Mini_project_draft_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mini Project --- Earthquake"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Clustering data\n",
    "Dataset from Kaggle : **\"Earthquake Damage Prediction\"**  \n",
    "Source: https://www.drivendata.org/competitions/57/nepal-earthquake/data/ (requires login)\n",
    "\n",
    "---\n",
    "\n",
    "### Essential Libraries\n",
    "\n",
    "Let us begin by importing the essential Python Libraries.\n",
    "\n",
    "> NumPy : Library for Numeric Computations in Python  \n",
    "> Pandas : Library for Data Acquisition and Preparation  \n",
    "> Matplotlib : Low-level library for Data Visualization  \n",
    "> Seaborn : Higher-level library for Data Visualization  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Basic Libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt # we only need pyplot\n",
    "sb.set() # set the default Seaborn style for graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
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   "outputs": [
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      "text/plain": [
       "             geo_level_1_id  geo_level_2_id  geo_level_3_id  \\\n",
       "building_id                                                   \n",
       "802906                    6             487           12198   \n",
       "28830                     8             900            2812   \n",
       "94947                    21             363            8973   \n",
       "590882                   22             418           10694   \n",
       "201944                   11             131            1488   \n",
       "\n",
       "             count_floors_pre_eq  age  area_percentage  height_percentage  \\\n",
       "building_id                                                                 \n",
       "802906                         2   30                6                  5   \n",
       "28830                          2   10                8                  7   \n",
       "94947                          2   10                5                  5   \n",
       "590882                         2   10                6                  5   \n",
       "201944                         3   30                8                  9   \n",
       "\n",
       "            land_surface_condition foundation_type roof_type  ...  \\\n",
       "building_id                                                   ...   \n",
       "802906                           t               r         n  ...   \n",
       "28830                            o               r         n  ...   \n",
       "94947                            t               r         n  ...   \n",
       "590882                           t               r         n  ...   \n",
       "201944                           t               r         n  ...   \n",
       "\n",
       "            has_secondary_use_agriculture has_secondary_use_hotel  \\\n",
       "building_id                                                         \n",
       "802906                                  0                       0   \n",
       "28830                                   0                       0   \n",
       "94947                                   0                       0   \n",
       "590882                                  0                       0   \n",
       "201944                                  0                       0   \n",
       "\n",
       "            has_secondary_use_rental has_secondary_use_institution  \\\n",
       "building_id                                                          \n",
       "802906                             0                             0   \n",
       "28830                              0                             0   \n",
       "94947                              0                             0   \n",
       "590882                             0                             0   \n",
       "201944                             0                             0   \n",
       "\n",
       "             has_secondary_use_school  has_secondary_use_industry  \\\n",
       "building_id                                                         \n",
       "802906                              0                           0   \n",
       "28830                               0                           0   \n",
       "94947                               0                           0   \n",
       "590882                              0                           0   \n",
       "201944                              0                           0   \n",
       "\n",
       "             has_secondary_use_health_post  has_secondary_use_gov_office  \\\n",
       "building_id                                                                \n",
       "802906                                   0                             0   \n",
       "28830                                    0                             0   \n",
       "94947                                    0                             0   \n",
       "590882                                   0                             0   \n",
       "201944                                   0                             0   \n",
       "\n",
       "             has_secondary_use_use_police  has_secondary_use_other  \n",
       "building_id                                                         \n",
       "802906                                  0                        0  \n",
       "28830                                   0                        0  \n",
       "94947                                   0                        0  \n",
       "590882                                  0                        0  \n",
       "201944                                  0                        0  \n",
       "\n",
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   "source": [
    "raw_data = pd.read_csv('train_values.csv')\n",
    "##setting building_id as the index for easy referencing\n",
    "raw_data = raw_data.set_index('building_id')\n",
    "raw_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reading up the data types so we are able to sort it out in terms of categorial, numerical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "geo_level_1_id                             int64\n",
       "geo_level_2_id                             int64\n",
       "geo_level_3_id                             int64\n",
       "count_floors_pre_eq                        int64\n",
       "age                                        int64\n",
       "area_percentage                            int64\n",
       "height_percentage                          int64\n",
       "land_surface_condition                    object\n",
       "foundation_type                           object\n",
       "roof_type                                 object\n",
       "ground_floor_type                         object\n",
       "other_floor_type                          object\n",
       "position                                  object\n",
       "plan_configuration                        object\n",
       "has_superstructure_adobe_mud               int64\n",
       "has_superstructure_mud_mortar_stone        int64\n",
       "has_superstructure_stone_flag              int64\n",
       "has_superstructure_cement_mortar_stone     int64\n",
       "has_superstructure_mud_mortar_brick        int64\n",
       "has_superstructure_cement_mortar_brick     int64\n",
       "has_superstructure_timber                  int64\n",
       "has_superstructure_bamboo                  int64\n",
       "has_superstructure_rc_non_engineered       int64\n",
       "has_superstructure_rc_engineered           int64\n",
       "has_superstructure_other                   int64\n",
       "legal_ownership_status                    object\n",
       "count_families                             int64\n",
       "has_secondary_use                          int64\n",
       "has_secondary_use_agriculture              int64\n",
       "has_secondary_use_hotel                    int64\n",
       "has_secondary_use_rental                   int64\n",
       "has_secondary_use_institution              int64\n",
       "has_secondary_use_school                   int64\n",
       "has_secondary_use_industry                 int64\n",
       "has_secondary_use_health_post              int64\n",
       "has_secondary_use_gov_office               int64\n",
       "has_secondary_use_use_police               int64\n",
       "has_secondary_use_other                    int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Checking for the number of values to ensure that there is no missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 260601 entries, 802906 to 747594\n",
      "Data columns (total 38 columns):\n",
      " #   Column                                  Non-Null Count   Dtype \n",
      "---  ------                                  --------------   ----- \n",
      " 0   geo_level_1_id                          260601 non-null  int64 \n",
      " 1   geo_level_2_id                          260601 non-null  int64 \n",
      " 2   geo_level_3_id                          260601 non-null  int64 \n",
      " 3   count_floors_pre_eq                     260601 non-null  int64 \n",
      " 4   age                                     260601 non-null  int64 \n",
      " 5   area_percentage                         260601 non-null  int64 \n",
      " 6   height_percentage                       260601 non-null  int64 \n",
      " 7   land_surface_condition                  260601 non-null  object\n",
      " 8   foundation_type                         260601 non-null  object\n",
      " 9   roof_type                               260601 non-null  object\n",
      " 10  ground_floor_type                       260601 non-null  object\n",
      " 11  other_floor_type                        260601 non-null  object\n",
      " 12  position                                260601 non-null  object\n",
      " 13  plan_configuration                      260601 non-null  object\n",
      " 14  has_superstructure_adobe_mud            260601 non-null  int64 \n",
      " 15  has_superstructure_mud_mortar_stone     260601 non-null  int64 \n",
      " 16  has_superstructure_stone_flag           260601 non-null  int64 \n",
      " 17  has_superstructure_cement_mortar_stone  260601 non-null  int64 \n",
      " 18  has_superstructure_mud_mortar_brick     260601 non-null  int64 \n",
      " 19  has_superstructure_cement_mortar_brick  260601 non-null  int64 \n",
      " 20  has_superstructure_timber               260601 non-null  int64 \n",
      " 21  has_superstructure_bamboo               260601 non-null  int64 \n",
      " 22  has_superstructure_rc_non_engineered    260601 non-null  int64 \n",
      " 23  has_superstructure_rc_engineered        260601 non-null  int64 \n",
      " 24  has_superstructure_other                260601 non-null  int64 \n",
      " 25  legal_ownership_status                  260601 non-null  object\n",
      " 26  count_families                          260601 non-null  int64 \n",
      " 27  has_secondary_use                       260601 non-null  int64 \n",
      " 28  has_secondary_use_agriculture           260601 non-null  int64 \n",
      " 29  has_secondary_use_hotel                 260601 non-null  int64 \n",
      " 30  has_secondary_use_rental                260601 non-null  int64 \n",
      " 31  has_secondary_use_institution           260601 non-null  int64 \n",
      " 32  has_secondary_use_school                260601 non-null  int64 \n",
      " 33  has_secondary_use_industry              260601 non-null  int64 \n",
      " 34  has_secondary_use_health_post           260601 non-null  int64 \n",
      " 35  has_secondary_use_gov_office            260601 non-null  int64 \n",
      " 36  has_secondary_use_use_police            260601 non-null  int64 \n",
      " 37  has_secondary_use_other                 260601 non-null  int64 \n",
      "dtypes: int64(30), object(8)\n",
      "memory usage: 77.5+ MB\n"
     ]
    }
   ],
   "source": [
    "raw_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Damage_score calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>94947</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>t</td>\n",
       "      <td>r</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>x</td>\n",
       "      <td>t</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>590882</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>t</td>\n",
       "      <td>r</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201944</th>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>t</td>\n",
       "      <td>r</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             count_floors_pre_eq  age  area_percentage  height_percentage  \\\n",
       "building_id                                                                 \n",
       "802906                         2   30                6                  5   \n",
       "28830                          2   10                8                  7   \n",
       "94947                          2   10                5                  5   \n",
       "590882                         2   10                6                  5   \n",
       "201944                         3   30                8                  9   \n",
       "\n",
       "            land_surface_condition foundation_type roof_type  \\\n",
       "building_id                                                    \n",
       "802906                           t               r         n   \n",
       "28830                            o               r         n   \n",
       "94947                            t               r         n   \n",
       "590882                           t               r         n   \n",
       "201944                           t               r         n   \n",
       "\n",
       "            ground_floor_type other_floor_type position  ...  \\\n",
       "building_id                                              ...   \n",
       "802906                      f                q        t  ...   \n",
       "28830                       x                q        s  ...   \n",
       "94947                       f                x        t  ...   \n",
       "590882                      f                x        s  ...   \n",
       "201944                      f                x        s  ...   \n",
       "\n",
       "            has_superstructure_mud_mortar_stone  \\\n",
       "building_id                                       \n",
       "802906                                        1   \n",
       "28830                                         1   \n",
       "94947                                         1   \n",
       "590882                                        1   \n",
       "201944                                        0   \n",
       "\n",
       "             has_superstructure_stone_flag  \\\n",
       "building_id                                  \n",
       "802906                                   0   \n",
       "28830                                    0   \n",
       "94947                                    0   \n",
       "590882                                   0   \n",
       "201944                                   0   \n",
       "\n",
       "             has_superstructure_cement_mortar_stone  \\\n",
       "building_id                                           \n",
       "802906                                            0   \n",
       "28830                                             0   \n",
       "94947                                             0   \n",
       "590882                                            0   \n",
       "201944                                            0   \n",
       "\n",
       "             has_superstructure_mud_mortar_brick  \\\n",
       "building_id                                        \n",
       "802906                                         0   \n",
       "28830                                          0   \n",
       "94947                                          0   \n",
       "590882                                         0   \n",
       "201944                                         0   \n",
       "\n",
       "             has_superstructure_cement_mortar_brick  \\\n",
       "building_id                                           \n",
       "802906                                            0   \n",
       "28830                                             0   \n",
       "94947                                             0   \n",
       "590882                                            0   \n",
       "201944                                            0   \n",
       "\n",
       "             has_superstructure_timber  has_superstructure_bamboo  \\\n",
       "building_id                                                         \n",
       "802906                               0                          0   \n",
       "28830                                0                          0   \n",
       "94947                                0                          0   \n",
       "590882                               1                          1   \n",
       "201944                               0                          0   \n",
       "\n",
       "             has_superstructure_rc_non_engineered  \\\n",
       "building_id                                         \n",
       "802906                                          0   \n",
       "28830                                           0   \n",
       "94947                                           0   \n",
       "590882                                          0   \n",
       "201944                                          0   \n",
       "\n",
       "             has_superstructure_rc_engineered  has_superstructure_other  \n",
       "building_id                                                              \n",
       "802906                                      0                         0  \n",
       "28830                                       0                         0  \n",
       "94947                                       0                         0  \n",
       "590882                                      0                         0  \n",
       "201944                                      0                         0  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variables_dropped = ['geo_level_1_id', 'geo_level_2_id','geo_level_3_id', 'legal_ownership_status',\n",
    "                    'count_families', 'has_secondary_use', 'has_secondary_use_agriculture','has_secondary_use_hotel',\n",
    "                     'has_secondary_use_rental', 'has_secondary_use_institution', 'has_secondary_use_school',\n",
    "                    'has_secondary_use_industry', 'has_secondary_use_health_post','has_secondary_use_gov_office',\n",
    "                    'has_secondary_use_use_police','has_secondary_use_other']\n",
    "score_calculation = raw_data.drop(variables_dropped, axis=1)\n",
    "score_calculation.head()"
   ]
  }
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