2014-2015/1S/DM/DM_0528/Bilan/Bilan.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from opytex import texenv\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Informations sur le devoir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'classe': '\\\\premiereS', 'date': '28 mai 2015', 'titre': 'DM 7'}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_name = 'DM_0528'\n",
    "classe = '1S'\n",
    "\n",
    "latex_info = {}\n",
    "latex_info['titre'] = 'DM 7' \n",
    "latex_info['classe'] = '\\\\premiereS'\n",
    "latex_info['date'] = '28 mai 2015'\n",
    "latex_info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import et premiers traitements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "notes = pd.ExcelFile(\"./../../../notes_\"+classe+\".xlsx\")\n",
    "notes.sheet_names\n",
    "notes = notes.parse(ds_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DM_0528', 'av_arrondi', 'Retard', 'subj_num', 'Exercice 1',\n",
       "       '1 (placer angle)', '2.a (calcul prod scal)', '2.b (calcul prod scal)',\n",
       "       'Exercice 2', '1.a (domaine def)', '1.b (domaine def)',\n",
       "       '1.c (domaine def)', '2.a (dommaine def)', '2.b (dérivation)',\n",
       "       '2.c (signe et variations)', '2.d (tangente)', 'Exercice 3',\n",
       "       '1 (termes suite)', '2.a (termes suites)', '2.b (géométrique)',\n",
       "       '2.c (Explicite)', '2.d (Explicite)', '3 (algorithme)',\n",
       "       '4 (algorithme)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "notes.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "notes = notes.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes = notes.drop('av_arrondi', axis=1)\n",
    "notes = notes.drop('subj_num', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "barem = notes[:1]\n",
    "notes = notes[1:]\n",
    "#notes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Supression des notes inutiles "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes = notes[notes[ds_name].notnull()]\n",
    "notes = notes[notes[ds_name] != 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes = notes.astype(float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Traitement des notes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DM_0528', 'Retard', 'Exercice 1', '1 (placer angle)',\n",
       "       '2.a (calcul prod scal)', '2.b (calcul prod scal)', 'Exercice 2',\n",
       "       '1.a (domaine def)', '1.b (domaine def)', '1.c (domaine def)',\n",
       "       '2.a (dommaine def)', '2.b (dérivation)', '2.c (signe et variations)',\n",
       "       '2.d (tangente)', 'Exercice 3', '1 (termes suite)',\n",
       "       '2.a (termes suites)', '2.b (géométrique)', '2.c (Explicite)',\n",
       "       '2.d (Explicite)', '3 (algorithme)', '4 (algorithme)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "notes.T.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "list_exo = [\"Exercice 1\", \"Exercice 2\", \"Exercice 3\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes[list_exo] = notes[list_exo].applymap(lambda x:round(x,2))\n",
    "#notes[list_exo]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1 (placer angle)',\n",
       " '2.a (calcul prod scal)',\n",
       " '2.b (calcul prod scal)',\n",
       " '1.a (domaine def)',\n",
       " '1.b (domaine def)',\n",
       " '1.c (domaine def)',\n",
       " '2.a (dommaine def)',\n",
       " '2.b (dérivation)',\n",
       " '2.c (signe et variations)',\n",
       " '2.d (tangente)',\n",
       " '1 (termes suite)',\n",
       " '2.a (termes suites)',\n",
       " '2.b (géométrique)',\n",
       " '2.c (Explicite)',\n",
       " '2.d (Explicite)',\n",
       " '3 (algorithme)',\n",
       " '4 (algorithme)']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "item_avec_note = list_exo + [ds_name, \"Retard\"]\n",
    "sous_exo = [i for i in notes.T.index if i not in item_avec_note]\n",
    "sous_exo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def toRepVal(val):\n",
    "    if pd.isnull(val):\n",
    "        return \"\\\\NoRep\"\n",
    "    elif val == 0:\n",
    "        return \"\\\\RepZ\"\n",
    "    elif val == 1:\n",
    "        return \"\\\\RepU\"\n",
    "    elif val == 2:\n",
    "        return \"\\\\RepD\"\n",
    "    elif val == 3:\n",
    "        return \"\\\\RepT\"\n",
    "    else:\n",
    "        return val"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
    "#notes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eleves = notes.copy()\n",
    "eleves[sous_exo] = notes[sous_exo].applymap(toRepVal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(notes.T.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparation du fichier .tex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
    "with open(\"./bilan.tex\",\"w\") as f:\n",
    "    f.write(bilan.render(eleves = eleves, barem = barem, ds_name = ds_name, latex_info = latex_info, nbr_questions = len(barem.T)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Un peu de statistiques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    27.000000\n",
       "mean     13.314815\n",
       "std       4.233902\n",
       "min       6.000000\n",
       "25%       9.000000\n",
       "50%      13.500000\n",
       "75%      17.000000\n",
       "max      20.000000\n",
       "Name: DM_0528, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "notes[ds_name].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f54263a3d30>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f542600fa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "notes_seules = notes[ds_name]\n",
    "notes_seules.hist(bins = (notes_seules.max() - notes_seules.min())*2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "notes_questions = notes[sous_exo]\n",
    "notes_analysis = notes_questions.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1.1</th>\n",
       "      <th>1.2</th>\n",
       "      <th>2.A.1</th>\n",
       "      <th>2.A.2</th>\n",
       "      <th>2.A.3.a</th>\n",
       "      <th>2.A.3.b</th>\n",
       "      <th>2.A.3.c</th>\n",
       "      <th>2.B.1</th>\n",
       "      <th>2.B.2</th>\n",
       "      <th>3.A.1</th>\n",
       "      <th>3.A.2</th>\n",
       "      <th>3.B.1</th>\n",
       "      <th>3.B.2</th>\n",
       "      <th>3.B.3</th>\n",
       "      <th>4.A.1</th>\n",
       "      <th>4.A.1.a</th>\n",
       "      <th>4.A.1.b</th>\n",
       "      <th>4.B.1</th>\n",
       "      <th>4.B.2</th>\n",
       "      <th>4.B.3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       1.1  1.2  2.A.1  2.A.2  2.A.3.a  2.A.3.b  2.A.3.c  2.B.1  2.B.2  3.A.1  \\\n",
       "count  NaN  NaN    NaN    NaN      NaN      NaN      NaN    NaN    NaN    NaN   \n",
       "\n",
       "       3.A.2  3.B.1  3.B.2  3.B.3  4.A.1  4.A.1.a  4.A.1.b  4.B.1  4.B.2  \\\n",
       "count    NaN    NaN    NaN    NaN    NaN      NaN      NaN    NaN    NaN   \n",
       "\n",
       "       4.B.3  \n",
       "count    NaN  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# J'aimerai récupérer le nom des questions qui ont été le moins répondus\n",
    "notes_analysis[:1][notes_analysis[:1] == 25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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