Expert Data Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# ignoring the warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# We will display plots right inside Jupyter Notebook\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# We will use the Seaborn library\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "# Graphics in SVG format are more sharp and legible. Sometimes it can take longer to load.\n",
    "# Use : %config InlineBackend.figure_format = 'png' in that case\n",
    "%config InlineBackend.figure_format = 'svg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('Data/Expert_Opinions.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7, 121)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Which mockup is a better Login screen design?</th>\n",
       "      <th>Why did you choose one over the other?</th>\n",
       "      <th>How would you rate the design in terms of usability? [Option #1]</th>\n",
       "      <th>How would you rate the design in terms of usability? [Option #2]</th>\n",
       "      <th>How would you rate the design in terms of completeness? [Option #1]</th>\n",
       "      <th>How would you rate the design in terms of completeness? [Option #2]</th>\n",
       "      <th>How would you rate the design in terms of familiarity? [Option #1]</th>\n",
       "      <th>How would you rate the design in terms of familiarity? [Option #2]</th>\n",
       "      <th>How would you rate the design in terms of attractiveness? [Option #1]</th>\n",
       "      <th>...</th>\n",
       "      <th>How would you rate the design in terms of usability? [Option #1].6</th>\n",
       "      <th>How would you rate the design in terms of usability? [Option  #2].3</th>\n",
       "      <th>How would you rate the design in terms of completeness? [Option  #1].4</th>\n",
       "      <th>How would you rate the design in terms of completeness? [Option  #2].4</th>\n",
       "      <th>How would you rate the design in terms of familiarity? [Option  #1].4</th>\n",
       "      <th>How would you rate the design in terms of familiarity? [Option  #2].4</th>\n",
       "      <th>How would you rate the design in terms of attractiveness? [Option  #1].4</th>\n",
       "      <th>How would you rate the design in terms of attractiveness? [Option  #2].4</th>\n",
       "      <th>How would you rate the design in terms of consistency? [Option  #1].4</th>\n",
       "      <th>How would you rate the design in terms of consistency? [Option #2].5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6/5/2018 15:46:51</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>I prefer darker backgrounds on average. Less e...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6/6/2018 23:55:51</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>it has more details and is more user friendly ...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6/6/2018 23:58:30</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>This design has sign up, remember me features ...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6/7/2018 0:16:22</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>Completer design, more readable name</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6/7/2018 2:07:42</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>More interaction options</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 121 columns</p>\n",
       "</div>"
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      "text/plain": [
       "           Timestamp Which mockup is a better Login screen design?  \\\n",
       "0  6/5/2018 15:46:51                                      Option 2   \n",
       "1  6/6/2018 23:55:51                                      Option 2   \n",
       "2  6/6/2018 23:58:30                                      Option 2   \n",
       "3   6/7/2018 0:16:22                                      Option 2   \n",
       "4   6/7/2018 2:07:42                                      Option 2   \n",
       "\n",
       "              Why did you choose one over the other?  \\\n",
       "0  I prefer darker backgrounds on average. Less e...   \n",
       "1  it has more details and is more user friendly ...   \n",
       "2  This design has sign up, remember me features ...   \n",
       "3               Completer design, more readable name   \n",
       "4                           More interaction options   \n",
       "\n",
       "   How would you rate the design in terms of usability? [Option #1]  \\\n",
       "0                                                  2                  \n",
       "1                                                  2                  \n",
       "2                                                  3                  \n",
       "3                                                  1                  \n",
       "4                                                  1                  \n",
       "\n",
       "   How would you rate the design in terms of usability? [Option #2]  \\\n",
       "0                                                  2                  \n",
       "1                                                  3                  \n",
       "2                                                  3                  \n",
       "3                                                  2                  \n",
       "4                                                  3                  \n",
       "\n",
       "   How would you rate the design in terms of completeness? [Option #1]  \\\n",
       "0                                                  2                     \n",
       "1                                                  1                     \n",
       "2                                                  2                     \n",
       "3                                                  1                     \n",
       "4                                                  1                     \n",
       "\n",
       "   How would you rate the design in terms of completeness? [Option #2]  \\\n",
       "0                                                  3                     \n",
       "1                                                  2                     \n",
       "2                                                  3                     \n",
       "3                                                  2                     \n",
       "4                                                  3                     \n",
       "\n",
       "   How would you rate the design in terms of familiarity? [Option #1]  \\\n",
       "0                                                  2                    \n",
       "1                                                  3                    \n",
       "2                                                  3                    \n",
       "3                                                  2                    \n",
       "4                                                  2                    \n",
       "\n",
       "   How would you rate the design in terms of familiarity? [Option #2]  \\\n",
       "0                                                  2                    \n",
       "1                                                  3                    \n",
       "2                                                  3                    \n",
       "3                                                  2                    \n",
       "4                                                  2                    \n",
       "\n",
       "   How would you rate the design in terms of attractiveness? [Option #1]  \\\n",
       "0                                                  2                       \n",
       "1                                                  2                       \n",
       "2                                                  3                       \n",
       "3                                                  2                       \n",
       "4                                                  2                       \n",
       "\n",
       "                                   ...                                   \\\n",
       "0                                  ...                                    \n",
       "1                                  ...                                    \n",
       "2                                  ...                                    \n",
       "3                                  ...                                    \n",
       "4                                  ...                                    \n",
       "\n",
       "   How would you rate the design in terms of usability? [Option #1].6  \\\n",
       "0                                                  2                    \n",
       "1                                                  2                    \n",
       "2                                                  2                    \n",
       "3                                                  2                    \n",
       "4                                                  2                    \n",
       "\n",
       "   How would you rate the design in terms of usability? [Option  #2].3  \\\n",
       "0                                                  2                     \n",
       "1                                                  3                     \n",
       "2                                                  2                     \n",
       "3                                                  2                     \n",
       "4                                                  3                     \n",
       "\n",
       "   How would you rate the design in terms of completeness? [Option  #1].4  \\\n",
       "0                                                  2                        \n",
       "1                                                  2                        \n",
       "2                                                  2                        \n",
       "3                                                  2                        \n",
       "4                                                  2                        \n",
       "\n",
       "  How would you rate the design in terms of completeness? [Option  #2].4  \\\n",
       "0                                                  2                       \n",
       "1                                                  3                       \n",
       "2                                                  2                       \n",
       "3                                                  2                       \n",
       "4                                                  3                       \n",
       "\n",
       "  How would you rate the design in terms of familiarity? [Option  #1].4  \\\n",
       "0                                                  2                      \n",
       "1                                                  3                      \n",
       "2                                                  3                      \n",
       "3                                                  2                      \n",
       "4                                                  2                      \n",
       "\n",
       "   How would you rate the design in terms of familiarity? [Option  #2].4  \\\n",
       "0                                                  2                       \n",
       "1                                                  3                       \n",
       "2                                                  3                       \n",
       "3                                                  2                       \n",
       "4                                                  3                       \n",
       "\n",
       "   How would you rate the design in terms of attractiveness? [Option  #1].4  \\\n",
       "0                                                  1                          \n",
       "1                                                  2                          \n",
       "2                                                  3                          \n",
       "3                                                  2                          \n",
       "4                                                  1                          \n",
       "\n",
       "   How would you rate the design in terms of attractiveness? [Option  #2].4  \\\n",
       "0                                                  2                          \n",
       "1                                                  3                          \n",
       "2                                                  2                          \n",
       "3                                                  1                          \n",
       "4                                                  3                          \n",
       "\n",
       "   How would you rate the design in terms of consistency? [Option  #1].4  \\\n",
       "0                                                  2                       \n",
       "1                                                  3                       \n",
       "2                                                  3                       \n",
       "3                                                  2                       \n",
       "4                                                  1                       \n",
       "\n",
       "   How would you rate the design in terms of consistency? [Option #2].5  \n",
       "0                                                  2                     \n",
       "1                                                  3                     \n",
       "2                                                  2                     \n",
       "3                                                  2                     \n",
       "4                                                  3                     \n",
       "\n",
       "[5 rows x 121 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each row represents an **Expert** entry and each column represents a **Participant** entry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Timestamp', 'Which mockup is a better Login screen design?',\n",
       "       'Why did you choose one over the other?',\n",
       "       'How would you rate the design in terms of usability? [Option #1]',\n",
       "       'How would you rate the design in terms of usability? [Option #2]',\n",
       "       'How would you rate the design in terms of completeness? [Option #1]',\n",
       "       'How would you rate the design in terms of completeness? [Option #2]',\n",
       "       'How would you rate the design in terms of familiarity? [Option #1]',\n",
       "       'How would you rate the design in terms of familiarity? [Option #2]',\n",
       "       'How would you rate the design in terms of attractiveness? [Option #1]',\n",
       "       ...\n",
       "       'How would you rate the design in terms of usability? [Option #1].6',\n",
       "       'How would you rate the design in terms of usability? [Option  #2].3',\n",
       "       'How would you rate the design in terms of completeness? [Option  #1].4',\n",
       "       'How would you rate the design in terms of completeness? [Option  #2].4',\n",
       "       'How would you rate the design in terms of familiarity? [Option  #1].4',\n",
       "       'How would you rate the design in terms of familiarity? [Option  #2].4',\n",
       "       'How would you rate the design in terms of attractiveness? [Option  #1].4',\n",
       "       'How would you rate the design in terms of attractiveness? [Option  #2].4',\n",
       "       'How would you rate the design in terms of consistency? [Option  #1].4',\n",
       "       'How would you rate the design in terms of consistency? [Option #2].5'],\n",
       "      dtype='object', length=121)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.drop(['Timestamp'],axis=1) # deleting the timestamp column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7, 120)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, we see that there are 120 columns. This is because there are 10 participants and 12 responses for each participants. The breakdown of questions are:\n",
    "- 1 question for choosing the better mockup.\n",
    "- 1 question for filling in the comments.\n",
    "- 5 questions with 2 subparts (one for each option)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Creating meaningful columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Setting the constants\n",
    "numQues = 5\n",
    "colsPerParticipant = 2*numQues + 2\n",
    "numParticipants = int(len(df.columns)/colsPerParticipant)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ques = ['Q' + str(i) for i in range(1,numQues+1)]\n",
    "part = ['P'+str(i) for i in range(1,numParticipants+1)]\n",
    "opt = ['O1','O2']\n",
    "design = [part[i]+'D' for i in range(len(part))]\n",
    "comments = [part[i]+'C' for i in range(len(part))] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tmp = [part[j] + ques[i] for j in range(len(part)) for i in range(len(ques))]\n",
    "tmp = [tmp[i] + opt[j] for i in range(len(tmp)) for j in range(len(opt))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final = []\n",
    "k = 0\n",
    "for i in range(len(tmp)):\n",
    "    if i%10 == 0:\n",
    "        final.append(design[k])\n",
    "        final.append(comments[k])\n",
    "        k += 1\n",
    "    final.append(tmp[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['P2D',\n",
       " 'P2C',\n",
       " 'P2Q1O1',\n",
       " 'P2Q1O2',\n",
       " 'P2Q2O1',\n",
       " 'P2Q2O2',\n",
       " 'P2Q3O1',\n",
       " 'P2Q3O2',\n",
       " 'P2Q4O1',\n",
       " 'P2Q4O2',\n",
       " 'P2Q5O1',\n",
       " 'P2Q5O2']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(final[12:24])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above are the values collected for each participant. Each participant will have 12 questions and 1 column for each question. Hence, we have 120 columns for 10 participants. Here, the column naming convention is such:\n",
    "* P1D: For participant1 what is the design preference\n",
    "* P1C: For participant1 what are the comments\n",
    "* P1Q1O1: For participant1 question1 option1 what is the rating given\n",
    "* P1Q1O2: For participant1 question1 option2 what is the rating given"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.columns = final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P1D</th>\n",
       "      <th>P1C</th>\n",
       "      <th>P1Q1O1</th>\n",
       "      <th>P1Q1O2</th>\n",
       "      <th>P1Q2O1</th>\n",
       "      <th>P1Q2O2</th>\n",
       "      <th>P1Q3O1</th>\n",
       "      <th>P1Q3O2</th>\n",
       "      <th>P1Q4O1</th>\n",
       "      <th>P1Q4O2</th>\n",
       "      <th>P1Q5O1</th>\n",
       "      <th>P1Q5O2</th>\n",
       "      <th>P2D</th>\n",
       "      <th>P2C</th>\n",
       "      <th>P2Q1O1</th>\n",
       "      <th>P2Q1O2</th>\n",
       "      <th>P2Q2O1</th>\n",
       "      <th>P2Q2O2</th>\n",
       "      <th>P2Q3O1</th>\n",
       "      <th>P2Q3O2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Option 2</td>\n",
       "      <td>I prefer darker backgrounds on average. Less e...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Option 2</td>\n",
       "      <td>More consistent color palette and hierarchy e....</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Option 2</td>\n",
       "      <td>it has more details and is more user friendly ...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Option 1</td>\n",
       "      <td>More details</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Option 2</td>\n",
       "      <td>This design has sign up, remember me features ...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>Option 1</td>\n",
       "      <td>It is a more complete design in the sense that...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Option 2</td>\n",
       "      <td>Completer design, more readable name</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Option 1</td>\n",
       "      <td>A Completer UI, Also having signing in options...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Option 2</td>\n",
       "      <td>More interaction options</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>Option 1</td>\n",
       "      <td>looks more complete. logo is misplaced in app-2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        P1D                                                P1C  P1Q1O1  \\\n",
       "0  Option 2  I prefer darker backgrounds on average. Less e...       2   \n",
       "1  Option 2  it has more details and is more user friendly ...       2   \n",
       "2  Option 2  This design has sign up, remember me features ...       3   \n",
       "3  Option 2               Completer design, more readable name       1   \n",
       "4  Option 2                           More interaction options       1   \n",
       "\n",
       "   P1Q1O2  P1Q2O1  P1Q2O2  P1Q3O1  P1Q3O2  P1Q4O1  P1Q4O2  P1Q5O1  P1Q5O2  \\\n",
       "0       2       2       3       2       2       2       2       2       2   \n",
       "1       3       1       2       3       3       2       3       2       2   \n",
       "2       3       2       3       3       3       3       1       3       2   \n",
       "3       2       1       2       2       2       2       1       2       2   \n",
       "4       3       1       3       2       2       2       2       3       2   \n",
       "\n",
       "        P2D                                                P2C  P2Q1O1  \\\n",
       "0  Option 2  More consistent color palette and hierarchy e....       2   \n",
       "1  Option 1                                       More details       3   \n",
       "2  Option 1  It is a more complete design in the sense that...       3   \n",
       "3  Option 1  A Completer UI, Also having signing in options...       3   \n",
       "4  Option 1    looks more complete. logo is misplaced in app-2       3   \n",
       "\n",
       "   P2Q1O2  P2Q2O1  P2Q2O2  P2Q3O1  P2Q3O2  \n",
       "0       2       2       2       2       2  \n",
       "1       2       1       2       2       2  \n",
       "2       2       3       2       3       3  \n",
       "3       1       3       1       2       1  \n",
       "4       1       2       1       3       1  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:5,:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "optionsdict = {'Option 1':1,'Option 2':2}\n",
    "for c in df.columns:\n",
    "    if c[-1] == 'D': df = df.replace({c:optionsdict})\n",
    "# replace the columns with design choices (ends with 'D') \n",
    "# between option 1 & 2 with numeric values (makes understanding easy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>P1D</th>\n",
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       "      <th>P1Q1O1</th>\n",
       "      <th>P1Q1O2</th>\n",
       "      <th>P1Q2O1</th>\n",
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       "      <th>P1Q3O1</th>\n",
       "      <th>P1Q3O2</th>\n",
       "      <th>P1Q4O1</th>\n",
       "      <th>P1Q4O2</th>\n",
       "      <th>P1Q5O1</th>\n",
       "      <th>P1Q5O2</th>\n",
       "      <th>P2D</th>\n",
       "      <th>P2C</th>\n",
       "      <th>P2Q1O1</th>\n",
       "      <th>P2Q1O2</th>\n",
       "      <th>P2Q2O1</th>\n",
       "      <th>P2Q2O2</th>\n",
       "      <th>P2Q3O1</th>\n",
       "      <th>P2Q3O2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>I prefer darker backgrounds on average. Less e...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>More consistent color palette and hierarchy e....</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>it has more details and is more user friendly ...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>More details</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>This design has sign up, remember me features ...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>It is a more complete design in the sense that...</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>Completer design, more readable name</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>A Completer UI, Also having signing in options...</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2</td>\n",
       "      <td>More interaction options</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>looks more complete. logo is misplaced in app-2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   P1D                                                P1C  P1Q1O1  P1Q1O2  \\\n",
       "0    2  I prefer darker backgrounds on average. Less e...       2       2   \n",
       "1    2  it has more details and is more user friendly ...       2       3   \n",
       "2    2  This design has sign up, remember me features ...       3       3   \n",
       "3    2               Completer design, more readable name       1       2   \n",
       "4    2                           More interaction options       1       3   \n",
       "\n",
       "   P1Q2O1  P1Q2O2  P1Q3O1  P1Q3O2  P1Q4O1  P1Q4O2  P1Q5O1  P1Q5O2  P2D  \\\n",
       "0       2       3       2       2       2       2       2       2    2   \n",
       "1       1       2       3       3       2       3       2       2    1   \n",
       "2       2       3       3       3       3       1       3       2    1   \n",
       "3       1       2       2       2       2       1       2       2    1   \n",
       "4       1       3       2       2       2       2       3       2    1   \n",
       "\n",
       "                                                 P2C  P2Q1O1  P2Q1O2  P2Q2O1  \\\n",
       "0  More consistent color palette and hierarchy e....       2       2       2   \n",
       "1                                       More details       3       2       1   \n",
       "2  It is a more complete design in the sense that...       3       2       3   \n",
       "3  A Completer UI, Also having signing in options...       3       1       3   \n",
       "4    looks more complete. logo is misplaced in app-2       3       1       2   \n",
       "\n",
       "   P2Q2O2  P2Q3O1  P2Q3O2  \n",
       "0       2       2       2  \n",
       "1       2       2       2  \n",
       "2       2       3       3  \n",
       "3       1       2       1  \n",
       "4       1       3       1  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:5,:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Read the mapping between design and assistance used. \n",
    "designmap = pd.read_csv('Data/Participant_Design_Map.csv')\n",
    "[designmap] = designmap.values.T.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 0, 1, 0, 1, 0, 0, 1, 0]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "designmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Separate the designs with Assistant and designs without Assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with_assistant_cols = []\n",
    "without_assistant_cols = []\n",
    "k = 0\n",
    "for c in df.columns:\n",
    "    # Uncomment the lines below to add the cols which donot contain 'O' (the 'D' and 'C' cols)\n",
    "    if 'O' not in c:\n",
    "        ;\n",
    "#         with_assistant_cols.append(c)\n",
    "#         without_assistant_cols.append(c)\n",
    "    # condition for design drawn with the assistant\n",
    "    elif (c.endswith('1') and designmap[k] == 1)\\\n",
    "         or (c.endswith('2') and designmap[k] == 0):\n",
    "        with_assistant_cols.append(c)\n",
    "    # condition for design drawn without the assistant\n",
    "    else:\n",
    "        without_assistant_cols.append(c)\n",
    "    \n",
    "    if (df.columns.get_loc(c) + 1)%(colsPerParticipant) == 0: k += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "wi_df = df[with_assistant_cols]\n",
    "wo_df = df[without_assistant_cols]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- *wi_df* is the dataframe for designs drawn with the assistant \n",
    "- *wo_df* is the dataframe for designs drawn without the assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P1Q1O2</th>\n",
       "      <th>P1Q2O2</th>\n",
       "      <th>P1Q3O2</th>\n",
       "      <th>P1Q4O2</th>\n",
       "      <th>P1Q5O2</th>\n",
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       "      <th>P2Q5O1</th>\n",
       "      <th>...</th>\n",
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       "      <th>P9Q3O1</th>\n",
       "      <th>P9Q4O1</th>\n",
       "      <th>P9Q5O1</th>\n",
       "      <th>P10Q1O2</th>\n",
       "      <th>P10Q2O2</th>\n",
       "      <th>P10Q3O2</th>\n",
       "      <th>P10Q4O2</th>\n",
       "      <th>P10Q5O2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.571429</td>\n",
       "      <td>2.714286</td>\n",
       "      <td>2.285714</td>\n",
       "      <td>1.857143</td>\n",
       "      <td>1.714286</td>\n",
       "      <td>2.714286</td>\n",
       "      <td>2.285714</td>\n",
       "      <td>2.571429</td>\n",
       "      <td>2.142857</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.142857</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.714286</td>\n",
       "      <td>1.571429</td>\n",
       "      <td>2.571429</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>2.714286</td>\n",
       "      <td>2.428571</td>\n",
       "      <td>2.571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.534522</td>\n",
       "      <td>0.487950</td>\n",
       "      <td>0.487950</td>\n",
       "      <td>0.690066</td>\n",
       "      <td>0.487950</td>\n",
       "      <td>0.487950</td>\n",
       "      <td>0.755929</td>\n",
       "      <td>0.534522</td>\n",
       "      <td>0.899735</td>\n",
       "      <td>0.816497</td>\n",
       "      <td>...</td>\n",
       "      <td>0.690066</td>\n",
       "      <td>0.786796</td>\n",
       "      <td>0.816497</td>\n",
       "      <td>0.755929</td>\n",
       "      <td>0.534522</td>\n",
       "      <td>0.534522</td>\n",
       "      <td>0.534522</td>\n",
       "      <td>0.487950</td>\n",
       "      <td>0.786796</td>\n",
       "      <td>0.534522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         P1Q1O2    P1Q2O2    P1Q3O2    P1Q4O2    P1Q5O2    P2Q1O1    P2Q2O1  \\\n",
       "count  7.000000  7.000000  7.000000  7.000000  7.000000  7.000000  7.000000   \n",
       "mean   2.571429  2.714286  2.285714  1.857143  1.714286  2.714286  2.285714   \n",
       "std    0.534522  0.487950  0.487950  0.690066  0.487950  0.487950  0.755929   \n",
       "min    2.000000  2.000000  2.000000  1.000000  1.000000  2.000000  1.000000   \n",
       "25%    2.000000  2.500000  2.000000  1.500000  1.500000  2.500000  2.000000   \n",
       "50%    3.000000  3.000000  2.000000  2.000000  2.000000  3.000000  2.000000   \n",
       "75%    3.000000  3.000000  2.500000  2.000000  2.000000  3.000000  3.000000   \n",
       "max    3.000000  3.000000  3.000000  3.000000  2.000000  3.000000  3.000000   \n",
       "\n",
       "         P2Q3O1    P2Q4O1    P2Q5O1    ...       P9Q1O1    P9Q2O1    P9Q3O1  \\\n",
       "count  7.000000  7.000000  7.000000    ...     7.000000  7.000000  7.000000   \n",
       "mean   2.571429  2.142857  2.000000    ...     2.142857  2.428571  2.000000   \n",
       "std    0.534522  0.899735  0.816497    ...     0.690066  0.786796  0.816497   \n",
       "min    2.000000  1.000000  1.000000    ...     1.000000  1.000000  1.000000   \n",
       "25%    2.000000  1.500000  1.500000    ...     2.000000  2.000000  1.500000   \n",
       "50%    3.000000  2.000000  2.000000    ...     2.000000  3.000000  2.000000   \n",
       "75%    3.000000  3.000000  2.500000    ...     2.500000  3.000000  2.500000   \n",
       "max    3.000000  3.000000  3.000000    ...     3.000000  3.000000  3.000000   \n",
       "\n",
       "         P9Q4O1    P9Q5O1   P10Q1O2   P10Q2O2   P10Q3O2   P10Q4O2   P10Q5O2  \n",
       "count  7.000000  7.000000  7.000000  7.000000  7.000000  7.000000  7.000000  \n",
       "mean   1.714286  1.571429  2.571429  2.428571  2.714286  2.428571  2.571429  \n",
       "std    0.755929  0.534522  0.534522  0.534522  0.487950  0.786796  0.534522  \n",
       "min    1.000000  1.000000  2.000000  2.000000  2.000000  1.000000  2.000000  \n",
       "25%    1.000000  1.000000  2.000000  2.000000  2.500000  2.000000  2.000000  \n",
       "50%    2.000000  2.000000  3.000000  2.000000  3.000000  3.000000  3.000000  \n",
       "75%    2.000000  2.000000  3.000000  3.000000  3.000000  3.000000  3.000000  \n",
       "max    3.000000  2.000000  3.000000  3.000000  3.000000  3.000000  3.000000  \n",
       "\n",
       "[8 rows x 50 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wi_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Getting rid of the 'P*' and 'O*' substrings\n",
    "wi_df.columns = [x[-4:-2] for x in wi_df.columns]\n",
    "wo_df.columns = [x[-4:-2] for x in wo_df.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Q1</th>\n",
       "      <th>Q2</th>\n",
       "      <th>Q3</th>\n",
       "      <th>Q4</th>\n",
       "      <th>Q5</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Q1  Q2  Q3  Q4  Q5  Q1  Q2  Q3  Q4  Q5 ...  Q1  Q2  Q3  Q4  Q5  Q1  Q2  Q3  \\\n",
       "0   2   3   2   2   2   2   2   2   2   1 ...   1   1   2   1   1   2   2   2   \n",
       "1   3   2   3   3   2   3   1   2   3   2 ...   2   3   3   3   2   3   3   3   \n",
       "2   3   3   3   1   2   3   3   3   1   2 ...   2   2   1   1   1   2   2   3   \n",
       "3   2   2   2   1   2   3   3   2   1   1 ...   2   2   1   1   1   2   2   2   \n",
       "4   3   3   2   2   2   3   2   3   2   2 ...   3   3   2   2   2   3   3   3   \n",
       "\n",
       "   Q4  Q5  \n",
       "0   2   2  \n",
       "1   3   3  \n",
       "2   2   2  \n",
       "3   1   2  \n",
       "4   3   3  \n",
       "\n",
       "[5 rows x 50 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wi_df.iloc[:5,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7, 50)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wi_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Saving the dataframes to csv file to be used with for Participant Data Analysis\n",
    "wi_df.to_csv('Data/wi_df.csv', index=False)\n",
    "wo_df.to_csv('Data/wo_df.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Grouping across different participants for question\n",
    "wi_df_grouped_mean = wi_df.groupby(wi_df.columns, axis=1).mean()\n",
    "wo_df_grouped_mean = wo_df.groupby(wo_df.columns, axis=1).mean()\n",
    "# Taking mean for each question\n",
    "wo_df_mean = wo_df_grouped_mean.mean()\n",
    "wi_df_mean = wi_df_grouped_mean.mean()\n",
    "# Find the std deviation\n",
    "wo_df_std = wo_df_grouped_mean.std()\n",
    "wi_df_std = wi_df_grouped_mean.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Similar to above, taking medians of median\n",
    "wi_df_grouped_median = wi_df.groupby(wi_df.columns, axis=1).median()\n",
    "wo_df_grouped_median = wo_df.groupby(wo_df.columns, axis=1).median()\n",
    "wo_df_median = wo_df_grouped_median.median()\n",
    "wi_df_median = wi_df_grouped_median.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
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       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Q1</th>\n",
       "      <td>1.814286</td>\n",
       "      <td>2.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q2</th>\n",
       "      <td>1.942857</td>\n",
       "      <td>2.185714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q3</th>\n",
       "      <td>2.200000</td>\n",
       "      <td>2.228571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q4</th>\n",
       "      <td>1.900000</td>\n",
       "      <td>1.957143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q5</th>\n",
       "      <td>2.185714</td>\n",
       "      <td>2.071429</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           0         1\n",
       "Q1  1.814286  2.300000\n",
       "Q2  1.942857  2.185714\n",
       "Q3  2.200000  2.228571\n",
       "Q4  1.900000  1.957143\n",
       "Q5  2.185714  2.071429"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ques_df_mean = pd.DataFrame([wo_df_mean, wi_df_mean]).T\n",
    "ques_df_mean # col-0: Without the assistant, col-1: With the assistant"
   ]
  },
  {
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   "execution_count": 29,
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    "ques_df_std = pd.DataFrame([wo_df_std, wi_df_std]).T\n",
    "ques_df_std # col-0: Without the assistant, col-1: With the assistant"
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  {
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   "source": [
    "ques_df_median = pd.DataFrame([wo_df_median, wi_df_median]).T\n",
    "ques_df_median # col-0: Without the assistant, col-1: With the assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true,
    "scrolled": true
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   "source": [
    "def plot_ques_wise(df,ylabel,yerr,filename):\n",
    "    labels = ['Usability','Completeness','Familiarity','Atractiveness','Consistency']\n",
    "    df.plot(kind='bar',yerr=yerr)\n",
    "    plt.legend(['Without Assistant','With Assistant'])\n",
    "    plt.xticks(range(5), labels, rotation=15)\n",
    "    plt.xlabel('Parameters')\n",
    "    plt.ylabel(ylabel)\n",
    "    plt.savefig(filename, bbox_inches='tight')"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TODO: Add labels on bar plots"
   ]
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  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
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   "source": [
    "plot_ques_wise(ques_df_median, 'Median Rating', yerr=0, filename='plots/expert_median.png')"
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What are the other kinds of plots that can be drawn from experts data?"
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
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