY/H0bFoHKppPNsP2h4rOvYJjM4Nxv6virwXdv/r+vYWpPloKPpMbbfIulpwGXA0ylLO3qZBAL/mPkh8+rGWkjj7JpwX0nb1fSOBE7Qon5KLwGavOJIKQJyHeUEuvmeRMBNtm+ShKQ7275Y0v26DmoGZ0k6mjKTPVw5ranmypI2r8dz0gtADe+p6lshkK8Ch1CqMzdbeKfHPgOcz6Ilii+kVGRt9ULRzsDEhO9xk4x1zqXv7RNZvABIsyR9h0kqiw/YfvI8hrM0+rZv+O/1+42S1gOuBdbtMJ5mJQkcTYP/r08Avmr7OqmpbXVLqPvUNmOSfVUNzlq8kJL0vYZyxX9DyuxVk2zvL+kc4N/r0H62v99lTNPYwPYuXQexFH5X25t8Czhe0p+B1gsHrUT5UBye6TGlcEVL3gDsTilXP1HLe6r6VgjkVtsHdx3ECNvU9vDnw3sknd1VMFOR9Crg1cC9J1QTvytwcjdRzUqf2gH8d9cB3EET9w0/krb3DR9TP5c/CJxJ+bz4dKcRNSrLQUeQpA8AT6VcDdmeUo74GNs7TPNrnenbvqo+knQvYDPbP5C0CrC87Ru6jmsiSYcCB9k+r+tYllYtTrA68L3hFgzxr5G0kmtj++nGWiHpxEmG3er7maR9KP3gvsniSWuTe8D6RtLPgDcPWhbUPaP/bXunbiNbXF22uialAMjbhu66oeXnQt9eb6NI0kG2X9t1HJOpW0xWanX5ddeSBI4oSWtRliXdVjd639X2VV3HNZm+7auapPAD0G6lLEmvoMyorGV701rp6xDbj+44tCVIupDSeP3XlBPSQVGNLTsNbBJ1P8oFtjfvOpalUZcFL/HG70abr0+2J7i1fcJ9JunXkwynkM0yImlryvL71SnvZ38CXlyryTZJ0kMpFw0Pl7Q25fxhsudJ3AF9rLY5ndbejyXtCRw5oSL6c21/otPAGpTloCOozvS8GtiIcvK/HqVJ6TFdxjWNvu2rOoxJCj80bE/KjPDPAWz/UtLduw1pSo/rOoDZqhdYfiFpI9u/6TqepTD8PrASpdn97zuKZUqS7gmsD6wsaRsWtYpZjbI0qUmS7gH8F7Ce7cdJ2oLSS/KwjkNbQt3n8zbbX+k6llFl+2xgK0mr1dvXdxvR9CTtTal6fT/K3sU7UeoJPKTLuKbSp9fbkMNZVG3zkdRqm51GNFpeYfvjgxu2/1wvhicJnCBJ4Gg6nJKgPLjevoKy+b/VJLBv+6r6VvjhZtv/GOwLlbQC02xO75LtywFqkrrSDA9vwZrABZJOY/H9KK1u8Mf214dvS/oS8NOOwpnOY4EXU5aJf3ho/HrgHV0ENEufpbwHv7Pe/j/KfqXmTkpt/1PSmynxxTIk6QW2vyDpDRPGAbD94Ul/sXtPA7ah7KXC9u8l3bXbkKb1WXryehuysu0TJKl+5u0j6QygyZYLPbR8PbaG21ft3KnjmJqUJHA0bWp7V9VmpLZvVMOVYWw/rf64T13fvzqltUVThqoU9q3ww0mS3kGZUdmZMkv8nY5jmpSkJ1MKgaxH2ad0L+AiStPXFq0EPHHotoD9O4rljtoMaG5muPbMOkLSMyYmro1b2/ZRkt4OYPtWSS2vGPiBpDexZGGNZveB9cRd6vfJEqgmL8JV/7BtSYMT6LvM9Asd69vrDfpXbXMmrZ1ffg/4iqRP1tuvpMFzyhYkCRxN/1DpBTd4E9+UBsvtS1rN9vV1/+LAoCDIqpS9Ey2ZWKVwwdDPLVcrfBvwMsqxfSVwLO1WytqPUhjoB7a3kfRI4AUdxzSdFWyfNDxQX3vNUmm+bup+S+AqGiz/PuRkSYfRn+Vef5N0Nxa9/+5IaXvSql3r9z2Hxgz0cn9SK2wPTkB/YHux6pp1X3lz6sXiY+rJ8xp1Cd1LKe1DWtW31xtMXm3zRZ1G9K85sOsAJngr5VznVfX28bR7ztOpFIYZQXW2512UTcfHUdbyv9j2j7qMayJJx9h+Yi1MMDgpHUhhgjEkaaHtBbWlxTZ1udo5trfqOrZhw+XUgV8N3XVX4GTbLSeuvSLpu9TlXra3qsuZzxo0LW5NXTFwEPBASn+4dYBn2j532l+MkdS3wka1UNsbgMdQPpO/b/v4bqOaWh9fb5KeZfurM411Tf3taxizlJnAEWT7eElnUmZUBOxl+48dh7UE20+s3zfpOpalIem/gAMmVJ56o+13dRrYBJKOsv3s+qE+8Y3clJnW/7H97fmPbkp/kbQq8GPgSElXM7RErSFfBL5Lz8qpD9Rltw+rN39ku9X9wtCz5V62z1RpF3I/yvvvL2zf0nFYU6qFxN4AbGR791q58H6NPyeaJ2knyr78dSbsC1wNWL6bqGblTOAvtt/cdSCztCmloNigX+8OtH9u+3ZKnYaZxrrWy76Gk1RwH1QZz8TCBJkJHFGS1mfJFgY/7i6iJQ3tsZtUq3vsJJ1le5sJY81d2ZW0ru0rVXoETmZtShnlZloc1P0nN1HetJ9P2R96pO1rOw1shKj0Ed0OOLIOPRc43XaTxVYk/Yhycne87W3rcq/9bT+828gmV4sQPAHYmMXff5ssBCLpK5RCYi+y/cCaFJ5ie+tuI+u3eiHgEcAewCFDd90AfMf2L7uIayaSLqa06bmcxfeINtemB0DSuba3VGlrsR8lcXm3G+yLLOlxwOOBZ7N4MabVgC1sb99JYCOmPoeXqOCe84gltX61JO4ASftT9nlcAPyzDpsyu9KSwR67lSj7686hnPxvCSwEmmqmO2T52sriZrh9D9idO45pCbavrN8vr2W0t6t3nWb7auBySc/vLMBJ2B6e9Tuis0BG2+OBrW3/E0DSEcBZtFtx8w3A0cCmkk6mLvfqNqRpfYdyIeM8Fr3/tqxXhcT6ou4VPknSZwdVj3visV0HsJQGJ/lPAD5l+38lvbfLgKbxe8q5zZMpCcrADZSkpUnqX1/DvlVw70ySwNH0VMpynuaKwQyz/UgASd8AtrV9Xr39QMpUfquOBE5QaboNpcdPswmLpGcDHwR+REmyD5L0Zttfs33GtL88zyQ9nVJd8+6UWAfLOFbrNLDRswaLCi+t3mEcs/FnYLHllcDWXQY0gw1anTWZQi8KifXYjbWa9ANY/AS6yUJiPUtYAa6ohWx2BvaXdGca7bln+xzgHElH2r6163iWQi/6Gva4gntnshx0BNVCCs+y/deuY5kNSRfYfsBMYy2RtAvw7/Xm8ba/32U806lFVnaus39IWodSsa6pYisAki4BnmT7oq5jGVV1xucDwImUpOphNNwwXKV/1pNtX1FvPwz4eMOFYfYHTrB9XNexzIakx1B6rA0XEnuJ7RM7DWxESDqOsvTvTZSlobsB19huuSJvb9Tly7sA59n+paR1gQe1+PqbYZ9+y0tuz7D9b5LOG7zvDsa6jm2YSouxqbjVCy9dShI4giR9HdgKOIHFr4K8rrOgpqHSrPpvwBfq0POBVW0/t7uo7jhJP7PdzFLW4Tfuens54JwWT6IlnWy7yfLpo6SeKA0vD76qy3imI2k74BPAk4BtKcuSnmj7t50GNgVJT6O8ly0H3EIPZrNrif1BIbFTWywk1ldDJ9DnDk7yJZ1ue7uZfjdGy0z79FudhZV0CvBQ4GvADyl9DT9g+36dBjYFSfe2felMY5EkcCRJ2m2ycZfmy82RtBKln8ugWuGPgYNt39RdVHfcZIVjulSXRWwJfKkO7Qqc2+KVaEkHAvcEvsXiFzC+0VVMo6ZWTjvb9t8kvYCSWB3Y6gkI3F5p8ZOUvXZPsH1NxyFNqba8eQplZqL5D1hJJ9h+9ExjccdIOtX2jpK+D3yUsi/sa7Y37Ti06JCkewLbU2YET+/BhbiLKNsI9qMUsvmg7VO7jGsqU7RlaW7msgXZEziCWk32pmL7JkmHAMfa/kXX8SwDzZz41QIPH6XM+jy0Dh9q+5vdRTWt1YAbKT2qBkxZ2x/LxsHAVpK2ohRdOQz4HGXfXTMm6VG1CqUJ9GGSWu5R9Vvg/NYTwHrxbRVg7drmZlAMZjVg/c4CGz3vlbQ68EZKP7vVaLgISMw9SS8H3k2ZVRvs09/X9me6jWxJtdrxrrbfBPyVsh+wSZI2p+y9Xb3WFxhYjaH9uLFIksARMs1688FypFbXmz+ZUrjkTsAmkrYG9m34JK83bFvSsXXpZ/OJlO1mP2BGyK31efEUyt66wyS9rOugJtHLHlXApcCP6t7s4dns1lpEvBL4D2A9SqXCQRJ4PfCxjmIaKfUEejOXnovXUYpqRLwZ2GbQsqAuxz4FaC4JtH1bbb/RB/cDnkiZsXzS0PgNwCu6CKh1SQJHy171+xM7jWLp7U1ZFvEjANtnS+pVA/kJWiuvfqak7Wyf3nUgU5H0FtsHSDqIyTfMN7mftaduUGm8/kLg/9U9oit2HNMSbJ9UT6J/MKgk3BO/rl93ql/Q0OqAAdsHAgdKeq3tg7qOZxTVE+jnUqoqRgxcS0lMBm6oY606S9LRlGb2w70jm7qwbPvbwLcl7WT7Z13H0wdJAkfIoC8c8Efg77b/Kem+wOZAyz1TbrF93YTWVM2dNA1Iei3wBdt/nuIhL5zPeGZhB+AFki6jvIG3ODP8VuAA4FeUlgAxd3YFnge81PZVkjaizMQ3p55E/1PS6rav6zqeWbrQ9leHByQ9q6tgZmL7IEkPZsnm9p/rLKjRcrKkj1EqhA6fQKdc/fi6BPi5pG9TznWeApwr6Q3Q5KqBlShJ6nB1zea2aQxfRK4XXxaTi8lLShI4mn5MucK/JqXk9+mUE7+mGoMPuUDS8yhN2DcDXkdZGtGqewCnSzqTsnzj+8P7f2yf31lkk+tD898/SFqPst/gEbQ3mzoyauL3dWCzOvRHoNU9olD2oZwn6XgWP4lu9QP97ZQr5jONNUHS54FNgbNZ1HjblH2i8a/bun7fd2jMLH5CHePlV/Vr4Nv1+107iGVGPdqmsbDrAPom1UFH0KAyUp2xWrkuszvb9tZdxzaZ2ufnnSwqBvJ9YD833Oy+Flx5DCVpWQAcBRxm+1fT/mJHahPVh1JOPk5u7Sp0fa6+Grg3pfz07XdRZi3v3UlgI0jSK4DdgbVsb1ovvBzSajXIvlQ7lvQ44PHAsymzPgOrAVvY3r6TwGYg6SJKfDkZiJhndTn+qrav7zqWqUg6nMm3aby0g3BiGcpM4GhSLan+fGBQ8GH5DuOZyRb1a4X69RTgyZS2Bk2qhTWuAq4CbgXWBL4m6Xjbb+k2usVJejfwLBYt3Thc0ldtv7fDsBZT9yQdJOlg26/qOp4RtydlD+7PAVwaLN+925Cm1lqyN43fU65EP5lSaGXgBtquBnk+pS3LlTM9MJaepHsA/wWsZ/txkrYAdrJ9WMehRUckfRHYgzLzfjqwmqQDbTe5LB84ZujnlYCnUd7vmiRpHcoWky0YqgqaZvFLykzgCJL0cEo56pNt7y/p3sB/tLp8StIvgDdRTkb+ORhvtW+ZpL2AF1GW0X0a+JbtW+oVvV+21v+pHt+tBn0XJa1M6RPXZKPXmFuSfm57h0E/S0krAGc2tkf0dnWm8v0s+YHe5OywpBVt31J/XhPY0Pa5HYc1JUknUpYsnsbi1UxTnXkZqFViDwfeaXur+no7q1ZsjjE0WJkl6fmUPq1vA85o9T14onqu81PbD+46lslIOo6yGuNNlGR7N+CaFnsjdy0zgSPI9knASUO3L6Xss2vVNba/03UQS2Et4OkTk9RaiKfFyqy/p5w831Rv35nFl1zGeDlJ0juAlSXtTFmG2/Lr73BKBeGPUErsvwRYrtOIpnd8bXuzAmVG8GpJp9hudTZwn64DGHFr2z6qVuTF9q2Sbpvpl2KkrShpReCpwMfqReQ+zchsBjS7egS4W219tNfgfFhSs9XRu5QkcATVK7uTrd9udSp8b0mfBk5g8SvRrVWeWqv+eOCE2wDY/pPti+Y9sJldRym+czzlebEzcJqkj0LTBTZibrwVeDlwHqVX3LGUGe1WrWz7BEmqF172kXQGpdlyi1a3fX1tCP0523tLanYmsJ4kxdz5W+0DN6hauCPlPTnG1yeBy4BzgB9LuhelP2dzav2D2ygFugauonyOtOqW+v1KSU+gXAhfa5rHj60kgaPpTUM/rwQ8g7JvrVUvobSxWJFFy0GbKz9Muao/SK4nVq80pahJi77J4tUff9RRHNGx2nfvAtubA5/qOp5Zunmw1FrSayiz2Kt2HNN0VpC0LqVAzDu7DmYqkn5q+6GSbmDxi4aDYkyrdRTaqHkDcDSwqaSTgXWAZ3YbUnTJ9keBjw4NXS6pyV6otf7BhbYf2HUsS+G9klanbIs6iFKcq9WVGJ3KnsAxIem0hqvT/SL707oj6eu2n9F1HDE/am+q19r+TdexzIak7YCLgDWA/Sgf6AfY/nmXcU2l9gT8T8qe7FfVPdkfzGtsfNV9gPejJNi/GOwZjfFUE5S9gYfVoZOAfVvthSrpCMqy1SypHDFJAkfQhGWKy1FaGBzYaqJVyw9/0PaFXccyW5KezqKWCz+x/a1uI7rjBgVCuo4j5oekHwPbUAqBDPfda7IQiKQFlBm1e1FWC0C5QN2LIgox3iStRNl3e/vnBaUly03T/mKMrNqn9XxgUPn4hZTibU/vLqqpSboYuA9wOeUzY7BaoMn3YEn3BQ4G7mH7gZK2BJ7cUkX0ViQJHEGSfs2i5T23Utae72v7p50FNY3ap2pT4NeUPYGtv8F8gvKG+KU6tCvwK9t7dhfVHTfoK9l1HDE/avXgJbS6N6xWt30zZQ9jH6oH5wQkbifpKEqbkC/UoecBa9h+VndRRZcm69vceC/ne0023vB78EmUz4xPDi5wSzq/Z0ta50X2BI6mLVjyyuPCTiOa3i5dB7CUHgXcf9BcuS6VuKDbkCJmZ6ZkT9LPbO80X/HMwjW2j+46iKXwKeoJCIDtc2tfsCSB4+mBtrcYun2ipN6seok58XdJDx1cmJf0EODvHcc0pVaTvWmsYvu0UtPmdi3XxehMksDRdASl0tRg4/HzgM9TGoY3p4dvMJcAG1GWRgBsWMf6amKRmxhvK838kHnVi+rBQ3ICEsPOlLSj7VMBJO1A2xdlY+69Cjii7g0E+DOll10sG3+UtCmLKvI+E7iy25DalCRwNOXK49y6K3CRpNPq7e2AhZKOhvb2VtVeOQdOM9ZyqeeYf63tEehL9eCBnIDEsH8DTpH0G8pz4l7ALySdR8PbHmJOXQQcQNkGswalZchTgWZbyfTMnsChwOaSrqBsNXp+tyG1KXsCR5CkL1AqOQ1fedzT9ou6jWw0TLWnaqC1vVWT7flLMZiYSmt7RPtWPbhWAz0UeDDlCv+vgef3cMVDLAN1P9WawP+rQz8G/jK4P8+L8SPpe5TnwJmUHnwA2P5QVzGNEkl3prRh2ZjSH/B6ygWXfbuMq0WZCRwhgyuLlCvmE688XtxlbKPE9kmS7glsTzm+p9u+quOwliDpuZSlwJsMZimruwJ/6iaq6IHWlgefImmLHlUPvtz2v0u6C7Cc7Ru6Dig69VTg5ZSZa1G2ZnzK9kFdBhWd2sB232oh9Mm3WZRk/77bUNqWmcARMlUFp4FccVw2JL0ceDfwQ8qH+sMp1Vc/02lgE9TnwybA+4G3Dd11A3Cu7exTiiVIeqDt87uOY6CH1YN/A3wP+ArwQ+dDdqxJOhfYyfbf6u27AD9r9fkbc0/SocBBts/rOpZRlEqgs5ckMGIp1ZL1D7Z9bb19N+CUPi1Zi/FVe1zuD9ydklANkqrVOg1sCj0sT74K8ETgOcC2wDHAl1tt0RNzq67Q2W7QF7D2DTzd9oO6jSzm29BqrRWAzYBL6cGFrb5Jkj17WQ4asfSupcymDdxQx5oi6ae2HyrpBhYv9tH0SX/MuQOAJ9m+qOtAZqPVZG8qtm8EjgKOkrQmcCBwErB8p4FFVw4Hfi7pm/X2U4HDugsnOvTErgMYZROS7JdISpI9g8wERiwlSZ8DHkRZd27gKZSqXucC2P5wd9FFTE/SybYf0nUco6wWj9qV0gN1IfAV21/vNqroiqRtKX17AX5i+6wu44kYRdkStfSSBEYsJUl7T3e/7ffMVywRS0vSgcA9gW/Rj757vSLpMuAsymzg0YO9YBERES1JEhgRMUYkHT7JsG2/dN6DGUGSVrN9fddxRERETCdJYMRSknQikzTUtv2oDsKJiIZIWgd4BaVH1e377pNkR0RES1IYJmLpvWno55WAZwBptxC9UKsTvgx4AOX5CyRJWYa+DfwE+AFDjaAjIiJakiQwYinZPmPC0MmSTuskmIil93ngYuCxwL7A84FeVArtiVVsv7XrICIiIqazXNcBRPSNpLWGvtaWtAuwetdxRczSfWz/J/A320cATwB26DimUXKMpMd3HURERMR0MhMYsfTOoOwJFHALcBlleV1EH9xSv/9F0gOBqyiN42PZ2At4h6SbKcc6fTkjIqI5SQIjlt5bge/Zvl7SfwLbAjd2HFPEbB1am5j/J3A0sCrw7m5DGh2279p1DBERETNJddCIpSTpXNtbSnoosB/w38C7bWdJXcSYkrS57YtrY/Al2D5zvmOKiIiYSmYCI5beoOLfE4BP2f5fSe/tMqCI2ZK0BvAilmxh8LqOQhoVbwB2Bz40yX0G0kImIiKakZnAiKUk6RjgCmBnylLQvwOn2d6q08AiZkHSKcCpwHnAPwfjtUhMzDFJO9s+vus4IiJivCUJjFhKklYBdgHOs/1LSesCD7J9XMehRcxI0pm2J12yGHMvxz8iIlqQJDAiYoxIej3wV+AY4ObBuO0/dRbUGJF0lu1tuo4jIiLGW/YERkSMl38AHwTeSdmrRv1+784iGi+58hoREZ1LEhgRMV7eSGkY/8euA4mIiIhuLNd1ABERMa8uIX0tu3RZ1wFERERkT2BExBiR9E3gAcCJLL4nMC0i5oCkBcDvbf++61giIiIGshw0ImK8fKt+xfx4LbClpP+zvWvXwUREREBmAiMiIuacpLvavqHrOCIiIiAzgRERY0XSr5mkQqXtVAddBiRN1gPwOuDy+Y4lIiJiKkkCIyLGy4Khn1cCngWs1VEso+gTwLbAuYCABwHnA6tLepXt47oMLiIiAlIdNCJirNi+dujrCtv/Azyh67hGyO+BbWwvsP1vwNbApcDOwAFdBhYRETGQmcCIiDEyYbnicpSZwXwWLDv3tX3B4IbtCyVtbvtSSV3GFRERcbt88EdEjJcPsWhP4K2UvnXP6iya0XOBpIOBL9fbuwIXSrozcEt3YUVERCyS6qAREWNE0krAM4CNWXQh0Lb37SyoESJpZeDVwEPr0MmUfYI3AavY/mtXsUVERAwkCYyIGCOSvgf8BTgTuG0wbvtDXcUUERER8ytJYETEGJF0vu0Hdh3HqJL0EGAf4F4MbblIC46IiGhJ9gRGRIyXUyQ9yPZ5XQcyog4DXg+cwdBMa0REREsyExgRMQYknUcpCLMCsBmlbcHNlF52tr1lh+GNDEk/t71D13FERERMJ0lgRMQYkHSv6e63ffl8xTLKJH0AWB74BiXJBsD2mZ0FFRERMUGSwIiIiGVE0omTDNv2o+Y9mIiIiCkkCYyIiIiIiBgjKQwTERHxL5L0AttfkPSGye63/eH5jikiImIqSQIjIiL+dXep3+/aaRQRERGzkOWgERERy4iktWz/acLYJrZ/3VVMEREREy3XdQAREREj5DuSVhvckHR/4DsdxhMREbGEJIERERHLzn9REsFVJf0b8DXgBR3HFBERsZjsCYyIiFhGbP+vpBWB4yj7A59m+/86DisiImIx2RMYERHxL5J0EDD8gfpo4FfAZQC2X9dBWBEREZPKTGBERMS/buGE22d0EkVERMQsZCYwIiIiIiJijGQmMCIiYhmR9BBgH+BelM9YAbZ97y7jioiIGJaZwIiIiGVE0sXA6ynLQW8bjNu+trOgIiIiJshMYERExLJzne3vdh1ERETEdDITGBERsYxI+gCwPPAN4ObBuO0zOwsqIiJigiSBERERy4ikEycZtu1HzXswERERU0gSGBERERERMUayJzAiImIZkvQE4AHASoMx2/t2F1FERMTilus6gIiIiFEh6RBgV+C1lPYQz6K0i4iIiGhGloNGREQsI5LOtb3l0PdVge/a/n9dxxYRETGQmcCIiIhl5+/1+42S1gNuAdbtMJ6IiIglZE9gRETEsnOMpDWAAygN4wE+3V04ERERS8py0IiIiGVE0srAq4D/Bxj4CXCw7Zs6DSwiImJIksCIiIhlRNJRwA3AF+rQ84DVbT+7u6giIiIWlyQwIiJiGZF0oe0tZhqLiIjoUgrDRERELDtnStpxcEPSDsDCDuOJiIhYQgrDRERE/IsknUfZA7gicIqk39Tb9wIu7jK2iIiIibIcNCIi4l8kadqG8LYvn69YIiIiZpIkMCIiIiIiYoxkT2BERERERMQYSRIYERERERExRpIERkREzJKkYyWtMcNjLpO0dv35lDv477xjwu079HciIiImkz2BERERy5Cky4AFtv/4L/yNv9peddlFFRERsUhmAiMiYqRIuouk/5V0jqTzJe1aZ+cOkHSepNMk3ac+dh1JX5d0ev16SB1fVdLh9fHnSnpGHR+e5fuWpDMkXSBp9yli+Wv9vq+ks+vXFZIOn+pvSPoAsHJ97JET/o4kfbD+d50nadc6/ghJP5L0NUkXSzpSkubwMEdERI+lT2BERIyaXYDf234CgKTVgf2B62w/SNKLgP8BnggcCHzE9k8lbQR8H7g/8J+Dx9e/seYk/85Lbf9J0srA6ZK+bvvayQKy/W7g3XUp6U+Aj03zN94m6TW2t57kTz0d2BrYCli7/s6P633bAA8Afg+cDDwE+OksjldERIyZzARGRMSoOQ/YWdL+kv6f7evq+JeGvu9Uf/534GOSzgaOBlaTtGod//jgD9r+8yT/zusknQOcCmwIbDZdUHVm7gvAh22fcUf+BvBQ4Eu2b7P9B+AkYLt632m2f2f7n8DZwMYz/K2IiBhTmQmMiIiRYvv/JG0LPB54r6QTBncNP6x+Xw7Y0fZNw39jppWUkh5BSRR3sn2jpB8BK80Q2j7A72wPloLekb8xnZuHfr6NfMZHRMQUMhMYEREjRdJ6wI22vwB8ENi23rXr0Pef1Z+PA1479Ltb1x+PB/YcGp+4HHR14M81edsc2HGGmJ5ESfheN8u/cYukFSf5Uz8BdpW0vKR1gIcBp033b0dEREyUJDAiIkbNg4DT6hLPvYH31vE1JZ0L7AW8vo69DlhQi79cCOxRx99bH39+Xa75yAn/xveAFSRdBHyAspxzOm8A1h/EJWnfGf7GocC5g8IwQ74JnAucA/wQeIvtq2b4tyMiIhaTFhERETHylkXbhoiIiFGRmcCIiIiIiIgxkpnAiIiIiIiIMZKZwIiIiIiIiDGSJDAiIiIiImKMJAmMiIiIiIgYI0kCIyIiIiIixkiSwIiIiIiIiDGSJDAiIiIiImKM/H9J2kTQkoCQjgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "sns.countplot('specialization', data = df, palette='hls') \n",
    "plt.xticks(rotation = 90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f27adbde",
   "metadata": {},
   "source": [
    "## 2.3 Columns with just one unique value are useless for building the future model, so there is a need to drop them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e69b144e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.614231Z",
     "start_time": "2022-05-24T08:22:15.604922Z"
    }
   },
   "outputs": [],
   "source": [
    "def drop_one_distinct_value_columns(df):\n",
    "    for col in df.columns:\n",
    "        if len(df[col].unique()) == 1:\n",
    "            df.drop(col,inplace=True,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e5a988cd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.745565Z",
     "start_time": "2022-05-24T08:22:15.618875Z"
    }
   },
   "outputs": [],
   "source": [
    "drop_one_distinct_value_columns(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "68585358",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.848346Z",
     "start_time": "2022-05-24T08:22:15.748112Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>prospect_id</th>\n",
       "      <td>7927b2df-8bba-4d29-b9a2-b6e0beafe620</td>\n",
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       "      <td>20ef72a2-fb3b-45e0-924e-551c5fa59095</td>\n",
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       "      <td>4aeae36b-2b57-494f-bdab-dd58844286b4</td>\n",
       "      <td>2d0109e9-dfb2-4664-83de-c2ea75ec7516</td>\n",
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       "      <td>c0b25922-511f-4c56-852e-ced210a45447</td>\n",
       "      <td>19d6451e-fcd6-407c-b83b-48e1af805ea9</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_number</th>\n",
       "      <td>660737.0</td>\n",
       "      <td>660728.0</td>\n",
       "      <td>660727.0</td>\n",
       "      <td>660719.0</td>\n",
       "      <td>660681.0</td>\n",
       "      <td>660680.0</td>\n",
       "      <td>660673.0</td>\n",
       "      <td>660664.0</td>\n",
       "      <td>660624.0</td>\n",
       "      <td>660616.0</td>\n",
       "      <td>...</td>\n",
       "      <td>579701.0</td>\n",
       "      <td>579697.0</td>\n",
       "      <td>579642.0</td>\n",
       "      <td>579622.0</td>\n",
       "      <td>579615.0</td>\n",
       "      <td>579564.0</td>\n",
       "      <td>579546.0</td>\n",
       "      <td>579545.0</td>\n",
       "      <td>579538.0</td>\n",
       "      <td>579533.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_origin</th>\n",
       "      <td>api</td>\n",
       "      <td>api</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>api</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>api</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>api</td>\n",
       "      <td>...</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>api</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "      <td>landing_page_submission</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_source</th>\n",
       "      <td>olark_chat</td>\n",
       "      <td>organic_search</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>google</td>\n",
       "      <td>olark_chat</td>\n",
       "      <td>google</td>\n",
       "      <td>olark_chat</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>google</td>\n",
       "      <td>...</td>\n",
       "      <td>google</td>\n",
       "      <td>google</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>direct_traffic</td>\n",
       "      <td>google</td>\n",
       "      <td>direct_traffic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_email</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_call</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>converted</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalvisits</th>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_time_spent_on_website</th>\n",
       "      <td>0.0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>1532.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>1428.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1640.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>...</td>\n",
       "      <td>870.0</td>\n",
       "      <td>1016.0</td>\n",
       "      <td>1770.0</td>\n",
       "      <td>1409.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>1845.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>1279.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_views_per_visit</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.67</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_activity</th>\n",
       "      <td>page_visited_on_website</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>unreachable</td>\n",
       "      <td>converted_to_lead</td>\n",
       "      <td>olark_chat_conversation</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>olark_chat_conversation</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>...</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>email_marked_spam</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>...</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>saudi_arabia</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>india</td>\n",
       "      <td>bangladesh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>specialization</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>business_administration</td>\n",
       "      <td>media_and_advertising</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>supply_chain_management</td>\n",
       "      <td>select</td>\n",
       "      <td>it_projects_management</td>\n",
       "      <td>finance_management</td>\n",
       "      <td>...</td>\n",
       "      <td>human_resource_management</td>\n",
       "      <td>banking,_investment_and_insurance</td>\n",
       "      <td>human_resource_management</td>\n",
       "      <td>select</td>\n",
       "      <td>business_administration</td>\n",
       "      <td>it_projects_management</td>\n",
       "      <td>media_and_advertising</td>\n",
       "      <td>business_administration</td>\n",
       "      <td>human_resource_management</td>\n",
       "      <td>supply_chain_management</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>how_did_you_hear_about_x_education</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>word_of_mouth</td>\n",
       "      <td>other</td>\n",
       "      <td>select</td>\n",
       "      <td>online_search</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>word_of_mouth</td>\n",
       "      <td>...</td>\n",
       "      <td>online_search</td>\n",
       "      <td>online_search</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>online_search</td>\n",
       "      <td>select</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_is_your_current_occupation</th>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>student</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>...</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>unemployed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_matters_most_to_you_in_choosing_a_course</th>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>...</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "      <td>better_career_prospects</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>search</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper_article</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x_education_forums</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>digital_advertisement</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>through_recommendations</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>interested_in_other_courses</td>\n",
       "      <td>ringing</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>ringing</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>...</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>ringing</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>wrong_number_given</td>\n",
       "      <td>invalid_number</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "      <td>will_revert_after_reading_the_email</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_quality</th>\n",
       "      <td>low_in_relevance</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "      <td>not_sure</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "      <td>low_in_relevance</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "      <td>...</td>\n",
       "      <td>might_be</td>\n",
       "      <td>high_in_relevance</td>\n",
       "      <td>not_sure</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "      <td>high_in_relevance</td>\n",
       "      <td>might_be</td>\n",
       "      <td>not_sure</td>\n",
       "      <td>might_be</td>\n",
       "      <td>might_be</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_profile</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>...</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>select</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>potential_lead</td>\n",
       "      <td>select</td>\n",
       "      <td>potential_lead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <td>select</td>\n",
       "      <td>select</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>thane_&amp;_outskirts</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>...</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>select</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>mumbai</td>\n",
       "      <td>other_metro_cities</td>\n",
       "      <td>other_cities</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_activity_index</th>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>...</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_profile_index</th>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>medium</td>\n",
       "      <td>...</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>high</td>\n",
       "      <td>medium</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_activity_score</th>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.306252</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_profile_score</th>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.344883</td>\n",
       "      <td>20.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a_free_copy_of_mastering_the_interview</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_notable_activity</th>\n",
       "      <td>modified</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>modified</td>\n",
       "      <td>modified</td>\n",
       "      <td>modified</td>\n",
       "      <td>modified</td>\n",
       "      <td>modified</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>...</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>email_opened</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>modified</td>\n",
       "      <td>email_marked_spam</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>sms_sent</td>\n",
       "      <td>modified</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32 rows × 9240 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                               0     \\\n",
       "prospect_id                                    7927b2df-8bba-4d29-b9a2-b6e0beafe620   \n",
       "lead_number                                                                660737.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                              olark_chat   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     0.0   \n",
       "total_time_spent_on_website                                                     0.0   \n",
       "page_views_per_visit                                                            0.0   \n",
       "last_activity                                               page_visited_on_website   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                    interested_in_other_courses   \n",
       "lead_quality                                                       low_in_relevance   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         select   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               1     \\\n",
       "prospect_id                                    2a272436-5132-4136-86fa-dcc88c88f482   \n",
       "lead_number                                                                660728.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                          organic_search   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     5.0   \n",
       "total_time_spent_on_website                                                   674.0   \n",
       "page_views_per_visit                                                            2.5   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                                        ringing   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         select   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                               2     \\\n",
       "prospect_id                                    8cc8c611-a219-4f35-ad23-fdfd2656bd8a   \n",
       "lead_number                                                                660727.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                  1532.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                              business_administration   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                             student   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                               3     \\\n",
       "prospect_id                                    0cc2df48-7cf4-4e39-9de9-19797f9b38cc   \n",
       "lead_number                                                                660719.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     1.0   \n",
       "total_time_spent_on_website                                                   305.0   \n",
       "page_views_per_visit                                                            1.0   \n",
       "last_activity                                                           unreachable   \n",
       "country                                                                       india   \n",
       "specialization                                                media_and_advertising   \n",
       "how_did_you_hear_about_x_education                                    word_of_mouth   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                                        ringing   \n",
       "lead_quality                                                               not_sure   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    13.0   \n",
       "asymmetrique_profile_score                                                     17.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               4     \\\n",
       "prospect_id                                    3256f628-e534-4826-9d63-4a8b88782852   \n",
       "lead_number                                                                660681.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                  1428.0   \n",
       "page_views_per_visit                                                            1.0   \n",
       "last_activity                                                     converted_to_lead   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                            other   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     18.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               5     \\\n",
       "prospect_id                                    2058ef08-2858-443e-a01f-a9237db2f5ce   \n",
       "lead_number                                                                660680.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                              olark_chat   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     0.0   \n",
       "total_time_spent_on_website                                                     0.0   \n",
       "page_views_per_visit                                                            0.0   \n",
       "last_activity                                               olark_chat_conversation   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                    high   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    17.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               6     \\\n",
       "prospect_id                                    9fae7df4-169d-489b-afe4-0f3d752542ed   \n",
       "lead_number                                                                660673.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                  1640.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                              supply_chain_management   \n",
       "how_did_you_hear_about_x_education                                    online_search   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                       low_in_relevance   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               7     \\\n",
       "prospect_id                                    20ef72a2-fb3b-45e0-924e-551c5fa59095   \n",
       "lead_number                                                                660664.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                              olark_chat   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     0.0   \n",
       "total_time_spent_on_website                                                     0.0   \n",
       "page_views_per_visit                                                            0.0   \n",
       "last_activity                                               olark_chat_conversation   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     15.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               8     \\\n",
       "prospect_id                                    cfa0128c-a0da-4656-9d47-0aa4e67bf690   \n",
       "lead_number                                                                660624.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                    71.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                               it_projects_management   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                              thane_&_outskirts   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     14.0   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                               9     \\\n",
       "prospect_id                                    af465dfc-7204-4130-9e05-33231863c4b5   \n",
       "lead_number                                                                660616.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     4.0   \n",
       "total_time_spent_on_website                                                    58.0   \n",
       "page_views_per_visit                                                            4.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                                   finance_management   \n",
       "how_did_you_hear_about_x_education                                    word_of_mouth   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    13.0   \n",
       "asymmetrique_profile_score                                                     16.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                               ...  \\\n",
       "prospect_id                                    ...   \n",
       "lead_number                                    ...   \n",
       "lead_origin                                    ...   \n",
       "lead_source                                    ...   \n",
       "do_not_email                                   ...   \n",
       "do_not_call                                    ...   \n",
       "converted                                      ...   \n",
       "totalvisits                                    ...   \n",
       "total_time_spent_on_website                    ...   \n",
       "page_views_per_visit                           ...   \n",
       "last_activity                                  ...   \n",
       "country                                        ...   \n",
       "specialization                                 ...   \n",
       "how_did_you_hear_about_x_education             ...   \n",
       "what_is_your_current_occupation                ...   \n",
       "what_matters_most_to_you_in_choosing_a_course  ...   \n",
       "search                                         ...   \n",
       "newspaper_article                              ...   \n",
       "x_education_forums                             ...   \n",
       "newspaper                                      ...   \n",
       "digital_advertisement                          ...   \n",
       "through_recommendations                        ...   \n",
       "tags                                           ...   \n",
       "lead_quality                                   ...   \n",
       "lead_profile                                   ...   \n",
       "city                                           ...   \n",
       "asymmetrique_activity_index                    ...   \n",
       "asymmetrique_profile_index                     ...   \n",
       "asymmetrique_activity_score                    ...   \n",
       "asymmetrique_profile_score                     ...   \n",
       "a_free_copy_of_mastering_the_interview         ...   \n",
       "last_notable_activity                          ...   \n",
       "\n",
       "                                                                               9230  \\\n",
       "prospect_id                                    d11c15b7-8056-45a6-8954-771c0d0495fe   \n",
       "lead_number                                                                579701.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                   870.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                            human_resource_management   \n",
       "how_did_you_hear_about_x_education                                    online_search   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    13.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                               9231  \\\n",
       "prospect_id                                    4aeae36b-2b57-494f-bdab-dd58844286b4   \n",
       "lead_number                                                                579697.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     8.0   \n",
       "total_time_spent_on_website                                                  1016.0   \n",
       "page_views_per_visit                                                            4.0   \n",
       "last_activity                                                          email_opened   \n",
       "country                                                                       india   \n",
       "specialization                                    banking,_investment_and_insurance   \n",
       "how_did_you_hear_about_x_education                                    online_search   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                      high_in_relevance   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                  email_opened   \n",
       "\n",
       "                                                                               9232  \\\n",
       "prospect_id                                    2d0109e9-dfb2-4664-83de-c2ea75ec7516   \n",
       "lead_number                                                                579642.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                  1770.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                            human_resource_management   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                                        ringing   \n",
       "lead_quality                                                               not_sure   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                      sms_sent   \n",
       "\n",
       "                                                                               9233  \\\n",
       "prospect_id                                    3f715465-2546-47cd-afa8-8b8dc63b8b43   \n",
       "lead_number                                                                579622.0   \n",
       "lead_origin                                                                     api   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                    13.0   \n",
       "total_time_spent_on_website                                                  1409.0   \n",
       "page_views_per_visit                                                            2.6   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                                               select   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                                         select   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                               14.306252   \n",
       "asymmetrique_profile_score                                                16.344883   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      sms_sent   \n",
       "\n",
       "                                                                               9234  \\\n",
       "prospect_id                                    c0b25922-511f-4c56-852e-ced210a45447   \n",
       "lead_number                                                                579615.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     5.0   \n",
       "total_time_spent_on_website                                                   210.0   \n",
       "page_views_per_visit                                                            2.5   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                              business_administration   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      modified   \n",
       "\n",
       "                                                                               9235  \\\n",
       "prospect_id                                    19d6451e-fcd6-407c-b83b-48e1af805ea9   \n",
       "lead_number                                                                579564.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                    yes   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     8.0   \n",
       "total_time_spent_on_website                                                  1845.0   \n",
       "page_views_per_visit                                                           2.67   \n",
       "last_activity                                                     email_marked_spam   \n",
       "country                                                                saudi_arabia   \n",
       "specialization                                               it_projects_management   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                      high_in_relevance   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     17.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                             email_marked_spam   \n",
       "\n",
       "                                                                               9236  \\\n",
       "prospect_id                                    82a7005b-7196-4d56-95ce-a79f937a158d   \n",
       "lead_number                                                                579546.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                   238.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                                media_and_advertising   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                             wrong_number_given   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    14.0   \n",
       "asymmetrique_profile_score                                                     19.0   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                      sms_sent   \n",
       "\n",
       "                                                                               9237  \\\n",
       "prospect_id                                    aac550fe-a586-452d-8d3c-f1b62c94e02c   \n",
       "lead_number                                                                579545.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                          direct_traffic   \n",
       "do_not_email                                                                    yes   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       0.0   \n",
       "totalvisits                                                                     2.0   \n",
       "total_time_spent_on_website                                                   199.0   \n",
       "page_views_per_visit                                                            2.0   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                              business_administration   \n",
       "how_did_you_hear_about_x_education                                           select   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                                                 invalid_number   \n",
       "lead_quality                                                               not_sure   \n",
       "lead_profile                                                         potential_lead   \n",
       "city                                                                         mumbai   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                     high   \n",
       "asymmetrique_activity_score                                                    13.0   \n",
       "asymmetrique_profile_score                                                     20.0   \n",
       "a_free_copy_of_mastering_the_interview                                          yes   \n",
       "last_notable_activity                                                      sms_sent   \n",
       "\n",
       "                                                                               9238  \\\n",
       "prospect_id                                    5330a7d1-2f2b-4df4-85d6-64ca2f6b95b9   \n",
       "lead_number                                                                579538.0   \n",
       "lead_origin                                                 landing_page_submission   \n",
       "lead_source                                                                  google   \n",
       "do_not_email                                                                     no   \n",
       "do_not_call                                                                      no   \n",
       "converted                                                                       1.0   \n",
       "totalvisits                                                                     3.0   \n",
       "total_time_spent_on_website                                                   499.0   \n",
       "page_views_per_visit                                                            3.0   \n",
       "last_activity                                                              sms_sent   \n",
       "country                                                                       india   \n",
       "specialization                                            human_resource_management   \n",
       "how_did_you_hear_about_x_education                                    online_search   \n",
       "what_is_your_current_occupation                                          unemployed   \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects   \n",
       "search                                                                           no   \n",
       "newspaper_article                                                                no   \n",
       "x_education_forums                                                               no   \n",
       "newspaper                                                                        no   \n",
       "digital_advertisement                                                            no   \n",
       "through_recommendations                                                          no   \n",
       "tags                                            will_revert_after_reading_the_email   \n",
       "lead_quality                                                               might_be   \n",
       "lead_profile                                                                 select   \n",
       "city                                                             other_metro_cities   \n",
       "asymmetrique_activity_index                                                  medium   \n",
       "asymmetrique_profile_index                                                   medium   \n",
       "asymmetrique_activity_score                                                    15.0   \n",
       "asymmetrique_profile_score                                                     16.0   \n",
       "a_free_copy_of_mastering_the_interview                                           no   \n",
       "last_notable_activity                                                      sms_sent   \n",
       "\n",
       "                                                                               9239  \n",
       "prospect_id                                    571b5c8e-a5b2-4d57-8574-f2ffb06fdeff  \n",
       "lead_number                                                                579533.0  \n",
       "lead_origin                                                 landing_page_submission  \n",
       "lead_source                                                          direct_traffic  \n",
       "do_not_email                                                                     no  \n",
       "do_not_call                                                                      no  \n",
       "converted                                                                       1.0  \n",
       "totalvisits                                                                     6.0  \n",
       "total_time_spent_on_website                                                  1279.0  \n",
       "page_views_per_visit                                                            3.0  \n",
       "last_activity                                                              sms_sent  \n",
       "country                                                                  bangladesh  \n",
       "specialization                                              supply_chain_management  \n",
       "how_did_you_hear_about_x_education                                           select  \n",
       "what_is_your_current_occupation                                          unemployed  \n",
       "what_matters_most_to_you_in_choosing_a_course               better_career_prospects  \n",
       "search                                                                           no  \n",
       "newspaper_article                                                                no  \n",
       "x_education_forums                                                               no  \n",
       "newspaper                                                                        no  \n",
       "digital_advertisement                                                            no  \n",
       "through_recommendations                                                          no  \n",
       "tags                                            will_revert_after_reading_the_email  \n",
       "lead_quality                                                               might_be  \n",
       "lead_profile                                                         potential_lead  \n",
       "city                                                                   other_cities  \n",
       "asymmetrique_activity_index                                                  medium  \n",
       "asymmetrique_profile_index                                                     high  \n",
       "asymmetrique_activity_score                                                    15.0  \n",
       "asymmetrique_profile_score                                                     18.0  \n",
       "a_free_copy_of_mastering_the_interview                                          yes  \n",
       "last_notable_activity                                                      modified  \n",
       "\n",
       "[32 rows x 9240 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e9c5ce8a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.867509Z",
     "start_time": "2022-05-24T08:22:15.855668Z"
    }
   },
   "outputs": [],
   "source": [
    "df.drop(['prospect_id', 'lead_number'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fe5102c4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:15.882471Z",
     "start_time": "2022-05-24T08:22:15.873553Z"
    }
   },
   "outputs": [],
   "source": [
    "categorical = ['lead_origin', 'lead_source', 'do_not_email', 'do_not_call',\n",
    "       'last_activity', 'country', 'specialization',\n",
    "       'how_did_you_hear_about_x_education', 'what_is_your_current_occupation',\n",
    "       'what_matters_most_to_you_in_choosing_a_course', 'search',\n",
    "       'newspaper_article', 'newspaper', 'digital_advertisement',\n",
    "       'through_recommendations', 'tags', 'lead_quality', 'lead_profile',\n",
    "       'city', 'asymmetrique_activity_index', 'asymmetrique_profile_index',\n",
    "       'a_free_copy_of_mastering_the_interview', 'last_notable_activity']\n",
    "\n",
    "numerical = ['totalvisits', 'totalvisits', 'total_time_spent_on_website', 'page_views_per_visit', \n",
    "             'asymmetrique_activity_score', 'asymmetrique_profile_score']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a1d11db",
   "metadata": {},
   "source": [
    "## 2.4 Feature importance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24a7a264",
   "metadata": {},
   "source": [
    "### 2.4.1 Overview of lead conversion rate (which is here just mean value, because target variable is categorical) and lead conversion risk ratio (chance to become an actual client) for each group of categorical variables - it's really helpful for better understanding of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "11525b10",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:16.300900Z",
     "start_time": "2022-05-24T08:22:15.885603Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>diff</th>\n",
       "      <th>convert_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_origin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>api</th>\n",
       "      <td>0.311453</td>\n",
       "      <td>-0.073937</td>\n",
       "      <td>0.808150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>landing_page_submission</th>\n",
       "      <td>0.361850</td>\n",
       "      <td>-0.023539</td>\n",
       "      <td>0.938920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_add_form</th>\n",
       "      <td>0.924791</td>\n",
       "      <td>0.539401</td>\n",
       "      <td>2.399626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_import</th>\n",
       "      <td>0.236364</td>\n",
       "      <td>-0.149026</td>\n",
       "      <td>0.613311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>quick_add_form</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
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       "    </tr>\n",
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      "text/plain": [
       "                             mean      diff  convert_risk\n",
       "lead_origin                                              \n",
       "api                      0.311453 -0.073937      0.808150\n",
       "landing_page_submission  0.361850 -0.023539      0.938920\n",
       "lead_add_form            0.924791  0.539401      2.399626\n",
       "lead_import              0.236364 -0.149026      0.613311\n",
       "quick_add_form           1.000000  0.614610      2.594777"
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       "      <th>diff</th>\n",
       "      <th>convert_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_source</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bing</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>-0.218723</td>\n",
       "      <td>0.432463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>blog</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>click2call</th>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.364610</td>\n",
       "      <td>1.946083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>direct_traffic</th>\n",
       "      <td>0.321667</td>\n",
       "      <td>-0.063722</td>\n",
       "      <td>0.834655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>facebook</th>\n",
       "      <td>0.236364</td>\n",
       "      <td>-0.149026</td>\n",
       "      <td>0.613311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>google</th>\n",
       "      <td>0.404263</td>\n",
       "      <td>0.018873</td>\n",
       "      <td>1.048971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>live_chat</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nc_edm</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>olark_chat</th>\n",
       "      <td>0.255271</td>\n",
       "      <td>-0.130119</td>\n",
       "      <td>0.662370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>organic_search</th>\n",
       "      <td>0.377816</td>\n",
       "      <td>-0.007573</td>\n",
       "      <td>0.980349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pay_per_click_ads</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>press_release</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reference</th>\n",
       "      <td>0.917603</td>\n",
       "      <td>0.532213</td>\n",
       "      <td>2.380975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>referral_sites</th>\n",
       "      <td>0.248000</td>\n",
       "      <td>-0.137390</td>\n",
       "      <td>0.643505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>social_media</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>testone</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>welearn</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>welearnblog_home</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>welingak_website</th>\n",
       "      <td>0.985915</td>\n",
       "      <td>0.600526</td>\n",
       "      <td>2.558231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>youtubechannel</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mean      diff  convert_risk\n",
       "lead_source                                        \n",
       "bing               0.166667 -0.218723      0.432463\n",
       "blog               0.000000 -0.385390      0.000000\n",
       "click2call         0.750000  0.364610      1.946083\n",
       "direct_traffic     0.321667 -0.063722      0.834655\n",
       "facebook           0.236364 -0.149026      0.613311\n",
       "google             0.404263  0.018873      1.048971\n",
       "live_chat          1.000000  0.614610      2.594777\n",
       "nc_edm             1.000000  0.614610      2.594777\n",
       "olark_chat         0.255271 -0.130119      0.662370\n",
       "organic_search     0.377816 -0.007573      0.980349\n",
       "pay_per_click_ads  0.000000 -0.385390      0.000000\n",
       "press_release      0.000000 -0.385390      0.000000\n",
       "reference          0.917603  0.532213      2.380975\n",
       "referral_sites     0.248000 -0.137390      0.643505\n",
       "social_media       0.500000  0.114610      1.297388\n",
       "testone            0.000000 -0.385390      0.000000\n",
       "welearn            1.000000  0.614610      2.594777\n",
       "welearnblog_home   0.000000 -0.385390      0.000000\n",
       "welingak_website   0.985915  0.600526      2.558231\n",
       "youtubechannel     0.000000 -0.385390      0.000000"
      ]
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>do_not_email</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
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       "      <td>0.019383</td>\n",
       "      <td>1.050296</td>\n",
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       "    <tr>\n",
       "      <th>yes</th>\n",
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      "text/plain": [
       "                  mean      diff  convert_risk\n",
       "do_not_email                                  \n",
       "no            0.404773  0.019383      1.050296\n",
       "yes           0.160763 -0.224627      0.417144"
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       "      <th>no</th>\n",
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       "    <tr>\n",
       "      <th>yes</th>\n",
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       "                 mean      diff  convert_risk\n",
       "do_not_call                                  \n",
       "no           0.385257 -0.000133      0.999655\n",
       "yes          1.000000  0.614610      2.594777"
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       "      <th>diff</th>\n",
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       "      <th>last_activity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>approached_upfront</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>converted_to_lead</th>\n",
       "      <td>0.126168</td>\n",
       "      <td>-0.259221</td>\n",
       "      <td>0.327378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_bounced</th>\n",
       "      <td>0.079755</td>\n",
       "      <td>-0.305635</td>\n",
       "      <td>0.206945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_link_clicked</th>\n",
       "      <td>0.273408</td>\n",
       "      <td>-0.111981</td>\n",
       "      <td>0.709433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_marked_spam</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_opened</th>\n",
       "      <td>0.376836</td>\n",
       "      <td>-0.008553</td>\n",
       "      <td>0.977806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_received</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>form_submitted_on_website</th>\n",
       "      <td>0.241379</td>\n",
       "      <td>-0.144010</td>\n",
       "      <td>0.626325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>had_a_phone_conversation</th>\n",
       "      <td>0.733333</td>\n",
       "      <td>0.347944</td>\n",
       "      <td>1.902836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>olark_chat_conversation</th>\n",
       "      <td>0.086331</td>\n",
       "      <td>-0.299059</td>\n",
       "      <td>0.224010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_visited_on_website</th>\n",
       "      <td>0.235937</td>\n",
       "      <td>-0.149452</td>\n",
       "      <td>0.612205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>resubscribed_to_emails</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sms_sent</th>\n",
       "      <td>0.629144</td>\n",
       "      <td>0.243754</td>\n",
       "      <td>1.632488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unreachable</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>-0.052056</td>\n",
       "      <td>0.864926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unsubscribed</th>\n",
       "      <td>0.262295</td>\n",
       "      <td>-0.123095</td>\n",
       "      <td>0.680597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>view_in_browser_link_clicked</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>-0.218723</td>\n",
       "      <td>0.432463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>visited_booth_in_tradeshow</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  mean      diff  convert_risk\n",
       "last_activity                                                 \n",
       "approached_upfront            1.000000  0.614610      2.594777\n",
       "converted_to_lead             0.126168 -0.259221      0.327378\n",
       "email_bounced                 0.079755 -0.305635      0.206945\n",
       "email_link_clicked            0.273408 -0.111981      0.709433\n",
       "email_marked_spam             1.000000  0.614610      2.594777\n",
       "email_opened                  0.376836 -0.008553      0.977806\n",
       "email_received                1.000000  0.614610      2.594777\n",
       "form_submitted_on_website     0.241379 -0.144010      0.626325\n",
       "had_a_phone_conversation      0.733333  0.347944      1.902836\n",
       "olark_chat_conversation       0.086331 -0.299059      0.224010\n",
       "page_visited_on_website       0.235937 -0.149452      0.612205\n",
       "resubscribed_to_emails        1.000000  0.614610      2.594777\n",
       "sms_sent                      0.629144  0.243754      1.632488\n",
       "unreachable                   0.333333 -0.052056      0.864926\n",
       "unsubscribed                  0.262295 -0.123095      0.680597\n",
       "view_in_browser_link_clicked  0.166667 -0.218723      0.432463\n",
       "visited_booth_in_tradeshow    0.000000 -0.385390      0.000000"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>diff</th>\n",
       "      <th>convert_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>asia/pacific_region</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>australia</th>\n",
       "      <td>0.230769</td>\n",
       "      <td>-0.154620</td>\n",
       "      <td>0.598795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bahrain</th>\n",
       "      <td>0.571429</td>\n",
       "      <td>0.186039</td>\n",
       "      <td>1.482730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bangladesh</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>belgium</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>canada</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>china</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>denmark</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>france</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>germany</th>\n",
       "      <td>0.250000</td>\n",
       "      <td>-0.135390</td>\n",
       "      <td>0.648694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ghana</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hong_kong</th>\n",
       "      <td>0.571429</td>\n",
       "      <td>0.186039</td>\n",
       "      <td>1.482730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>india</th>\n",
       "      <td>0.388361</td>\n",
       "      <td>0.002972</td>\n",
       "      <td>1.007711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>indonesia</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>italy</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kenya</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kuwait</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>liberia</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>malaysia</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>netherlands</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nigeria</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oman</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>philippines</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>qatar</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>-0.285390</td>\n",
       "      <td>0.259478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>russia</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>saudi_arabia</th>\n",
       "      <td>0.190476</td>\n",
       "      <td>-0.194913</td>\n",
       "      <td>0.494243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>singapore</th>\n",
       "      <td>0.458333</td>\n",
       "      <td>0.072944</td>\n",
       "      <td>1.189273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>south_africa</th>\n",
       "      <td>0.250000</td>\n",
       "      <td>-0.135390</td>\n",
       "      <td>0.648694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sri_lanka</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sweden</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>-0.052056</td>\n",
       "      <td>0.864926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>switzerland</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tanzania</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uganda</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>united_arab_emirates</th>\n",
       "      <td>0.377358</td>\n",
       "      <td>-0.008031</td>\n",
       "      <td>0.979161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>united_kingdom</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>-0.052056</td>\n",
       "      <td>0.864926</td>\n",
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       "    <tr>\n",
       "      <th>united_states</th>\n",
       "      <td>0.260870</td>\n",
       "      <td>-0.124520</td>\n",
       "      <td>0.676898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unknown</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.185390</td>\n",
       "      <td>0.518955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vietnam</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                          mean      diff  convert_risk\n",
       "country                                               \n",
       "asia/pacific_region   0.500000  0.114610      1.297388\n",
       "australia             0.230769 -0.154620      0.598795\n",
       "bahrain               0.571429  0.186039      1.482730\n",
       "bangladesh            0.500000  0.114610      1.297388\n",
       "belgium               0.000000 -0.385390      0.000000\n",
       "canada                0.000000 -0.385390      0.000000\n",
       "china                 0.000000 -0.385390      0.000000\n",
       "denmark               1.000000  0.614610      2.594777\n",
       "france                0.500000  0.114610      1.297388\n",
       "germany               0.250000 -0.135390      0.648694\n",
       "ghana                 0.000000 -0.385390      0.000000\n",
       "hong_kong             0.571429  0.186039      1.482730\n",
       "india                 0.388361  0.002972      1.007711\n",
       "indonesia             0.000000 -0.385390      0.000000\n",
       "italy                 0.000000 -0.385390      0.000000\n",
       "kenya                 0.000000 -0.385390      0.000000\n",
       "kuwait                0.000000 -0.385390      0.000000\n",
       "liberia               0.000000 -0.385390      0.000000\n",
       "malaysia              0.000000 -0.385390      0.000000\n",
       "netherlands           0.500000  0.114610      1.297388\n",
       "nigeria               0.000000 -0.385390      0.000000\n",
       "oman                  0.500000  0.114610      1.297388\n",
       "philippines           0.000000 -0.385390      0.000000\n",
       "qatar                 0.100000 -0.285390      0.259478\n",
       "russia                0.000000 -0.385390      0.000000\n",
       "saudi_arabia          0.190476 -0.194913      0.494243\n",
       "singapore             0.458333  0.072944      1.189273\n",
       "south_africa          0.250000 -0.135390      0.648694\n",
       "sri_lanka             0.000000 -0.385390      0.000000\n",
       "sweden                0.333333 -0.052056      0.864926\n",
       "switzerland           0.000000 -0.385390      0.000000\n",
       "tanzania              0.000000 -0.385390      0.000000\n",
       "uganda                0.000000 -0.385390      0.000000\n",
       "united_arab_emirates  0.377358 -0.008031      0.979161\n",
       "united_kingdom        0.333333 -0.052056      0.864926\n",
       "united_states         0.260870 -0.124520      0.676898\n",
       "unknown               0.200000 -0.185390      0.518955\n",
       "vietnam               0.000000 -0.385390      0.000000"
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       "  <tbody>\n",
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       "      <th>banking,_investment_and_insurance</th>\n",
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       "      <td>0.108693</td>\n",
       "      <td>1.282035</td>\n",
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       "      <td>1.152519</td>\n",
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       "      <th>finance_management</th>\n",
       "      <td>0.446721</td>\n",
       "      <td>0.061332</td>\n",
       "      <td>1.159142</td>\n",
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       "      <th>healthcare_management</th>\n",
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       "      <td>0.111466</td>\n",
       "      <td>1.289229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hospitality_management</th>\n",
       "      <td>0.421053</td>\n",
       "      <td>0.035663</td>\n",
       "      <td>1.092538</td>\n",
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       "    <tr>\n",
       "      <th>human_resource_management</th>\n",
       "      <td>0.457547</td>\n",
       "      <td>0.072158</td>\n",
       "      <td>1.187233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>international_business</th>\n",
       "      <td>0.359551</td>\n",
       "      <td>-0.025839</td>\n",
       "      <td>0.932953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>it_projects_management</th>\n",
       "      <td>0.382514</td>\n",
       "      <td>-0.002876</td>\n",
       "      <td>0.992538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>marketing_management</th>\n",
       "      <td>0.486874</td>\n",
       "      <td>0.101484</td>\n",
       "      <td>1.263328</td>\n",
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       "    <tr>\n",
       "      <th>media_and_advertising</th>\n",
       "      <td>0.418719</td>\n",
       "      <td>0.033330</td>\n",
       "      <td>1.086483</td>\n",
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       "    <tr>\n",
       "      <th>operations_management</th>\n",
       "      <td>0.473161</td>\n",
       "      <td>0.087771</td>\n",
       "      <td>1.227747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>retail_management</th>\n",
       "      <td>0.340000</td>\n",
       "      <td>-0.045390</td>\n",
       "      <td>0.882224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rural_and_agribusiness</th>\n",
       "      <td>0.424658</td>\n",
       "      <td>0.039268</td>\n",
       "      <td>1.101891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>select</th>\n",
       "      <td>0.286686</td>\n",
       "      <td>-0.098703</td>\n",
       "      <td>0.743887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>services_excellence</th>\n",
       "      <td>0.275000</td>\n",
       "      <td>-0.110390</td>\n",
       "      <td>0.713564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>supply_chain_management</th>\n",
       "      <td>0.432665</td>\n",
       "      <td>0.047275</td>\n",
       "      <td>1.122668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>travel_and_tourism</th>\n",
       "      <td>0.354680</td>\n",
       "      <td>-0.030710</td>\n",
       "      <td>0.920315</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "                                       mean      diff  convert_risk\n",
       "specialization                                                     \n",
       "banking,_investment_and_insurance  0.494083  0.108693      1.282035\n",
       "business_administration            0.444169  0.058779      1.152519\n",
       "e-business                         0.368421 -0.016969      0.955970\n",
       "e-commerce                         0.357143 -0.028247      0.926706\n",
       "finance_management                 0.446721  0.061332      1.159142\n",
       "healthcare_management              0.496855  0.111466      1.289229\n",
       "hospitality_management             0.421053  0.035663      1.092538\n",
       "human_resource_management          0.457547  0.072158      1.187233\n",
       "international_business             0.359551 -0.025839      0.932953\n",
       "it_projects_management             0.382514 -0.002876      0.992538\n",
       "marketing_management               0.486874  0.101484      1.263328\n",
       "media_and_advertising              0.418719  0.033330      1.086483\n",
       "operations_management              0.473161  0.087771      1.227747\n",
       "retail_management                  0.340000 -0.045390      0.882224\n",
       "rural_and_agribusiness             0.424658  0.039268      1.101891\n",
       "select                             0.286686 -0.098703      0.743887\n",
       "services_excellence                0.275000 -0.110390      0.713564\n",
       "supply_chain_management            0.432665  0.047275      1.122668\n",
       "travel_and_tourism                 0.354680 -0.030710      0.920315"
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>multiple_sources</th>\n",
       "      <td>0.368421</td>\n",
       "      <td>-0.016969</td>\n",
       "      <td>0.955970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>online_search</th>\n",
       "      <td>0.424505</td>\n",
       "      <td>0.039115</td>\n",
       "      <td>1.101496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other</th>\n",
       "      <td>0.403226</td>\n",
       "      <td>0.017836</td>\n",
       "      <td>1.046281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>select</th>\n",
       "      <td>0.374345</td>\n",
       "      <td>-0.011045</td>\n",
       "      <td>0.971341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sms</th>\n",
       "      <td>0.217391</td>\n",
       "      <td>-0.167998</td>\n",
       "      <td>0.564082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>social_media</th>\n",
       "      <td>0.417910</td>\n",
       "      <td>0.032521</td>\n",
       "      <td>1.084384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>student_of_someschool</th>\n",
       "      <td>0.461290</td>\n",
       "      <td>0.075901</td>\n",
       "      <td>1.196945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>word_of_mouth</th>\n",
       "      <td>0.436782</td>\n",
       "      <td>0.051392</td>\n",
       "      <td>1.133351</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        mean      diff  convert_risk\n",
       "how_did_you_hear_about_x_education                                  \n",
       "advertisements                      0.457143  0.071753      1.186184\n",
       "email                               0.500000  0.114610      1.297388\n",
       "multiple_sources                    0.368421 -0.016969      0.955970\n",
       "online_search                       0.424505  0.039115      1.101496\n",
       "other                               0.403226  0.017836      1.046281\n",
       "select                              0.374345 -0.011045      0.971341\n",
       "sms                                 0.217391 -0.167998      0.564082\n",
       "social_media                        0.417910  0.032521      1.084384\n",
       "student_of_someschool               0.461290  0.075901      1.196945\n",
       "word_of_mouth                       0.436782  0.051392      1.133351"
      ]
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       "    <tr>\n",
       "      <th>what_is_your_current_occupation</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>businessman</th>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.239610</td>\n",
       "      <td>1.621735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>housewife</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other</th>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.239610</td>\n",
       "      <td>1.621735</td>\n",
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       "    <tr>\n",
       "      <th>student</th>\n",
       "      <td>0.371429</td>\n",
       "      <td>-0.013961</td>\n",
       "      <td>0.963774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unemployed</th>\n",
       "      <td>0.339083</td>\n",
       "      <td>-0.046306</td>\n",
       "      <td>0.879845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>working_professional</th>\n",
       "      <td>0.916431</td>\n",
       "      <td>0.531041</td>\n",
       "      <td>2.377933</td>\n",
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      "text/plain": [
       "                                     mean      diff  convert_risk\n",
       "what_is_your_current_occupation                                  \n",
       "businessman                      0.625000  0.239610      1.621735\n",
       "housewife                        1.000000  0.614610      2.594777\n",
       "other                            0.625000  0.239610      1.621735\n",
       "student                          0.371429 -0.013961      0.963774\n",
       "unemployed                       0.339083 -0.046306      0.879845\n",
       "working_professional             0.916431  0.531041      2.377933"
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>better_career_prospects</th>\n",
       "      <td>0.385407</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>1.000044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>flexibility_&amp;_convenience</th>\n",
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       "      <th>other</th>\n",
       "      <td>0.000000</td>\n",
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       "                                                   mean      diff  \\\n",
       "what_matters_most_to_you_in_choosing_a_course                       \n",
       "better_career_prospects                        0.385407  0.000017   \n",
       "flexibility_&_convenience                      0.500000  0.114610   \n",
       "other                                          0.000000 -0.385390   \n",
       "\n",
       "                                               convert_risk  \n",
       "what_matters_most_to_you_in_choosing_a_course                \n",
       "better_career_prospects                            1.000044  \n",
       "flexibility_&_convenience                          1.297388  \n",
       "other                                              0.000000  "
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
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       "      <td>0.000043</td>\n",
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       "            mean      diff  convert_risk\n",
       "search                                  \n",
       "no      0.385432  0.000043      1.000111\n",
       "yes     0.357143 -0.028247      0.926706"
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       "      <th>yes</th>\n",
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      "text/plain": [
       "                       mean      diff  convert_risk\n",
       "newspaper_article                                  \n",
       "no                 0.385365 -0.000025      0.999936\n",
       "yes                0.500000  0.114610      1.297388"
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       "      <th>no</th>\n",
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       "      <th>yes</th>\n",
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      "text/plain": [
       "               mean      diff  convert_risk\n",
       "newspaper                                  \n",
       "no         0.385431  0.000042      1.000108\n",
       "yes        0.000000 -0.385390      0.000000"
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
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       "      <th>yes</th>\n",
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       "                           mean      diff  convert_risk\n",
       "digital_advertisement                                  \n",
       "no                     0.385448  0.000059      1.000152\n",
       "yes                    0.250000 -0.135390      0.648694"
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
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       "      <th>yes</th>\n",
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       "                             mean      diff  convert_risk\n",
       "through_recommendations                                  \n",
       "no                       0.385140 -0.000249      0.999353\n",
       "yes                      0.714286  0.328896      1.853412"
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>already_a_student</th>\n",
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       "      <td>-0.378938</td>\n",
       "      <td>0.016740</td>\n",
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       "      <th>busy</th>\n",
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       "      <td>0.179127</td>\n",
       "      <td>1.464793</td>\n",
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       "    <tr>\n",
       "      <th>closed_by_horizzon</th>\n",
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       "      <td>0.609024</td>\n",
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       "    <tr>\n",
       "      <th>diploma_holder_(not_eligible)</th>\n",
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       "      <td>-0.369517</td>\n",
       "      <td>0.041187</td>\n",
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       "    <tr>\n",
       "      <th>graduation_in_progress</th>\n",
       "      <td>0.063063</td>\n",
       "      <td>-0.322327</td>\n",
       "      <td>0.163635</td>\n",
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       "    <tr>\n",
       "      <th>in_confusion_whether_part_time_or_dlp</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>-0.185390</td>\n",
       "      <td>0.518955</td>\n",
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       "    <tr>\n",
       "      <th>in_touch_with_eins</th>\n",
       "      <td>0.250000</td>\n",
       "      <td>-0.135390</td>\n",
       "      <td>0.648694</td>\n",
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       "    <tr>\n",
       "      <th>interested__in_full_time_mba</th>\n",
       "      <td>0.025641</td>\n",
       "      <td>-0.359749</td>\n",
       "      <td>0.066533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interested_in_next_batch</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interested_in_other_courses</th>\n",
       "      <td>0.025341</td>\n",
       "      <td>-0.360048</td>\n",
       "      <td>0.065755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>invalid_number</th>\n",
       "      <td>0.012048</td>\n",
       "      <td>-0.373341</td>\n",
       "      <td>0.031262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lateral_student</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lost_to_eins</th>\n",
       "      <td>0.977143</td>\n",
       "      <td>0.591753</td>\n",
       "      <td>2.535468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lost_to_others</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>not_doing_further_education</th>\n",
       "      <td>0.006897</td>\n",
       "      <td>-0.378493</td>\n",
       "      <td>0.017895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number_not_provided</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>opp_hangup</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>-0.294481</td>\n",
       "      <td>0.235889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>recognition_issue_(dec_approval)</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ringing</th>\n",
       "      <td>0.028263</td>\n",
       "      <td>-0.357127</td>\n",
       "      <td>0.073335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shall_take_in_the_next_coming_month</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.114610</td>\n",
       "      <td>1.297388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>still_thinking</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>-0.218723</td>\n",
       "      <td>0.432463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>switched_off</th>\n",
       "      <td>0.016667</td>\n",
       "      <td>-0.368723</td>\n",
       "      <td>0.043246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>university_not_recognized</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>want_to_take_admission_but_has_financial_problems</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>-0.052056</td>\n",
       "      <td>0.864926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>will_revert_after_reading_the_email</th>\n",
       "      <td>0.524055</td>\n",
       "      <td>0.138666</td>\n",
       "      <td>1.359807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wrong_number_given</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                       mean      diff  \\\n",
       "tags                                                                    \n",
       "already_a_student                                  0.006452 -0.378938   \n",
       "busy                                               0.564516  0.179127   \n",
       "closed_by_horizzon                                 0.994413  0.609024   \n",
       "diploma_holder_(not_eligible)                      0.015873 -0.369517   \n",
       "graduation_in_progress                             0.063063 -0.322327   \n",
       "in_confusion_whether_part_time_or_dlp              0.200000 -0.185390   \n",
       "in_touch_with_eins                                 0.250000 -0.135390   \n",
       "interested__in_full_time_mba                       0.025641 -0.359749   \n",
       "interested_in_next_batch                           1.000000  0.614610   \n",
       "interested_in_other_courses                        0.025341 -0.360048   \n",
       "invalid_number                                     0.012048 -0.373341   \n",
       "lateral_student                                    1.000000  0.614610   \n",
       "lost_to_eins                                       0.977143  0.591753   \n",
       "lost_to_others                                     0.000000 -0.385390   \n",
       "not_doing_further_education                        0.006897 -0.378493   \n",
       "number_not_provided                                0.000000 -0.385390   \n",
       "opp_hangup                                         0.090909 -0.294481   \n",
       "recognition_issue_(dec_approval)                   0.000000 -0.385390   \n",
       "ringing                                            0.028263 -0.357127   \n",
       "shall_take_in_the_next_coming_month                0.500000  0.114610   \n",
       "still_thinking                                     0.166667 -0.218723   \n",
       "switched_off                                       0.016667 -0.368723   \n",
       "university_not_recognized                          0.000000 -0.385390   \n",
       "want_to_take_admission_but_has_financial_problems  0.333333 -0.052056   \n",
       "will_revert_after_reading_the_email                0.524055  0.138666   \n",
       "wrong_number_given                                 0.000000 -0.385390   \n",
       "\n",
       "                                                   convert_risk  \n",
       "tags                                                             \n",
       "already_a_student                                      0.016740  \n",
       "busy                                                   1.464793  \n",
       "closed_by_horizzon                                     2.580281  \n",
       "diploma_holder_(not_eligible)                          0.041187  \n",
       "graduation_in_progress                                 0.163635  \n",
       "in_confusion_whether_part_time_or_dlp                  0.518955  \n",
       "in_touch_with_eins                                     0.648694  \n",
       "interested__in_full_time_mba                           0.066533  \n",
       "interested_in_next_batch                               2.594777  \n",
       "interested_in_other_courses                            0.065755  \n",
       "invalid_number                                         0.031262  \n",
       "lateral_student                                        2.594777  \n",
       "lost_to_eins                                           2.535468  \n",
       "lost_to_others                                         0.000000  \n",
       "not_doing_further_education                            0.017895  \n",
       "number_not_provided                                    0.000000  \n",
       "opp_hangup                                             0.235889  \n",
       "recognition_issue_(dec_approval)                       0.000000  \n",
       "ringing                                                0.073335  \n",
       "shall_take_in_the_next_coming_month                    1.297388  \n",
       "still_thinking                                         0.432463  \n",
       "switched_off                                           0.043246  \n",
       "university_not_recognized                              0.000000  \n",
       "want_to_take_admission_but_has_financial_problems      0.864926  \n",
       "will_revert_after_reading_the_email                    1.359807  \n",
       "wrong_number_given                                     0.000000  "
      ]
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       "    <tr>\n",
       "      <th>lead_quality</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>high_in_relevance</th>\n",
       "      <td>0.946625</td>\n",
       "      <td>0.561235</td>\n",
       "      <td>2.456280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>low_in_relevance</th>\n",
       "      <td>0.818182</td>\n",
       "      <td>0.432792</td>\n",
       "      <td>2.122999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>might_be</th>\n",
       "      <td>0.348190</td>\n",
       "      <td>-0.037199</td>\n",
       "      <td>0.903476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>not_sure</th>\n",
       "      <td>0.243590</td>\n",
       "      <td>-0.141800</td>\n",
       "      <td>0.632061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>worst</th>\n",
       "      <td>0.019967</td>\n",
       "      <td>-0.365423</td>\n",
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       "  </tbody>\n",
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       "                       mean      diff  convert_risk\n",
       "lead_quality                                       \n",
       "high_in_relevance  0.946625  0.561235      2.456280\n",
       "low_in_relevance   0.818182  0.432792      2.122999\n",
       "might_be           0.348190 -0.037199      0.903476\n",
       "not_sure           0.243590 -0.141800      0.632061\n",
       "worst              0.019967 -0.365423      0.051809"
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>dual_specialization_student</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lateral_student</th>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.572944</td>\n",
       "      <td>2.486661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_leads</th>\n",
       "      <td>0.369610</td>\n",
       "      <td>-0.015780</td>\n",
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       "    <tr>\n",
       "      <th>potential_lead</th>\n",
       "      <td>0.785493</td>\n",
       "      <td>0.400103</td>\n",
       "      <td>2.038179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>select</th>\n",
       "      <td>0.300802</td>\n",
       "      <td>-0.084587</td>\n",
       "      <td>0.780515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>student_of_someschool</th>\n",
       "      <td>0.037344</td>\n",
       "      <td>-0.348045</td>\n",
       "      <td>0.096900</td>\n",
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      ],
      "text/plain": [
       "                                 mean      diff  convert_risk\n",
       "lead_profile                                                 \n",
       "dual_specialization_student  1.000000  0.614610      2.594777\n",
       "lateral_student              0.958333  0.572944      2.486661\n",
       "other_leads                  0.369610 -0.015780      0.959055\n",
       "potential_lead               0.785493  0.400103      2.038179\n",
       "select                       0.300802 -0.084587      0.780515\n",
       "student_of_someschool        0.037344 -0.348045      0.096900"
      ]
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       "      <th>diff</th>\n",
       "      <th>convert_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mumbai</th>\n",
       "      <td>0.315166</td>\n",
       "      <td>-0.070224</td>\n",
       "      <td>0.817785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_cities</th>\n",
       "      <td>0.402332</td>\n",
       "      <td>0.016943</td>\n",
       "      <td>1.043963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_cities_of_maharashtra</th>\n",
       "      <td>0.439825</td>\n",
       "      <td>0.054435</td>\n",
       "      <td>1.141248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_metro_cities</th>\n",
       "      <td>0.407895</td>\n",
       "      <td>0.022505</td>\n",
       "      <td>1.058396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>select</th>\n",
       "      <td>0.490440</td>\n",
       "      <td>0.105051</td>\n",
       "      <td>1.272583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>thane_&amp;_outskirts</th>\n",
       "      <td>0.449468</td>\n",
       "      <td>0.064078</td>\n",
       "      <td>1.166269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tier_ii_cities</th>\n",
       "      <td>0.337838</td>\n",
       "      <td>-0.047552</td>\n",
       "      <td>0.876614</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 mean      diff  convert_risk\n",
       "city                                                         \n",
       "mumbai                       0.315166 -0.070224      0.817785\n",
       "other_cities                 0.402332  0.016943      1.043963\n",
       "other_cities_of_maharashtra  0.439825  0.054435      1.141248\n",
       "other_metro_cities           0.407895  0.022505      1.058396\n",
       "select                       0.490440  0.105051      1.272583\n",
       "thane_&_outskirts            0.449468  0.064078      1.166269\n",
       "tier_ii_cities               0.337838 -0.047552      0.876614"
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       "    <tr>\n",
       "      <th>asymmetrique_activity_index</th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>high</th>\n",
       "      <td>0.298417</td>\n",
       "      <td>-0.086973</td>\n",
       "      <td>0.774324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>low</th>\n",
       "      <td>0.091160</td>\n",
       "      <td>-0.294229</td>\n",
       "      <td>0.236540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>medium</th>\n",
       "      <td>0.407472</td>\n",
       "      <td>0.022082</td>\n",
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      "text/plain": [
       "                                 mean      diff  convert_risk\n",
       "asymmetrique_activity_index                                  \n",
       "high                         0.298417 -0.086973      0.774324\n",
       "low                          0.091160 -0.294229      0.236540\n",
       "medium                       0.407472  0.022082      1.057298"
      ]
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>high</th>\n",
       "      <td>0.474353</td>\n",
       "      <td>0.088964</td>\n",
       "      <td>1.230841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>low</th>\n",
       "      <td>0.483871</td>\n",
       "      <td>0.098481</td>\n",
       "      <td>1.255537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>medium</th>\n",
       "      <td>0.356980</td>\n",
       "      <td>-0.028410</td>\n",
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      "text/plain": [
       "                                mean      diff  convert_risk\n",
       "asymmetrique_profile_index                                  \n",
       "high                        0.474353  0.088964      1.230841\n",
       "low                         0.483871  0.098481      1.255537\n",
       "medium                      0.356980 -0.028410      0.926283"
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no</th>\n",
       "      <td>0.398457</td>\n",
       "      <td>0.013068</td>\n",
       "      <td>1.033907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yes</th>\n",
       "      <td>0.356648</td>\n",
       "      <td>-0.028741</td>\n",
       "      <td>0.925422</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            mean      diff  convert_risk\n",
       "a_free_copy_of_mastering_the_interview                                  \n",
       "no                                      0.398457  0.013068      1.033907\n",
       "yes                                     0.356648 -0.028741      0.925422"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>diff</th>\n",
       "      <th>convert_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_notable_activity</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>approached_upfront</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_bounced</th>\n",
       "      <td>0.150000</td>\n",
       "      <td>-0.235390</td>\n",
       "      <td>0.389217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_link_clicked</th>\n",
       "      <td>0.260116</td>\n",
       "      <td>-0.125274</td>\n",
       "      <td>0.674942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_marked_spam</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_opened</th>\n",
       "      <td>0.369296</td>\n",
       "      <td>-0.016094</td>\n",
       "      <td>0.958241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>email_received</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>form_submitted_on_website</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>had_a_phone_conversation</th>\n",
       "      <td>0.928571</td>\n",
       "      <td>0.543182</td>\n",
       "      <td>2.409436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>modified</th>\n",
       "      <td>0.229821</td>\n",
       "      <td>-0.155569</td>\n",
       "      <td>0.596334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>olark_chat_conversation</th>\n",
       "      <td>0.136612</td>\n",
       "      <td>-0.248778</td>\n",
       "      <td>0.354478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>page_visited_on_website</th>\n",
       "      <td>0.292453</td>\n",
       "      <td>-0.092937</td>\n",
       "      <td>0.758850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>resubscribed_to_emails</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.614610</td>\n",
       "      <td>2.594777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sms_sent</th>\n",
       "      <td>0.694291</td>\n",
       "      <td>0.308901</td>\n",
       "      <td>1.801530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unreachable</th>\n",
       "      <td>0.687500</td>\n",
       "      <td>0.302110</td>\n",
       "      <td>1.783909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unsubscribed</th>\n",
       "      <td>0.297872</td>\n",
       "      <td>-0.087517</td>\n",
       "      <td>0.772912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>view_in_browser_link_clicked</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.385390</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  mean      diff  convert_risk\n",
       "last_notable_activity                                         \n",
       "approached_upfront            1.000000  0.614610      2.594777\n",
       "email_bounced                 0.150000 -0.235390      0.389217\n",
       "email_link_clicked            0.260116 -0.125274      0.674942\n",
       "email_marked_spam             1.000000  0.614610      2.594777\n",
       "email_opened                  0.369296 -0.016094      0.958241\n",
       "email_received                1.000000  0.614610      2.594777\n",
       "form_submitted_on_website     0.000000 -0.385390      0.000000\n",
       "had_a_phone_conversation      0.928571  0.543182      2.409436\n",
       "modified                      0.229821 -0.155569      0.596334\n",
       "olark_chat_conversation       0.136612 -0.248778      0.354478\n",
       "page_visited_on_website       0.292453 -0.092937      0.758850\n",
       "resubscribed_to_emails        1.000000  0.614610      2.594777\n",
       "sms_sent                      0.694291  0.308901      1.801530\n",
       "unreachable                   0.687500  0.302110      1.783909\n",
       "unsubscribed                  0.297872 -0.087517      0.772912\n",
       "view_in_browser_link_clicked  0.000000 -0.385390      0.000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for col in categorical:\n",
    "    df_group = df.groupby(by=col).converted.agg(['mean'])\n",
    "    df_group['diff'] = df_group['mean'] - global_mean\n",
    "    df_group['convert_risk'] = df_group['mean'] / global_mean\n",
    "    display(df_group)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83be1431",
   "metadata": {},
   "source": [
    "### 2.4.2 Mutual information - usage for it is to better measure the dependency between a categorical variable, and the target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "69343ec8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:16.312131Z",
     "start_time": "2022-05-24T08:22:16.305943Z"
    }
   },
   "outputs": [],
   "source": [
    "def calc_mutal_info_score(series):\n",
    "    return mutual_info_score(series, df.converted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e41a7fe0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:16.778741Z",
     "start_time": "2022-05-24T08:22:16.329942Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mutual_info</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>0.206630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_quality</th>\n",
       "      <td>0.107821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_activity</th>\n",
       "      <td>0.084493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_profile</th>\n",
       "      <td>0.082869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_notable_activity</th>\n",
       "      <td>0.073860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_source</th>\n",
       "      <td>0.061560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_origin</th>\n",
       "      <td>0.056251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_is_your_current_occupation</th>\n",
       "      <td>0.053389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>specialization</th>\n",
       "      <td>0.014624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <td>0.012024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_activity_index</th>\n",
       "      <td>0.011140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_email</th>\n",
       "      <td>0.010327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asymmetrique_profile_index</th>\n",
       "      <td>0.005266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <td>0.002900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>how_did_you_hear_about_x_education</th>\n",
       "      <td>0.001446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a_free_copy_of_mastering_the_interview</th>\n",
       "      <td>0.000797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>do_not_call</th>\n",
       "      <td>0.000206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>through_recommendations</th>\n",
       "      <td>0.000168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_matters_most_to_you_in_choosing_a_course</th>\n",
       "      <td>0.000059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper</th>\n",
       "      <td>0.000053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>digital_advertisement</th>\n",
       "      <td>0.000018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>newspaper_article</th>\n",
       "      <td>0.000006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>search</th>\n",
       "      <td>0.000003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               mutual_info\n",
       "tags                                              0.206630\n",
       "lead_quality                                      0.107821\n",
       "last_activity                                     0.084493\n",
       "lead_profile                                      0.082869\n",
       "last_notable_activity                             0.073860\n",
       "lead_source                                       0.061560\n",
       "lead_origin                                       0.056251\n",
       "what_is_your_current_occupation                   0.053389\n",
       "specialization                                    0.014624\n",
       "city                                              0.012024\n",
       "asymmetrique_activity_index                       0.011140\n",
       "do_not_email                                      0.010327\n",
       "asymmetrique_profile_index                        0.005266\n",
       "country                                           0.002900\n",
       "how_did_you_hear_about_x_education                0.001446\n",
       "a_free_copy_of_mastering_the_interview            0.000797\n",
       "do_not_call                                       0.000206\n",
       "through_recommendations                           0.000168\n",
       "what_matters_most_to_you_in_choosing_a_course     0.000059\n",
       "newspaper                                         0.000053\n",
       "digital_advertisement                             0.000018\n",
       "newspaper_article                                 0.000006\n",
       "search                                            0.000003"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mutual_info = df[categorical].apply(calc_mutal_info_score)\n",
    "df_mutual_info = df_mutual_info.sort_values(ascending=False).to_frame(name=\"mutual_info\")\n",
    "df_mutual_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ba75f6e1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:17.515197Z",
     "start_time": "2022-05-24T08:22:16.781781Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "\n",
    "sns.barplot(data=df_mutual_info.T)\n",
    "plt.xticks(rotation = 90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f9e68d16",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:17.527387Z",
     "start_time": "2022-05-24T08:22:17.518286Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mutual_info</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>0.206630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_quality</th>\n",
       "      <td>0.107821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_activity</th>\n",
       "      <td>0.084493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_profile</th>\n",
       "      <td>0.082869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_notable_activity</th>\n",
       "      <td>0.073860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_source</th>\n",
       "      <td>0.061560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead_origin</th>\n",
       "      <td>0.056251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>what_is_your_current_occupation</th>\n",
       "      <td>0.053389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 mutual_info\n",
       "tags                                0.206630\n",
       "lead_quality                        0.107821\n",
       "last_activity                       0.084493\n",
       "lead_profile                        0.082869\n",
       "last_notable_activity               0.073860\n",
       "lead_source                         0.061560\n",
       "lead_origin                         0.056251\n",
       "what_is_your_current_occupation     0.053389"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "important_features = df_mutual_info.loc[df_mutual_info.mutual_info > 0.02]\n",
    "important_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "885e8b22",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:17.537447Z",
     "start_time": "2022-05-24T08:22:17.530660Z"
    }
   },
   "outputs": [],
   "source": [
    "base_feautres = categorical + numerical\n",
    "important_categorical_features = list(important_features.T.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80cd731a",
   "metadata": {},
   "source": [
    "### 2.4.3 Correlation coefficient -  usage for it is to better measure the dependency between a binary target variable and a numerical feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0cdc4ae8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:17.583557Z",
     "start_time": "2022-05-24T08:22:17.540171Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "total_time_spent_on_website    0.362483\n",
       "asymmetrique_profile_score     0.160700\n",
       "asymmetrique_activity_score    0.123491\n",
       "totalvisits                    0.030091\n",
       "totalvisits                    0.030091\n",
       "page_views_per_visit          -0.003294\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[numerical].corrwith(df.converted).sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3594204",
   "metadata": {},
   "source": [
    "### Here, on the ’total_time_spent’ column, is shown positive correlation between the target variable, so when people are spending more time on the course website, then they are more likely going to convert into actual customers. Here it’s able to observe the opposite case with a negative correlation on the ‘page_views_per_visit’ column and that means if page views are higher, then people less likely going to convert."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3ddc86ff",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:17.958522Z",
     "start_time": "2022-05-24T08:22:17.586939Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='converted', ylabel='total_time_spent_on_website'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(x=\"converted\", y=\"total_time_spent_on_website\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "acdb7fc4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:18.530793Z",
     "start_time": "2022-05-24T08:22:17.966497Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='converted', ylabel='page_views_per_visit'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DBjJl3AimjCt/Z3dDy2aWrtpQdumTJSuzp/lu2ryFl5etf2u3wfaqBojdRw5JQmObqb7JlYmn+fZvlQyJ7Si5UToLWBQRl2W0mQI8nw5cHwIMJtncaAUwWtLYiGgi2eyooch6zXqzIdVV7DVmGHtlTPNt2byF11Zt2G5Ave2KZOmq8tN8N2+JrdN8y3yulKzflbX0Sd3oGk/z7cMqGRLlbqgeCUwHnpa0ID12ITAJICKuJHk473RJLUAzMC0iAtgs6ZvA/WnYzCNZrtzMyqiuGsDEXYYycZfsab5vrNmw3dInpaGSNc339dUbeX31Rua9vKLsZ48ZPqjsE+ttVyTDB1fmr5pVzS2sSXdIXLOhhfWbWhk6qNB/6/Z7inJrGZRrKB1JcvtnnaTTSAapfxoRLxdZYB719fXR0OCLjUp436UP8uKb69hrzDAe+OZxPV2OdYO2ab5ZS58sXtHM+oxpvp0ZVVOdufTJxNqhjKwZ2OkMrbv+vIQL73x6mxpG1VTzk2kH8b6p43aoLktImhcR5WZ/57qSuAJ4t6R3A+eTPOR2PXDszpdoZj2tdJrvwZNqtzsfEaxc37LNFUj7AfbVG8pvMdM2zXfhq+Wn+Q4fPDBz6ZO62hpebFrLN25dsN2Yy6rmFs6+cR6//fpRmWM5tnPyhERrOm5wEvCziJgl6ayiCjOz3kUStcMGUTsse5rv6g0tycB6+2dF0q/LM6b5rt3Y2uE03wGi7KA8wKbWLVzzp5f4wSnv2qGfyzqWJyTWSPoX4DTgGEkDAK8nYGZvGTmkmpHjq3nn+OxpvktKFl5sv/RJ1jTfrIBo0/DS8p0t3TLkCYlpwOeAsyLitXRdpR8XU5aZ9UVDBw1kn91GZO5y2DbNt/3SJ7956tWyM7PaVPs5j8LkCYmPAb+OiOcAIuIVkjEJM7OKyJrmO3RQFTfNfSWz3/Hv3K3o0vqtPPE7CbhK0guSfinpnHQQ28ysUGcf8w5GDin/b9rdRw5h+hF7dnNF/UeXQyIiLoqI9wP7A38ELgDmF1WYmVmbSbsO5RczDufdE7YdMD987124ecbhjBk+uIcq6/u6HBKSviPpHuA+YArwTWBCUYWZmZXaf49R/OqfjqJudA0AE2pruHnGEZkbTVll5BmT+ATJ/hB3A38AHo2I8lMRzMwKMmhg8m9bD1Z3jzy3mw4hWZ31ceCDJEttPFxUYWZm1vO6fCUh6QCSpbuPBeqBv5OMTZiZWR+V53bTv5OEwuXAExFRfpstMzPrM/JsX/pxSTXAJAeEmVn/kGd204nAAuB36fuDJM0uqC4zM+sF8kwP+FfgMGAlQEQsINl72szM+qg8IdESEavaHfOe0mZmfViegeuFkj4HVEnaB/g68EgxZZmZWW+Q50riHJIlOTYCvwBWA+cVUJOZmfUSeWY3rQe+nf4xM7N+oNMrCUk/Sb/+WtLs9n866TtR0gOSGiUtlHRumTYnSXpK0gJJDZKOand+pKTFkn6W82czM7Od1JUriRvSr5fuwOe3AudHxHxJI4B5kuZERGNJm/uB2enWqAcCtwJTS85fDDy0A9/bzMx2UqchERHz0pe7AnfnWdQvIpYCS9PXayQtAuqAxpI2a0u6DKNkxpSkfwR2I3k2o76r39fMzCojz8D1icCzkm6Q9HFJeWZGIWkycDAwt8y5UyT9hWSF2S+mxwYA/0GyJLmZmfWAPKvAfoFkH4lfAp8Fnpd0dVf6ShoO3A6cFxGry3z2nRExFTiZ5PYSwFeB30bE4k4+e0Y6ltHQ1NTU1R/HzMy6INfVQES0pBsPBVBD8pf6lzrqI6maJCBuiog7Ovn8hyTtLWkMcARwtKSvAsOBQZLWRsS32vWZCcwEqK+v98N9ZmYVlGep8I8A04DjgAeBq4FPd9JHwCxgUURcltFmCvB8OnB9CDAYWBYRny9pcyZQ3z4gzMysWHmuJE4HbgHOzjF4fSQwnWSDogXpsQuBSQARcSXwSeB0SS1AMzAtInxFYGbWC+R5mO6zHZ2X9GhEHNGuz8OAOvncS4BLOmlzLXBtlwo1M7OKqeQmsUMq+FlmZtYLVDIkfIvIzKyPqWRImJlZH1PJkOhw7MHMzN5+coWEpD0lHZ++rknXY2ozvaKVmZlZj8uzx/WXgduAq9JDE4C72s5HxDMVrczMzHpcniuJr5E897AaICKeA8YVUZSZmfUOeUJiY0RsanuTLvDnGU1mZn1YnpD4g6QLgRpJHyRZ6O/XxZRlZma9QZ6Q+BbQBDwNnA38FvhOEUWZmVnvkGdZji3Af6V/zMysH8izCuzTbD8GsQpoAL4fEcsqWZiZmfW8PKvA3gNsBn6evv8MMBR4jWTxvRMrWpmZmfW4PCFxfEQcUvL+aUnzI+IQSadVujAzM+t5eQauqyQd1vZG0qFAVfq2taJVmZlZr5DnSuJLwDXpftUieajuS5KGAT8sojgzM+tZeWY3PQG8S9Ko9P2qktO3VrowMzPreXmuJJD0MWB/YEiyfTVExPcKqMvMzHqBPAv8XQlMA84hud30KWDPguoyM7NeIM/A9Xsj4nRgRUR8FzgC2LeYsszMrDfIExLN6df1kvYAWoDxHXWQNFHSA5IaJS2UdG6ZNidJekrSAkkNko5Kjx8k6dG031OSpuWo1czMKiDPmMRvJI0GfgTMS49d3UmfVuD8iJifblA0T9KciGgsaXM/MDsiQtKBJIPgU4H1wOkR8VwaSvMk3RsRK3PUbGZmOyFPSFwKfAU4GngU+CNwRUcdImIpsDR9vUbSIqAOaCxps7akyzDSpT8i4tmSNq9KegMYC6zMUbOZme2EPLebriOZ2XQ58J/AfsD1Xe0saTJwMDC3zLlTJP0FuBv4YpnzhwGDgOfLnJuR3qZqaGpq6mo5ZmbWBXmuJA6IiP1K3j8gqTGzdYn0AbzbgfMiYnX78xFxJ3CnpGOAi4HjS/qOB24AzkhXom3fdyYwE6C+vt6bIJmZVVCeK4n5kg5veyPpPSQrwHZIUjVJQNwUEXd01DYiHgL2ljQm7TuS5Ori2xHxWI5azcysAvJcSfwj8IikV9L3k4C/ti0hHhEHtu+g5Im7WcCiiLis3IdKmgI8nw5cHwIMBpZJGgTcCVwfEbflqNPMzCokT0icsAOffyQwnWTF2AXpsQtJAoaIuBL4JHC6pBaSabbT0sD4NHAMsKukM9O+Z0bEAszMrFvkWbvp5bwfHhEPkzyd3VGbS4BLyhy/Ebgx7/c0M7PKyTMmYWZm/YxDwszMMuVaBdb6jwm1Ndt8NbP+ySFhZd1w1nt6ugQz6wV8u8nMzDI5JMzMLJNDwszMMjkkzMwsk0PCzMwyOSTMzCyTQ8LMzDI5JMzMLJNDwszMMjkkzMwsk0PCzMwyOSTMzCyTQ8LMzDI5JMzMLJNDwszMMhUaEpImSnpAUqOkhZLOLdPmJElPSVogqUHSUSXnzpD0XPrnjCJrNTOz7RW96VArcH5EzJc0ApgnaU5ENJa0uR+YHREh6UDgVmCqpF2Ai4B6INK+syNiRcE1m5lZqtAriYhYGhHz09drgEVAXbs2ayMi0rfDSAIB4MPAnIhYngbDHOCEIus1M7NtdduYhKTJwMHA3DLnTpH0F+Bu4Ivp4Trg7yXNFtMuYNK+M9LbVA1NTU0Vr9vMrD/rlpCQNBy4HTgvIla3Px8Rd0bEVOBk4OI8nx0RMyOiPiLqx44dW5F6zcwsUXhISKomCYibIuKOjtpGxEPA3pLGAEuAiSWnJ6THzMysmxQ9u0nALGBRRFyW0WZK2g5JhwCDgWXAvcCHJNVKqgU+lB4zM7NuUvTspiOB6cDTkhakxy4EJgFExJXAJ4HTJbUAzcC0dCB7uaSLgSfSft+LiOUF12tmZiUKDYmIeBhQJ20uAS7JOHcNcE0BpZmZWRf4iWszM8vkkDAzs0wOCTMzy+SQMDOzTA4JMzPL5JAwM7NMDgkzM8vkkDAzs0wOCTMzy+SQMDOzTA4JMzPL5JAwM7NMDgkzM8vkkDAzs0wOCTMzy+SQMDOzTEXvTGdmVlETamu2+WrFckiY2dvKDWe9p6dL6Fd8u8nMzDIVGhKSJkp6QFKjpIWSzi3T5vOSnpL0tKRHJL275Nz/SPs9I+kXkoYUWa+ZmW2r6CuJVuD8iNgPOBz4mqT92rV5ETg2It4FXAzMBJBUB3wdqI+IA4Aq4DMF12tmZiUKHZOIiKXA0vT1GkmLgDqgsaTNIyVdHgMmtKuvRlILMBR4tch6zcxsW902JiFpMnAwMLeDZmcB9wBExBLgUuAVkqBZFRH3FVymmZmV6JaQkDQcuB04LyJWZ7R5H0lI/HP6vhY4CdgL2AMYJum0Mv1mSGqQ1NDU1FTUj2Bm1i8VHhKSqkkC4qaIuCOjzYHA1cBJEbEsPXw88GJENEVEC3AH8N72fSNiZkTUR0T92LFji/khzMz6qULHJCQJmAUsiojLMtpMIgmA6RHxbMmpV4DDJQ0FmoEPAA0dfb958+a9KenlihRvAGOAN3u6CLMy/LtZWXtmnVBEFPZdJR0F/BF4GtiSHr4QmAQQEVdKuhr4JND2l3trRNSn/b8LTCOZJfVn4EsRsbGwgm0bkhra/r8w6038u9l9Cg0Je3vzf4jWW/l3s/v4iWszM8vkkLCOzOzpAswy+Hezm/h2k5mZZfKVhJmZZXJImJlZJoeEIekESX+V9DdJ3ypzfrCkW9Lzc9MlVswKJ+kaSW9IeibjvCRdnv5uPiXpkO6usa9zSPRzkqqA/w18BNgP+GyZlXrPAlZExBTgfwGXdG+V1o9dC5zQwfmPAPukf2YAV3RDTf2KQ8IOA/4WES9ExCbgZpI1s0qdBFyXvr4N+ED6NL1ZoSLiIWB5B01OAq6PxGPAaEnju6e6/sEhYXXA30veL06PlW0TEa3AKmDXbqnOrGNd+f21neCQMDOzTA4JWwJMLHk/IT1Wto2kgcAoYBlmPa8rv7+2ExwS9gSwj6S9JA0i2SJ2drs2s4Ez0tenAr8PP4VpvcNs4PR0ltPhJJuTLe3povqSQpcKt94vIlol/RNwL8k+4tdExEJJ3wMaImI2yXLvN0j6G8kgovcat24h6RfAccAYSYuBi4BqSFaRBn4LfBT4G7Ae+ELPVNp3eVkOMzPL5NtNZmaWySFhZmaZHBJmZpbJIWFmZpkcEmZmlskhYdZLSBot6as70O9fJX2ziJrMHBJmvUD6JPtoIHdImBXJIWGWknR6uifBk5JukDRZ0u/TY/dLmpS2uzbdw+ARSS9IOjU9frOkj5V83rWSTpVUJenHkp5IP+vs9Pxxkv4oaTbQCPw78A5JCyT9OG1zQUm/75Z89rclPSvpYeAfuu9/Jetv/MS1GSBpf+A7wHsj4k1Ju5Asj35dRFwn6YvA5cDJaZfxwFHAVJKlIW4DbgE+DdydLnHyAeArJPtxrIqIQyUNBv4k6b70cw4BDoiIF9PNnA6IiIPSmj5Esk/CYYCA2ZKOAdaRPPV+EMl/w/OBeUX872LmkDBLvB/4ZUS8CRARyyUdAXwiPX8D8KOS9ndFxBagUdJu6bF7gJ+mQXAC8FBENKd/2R/YdsVBskDiPsAm4PGIeDGjpg+lf/6cvh+e9hsB3BkR6wHSKxGzQjgkzHbMxpLXAoiIDZIeBD4MTCPZwKnt/DkRcW/pB0g6juSqIIuAH0bEVe36nbcTdZvl4jEJs8TvgU9J2hUgvd30CFsXM/w88McufM4tJIvMHQ38Lj12L/AVSdXpZ+8raViZvmtIrhIo6fdFScPTfnWSxgEPASdLqpE0Ajix6z+mWT6+kjAD0pVv/w34g6TNJLd4zgH+r6QLgCa6tsLofSS3pn6VbgcLcDUwGZifbvvaxNaxjdIalkn6k6RngHsi4gJJ7wQeTXeLXQucFhHzJd0CPAm8QbLcu1khvAqsmZll8u0mMzPL5JAwM7NMDgkzM8vkkDAzs0wOCTMzy+SQMDOzTA4JMzPL9P8B/e4cxPP8f4sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(x=\"converted\", y=\"page_views_per_visit\", data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9487b967",
   "metadata": {},
   "source": [
    "# 3. Split data into train, validation and test datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4b8ecd85",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:18.571311Z",
     "start_time": "2022-05-24T08:22:18.533447Z"
    }
   },
   "outputs": [],
   "source": [
    "df_train_full, df_test = train_test_split(df, test_size=0.2, random_state=1)\n",
    "\n",
    "df_train, df_valid = train_test_split(df_train_full, test_size=0.25, random_state=1)\n",
    "\n",
    "y_train = df_train.converted.values\n",
    "y_valid = df_valid.converted.values\n",
    "\n",
    "del df_train['converted']\n",
    "del df_valid['converted']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52accac5",
   "metadata": {},
   "source": [
    "## 3.1 One-hot encoding for categorical features during model training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "dfa9ea47",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:18.598689Z",
     "start_time": "2022-05-24T08:22:18.575964Z"
    }
   },
   "outputs": [],
   "source": [
    "def train_model(df, y, cat_features):\n",
    "    dictionary = df[cat_features + numerical].to_dict(orient='records')\n",
    "    \n",
    "    dv = DictVectorizer(sparse=False)\n",
    "    dv.fit(dictionary)\n",
    "\n",
    "    X = dv.transform(dictionary)\n",
    "    \n",
    "    model = LogisticRegression(solver='liblinear',random_state=1)\n",
    "    model.fit(X, y)\n",
    "    \n",
    "    return dv, model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31978f90",
   "metadata": {},
   "source": [
    "# 4. Logistic regression and making predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "351ffd54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.005077Z",
     "start_time": "2022-05-24T08:22:18.605475Z"
    }
   },
   "outputs": [],
   "source": [
    "dv, model = train_model(df_train, y_train, categorical)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "e6f077b1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.015612Z",
     "start_time": "2022-05-24T08:22:20.008843Z"
    }
   },
   "outputs": [],
   "source": [
    "def make_prediction(df, dv, model, cat_features):\n",
    "    dictionary = df[cat_features + numerical].to_dict(orient='records')\n",
    "    \n",
    "    X = dv.transform(dictionary)\n",
    "    y_prediction = model.predict_proba(X)[:,1]\n",
    "    \n",
    "    return y_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4ddf4e2a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.387853Z",
     "start_time": "2022-05-24T08:22:20.019563Z"
    }
   },
   "outputs": [],
   "source": [
    "y_prediction = make_prediction(df_valid, dv, model, categorical)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f99eba5",
   "metadata": {},
   "source": [
    "## 4.1 Accuracy of the model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7f06e5",
   "metadata": {},
   "source": [
    "### The assumption of threshold is that every lead with score above > 0.5 is going to convert:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ed797bc9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.411039Z",
     "start_time": "2022-05-24T08:22:20.400628Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.926948051948052"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "converted = y_prediction >= 0.5\n",
    "accuracy_score(y_valid, converted)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9411e0e4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-23T17:07:14.195277Z",
     "start_time": "2022-05-23T17:07:14.191267Z"
    }
   },
   "source": [
    "### The best accuracy is for threshold = 0.4:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9216a0ac",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.442345Z",
     "start_time": "2022-05-24T08:22:20.415364Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9334415584415584 0.4\n"
     ]
    }
   ],
   "source": [
    "tresholds = np.linspace(0, 1, 11)\n",
    "\n",
    "maximum = (0.0,0.0)\n",
    "converted = []\n",
    "acc = 0.0\n",
    "for t in tresholds:\n",
    "    converted = y_prediction >= t\n",
    "    acc = accuracy_score(y_valid, converted)\n",
    "    if acc > maximum[0]:\n",
    "        maximum = (acc,t)\n",
    "        \n",
    "best_threshold = maximum[1]\n",
    "best_acc = maximum[0]\n",
    "print(best_acc, best_threshold)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb45aaa0",
   "metadata": {},
   "source": [
    "## 4.2 ROC curves and Area Under the ROC curve (AUC score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a8f32e27",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.452244Z",
     "start_time": "2022-05-24T08:22:20.445583Z"
    }
   },
   "outputs": [],
   "source": [
    "def draw_roc_curve(y_valid, y_prediction):\n",
    "    fpr, tpr, _ = roc_curve(y_valid,  y_prediction, drop_intermediate=False)\n",
    "    auc_score = roc_auc_score(y_valid, y_prediction)\n",
    "    \n",
    "    plt.figure(figsize=(5, 5))\n",
    "    plt.plot( fpr, tpr, label='ROC curve')\n",
    "    plt.plot([0, 1], [0, 1], 'k--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    \n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    \n",
    "    plt.show()\n",
    "    return auc_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "64ba681c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.654400Z",
     "start_time": "2022-05-24T08:22:20.456076Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.9741369090330512"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biased_roc = draw_roc_curve(y_valid, y_prediction)\n",
    "biased_roc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "630ec4a8",
   "metadata": {},
   "source": [
    "## ROC curve of the model could be biased, because of the 'lead_quality' and 'tags' columns. Information from these columns is hardly subjective and made by the company, so they might be the cause of bias. The decision about dropping these off from the categorical features list is made."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1c4bed8b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:20.664234Z",
     "start_time": "2022-05-24T08:22:20.658309Z"
    }
   },
   "outputs": [],
   "source": [
    "categorical_2 = ['lead_origin', 'lead_source', 'do_not_email', 'do_not_call',\n",
    "       'last_activity', 'country', 'specialization',\n",
    "       'how_did_you_hear_about_x_education', 'what_is_your_current_occupation',\n",
    "       'what_matters_most_to_you_in_choosing_a_course', 'search',\n",
    "       'newspaper_article', 'newspaper', 'digital_advertisement',\n",
    "       'through_recommendations', 'lead_profile',\n",
    "       'city', 'asymmetrique_activity_index', 'asymmetrique_profile_index',\n",
    "       'a_free_copy_of_mastering_the_interview', 'last_notable_activity']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "e121eb64",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:21.840623Z",
     "start_time": "2022-05-24T08:22:20.669883Z"
    }
   },
   "outputs": [],
   "source": [
    "dv_2, model_2 = train_model(df_train, y_train, categorical_2)\n",
    "y_prediction_2 = make_prediction(df_valid, dv_2, model_2, categorical_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "31920728",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:21.889451Z",
     "start_time": "2022-05-24T08:22:21.850743Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8382034632034632"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "converted_2 = y_prediction_2 >= 0.5\n",
    "accuracy_score(y_valid, converted_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "2cb2dfa2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.152823Z",
     "start_time": "2022-05-24T08:22:21.893817Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.9137720179450542"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fixed_roc = draw_roc_curve(y_valid, y_prediction_2)\n",
    "fixed_roc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a92e6c50",
   "metadata": {},
   "source": [
    "# 5. Model testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "737e0559",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.700605Z",
     "start_time": "2022-05-24T08:22:22.160482Z"
    }
   },
   "outputs": [],
   "source": [
    "df_check, string_columns_check, numerical_columns_check = load_dataset('leads.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "f28aecf9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.726281Z",
     "start_time": "2022-05-24T08:22:22.709045Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([2140, 7707, 1522, 1873, 8100, 7332, 1094, 2397, 1103, 2257,\n",
       "            ...\n",
       "            1300, 4506, 8340, 8933, 2080, 1837, 7173,  634, 4406, 3465],\n",
       "           dtype='int64', length=1848)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
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   ],
   "source": [
    "df_test.index"
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   "cell_type": "code",
   "execution_count": 56,
   "id": "333ba683",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.765356Z",
     "start_time": "2022-05-24T08:22:22.731621Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.80900363])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "lead = df_test[categorical_2 + numerical].loc[2080].to_dict()\n",
    "X_test = dv.transform(lead)\n",
    "y_test_prediction = model.predict_proba(X_test)\n",
    "\n",
    "y_test_prediction[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "51b96ad9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.792131Z",
     "start_time": "2022-05-24T08:22:22.772941Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "y_test_actual = df_check.converted.loc[2080]\n",
    "y_test_actual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "79d20801",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-24T08:22:22.815024Z",
     "start_time": "2022-05-24T08:22:22.796910Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(y_test_prediction[:,1] > best_threshold)  == y_test_actual"
   ]
  }
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