{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploration des résultats des 302"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from math import ceil\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from pprint import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "db = \"recopytex.db\"\n",
    "conn = sqlite3.connect(db)\n",
    "c = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tribe_name = \"302\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Id de la classe de 302"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tribe_id = c.execute(\"SELECT id from tribe WHERE tribe.name ==  ?\", (tribe_name,)).fetchone()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(tribe_id)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluations disponibles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "evals = c.execute(\"SELECT id, name from eval WHERE eval.tribe_id == ?\", (tribe_id,))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 'DS1 mise en jambe')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "evals.fetchmany()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DS 1 mise en jambre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eval_id = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "questions_scores = pd.read_sql_query(\"SELECT student.name, student.surname, score.value, question.competence\\\n",
    "                FROM score\\\n",
    "                JOIN question ON score.question_id==question.id \\\n",
    "                JOIN exercise ON question.exercise_id==exercise.id \\\n",
    "                JOIN eval ON exercise.eval_id==eval.id \\\n",
    "                JOIN student ON score.student_id==student.id\\\n",
    "                WHERE eval.id == (?)\",\n",
    "                 conn,\n",
    "                params = (eval_id,))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "questions_scores = questions_scores[questions_scores[\"value\"]!='']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def note2score(x):\n",
    "    if x[\"value\"] == '.':\n",
    "        return 0\n",
    "    if x[\"value\"] not in [0, 1, 2, 3]:\n",
    "        raise ValueError(f\"The evaluation is out of range: {x['value']} at {x}\")\n",
    "    return x[\"value\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "questions_scores[\"score\"] = questions_scores.apply(note2score, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "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",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>surname</th>\n",
       "      <th>value</th>\n",
       "      <th>competence</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABDALLAH ALLAOUI</td>\n",
       "      <td>Taiassima</td>\n",
       "      <td>1</td>\n",
       "      <td>Cher</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABDALLAH ALLAOUI</td>\n",
       "      <td>Taiassima</td>\n",
       "      <td>2</td>\n",
       "      <td>Cal</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABDALLAH ALLAOUI</td>\n",
       "      <td>Taiassima</td>\n",
       "      <td>.</td>\n",
       "      <td>Cal</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANI</td>\n",
       "      <td>Ismou</td>\n",
       "      <td>2</td>\n",
       "      <td>Cher</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANI</td>\n",
       "      <td>Ismou</td>\n",
       "      <td>2</td>\n",
       "      <td>Cal</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               name    surname value competence  score\n",
       "0  ABDALLAH ALLAOUI  Taiassima     1       Cher      1\n",
       "1  ABDALLAH ALLAOUI  Taiassima     2        Cal      2\n",
       "2  ABDALLAH ALLAOUI  Taiassima     .        Cal      0\n",
       "3             ADANI      Ismou     2       Cher      2\n",
       "4             ADANI      Ismou     2        Cal      2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "questions_scores.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "questions_scores[\"fullname\"] = questions_scores[\"name\"] + \" \" + questions_scores[\"surname\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def score_mean(x):\n",
    "    mean = np.mean(x)\n",
    "    return round(mean, 0)\n",
    "\n",
    "score_mean.__name__ = \"Moyenne discrète\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "report_comp = pd.pivot_table(questions_scores,\n",
    "              index=[\"fullname\"],\n",
    "              columns = ['competence'],\n",
    "              values = [\"score\"],\n",
    "              aggfunc = [score_mean])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Applatissement du nom des colonnes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "report_comp.columns = report_comp.columns.levels[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "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",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>competence</th>\n",
       "      <th>Cal</th>\n",
       "      <th>Cher</th>\n",
       "      <th>Com</th>\n",
       "      <th>Rai</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fullname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ABDALLAH ALLAOUI Taiassima</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADANI Ismou</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AHAMADA Dhoulkamal</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AHAMADI Asbahati</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AHAMADI OUSSENI Ansufiddine</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AHAMED Fayadhi</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AHMED SAID Hadaïta</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALI MADI Anissa</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALI Raydel</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ATTOUMANE ALI Fatima</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BACHIROU Elzame</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BINALI Zalida</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOINA Abdillah Mze Limassi</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOUDRA Zaankidine</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HALADI Asna</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HALIDI Soibrata</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HAMEDALY Doulkifly</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBRAHIM Nassur</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INOUSSA Anchoura</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MOHAMED Nadia</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MOUHOUDHOIRE Izak</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MOUSSRI Bakari</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAKOTRA Claudiana</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAÏD Fatoumia</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOUFAIL Salahou</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "competence                   Cal  Cher  Com  Rai\n",
       "fullname                                        \n",
       "ABDALLAH ALLAOUI Taiassima     2     2    2    2\n",
       "ADANI Ismou                    1     2    1    2\n",
       "AHAMADA Dhoulkamal             0     3    1    0\n",
       "AHAMADI Asbahati               3     3    3    3\n",
       "AHAMADI OUSSENI Ansufiddine    1     1    1    0\n",
       "AHAMED Fayadhi                 1     3    2    1\n",
       "AHMED SAID Hadaïta             2     3    3    3\n",
       "ALI MADI Anissa                2     3    2    3\n",
       "ALI Raydel                     3     2    2    2\n",
       "ATTOUMANE ALI Fatima           1     1    0    0\n",
       "BACHIROU Elzame                0     2    1    0\n",
       "BINALI Zalida                  1     2    2    0\n",
       "BOINA Abdillah Mze Limassi     2     2    2    3\n",
       "BOUDRA Zaankidine              0     0    0    0\n",
       "HALADI Asna                    2     3    3    3\n",
       "HALIDI Soibrata                1     2    2    0\n",
       "HAMEDALY Doulkifly             1     0    1    1\n",
       "IBRAHIM Nassur                 1     2    1    1\n",
       "INOUSSA Anchoura               1     2    2    2\n",
       "MOHAMED Nadia                  0     1    0    0\n",
       "MOUHOUDHOIRE Izak              0     1    0    0\n",
       "MOUSSRI Bakari                 0     2    1    1\n",
       "SAKOTRA Claudiana              1     0    1    0\n",
       "SAÏD Fatoumia                  2     3    2    3\n",
       "TOUFAIL Salahou                1     2    3    3"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "report_comp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAs0AAAJeCAYAAABPvThsAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTprNzMzMzKr4f8Lfv9sZKHahAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f528777cc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 10))\n",
    "ax = sns.heatmap(report_comp, cmap='YlOrRd', linewidths=.5)\n",
    "ax.tick_params(labelbottom='on',labeltop='on')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}