User Rep Scores - old.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# User Rep Scores\n",
    "- Goal: output a csv for each user in the datahunt, with each row corresponding to a single answer\n",
    "- only looking at the parent questions for now\n",
    "- also the ordinal questions are not in number form so I had to manually convert them (ex. T1.Q12)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy as sp\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Task File</th>\n",
       "      <th>Article Number</th>\n",
       "      <th>Question Label</th>\n",
       "      <th>Answer Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q11</td>\n",
       "      <td>T1.Q11.A2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q13</td>\n",
       "      <td>T1.Q13.A5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q14</td>\n",
       "      <td>T1.Q14.A7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q4</td>\n",
       "      <td>T1.Q4.A4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313</td>\n",
       "      <td>313</td>\n",
       "      <td>Probability</td>\n",
       "      <td>100026</td>\n",
       "      <td>T1.Q5</td>\n",
       "      <td>T1.Q5.A1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>Probability</td>\n",
       "      <td>100026</td>\n",
       "      <td>T1.Q6</td>\n",
       "      <td>T1.Q6.A1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>315</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q10</td>\n",
       "      <td>T1.Q10.A8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q3</td>\n",
       "      <td>T1.Q3.A7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>317</td>\n",
       "      <td>317</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q9</td>\n",
       "      <td>T1.Q9.A5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>318 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0    Task File  Article Number Question Label Answer Label\n",
       "0             0     Evidence            1712         T1.Q11    T1.Q11.A2\n",
       "1             1     Evidence            1712         T1.Q13    T1.Q13.A5\n",
       "2             2     Evidence            1712         T1.Q14    T1.Q14.A7\n",
       "3             3     Evidence            1712          T1.Q3            0\n",
       "4             4     Evidence            1712          T1.Q4     T1.Q4.A4\n",
       "..          ...          ...             ...            ...          ...\n",
       "313         313  Probability          100026          T1.Q5     T1.Q5.A1\n",
       "314         314  Probability          100026          T1.Q6     T1.Q6.A1\n",
       "315         315    Reasoning            1712         T1.Q10    T1.Q10.A8\n",
       "316         316    Reasoning            1712          T1.Q3     T1.Q3.A7\n",
       "317         317    Reasoning            1712          T1.Q9     T1.Q9.A5\n",
       "\n",
       "[318 rows x 5 columns]"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Kai's convergence answer csv\n",
    "answers_df = pd.read_csv(\"convergence/Answer_Consensus.csv\")\n",
    "answers_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_question_base_label(row):\n",
    "    if \"A\" not in row['Question Label']:\n",
    "        return row['Question Label']\n",
    "    else:\n",
    "        base_end_index = row['Question Label'].index(\"A\") - 1\n",
    "        return row['Question Label'][:base_end_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Task File</th>\n",
       "      <th>Article Number</th>\n",
       "      <th>Question Label</th>\n",
       "      <th>Answer Label</th>\n",
       "      <th>Question Base Label</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q11</td>\n",
       "      <td>T1.Q11.A2</td>\n",
       "      <td>T1.Q11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q13</td>\n",
       "      <td>T1.Q13.A5</td>\n",
       "      <td>T1.Q13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q14</td>\n",
       "      <td>T1.Q14.A7</td>\n",
       "      <td>T1.Q14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q3</td>\n",
       "      <td>0</td>\n",
       "      <td>T1.Q3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>Evidence</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q4</td>\n",
       "      <td>T1.Q4.A4</td>\n",
       "      <td>T1.Q4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313</td>\n",
       "      <td>313</td>\n",
       "      <td>Probability</td>\n",
       "      <td>100026</td>\n",
       "      <td>T1.Q5</td>\n",
       "      <td>T1.Q5.A1</td>\n",
       "      <td>T1.Q5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>314</td>\n",
       "      <td>314</td>\n",
       "      <td>Probability</td>\n",
       "      <td>100026</td>\n",
       "      <td>T1.Q6</td>\n",
       "      <td>T1.Q6.A1</td>\n",
       "      <td>T1.Q6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>315</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q10</td>\n",
       "      <td>T1.Q10.A8</td>\n",
       "      <td>T1.Q10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q3</td>\n",
       "      <td>T1.Q3.A7</td>\n",
       "      <td>T1.Q3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>317</td>\n",
       "      <td>317</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q9</td>\n",
       "      <td>T1.Q9.A5</td>\n",
       "      <td>T1.Q9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>318 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0    Task File  Article Number Question Label Answer Label  \\\n",
       "0             0     Evidence            1712         T1.Q11    T1.Q11.A2   \n",
       "1             1     Evidence            1712         T1.Q13    T1.Q13.A5   \n",
       "2             2     Evidence            1712         T1.Q14    T1.Q14.A7   \n",
       "3             3     Evidence            1712          T1.Q3            0   \n",
       "4             4     Evidence            1712          T1.Q4     T1.Q4.A4   \n",
       "..          ...          ...             ...            ...          ...   \n",
       "313         313  Probability          100026          T1.Q5     T1.Q5.A1   \n",
       "314         314  Probability          100026          T1.Q6     T1.Q6.A1   \n",
       "315         315    Reasoning            1712         T1.Q10    T1.Q10.A8   \n",
       "316         316    Reasoning            1712          T1.Q3     T1.Q3.A7   \n",
       "317         317    Reasoning            1712          T1.Q9     T1.Q9.A5   \n",
       "\n",
       "    Question Base Label  \n",
       "0                T1.Q11  \n",
       "1                T1.Q13  \n",
       "2                T1.Q14  \n",
       "3                 T1.Q3  \n",
       "4                 T1.Q4  \n",
       "..                  ...  \n",
       "313               T1.Q5  \n",
       "314               T1.Q6  \n",
       "315              T1.Q10  \n",
       "316               T1.Q3  \n",
       "317               T1.Q9  \n",
       "\n",
       "[318 rows x 6 columns]"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "answers_df[\"Question Base Label\"] = answers_df.apply(get_question_base_label, axis=1)\n",
    "answers_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "#array of questions that are \"parent\" questions\n",
    "language_parents = [\"T1.Q1\"]\n",
    "probability_parents = [\"T1.Q1\", \"T1.Q2\", \"T1.Q5\", \"T1.Q6\", ]\n",
    "reasoning_parents = [\"T1.Q1\"]\n",
    "evidence_parents = [\"T1.Q1\", \"T1.Q9\", \"T1.Q12\"]\n",
    "\n",
    "#corresponding list of question types, language_parents[n] maps to language_parent_types[n]\n",
    "language_parents_types = [\"select_all\"]\n",
    "probability_parents_types = [\"ordinal\", \"ordinal\", \"ordinal\", \"select_one\", \"ordinal\", \"ordinal\"]\n",
    "reasoning_parents_types = [\"select_all\"]\n",
    "evidence_parents_types = [\"select_one\", \"ordinal\", \"ordinal\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fill this in, either \"language\", \"probability\", \"reasoning\", or \"evidence\"\n",
    "task_type = \"reasoning\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "#cuts down answers_df to the rows with the relevant task type\n",
    "if task_type == \"language\":\n",
    "    task_answers_df = answers_df.loc[answers_df[\"Task File\"] == \"Language\"]\n",
    "    parent_questions = language_parents\n",
    "elif task_type == \"probability\":\n",
    "    task_answers_df = answers_df.loc[answers_df[\"Task File\"] == \"Probability\"]\n",
    "    parent_questions = probability_parents\n",
    "elif task_type == \"reasoning\":\n",
    "    task_answers_df = answers_df.loc[answers_df[\"Task File\"] == \"Reasoning\"]\n",
    "    parent_questions = reasoning_parents\n",
    "elif task_type == \"evidence\":\n",
    "    task_answers_df = answers_df.loc[answers_df[\"Task File\"] == \"Evidence\"]\n",
    "    parent_questions = evidence_parents\n",
    "else:\n",
    "    print(\"Invalid task type\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#read csv into df, set parent_df to the relevant columns of the parent questions\n",
    "df = pd.read_csv(\"testing-format/BETA_Language-2020-05-20T0110-DataHunt.csv\")\n",
    "df = df[[\"contributor_uuid\", \"quiz_task_uuid\", \"article_number\", \"question_label\", \n",
    "         \"answer_label\", \"answer_text\", \"quiz_taskrun_uuid\", \"finish_time\"]]\n",
    "\n",
    "#creates a dictionary mapping the task type to an list of which questions are parent questions\n",
    "task_parents = {\"language\": language_parents, \"probability\": probability_parents,\n",
    "                \"reasoning\": reasoning_parents, \"evidence\": evidence_parents}\n",
    "task_parents_types = {\"language\": language_parents_types, \"probability\": probability_parents_types,\n",
    "                \"reasoning\": reasoning_parents_types, \"evidence\": evidence_parents_types}\n",
    "\n",
    "\n",
    "parent_df = df.loc[df['question_label'].isin(task_parents[task_type])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>contributor_uuid</th>\n",
       "      <th>quiz_task_uuid</th>\n",
       "      <th>question_type</th>\n",
       "      <th>article_number</th>\n",
       "      <th>question_label</th>\n",
       "      <th>answer_label</th>\n",
       "      <th>answer_text</th>\n",
       "      <th>quiz_taskrun_uuid</th>\n",
       "      <th>finish_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>f9143626-bfe0-4e69-b652-6d1525ab4eb0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>select_all</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>Exaggeration</td>\n",
       "      <td>834a1f2e-ec75-48b3-976c-f8afc38601fb</td>\n",
       "      <td>2019-09-04 22:50:32.477936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>f9143626-bfe0-4e69-b652-6d1525ab4eb0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>select_all</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>Exaggeration</td>\n",
       "      <td>834a1f2e-ec75-48b3-976c-f8afc38601fb</td>\n",
       "      <td>2019-09-04 22:50:32.477936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>f9143626-bfe0-4e69-b652-6d1525ab4eb0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>select_all</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>Shock or surprise</td>\n",
       "      <td>834a1f2e-ec75-48b3-976c-f8afc38601fb</td>\n",
       "      <td>2019-09-04 22:50:32.477936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>f9143626-bfe0-4e69-b652-6d1525ab4eb0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>select_all</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A6</td>\n",
       "      <td>Slang</td>\n",
       "      <td>834a1f2e-ec75-48b3-976c-f8afc38601fb</td>\n",
       "      <td>2019-09-04 22:50:32.477936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>f9143626-bfe0-4e69-b652-6d1525ab4eb0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>select_all</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A12</td>\n",
       "      <td>Other problem with language</td>\n",
       "      <td>834a1f2e-ec75-48b3-976c-f8afc38601fb</td>\n",
       "      <td>2019-09-04 22:50:32.477936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3269</td>\n",
       "      <td>782cf148-ffac-43f1-99aa-27a9d64b5212</td>\n",
       "      <td>c251992c-ad2b-4586-bc70-f98f62f8b402</td>\n",
       "      <td>select_all</td>\n",
       "      <td>100004</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A7</td>\n",
       "      <td>Typos</td>\n",
       "      <td>06c101df-54fe-462d-8984-f32e77f304e0</td>\n",
       "      <td>2019-09-19 23:16:03.359649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3274</td>\n",
       "      <td>40e8da50-18a7-4eaf-aba1-69b3ee956fc1</td>\n",
       "      <td>c251992c-ad2b-4586-bc70-f98f62f8b402</td>\n",
       "      <td>select_all</td>\n",
       "      <td>100004</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>Metaphorical Language</td>\n",
       "      <td>9d95dbe6-662e-4cf8-aaca-7ac6c7d3e65d</td>\n",
       "      <td>2019-09-20 07:57:36.239145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3279</td>\n",
       "      <td>3c97d749-8996-4a96-97af-73ecdc5a4716</td>\n",
       "      <td>c251992c-ad2b-4586-bc70-f98f62f8b402</td>\n",
       "      <td>select_all</td>\n",
       "      <td>100004</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A7</td>\n",
       "      <td>Typos</td>\n",
       "      <td>a87ae1c1-7019-4ef8-b33a-d2bd22d689d9</td>\n",
       "      <td>2019-09-21 00:52:12.951237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3284</td>\n",
       "      <td>a31c365c-986b-4dbe-b752-bbb5986cc7f2</td>\n",
       "      <td>c251992c-ad2b-4586-bc70-f98f62f8b402</td>\n",
       "      <td>select_all</td>\n",
       "      <td>100004</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A7</td>\n",
       "      <td>Typos</td>\n",
       "      <td>fbc4942e-379d-4726-b6be-629f28208278</td>\n",
       "      <td>2019-09-28 08:03:12.014527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3289</td>\n",
       "      <td>0e4b8a3e-2714-4b5f-ba10-bb576aaa5cc6</td>\n",
       "      <td>c251992c-ad2b-4586-bc70-f98f62f8b402</td>\n",
       "      <td>select_all</td>\n",
       "      <td>100004</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>T1.Q1.A7</td>\n",
       "      <td>Typos</td>\n",
       "      <td>98149bd8-6a20-4fb2-adf5-bbd59af3f7f3</td>\n",
       "      <td>2019-10-02 23:08:42.876182</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1280 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          contributor_uuid  \\\n",
       "0     f9143626-bfe0-4e69-b652-6d1525ab4eb0   \n",
       "1     f9143626-bfe0-4e69-b652-6d1525ab4eb0   \n",
       "2     f9143626-bfe0-4e69-b652-6d1525ab4eb0   \n",
       "3     f9143626-bfe0-4e69-b652-6d1525ab4eb0   \n",
       "4     f9143626-bfe0-4e69-b652-6d1525ab4eb0   \n",
       "...                                    ...   \n",
       "3269  782cf148-ffac-43f1-99aa-27a9d64b5212   \n",
       "3274  40e8da50-18a7-4eaf-aba1-69b3ee956fc1   \n",
       "3279  3c97d749-8996-4a96-97af-73ecdc5a4716   \n",
       "3284  a31c365c-986b-4dbe-b752-bbb5986cc7f2   \n",
       "3289  0e4b8a3e-2714-4b5f-ba10-bb576aaa5cc6   \n",
       "\n",
       "                            quiz_task_uuid question_type  article_number  \\\n",
       "0     a25ed7d6-4f1b-40a4-9f72-54e13e5658eb    select_all            1712   \n",
       "1     a25ed7d6-4f1b-40a4-9f72-54e13e5658eb    select_all            1712   \n",
       "2     a25ed7d6-4f1b-40a4-9f72-54e13e5658eb    select_all            1712   \n",
       "3     a25ed7d6-4f1b-40a4-9f72-54e13e5658eb    select_all            1712   \n",
       "4     a25ed7d6-4f1b-40a4-9f72-54e13e5658eb    select_all            1712   \n",
       "...                                    ...           ...             ...   \n",
       "3269  c251992c-ad2b-4586-bc70-f98f62f8b402    select_all          100004   \n",
       "3274  c251992c-ad2b-4586-bc70-f98f62f8b402    select_all          100004   \n",
       "3279  c251992c-ad2b-4586-bc70-f98f62f8b402    select_all          100004   \n",
       "3284  c251992c-ad2b-4586-bc70-f98f62f8b402    select_all          100004   \n",
       "3289  c251992c-ad2b-4586-bc70-f98f62f8b402    select_all          100004   \n",
       "\n",
       "     question_label answer_label                  answer_text  \\\n",
       "0             T1.Q1     T1.Q1.A2                 Exaggeration   \n",
       "1             T1.Q1     T1.Q1.A2                 Exaggeration   \n",
       "2             T1.Q1     T1.Q1.A5            Shock or surprise   \n",
       "3             T1.Q1     T1.Q1.A6                        Slang   \n",
       "4             T1.Q1    T1.Q1.A12  Other problem with language   \n",
       "...             ...          ...                          ...   \n",
       "3269          T1.Q1     T1.Q1.A7                        Typos   \n",
       "3274          T1.Q1     T1.Q1.A1        Metaphorical Language   \n",
       "3279          T1.Q1     T1.Q1.A7                        Typos   \n",
       "3284          T1.Q1     T1.Q1.A7                        Typos   \n",
       "3289          T1.Q1     T1.Q1.A7                        Typos   \n",
       "\n",
       "                         quiz_taskrun_uuid                 finish_time  \n",
       "0     834a1f2e-ec75-48b3-976c-f8afc38601fb  2019-09-04 22:50:32.477936  \n",
       "1     834a1f2e-ec75-48b3-976c-f8afc38601fb  2019-09-04 22:50:32.477936  \n",
       "2     834a1f2e-ec75-48b3-976c-f8afc38601fb  2019-09-04 22:50:32.477936  \n",
       "3     834a1f2e-ec75-48b3-976c-f8afc38601fb  2019-09-04 22:50:32.477936  \n",
       "4     834a1f2e-ec75-48b3-976c-f8afc38601fb  2019-09-04 22:50:32.477936  \n",
       "...                                    ...                         ...  \n",
       "3269  06c101df-54fe-462d-8984-f32e77f304e0  2019-09-19 23:16:03.359649  \n",
       "3274  9d95dbe6-662e-4cf8-aaca-7ac6c7d3e65d  2019-09-20 07:57:36.239145  \n",
       "3279  a87ae1c1-7019-4ef8-b33a-d2bd22d689d9  2019-09-21 00:52:12.951237  \n",
       "3284  fbc4942e-379d-4726-b6be-629f28208278  2019-09-28 08:03:12.014527  \n",
       "3289  98149bd8-6a20-4fb2-adf5-bbd59af3f7f3  2019-10-02 23:08:42.876182  \n",
       "\n",
       "[1280 rows x 9 columns]"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#adds a column with the question_type of the question_label\n",
    "question_types = []\n",
    "for i in parent_df['question_label']:\n",
    "    question_type = task_parents_types[task_type][task_parents[task_type].index(i)]\n",
    "    question_types.append(question_type)\n",
    "        \n",
    "parent_df.insert(2, \"question_type\", question_types, True)\n",
    "parent_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Unnamed: 0</th>\n",
       "      <th>Task File</th>\n",
       "      <th>Article Number</th>\n",
       "      <th>Question Label</th>\n",
       "      <th>Answer Label</th>\n",
       "      <th>Question Base Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>315</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q10</td>\n",
       "      <td>T1.Q10.A8</td>\n",
       "      <td>T1.Q10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>316</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q3</td>\n",
       "      <td>T1.Q3.A7</td>\n",
       "      <td>T1.Q3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>317</td>\n",
       "      <td>317</td>\n",
       "      <td>Reasoning</td>\n",
       "      <td>1712</td>\n",
       "      <td>T1.Q9</td>\n",
       "      <td>T1.Q9.A5</td>\n",
       "      <td>T1.Q9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  Task File  Article Number Question Label Answer Label  \\\n",
       "315         315  Reasoning            1712         T1.Q10    T1.Q10.A8   \n",
       "316         316  Reasoning            1712          T1.Q3     T1.Q3.A7   \n",
       "317         317  Reasoning            1712          T1.Q9     T1.Q9.A5   \n",
       "\n",
       "    Question Base Label  \n",
       "315              T1.Q10  \n",
       "316               T1.Q3  \n",
       "317               T1.Q9  "
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#task_answers_df.loc[task_answers_df[\"Question Base Label\"] == 'T1.Q1']\n",
    "task_answers_df\n",
    "#answers_df.loc[answers_df[\"Task File\"] == \"Reasoning\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[]]"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#NEED TO FIX THIS SO THAT THE CONVERGED ANSWERS COME FROM KAIS CSV\n",
    "#converged_answers = [['T1.Q1.A2']]\n",
    "converged_answers = []\n",
    "\n",
    "for i in np.arange(len(parent_questions)):\n",
    "    answers = []\n",
    "    converged_answers.append(answers)\n",
    "    \n",
    "converged_answers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"Select All That Apply\" Questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#selected is one answer_label, correct is array of correct answer_labels\n",
    "def selectAllQ(selected, correct):\n",
    "    if selected in correct:\n",
    "        return 1\n",
    "    else:\n",
    "        return 0    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"Select One\" Questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def selectOneQ(selected, correct):\n",
    "    if selected == correct:\n",
    "        return 1\n",
    "    return 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ordinal Data Questions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#uses the last value of the question label, ex. 1 in \"T1.Q9.A1\", as the numerical representation of the answer \n",
    "def question_to_int(selection):\n",
    "    return int(selection[-1])\n",
    "\n",
    "v_question_to_int = np.vectorize(question_to_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#selected and correct are answer_label(s), question is a question_label, both strings\n",
    "def ordinalDataQ(selected, question, correct):\n",
    "    data = parent_df[parent_df['question_label'].str.match(question)]\n",
    "    data = data['answer_label'].values\n",
    "    #array of 1,2,3,4s\n",
    "    data_int = v_question_to_int(data)\n",
    "    selected_int = question_to_int(selected)\n",
    "    correct_int = question_to_int(correct)\n",
    "    \n",
    "    std = np.std(data_int)\n",
    "    z_score = (selected_int - correct_int)/std\n",
    "    return 1 - abs(z_score)/3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "user_score_dict = {}\n",
    "test_dict = {}\n",
    "for index, row in parent_df.iterrows():\n",
    "    if row['contributor_uuid'] not in user_score_dict:\n",
    "        user_score_dict[row['contributor_uuid']] = pd.DataFrame(columns=['quiz_task_uuid', 'quiz_taskrun_uuid', 'question_label', 'question_type', 'answer_label', 'answer_score', 'time_stamp'])\n",
    "    if row['question_type'] == \"select_all\":\n",
    "        score = selectAllQ(row['answer_label'], converged_answers[task_parents[task_type].index(row['question_label'])])\n",
    "    elif row['question_type'] == \"select_one\":\n",
    "        score = selectOneQ(row['answer_label'], converged_answers[task_parents[task_type].index(row['question_label'])])\n",
    "    else:\n",
    "        score = ordinalDataQ(row['answer_label'], row['question_label'], converged_answers[task_parents[task_type].index(row['question_label'])])\n",
    "    user_score_dict[row['contributor_uuid']] = user_score_dict[row['contributor_uuid']].append({'quiz_task_uuid': row['quiz_task_uuid'], 'quiz_taskrun_uuid': row['quiz_taskrun_uuid'], 'question_label': row['question_label'], 'question_type': row['question_type'], 'answer_label': row['answer_label'], 'answer_score': score, 'time_stamp': row['finish_time']}, ignore_index=True)\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>quiz_task_uuid</th>\n",
       "      <th>quiz_taskrun_uuid</th>\n",
       "      <th>question_label</th>\n",
       "      <th>question_type</th>\n",
       "      <th>answer_label</th>\n",
       "      <th>answer_score</th>\n",
       "      <th>time_stamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>cc0923e0-258b-42f7-86df-d68ef9d4d54c</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:40:45.253905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>cc0923e0-258b-42f7-86df-d68ef9d4d54c</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:40:45.253905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>cc0923e0-258b-42f7-86df-d68ef9d4d54c</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:40:45.253905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>a25ed7d6-4f1b-40a4-9f72-54e13e5658eb</td>\n",
       "      <td>cc0923e0-258b-42f7-86df-d68ef9d4d54c</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A6</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:40:45.253905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A11</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>f65e3f32-7347-42b3-a6b2-39bc62e226c2</td>\n",
       "      <td>76439f35-ad5a-482c-a1d6-8ca8bf05332b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A11</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:44:25.657454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>8a155187-7903-4284-97a2-c40404008deb</td>\n",
       "      <td>7406f8fb-d279-48a7-8edb-f113dc428436</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:47:48.391210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>8a155187-7903-4284-97a2-c40404008deb</td>\n",
       "      <td>7406f8fb-d279-48a7-8edb-f113dc428436</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:47:48.391210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>8a155187-7903-4284-97a2-c40404008deb</td>\n",
       "      <td>7406f8fb-d279-48a7-8edb-f113dc428436</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:47:48.391210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>946cc55d-ec61-41df-bf09-3359b9dc76e2</td>\n",
       "      <td>c4811b2f-0b5c-4c57-ada5-85dbd6f7e998</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:48:45.529046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>430c7d69-746d-494a-ae25-abbf1c003b3b</td>\n",
       "      <td>0b766720-92cc-4369-a6db-a70b69dd8b4f</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:49:56.024291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>430c7d69-746d-494a-ae25-abbf1c003b3b</td>\n",
       "      <td>0b766720-92cc-4369-a6db-a70b69dd8b4f</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:49:56.024291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>430c7d69-746d-494a-ae25-abbf1c003b3b</td>\n",
       "      <td>0b766720-92cc-4369-a6db-a70b69dd8b4f</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:49:56.024291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A1</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>6c7879c3-c0da-4b76-bd7b-8b766e6b353d</td>\n",
       "      <td>314455f5-5a22-4411-accb-de190289129a</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A13</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:52:24.113707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A2</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A10</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A10</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A10</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>156e8426-0563-41af-95b1-5e32f270aa1d</td>\n",
       "      <td>6f541985-1a5f-47f9-8ed8-b12474fd08d8</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:54:04.239497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5</td>\n",
       "      <td>890be121-d254-4aef-9c74-f22204483d91</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:56:07.230406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5</td>\n",
       "      <td>890be121-d254-4aef-9c74-f22204483d91</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:56:07.230406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5</td>\n",
       "      <td>890be121-d254-4aef-9c74-f22204483d91</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:56:07.230406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5</td>\n",
       "      <td>890be121-d254-4aef-9c74-f22204483d91</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A10</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:56:07.230406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A5</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A4</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf</td>\n",
       "      <td>01ba9fa5-a13f-441e-8493-9d451db3722b</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A3</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:57:55.065468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>94b91775-17a6-421b-8968-525e00dcd1ce</td>\n",
       "      <td>fb345f28-ee33-4927-b726-0926afde3634</td>\n",
       "      <td>T1.Q1</td>\n",
       "      <td>select_all</td>\n",
       "      <td>T1.Q1.A13</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-09-20 07:58:36.292159</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          quiz_task_uuid  \\\n",
       "0   a25ed7d6-4f1b-40a4-9f72-54e13e5658eb   \n",
       "1   a25ed7d6-4f1b-40a4-9f72-54e13e5658eb   \n",
       "2   a25ed7d6-4f1b-40a4-9f72-54e13e5658eb   \n",
       "3   a25ed7d6-4f1b-40a4-9f72-54e13e5658eb   \n",
       "4   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "5   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "6   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "7   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "8   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "9   f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "10  f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "11  f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "12  f65e3f32-7347-42b3-a6b2-39bc62e226c2   \n",
       "13  8a155187-7903-4284-97a2-c40404008deb   \n",
       "14  8a155187-7903-4284-97a2-c40404008deb   \n",
       "15  8a155187-7903-4284-97a2-c40404008deb   \n",
       "16  946cc55d-ec61-41df-bf09-3359b9dc76e2   \n",
       "17  430c7d69-746d-494a-ae25-abbf1c003b3b   \n",
       "18  430c7d69-746d-494a-ae25-abbf1c003b3b   \n",
       "19  430c7d69-746d-494a-ae25-abbf1c003b3b   \n",
       "20  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "21  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "22  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "23  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "24  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "25  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "26  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "27  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "28  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "29  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "30  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "31  6c7879c3-c0da-4b76-bd7b-8b766e6b353d   \n",
       "32  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "33  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "34  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "35  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "36  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "37  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "38  156e8426-0563-41af-95b1-5e32f270aa1d   \n",
       "39  887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5   \n",
       "40  887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5   \n",
       "41  887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5   \n",
       "42  887ec9e8-c7e0-4eed-8cbf-ad7fc96a60d5   \n",
       "43  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "44  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "45  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "46  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "47  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "48  da7af1d8-5f23-4c4e-9f2a-f0bb35798aaf   \n",
       "49  94b91775-17a6-421b-8968-525e00dcd1ce   \n",
       "\n",
       "                       quiz_taskrun_uuid question_label question_type  \\\n",
       "0   cc0923e0-258b-42f7-86df-d68ef9d4d54c          T1.Q1    select_all   \n",
       "1   cc0923e0-258b-42f7-86df-d68ef9d4d54c          T1.Q1    select_all   \n",
       "2   cc0923e0-258b-42f7-86df-d68ef9d4d54c          T1.Q1    select_all   \n",
       "3   cc0923e0-258b-42f7-86df-d68ef9d4d54c          T1.Q1    select_all   \n",
       "4   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "5   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "6   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "7   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "8   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "9   76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "10  76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "11  76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "12  76439f35-ad5a-482c-a1d6-8ca8bf05332b          T1.Q1    select_all   \n",
       "13  7406f8fb-d279-48a7-8edb-f113dc428436          T1.Q1    select_all   \n",
       "14  7406f8fb-d279-48a7-8edb-f113dc428436          T1.Q1    select_all   \n",
       "15  7406f8fb-d279-48a7-8edb-f113dc428436          T1.Q1    select_all   \n",
       "16  c4811b2f-0b5c-4c57-ada5-85dbd6f7e998          T1.Q1    select_all   \n",
       "17  0b766720-92cc-4369-a6db-a70b69dd8b4f          T1.Q1    select_all   \n",
       "18  0b766720-92cc-4369-a6db-a70b69dd8b4f          T1.Q1    select_all   \n",
       "19  0b766720-92cc-4369-a6db-a70b69dd8b4f          T1.Q1    select_all   \n",
       "20  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "21  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "22  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "23  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "24  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "25  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "26  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "27  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "28  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "29  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "30  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "31  314455f5-5a22-4411-accb-de190289129a          T1.Q1    select_all   \n",
       "32  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "33  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "34  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "35  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "36  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "37  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "38  6f541985-1a5f-47f9-8ed8-b12474fd08d8          T1.Q1    select_all   \n",
       "39  890be121-d254-4aef-9c74-f22204483d91          T1.Q1    select_all   \n",
       "40  890be121-d254-4aef-9c74-f22204483d91          T1.Q1    select_all   \n",
       "41  890be121-d254-4aef-9c74-f22204483d91          T1.Q1    select_all   \n",
       "42  890be121-d254-4aef-9c74-f22204483d91          T1.Q1    select_all   \n",
       "43  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "44  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "45  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "46  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "47  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "48  01ba9fa5-a13f-441e-8493-9d451db3722b          T1.Q1    select_all   \n",
       "49  fb345f28-ee33-4927-b726-0926afde3634          T1.Q1    select_all   \n",
       "\n",
       "   answer_label answer_score                  time_stamp  \n",
       "0      T1.Q1.A2            1  2019-09-20 07:40:45.253905  \n",
       "1      T1.Q1.A4            0  2019-09-20 07:40:45.253905  \n",
       "2      T1.Q1.A5            0  2019-09-20 07:40:45.253905  \n",
       "3      T1.Q1.A6            0  2019-09-20 07:40:45.253905  \n",
       "4      T1.Q1.A1            0  2019-09-20 07:44:25.657454  \n",
       "5      T1.Q1.A3            0  2019-09-20 07:44:25.657454  \n",
       "6      T1.Q1.A3            0  2019-09-20 07:44:25.657454  \n",
       "7      T1.Q1.A3            0  2019-09-20 07:44:25.657454  \n",
       "8      T1.Q1.A4            0  2019-09-20 07:44:25.657454  \n",
       "9      T1.Q1.A4            0  2019-09-20 07:44:25.657454  \n",
       "10     T1.Q1.A4            0  2019-09-20 07:44:25.657454  \n",
       "11    T1.Q1.A11            0  2019-09-20 07:44:25.657454  \n",
       "12    T1.Q1.A11            0  2019-09-20 07:44:25.657454  \n",
       "13     T1.Q1.A2            1  2019-09-20 07:47:48.391210  \n",
       "14     T1.Q1.A3            0  2019-09-20 07:47:48.391210  \n",
       "15     T1.Q1.A4            0  2019-09-20 07:47:48.391210  \n",
       "16     T1.Q1.A2            1  2019-09-20 07:48:45.529046  \n",
       "17     T1.Q1.A2            1  2019-09-20 07:49:56.024291  \n",
       "18     T1.Q1.A2            1  2019-09-20 07:49:56.024291  \n",
       "19     T1.Q1.A4            0  2019-09-20 07:49:56.024291  \n",
       "20     T1.Q1.A2            1  2019-09-20 07:52:24.113707  \n",
       "21     T1.Q1.A4            0  2019-09-20 07:52:24.113707  \n",
       "22     T1.Q1.A3            0  2019-09-20 07:52:24.113707  \n",
       "23     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "24     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "25     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "26     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "27     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "28     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "29     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "30     T1.Q1.A1            0  2019-09-20 07:52:24.113707  \n",
       "31    T1.Q1.A13            0  2019-09-20 07:52:24.113707  \n",
       "32     T1.Q1.A2            1  2019-09-20 07:54:04.239497  \n",
       "33     T1.Q1.A2            1  2019-09-20 07:54:04.239497  \n",
       "34     T1.Q1.A2            1  2019-09-20 07:54:04.239497  \n",
       "35    T1.Q1.A10            0  2019-09-20 07:54:04.239497  \n",
       "36    T1.Q1.A10            0  2019-09-20 07:54:04.239497  \n",
       "37    T1.Q1.A10            0  2019-09-20 07:54:04.239497  \n",
       "38     T1.Q1.A3            0  2019-09-20 07:54:04.239497  \n",
       "39     T1.Q1.A4            0  2019-09-20 07:56:07.230406  \n",
       "40     T1.Q1.A4            0  2019-09-20 07:56:07.230406  \n",
       "41     T1.Q1.A5            0  2019-09-20 07:56:07.230406  \n",
       "42    T1.Q1.A10            0  2019-09-20 07:56:07.230406  \n",
       "43     T1.Q1.A5            0  2019-09-20 07:57:55.065468  \n",
       "44     T1.Q1.A5            0  2019-09-20 07:57:55.065468  \n",
       "45     T1.Q1.A5            0  2019-09-20 07:57:55.065468  \n",
       "46     T1.Q1.A4            0  2019-09-20 07:57:55.065468  \n",
       "47     T1.Q1.A3            0  2019-09-20 07:57:55.065468  \n",
       "48     T1.Q1.A3            0  2019-09-20 07:57:55.065468  \n",
       "49    T1.Q1.A13            0  2019-09-20 07:58:36.292159  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#example output csv for a given contributor_uuid\n",
    "user_score_dict['9edd2824-48d3-49db-97ae-9713b37592d3']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#group by user group by task type avg var\n",
    "def variances(df):\n",
    "    #assume df passed in is pd df and organized like Jay's drawing\n",
    "    df = df[[\"question_type\", \"answer_score\"]]\n",
    "    df = df.groupby(\"question_type\").agg({'answer_score': np.var})\n",
    "    return df\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "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>answer_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>question_type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>select_all</td>\n",
       "      <td>0.150612</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               answer_score\n",
       "question_type              \n",
       "select_all         0.150612"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variances(user_score_dict['9edd2824-48d3-49db-97ae-9713b37592d3'])"
   ]
  },
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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