2. post_annotation_check_HIT.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "class HIT(object):\n",
    "    def __init__(self, row, df_s):\n",
    "\n",
    "        self.hit_id = row['HITId']\n",
    "        self.worker_id = row['WorkerId']\n",
    "        self.assignment_id = row['AssignmentId']\n",
    "        self.working_time = round(row['WorkTimeInSeconds']/60,2)\n",
    "        self.ans = row['Answer.Q1']\n",
    "        self.quality_score = 0\n",
    "        for data in row['Answer.Q1'].split('|'):\n",
    "            id,_,ans = data.split('__')\n",
    "            if 'TRAP-SAME' in id and int(ans) >= 90:\n",
    "                self.quality_score += 1\n",
    "            elif 'TRAP-DIFFERENT' in id and int(ans) <= 10:\n",
    "                self.quality_score += 1\n",
    "\n",
    "        self.task_id = -1\n",
    "        for idx, datum in df_s.iterrows():\n",
    "            if datum['text_0'].replace('\\'','') in self.ans:\n",
    "                self.task_id = idx\n",
    "                break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('mturk/annotation_result/RU/raw/batch.csv')\n",
    "df_s = pd.read_csv('mturk/images/RU/turker.csv')\n",
    "\n",
    "hits = []\n",
    "for idx, row in df.iterrows():\n",
    "    hits.append(HIT(row, df_s))\n",
    "\n",
    "res = pd.DataFrame(columns=['task_id', 'hit_id', 'worker_id', 'assignment_id', 'quality_score', 'working_time(min)'])\n",
    "for idx in range(len(hits)):\n",
    "    res = res.append({\n",
    "            'task_id': hits[idx].task_id,\n",
    "            'hit_id': hits[idx].hit_id,\n",
    "            'worker_id': hits[idx].worker_id,\n",
    "            'assignment_id': hits[idx].assignment_id,\n",
    "            'working_time(min)': hits[idx].working_time,\n",
    "            'quality_score': hits[idx].quality_score\n",
    "        }, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "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>task_id</th>\n",
       "      <th>hit_id</th>\n",
       "      <th>worker_id</th>\n",
       "      <th>assignment_id</th>\n",
       "      <th>quality_score</th>\n",
       "      <th>working_time(min)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2</td>\n",
       "      <td>A4GKTYOXL27QT</td>\n",
       "      <td>351SEKWQS0HRTBDQGDERVB2000YMDS</td>\n",
       "      <td>10</td>\n",
       "      <td>23.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2</td>\n",
       "      <td>A2Z596CRYWL6XC</td>\n",
       "      <td>3CTOC39K37QLBU6VM3YDFR0NAMV7JT</td>\n",
       "      <td>10</td>\n",
       "      <td>26.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2</td>\n",
       "      <td>A11T4227GSO6EP</td>\n",
       "      <td>3RJSC4XJ10UZMKRQC29AZ27VLCK051</td>\n",
       "      <td>10</td>\n",
       "      <td>55.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3IZPORCT1F9WFNXRHFOXKBFIRDYRH9</td>\n",
       "      <td>A2Z596CRYWL6XC</td>\n",
       "      <td>386CSBG1OZMJTHW3YJDU6ECDT63Q64</td>\n",
       "      <td>10</td>\n",
       "      <td>26.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>3IZPORCT1F9WFNXRHFOXKBFIRDYRH9</td>\n",
       "      <td>A3U1K9X1LXA5JA</td>\n",
       "      <td>3RKNTXVS3MYDREL8QZNTJGDUT0VA4M</td>\n",
       "      <td>9</td>\n",
       "      <td>53.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>3IZPORCT1F9WFNXRHFOXKBFIRDYRH9</td>\n",
       "      <td>AA3V5BYE3MSQW</td>\n",
       "      <td>3RU7GD8VPOT3G3TL5J187EIV60ISP7</td>\n",
       "      <td>10</td>\n",
       "      <td>42.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM</td>\n",
       "      <td>A2CPJ227RHJRRZ</td>\n",
       "      <td>3E4GGUZ1T8R90DF7YCHUKFJSEV8K2O</td>\n",
       "      <td>10</td>\n",
       "      <td>74.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM</td>\n",
       "      <td>A4GKTYOXL27QT</td>\n",
       "      <td>3UOUJI6MTDEO4PNGGF6PGSMMTV9XUB</td>\n",
       "      <td>9</td>\n",
       "      <td>25.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5</td>\n",
       "      <td>3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM</td>\n",
       "      <td>A2Z596CRYWL6XC</td>\n",
       "      <td>3XC1O3LBOSME4IR22RDR025X38STLU</td>\n",
       "      <td>10</td>\n",
       "      <td>37.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  task_id                          hit_id       worker_id  \\\n",
       "0       3  3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2   A4GKTYOXL27QT   \n",
       "1       3  3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2  A2Z596CRYWL6XC   \n",
       "2       3  3MZ3TAMYTLNWBI8BNX6IKNGXRQDRI2  A11T4227GSO6EP   \n",
       "3       4  3IZPORCT1F9WFNXRHFOXKBFIRDYRH9  A2Z596CRYWL6XC   \n",
       "4       4  3IZPORCT1F9WFNXRHFOXKBFIRDYRH9  A3U1K9X1LXA5JA   \n",
       "5       4  3IZPORCT1F9WFNXRHFOXKBFIRDYRH9   AA3V5BYE3MSQW   \n",
       "6       5  3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM  A2CPJ227RHJRRZ   \n",
       "7       5  3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM   A4GKTYOXL27QT   \n",
       "8       5  3S1L4CQSFX5K2AK4KEEBM0EVBUXAFM  A2Z596CRYWL6XC   \n",
       "\n",
       "                    assignment_id quality_score  working_time(min)  \n",
       "0  351SEKWQS0HRTBDQGDERVB2000YMDS            10              23.42  \n",
       "1  3CTOC39K37QLBU6VM3YDFR0NAMV7JT            10              26.43  \n",
       "2  3RJSC4XJ10UZMKRQC29AZ27VLCK051            10              55.82  \n",
       "3  386CSBG1OZMJTHW3YJDU6ECDT63Q64            10              26.12  \n",
       "4  3RKNTXVS3MYDREL8QZNTJGDUT0VA4M             9              53.00  \n",
       "5  3RU7GD8VPOT3G3TL5J187EIV60ISP7            10              42.32  \n",
       "6  3E4GGUZ1T8R90DF7YCHUKFJSEV8K2O            10              74.18  \n",
       "7  3UOUJI6MTDEO4PNGGF6PGSMMTV9XUB             9              25.85  \n",
       "8  3XC1O3LBOSME4IR22RDR025X38STLU            10              37.22  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}