2015-2016/3e/DS/DS_15_09_25/Bilan/Bilan309.ipynb

1301 lines
52 KiB
Plaintext
Raw Normal View History

2017-06-16 06:48:54 +00:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 18,
"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": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"{'classe': '309', 'date': '25 septembre 2015', 'titre': 'DS 1'}"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds_name = \"DS_15_09_25\"\n",
"classe = \"309\"\n",
"\n",
"latex_info = {}\n",
"latex_info['titre'] = \"DS 1\"\n",
"latex_info['classe'] = classe\n",
"latex_info['date'] = \"25 septembre 2015\"\n",
"latex_info"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import et premiers traitements"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"notes = pd.ExcelFile(\"./../../../\"+classe+\".xlsx\")\n",
"notes.sheet_names\n",
"notes = notes.parse(ds_name)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Index([ 'DS_15_09_25', 'numero sujet', 'Presentation',\n",
" 'Exercice 1', 1, 2,\n",
" 'Exercice 2', '1 (Division)', '2.a (Division)',\n",
" '2.b (PGCD)', 'Exercice 3', '1 (Vrai Faux)',\n",
" '2 (Proba)', '3 (Proba)', 'Exercice 4',\n",
" '1 (Modélisation)', '1 (Explication)'],\n",
" dtype='object')"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes.index"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"notes = notes.T"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#notes = notes.drop('av_arrondi', axis=1)\n",
"notes = notes.drop('numero sujet', axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"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>DS_15_09_25</th>\n",
" <th>Presentation</th>\n",
" <th>Exercice 1</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>Exercice 2</th>\n",
" <th>1 (Division)</th>\n",
" <th>2.a (Division)</th>\n",
" <th>2.b (PGCD)</th>\n",
" <th>Exercice 3</th>\n",
" <th>1 (Vrai Faux)</th>\n",
" <th>2 (Proba)</th>\n",
" <th>3 (Proba)</th>\n",
" <th>Exercice 4</th>\n",
" <th>1 (Modélisation)</th>\n",
" <th>1 (Explication)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU Farida</th>\n",
" <td>9.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4.833333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABOU BACAR Djaha</th>\n",
" <td>16.5</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>6.333333</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>5.333333</td>\n",
" <td>4</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>1.5</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADA Nabaouya</th>\n",
" <td>9.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>4.000000</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Faina</th>\n",
" <td>4.5</td>\n",
" <td>1.0</td>\n",
" <td>1.5</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Mardhuia</th>\n",
" <td>11.5</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>4.666667</td>\n",
" <td>4</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.5</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI SOULAIMANA Chamsia</th>\n",
" <td>14.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>5.500000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALSENE ALI MADI Stela</th>\n",
" <td>8.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3.833333</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0.5</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANDRIATAHIANA Hoby</th>\n",
" <td>11.0</td>\n",
" <td>1.0</td>\n",
" <td>2.5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>4.333333</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANLI Emeline</th>\n",
" <td>4.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.5</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATHOUMANE Naouidat</th>\n",
" <td>8.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1.166667</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BOUDRA Nassifanya</th>\n",
" <td>14.5</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>5.500000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHANFI Nadhrati</th>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.000000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Moinécha</th>\n",
" <td>12.5</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4.833333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>1.5</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HALIDI Nisma</th>\n",
" <td>10.0</td>\n",
" <td>0.5</td>\n",
" <td>2.5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4.833333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HAMZA Samianti</th>\n",
" <td>4.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1.000000</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Mouslimati</th>\n",
" <td>5.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Chaharazadi</th>\n",
" <td>10.5</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2.666667</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>4.166667</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.5</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Nasmi</th>\n",
" <td>14.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>4.333333</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>4.500000</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Dhoirfia</th>\n",
" <td>13.5</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>5.500000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LOUTOUFI Nachima</th>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MALIDE El-Anzize</th>\n",
" <td>9.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>5.500000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MONNE Kevin</th>\n",
" <td>14.0</td>\n",
" <td>0.5</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>4.000000</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>3.500000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUSSA Roibouanti</th>\n",
" <td>13.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.333333</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>5.000000</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0.5</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>OUSSENI Hilma</th>\n",
" <td>4.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1.166667</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAANLI Natali</th>\n",
" <td>19.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>7.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>5.000000</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAID AHAMADA Roukaya</th>\n",
" <td>14.5</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>4.666667</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>4.166667</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SANDA Issoufi</th>\n",
" <td>5.0</td>\n",
" <td>0.5</td>\n",
" <td>0.5</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4.166667</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOILIHI Soifia</th>\n",
" <td>9.0</td>\n",
" <td>1.0</td>\n",
" <td>1.5</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>4.166667</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.5</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOUFIANI Laila</th>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1.000000</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>YOUSSOUF Sitirati</th>\n",
" <td>3.5</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DS_15_09_25 Presentation Exercice 1 1 2 \\\n",
"ABDOU Farida 9.0 1.0 0.0 NaN NaN \n",
"ABOU BACAR Djaha 16.5 1.0 2.5 3 2 \n",
"AHAMADA Nabaouya 9.0 1.0 0.0 0 0 \n",
"AHAMADI Faina 4.5 1.0 1.5 3 NaN \n",
"ALI Mardhuia 11.5 1.0 2.5 3 2 \n",
"ALI SOULAIMANA Chamsia 14.0 1.0 3.0 3 3 \n",
"ALSENE ALI MADI Stela 8.5 1.0 0.0 0 0 \n",
"ANDRIATAHIANA Hoby 11.0 1.0 2.5 3 2 \n",
"ANLI Emeline 4.0 0.0 0.0 0 0 \n",
"ATHOUMANE Naouidat 8.0 1.0 2.0 3 1 \n",
"BOUDRA Nassifanya 14.5 1.0 3.0 3 3 \n",
"CHANFI Nadhrati 3.0 1.0 0.0 0 0 \n",
"COMBO Moinécha 12.5 1.0 3.0 3 3 \n",
"HALIDI Nisma 10.0 0.5 2.5 3 2 \n",
"HAMZA Samianti 4.5 1.0 0.0 0 0 \n",
"HOUMADI Mouslimati 5.5 1.0 0.0 0 0 \n",
"HOUMADI Chaharazadi 10.5 1.0 2.0 2 2 \n",
"HOUMADI Nasmi 14.0 1.0 2.0 2 2 \n",
"HOUMADI Dhoirfia 13.5 1.0 3.0 3 3 \n",
"LOUTOUFI Nachima 4.0 1.0 0.0 0 0 \n",
"MALIDE El-Anzize 9.5 1.0 0.0 0 0 \n",
"MONNE Kevin 14.0 0.5 3.0 3 3 \n",
"MOUSSA Roibouanti 13.0 1.0 3.0 3 3 \n",
"OUSSENI Hilma 4.5 1.0 0.0 0 0 \n",
"SAANLI Natali 19.0 1.0 3.0 3 3 \n",
"SAID AHAMADA Roukaya 14.5 1.0 3.0 3 3 \n",
"SANDA Issoufi 5.0 0.5 0.5 1 0 \n",
"SOILIHI Soifia 9.0 1.0 1.5 2 1 \n",
"SOUFIANI Laila 4.0 1.0 0.0 0 0 \n",
"YOUSSOUF Sitirati 3.5 1.0 0.0 0 0 \n",
"\n",
" Exercice 2 1 (Division) 2.a (Division) 2.b (PGCD) \\\n",
"ABDOU Farida 2.000000 0 0 2 \n",
"ABOU BACAR Djaha 6.333333 2 3 3 \n",
"AHAMADA Nabaouya 3.000000 0 0 3 \n",
"AHAMADI Faina 2.000000 0 0 2 \n",
"ALI Mardhuia 3.000000 0 0 3 \n",
"ALI SOULAIMANA Chamsia 3.000000 0 0 2 \n",
"ALSENE ALI MADI Stela 3.000000 0 0 3 \n",
"ANDRIATAHIANA Hoby 4.333333 0 2 3 \n",
"ANLI Emeline 3.000000 0 0 3 \n",
"ATHOUMANE Naouidat 2.000000 0 0 2 \n",
"BOUDRA Nassifanya 3.000000 0 0 3 \n",
"CHANFI Nadhrati 0.000000 0 NaN NaN \n",
"COMBO Moinécha 2.000000 0 0 2 \n",
"HALIDI Nisma 2.000000 0 0 2 \n",
"HAMZA Samianti 1.000000 0 0 1 \n",
"HOUMADI Mouslimati 3.000000 0 0 3 \n",
"HOUMADI Chaharazadi 2.666667 0 1 2 \n",
"HOUMADI Nasmi 4.333333 0 2 3 \n",
"HOUMADI Dhoirfia 2.000000 0 0 2 \n",
"LOUTOUFI Nachima 1.000000 0 0 1 \n",
"MALIDE El-Anzize 2.000000 0 0 2 \n",
"MONNE Kevin 4.000000 0 3 2 \n",
"MOUSSA Roibouanti 3.333333 2 3 0 \n",
"OUSSENI Hilma 1.000000 0 0 1 \n",
"SAANLI Natali 7.000000 3 3 3 \n",
"SAID AHAMADA Roukaya 4.666667 1 3 2 \n",
"SANDA Issoufi 0.000000 0 0 0 \n",
"SOILIHI Soifia 2.000000 0 0 2 \n",
"SOUFIANI Laila 2.000000 0 0 2 \n",
"YOUSSOUF Sitirati 2.000000 0 0 2 \n",
"\n",
" Exercice 3 1 (Vrai Faux) 2 (Proba) 3 (Proba) \\\n",
"ABDOU Farida 4.833333 3 3 2 \n",
"ABOU BACAR Djaha 5.333333 4 3 2 \n",
"AHAMADA Nabaouya 4.000000 4 2 1 \n",
"AHAMADI Faina 0.000000 0 NaN NaN \n",
"ALI Mardhuia 4.666667 4 3 1 \n",
"ALI SOULAIMANA Chamsia 5.500000 3 3 3 \n",
"ALSENE ALI MADI Stela 3.833333 1 3 2 \n",
"ANDRIATAHIANA Hoby 3.000000 2 3 NaN \n",
"ANLI Emeline 0.500000 1 0 0 \n",
"ATHOUMANE Naouidat 1.166667 1 1 NaN \n",
"BOUDRA Nassifanya 5.500000 3 3 3 \n",
"CHANFI Nadhrati 2.000000 4 0 0 \n",
"COMBO Moinécha 4.833333 3 3 2 \n",
"HALIDI Nisma 4.833333 3 3 2 \n",
"HAMZA Samianti 1.000000 2 NaN NaN \n",
"HOUMADI Mouslimati 0.500000 1 0 0 \n",
"HOUMADI Chaharazadi 4.166667 3 3 1 \n",
"HOUMADI Nasmi 4.500000 1 3 3 \n",
"HOUMADI Dhoirfia 5.500000 3 3 3 \n",
"LOUTOUFI Nachima 0.500000 1 0 0 \n",
"MALIDE El-Anzize 5.500000 3 3 3 \n",
"MONNE Kevin 3.500000 3 0 3 \n",
"MOUSSA Roibouanti 5.000000 2 3 3 \n",
"OUSSENI Hilma 1.166667 1 0 1 \n",
"SAANLI Natali 5.000000 2 3 3 \n",
"SAID AHAMADA Roukaya 4.166667 3 3 1 \n",
"SANDA Issoufi 4.166667 3 3 1 \n",
"SOILIHI Soifia 4.166667 3 3 1 \n",
"SOUFIANI Laila 1.000000 2 NaN NaN \n",
"YOUSSOUF Sitirati 0.500000 1 NaN NaN \n",
"\n",
" Exercice 4 1 (Modélisation) 1 (Explication) \n",
"ABDOU Farida 1.0 2 0 \n",
"ABOU BACAR Djaha 1.5 1 2 \n",
"AHAMADA Nabaouya 1.0 1 1 \n",
"AHAMADI Faina 0.0 0 0 \n",
"ALI Mardhuia 0.5 0 1 \n",
"ALI SOULAIMANA Chamsia 1.5 2 1 \n",
"ALSENE ALI MADI Stela 0.5 1 NaN \n",
"ANDRIATAHIANA Hoby 0.0 0 0 \n",
"ANLI Emeline 0.5 0 1 \n",
"ATHOUMANE Naouidat 2.0 2 2 \n",
"BOUDRA Nassifanya 2.0 1 3 \n",
"CHANFI Nadhrati 0.0 0 NaN \n",
"COMBO Moinécha 1.5 1 2 \n",
"HALIDI Nisma 0.0 0 0 \n",
"HAMZA Samianti 1.5 2 1 \n",
"HOUMADI Mouslimati 1.0 1 1 \n",
"HOUMADI Chaharazadi 0.5 1 0 \n",
"HOUMADI Nasmi 2.0 2 2 \n",
"HOUMADI Dhoirfia 2.0 2 2 \n",
"LOUTOUFI Nachima 1.5 2 1 \n",
"MALIDE El-Anzize 1.0 0 2 \n",
"MONNE Kevin 3.0 3 3 \n",
"MOUSSA Roibouanti 0.5 0 1 \n",
"OUSSENI Hilma 1.5 1 2 \n",
"SAANLI Natali 3.0 3 3 \n",
"SAID AHAMADA Roukaya 1.5 2 1 \n",
"SANDA Issoufi 0.0 0 NaN \n",
"SOILIHI Soifia 0.5 1 0 \n",
"SOUFIANI Laila 0.0 0 NaN \n",
"YOUSSOUF Sitirati 0.0 NaN NaN "
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"barem = notes[:1]\n",
"notes = notes[1:]\n",
"notes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Supression des notes inutiles "
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"ename": "TypeError",
"evalue": "invalid type comparison",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-25-5bb918f5a68f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mnotes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mds_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnotnull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mnotes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mds_name\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m'abs'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m/home/lafrite/.virtualenvs/enseignement/lib/python3.4/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(self, other, axis)\u001b[0m\n\u001b[0;32m 612\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 613\u001b[0m \u001b[1;31m# scalars\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 614\u001b[1;33m \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mna_op\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mother\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 615\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misscalar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 616\u001b[0m raise TypeError('Could not compare %s type with Series'\n",
"\u001b[1;32m/home/lafrite/.virtualenvs/enseignement/lib/python3.4/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mna_op\u001b[1;34m(x, y)\u001b[0m\n\u001b[0;32m 566\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 567\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 568\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"invalid type comparison\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 569\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mAttributeError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 570\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mTypeError\u001b[0m: invalid type comparison"
]
}
],
"source": [
"notes = notes[notes[ds_name].notnull()]\n",
"#notes = notes[notes[ds_name] != 'abs']"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes = notes.astype(float)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Traitement des notes"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Index([ 'DS_15_09_25', 'Presentation', 'Exercice 1',\n",
" 1, 2, 'Exercice 2',\n",
" '1 (Division)', '2.a (Division)', '2.b (PGCD)',\n",
" 'Exercice 3', '1 (Vrai Faux)', '2 (Proba)',\n",
" '3 (Proba)', 'Exercice 4', '1 (Modélisation)',\n",
" '1 (Explication)'],\n",
" dtype='object')"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes.T.index"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"list_exo = [\"Exercice 1\", \"Exercice 2\", \"Exercice 3\", \"Exercice 4\"]"
]
},
{
"cell_type": "code",
"execution_count": 29,
"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": 30,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[1,\n",
" 2,\n",
" '1 (Division)',\n",
" '2.a (Division)',\n",
" '2.b (PGCD)',\n",
" '1 (Vrai Faux)',\n",
" '2 (Proba)',\n",
" '3 (Proba)',\n",
" '1 (Modélisation)',\n",
" '1 (Explication)']"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"item_avec_note = list_exo + [ds_name, \"Presentation\"]\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": 31,
"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": 32,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
"#notes"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"eleves = notes.copy()\n",
"eleves[sous_exo] = notes[sous_exo].applymap(toRepVal)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"16"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(notes.T.index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Preparation du fichier .tex"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
"with open(\"./bilan309.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": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"count 30.000000\n",
"mean 9.466667\n",
"std 4.468150\n",
"min 3.000000\n",
"25% 4.625000\n",
"50% 9.250000\n",
"75% 13.375000\n",
"max 19.000000\n",
"Name: DS_15_09_25, dtype: float64"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes[ds_name].describe()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f16822e6c88>"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXUAAAEACAYAAABMEua6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nY6XcqVfP5/l4c6duZjb
"text/plain": [
"<matplotlib.figure.Figure at 0x7f16822e6198>"
]
},
"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": 154,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes_questions = notes[sous_exo]\n",
"notes_analysis = notes_questions.describe()"
]
},
{
"cell_type": "code",
"execution_count": 155,
"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.a</th>\n",
" <th>1.1.b</th>\n",
" <th>1.1.c</th>\n",
" <th>1.2.a</th>\n",
" <th>1.2.b</th>\n",
" <th>1.2.c</th>\n",
" <th>1.2.d</th>\n",
" <th>1.3.a</th>\n",
" <th>1.3.b</th>\n",
" <th>1.3.c</th>\n",
" <th>...</th>\n",
" <th>2.2</th>\n",
" <th>2.3</th>\n",
" <th>3.1.a</th>\n",
" <th>3.1.b</th>\n",
" <th>3.1.c</th>\n",
" <th>3.1.d</th>\n",
" <th>3.2.a</th>\n",
" <th>3.2.b</th>\n",
" <th>3.2.c</th>\n",
" <th>3.2.d</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>25</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",
"<p>1 rows × 22 columns</p>\n",
"</div>"
],
"text/plain": [
" 1.1.a 1.1.b 1.1.c 1.2.a 1.2.b 1.2.c 1.2.d 1.3.a 1.3.b 1.3.c \\\n",
"count 25 25 25 25 NaN NaN NaN 25 25 NaN \n",
"\n",
" ... 2.2 2.3 3.1.a 3.1.b 3.1.c 3.1.d 3.2.a 3.2.b 3.2.c 3.2.d \n",
"count ... NaN 25 NaN NaN NaN NaN NaN NaN NaN NaN \n",
"\n",
"[1 rows x 22 columns]"
]
},
"execution_count": 155,
"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": []
}
],
"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": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}