817 lines
431 KiB
Plaintext
817 lines
431 KiB
Plaintext
|
{
|
|||
|
|
"cells": [
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 1,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"import pandas as pd\n",
|
|||
|
|
"from opytex import texenv\n",
|
|||
|
|
"%matplotlib inline\n",
|
|||
|
|
"import matplotlib.pyplot as plt\n",
|
|||
|
|
"plt.style.use(\"seaborn-notebook\")"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Informations sur le devoir"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 2,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"{'classe': '309', 'date': '15 février 2016', 'titre': 'Brevet Blanc Février'}"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 2,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"ds_name = \"BB_16_02_15\"\n",
|
|||
|
|
"classe = \"309\"\n",
|
|||
|
|
"\n",
|
|||
|
|
"latex_info = {}\n",
|
|||
|
|
"latex_info['titre'] = \"Brevet Blanc Février\"\n",
|
|||
|
|
"latex_info['classe'] = \"309\"\n",
|
|||
|
|
"latex_info['date'] = \"15 février 2016\"\n",
|
|||
|
|
"latex_info"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Import et premiers traitements"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 3,
|
|||
|
|
"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": 4,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"ds_name = \"Brevet blanc Fevrier\""
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 5,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false,
|
|||
|
|
"scrolled": true
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Index(['Brevet blanc Fevrier', 'Présentation', 'Exercice 1',\n",
|
|||
|
|
" 'Comprendre le programme de calcul', 'Programme à l'envers',\n",
|
|||
|
|
" 'Calcul literral', 'Exercice 2', 'Construction', 'Pythagore',\n",
|
|||
|
|
" 'Choix proposition', 'Exercice 3', 'Exercice 4',\n",
|
|||
|
|
" 'Probabilité « normale »', 'Probabilité « changement »', '2 épreuves',\n",
|
|||
|
|
" 'Exercice 5', 'Divisibilité', 'PGCD', 'Réduction', 'Divisibilité',\n",
|
|||
|
|
" 'Utilisation du PGCD', 'Exercice 6', 'Extraire l'information',\n",
|
|||
|
|
" 'Argumentation', 'Résolution', 'Exercice 7', 'Lecture graphique',\n",
|
|||
|
|
" 'Moyenne', 'Total', 'Formule tableur (somme)',\n",
|
|||
|
|
" 'Formule tableur (moiyenne)'],\n",
|
|||
|
|
" dtype='object')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 5,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes.index"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 6,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes = notes.T"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 7,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"#notes = notes.drop('av_arrondi', axis=1)\n",
|
|||
|
|
"#notes = notes.drop('num_sujet', axis=1)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 8,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"barem = notes[:1]\n",
|
|||
|
|
"notes = notes[1:]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/html": [
|
|||
|
|
"<div>\n",
|
|||
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|||
|
|
" <thead>\n",
|
|||
|
|
" <tr style=\"text-align: right;\">\n",
|
|||
|
|
" <th></th>\n",
|
|||
|
|
" <th>Brevet blanc Fevrier</th>\n",
|
|||
|
|
" <th>Présentation</th>\n",
|
|||
|
|
" <th>Exercice 1</th>\n",
|
|||
|
|
" <th>Comprendre le programme de calcul</th>\n",
|
|||
|
|
" <th>Programme à l'envers</th>\n",
|
|||
|
|
" <th>Calcul literral</th>\n",
|
|||
|
|
" <th>Exercice 2</th>\n",
|
|||
|
|
" <th>Construction</th>\n",
|
|||
|
|
" <th>Pythagore</th>\n",
|
|||
|
|
" <th>Choix proposition</th>\n",
|
|||
|
|
" <th>...</th>\n",
|
|||
|
|
" <th>Exercice 6</th>\n",
|
|||
|
|
" <th>Extraire l'information</th>\n",
|
|||
|
|
" <th>Argumentation</th>\n",
|
|||
|
|
" <th>Résolution</th>\n",
|
|||
|
|
" <th>Exercice 7</th>\n",
|
|||
|
|
" <th>Lecture graphique</th>\n",
|
|||
|
|
" <th>Moyenne</th>\n",
|
|||
|
|
" <th>Total</th>\n",
|
|||
|
|
" <th>Formule tableur (somme)</th>\n",
|
|||
|
|
" <th>Formule tableur (moiyenne)</th>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </thead>\n",
|
|||
|
|
" <tbody>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>ABDOU Farida</th>\n",
|
|||
|
|
" <td>16.0</td>\n",
|
|||
|
|
" <td>2.5</td>\n",
|
|||
|
|
" <td>1.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>0.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>3.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>ABOU BACAR Djaha</th>\n",
|
|||
|
|
" <td>22.0</td>\n",
|
|||
|
|
" <td>2.5</td>\n",
|
|||
|
|
" <td>3.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>3.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>3.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>AHAMADA Nabaouya</th>\n",
|
|||
|
|
" <td>16.5</td>\n",
|
|||
|
|
" <td>3.0</td>\n",
|
|||
|
|
" <td>2.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>5.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>AHAMADI Faina</th>\n",
|
|||
|
|
" <td>5.0</td>\n",
|
|||
|
|
" <td>3.0</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>0.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>ALI Mardhuia</th>\n",
|
|||
|
|
" <td>23.0</td>\n",
|
|||
|
|
" <td>4.0</td>\n",
|
|||
|
|
" <td>2.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>3.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>1.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>4.0</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>5 rows × 31 columns</p>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" Brevet blanc Fevrier Présentation Exercice 1 \\\n",
|
|||
|
|
"ABDOU Farida 16.0 2.5 1.5 \n",
|
|||
|
|
"ABOU BACAR Djaha 22.0 2.5 3.0 \n",
|
|||
|
|
"AHAMADA Nabaouya 16.5 3.0 2.0 \n",
|
|||
|
|
"AHAMADI Faina 5.0 3.0 0.0 \n",
|
|||
|
|
"ALI Mardhuia 23.0 4.0 2.5 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Comprendre le programme de calcul Programme à l'envers \\\n",
|
|||
|
|
"ABDOU Farida NaN NaN \n",
|
|||
|
|
"ABOU BACAR Djaha NaN NaN \n",
|
|||
|
|
"AHAMADA Nabaouya NaN NaN \n",
|
|||
|
|
"AHAMADI Faina NaN NaN \n",
|
|||
|
|
"ALI Mardhuia NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Calcul literral Exercice 2 Construction Pythagore \\\n",
|
|||
|
|
"ABDOU Farida NaN 0.5 NaN NaN \n",
|
|||
|
|
"ABOU BACAR Djaha NaN 3.5 NaN NaN \n",
|
|||
|
|
"AHAMADA Nabaouya NaN 0.0 NaN NaN \n",
|
|||
|
|
"AHAMADI Faina NaN 0.0 NaN NaN \n",
|
|||
|
|
"ALI Mardhuia NaN 3.5 NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Choix proposition ... Exercice 6 \\\n",
|
|||
|
|
"ABDOU Farida NaN ... 0.0 \n",
|
|||
|
|
"ABOU BACAR Djaha NaN ... 0.0 \n",
|
|||
|
|
"AHAMADA Nabaouya NaN ... 0.5 \n",
|
|||
|
|
"AHAMADI Faina NaN ... 0.0 \n",
|
|||
|
|
"ALI Mardhuia NaN ... 1.5 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Extraire l'information Argumentation Résolution \\\n",
|
|||
|
|
"ABDOU Farida NaN NaN NaN \n",
|
|||
|
|
"ABOU BACAR Djaha NaN NaN NaN \n",
|
|||
|
|
"AHAMADA Nabaouya NaN NaN NaN \n",
|
|||
|
|
"AHAMADI Faina NaN NaN NaN \n",
|
|||
|
|
"ALI Mardhuia NaN NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Exercice 7 Lecture graphique Moyenne Total \\\n",
|
|||
|
|
"ABDOU Farida 3.5 NaN NaN NaN \n",
|
|||
|
|
"ABOU BACAR Djaha 3.0 NaN NaN NaN \n",
|
|||
|
|
"AHAMADA Nabaouya 5.5 NaN NaN NaN \n",
|
|||
|
|
"AHAMADI Faina 0.0 NaN NaN NaN \n",
|
|||
|
|
"ALI Mardhuia 4.0 NaN NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Formule tableur (somme) Formule tableur (moiyenne) \n",
|
|||
|
|
"ABDOU Farida NaN NaN \n",
|
|||
|
|
"ABOU BACAR Djaha NaN NaN \n",
|
|||
|
|
"AHAMADA Nabaouya NaN NaN \n",
|
|||
|
|
"AHAMADI Faina NaN NaN \n",
|
|||
|
|
"ALI Mardhuia NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
"[5 rows x 31 columns]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes.head()\n",
|
|||
|
|
"#barem"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## Supression des notes inutiles "
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 10,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes = notes[notes[ds_name].notnull()]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 11,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes = notes.astype(float)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## Traitement des notes"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 12,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false,
|
|||
|
|
"scrolled": true
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Index(['Brevet blanc Fevrier', 'Présentation', 'Exercice 1',\n",
|
|||
|
|
" 'Comprendre le programme de calcul', 'Programme à l'envers',\n",
|
|||
|
|
" 'Calcul literral', 'Exercice 2', 'Construction', 'Pythagore',\n",
|
|||
|
|
" 'Choix proposition', 'Exercice 3', 'Exercice 4',\n",
|
|||
|
|
" 'Probabilité « normale »', 'Probabilité « changement »', '2 épreuves',\n",
|
|||
|
|
" 'Exercice 5', 'Divisibilité', 'PGCD', 'Réduction', 'Divisibilité',\n",
|
|||
|
|
" 'Utilisation du PGCD', 'Exercice 6', 'Extraire l'information',\n",
|
|||
|
|
" 'Argumentation', 'Résolution', 'Exercice 7', 'Lecture graphique',\n",
|
|||
|
|
" 'Moyenne', 'Total', 'Formule tableur (somme)',\n",
|
|||
|
|
" 'Formule tableur (moiyenne)'],\n",
|
|||
|
|
" dtype='object')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 12,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes.T.index"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"Liste des exercices (non noté en compétences)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 13,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"['Exercice 1',\n",
|
|||
|
|
" 'Exercice 2',\n",
|
|||
|
|
" 'Exercice 3',\n",
|
|||
|
|
" 'Exercice 4',\n",
|
|||
|
|
" 'Exercice 5',\n",
|
|||
|
|
" 'Exercice 6',\n",
|
|||
|
|
" 'Exercice 7']"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 13,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"list_exo = [\"Exercice \"+str(i+1) for i in range(7)]\n",
|
|||
|
|
"list_exo"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"Les autres types de notes (presentation, malus...) qui ne sont pas en compétences"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 14,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"autres_notes = [\"Présentation\"]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 15,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes[list_exo] = notes[list_exo].applymap(lambda x:round(x,2))\n",
|
|||
|
|
"#notes[list_exo]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"Les éléments avec notes et les éléments par compétences (sous_exo)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 16,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false,
|
|||
|
|
"scrolled": true
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"['Comprendre le programme de calcul',\n",
|
|||
|
|
" \"Programme à l'envers\",\n",
|
|||
|
|
" 'Calcul literral',\n",
|
|||
|
|
" 'Construction',\n",
|
|||
|
|
" 'Pythagore',\n",
|
|||
|
|
" 'Choix proposition',\n",
|
|||
|
|
" 'Probabilité «\\xa0normale\\xa0»',\n",
|
|||
|
|
" 'Probabilité «\\xa0changement\\xa0»',\n",
|
|||
|
|
" '2 épreuves',\n",
|
|||
|
|
" 'Divisibilité',\n",
|
|||
|
|
" 'PGCD',\n",
|
|||
|
|
" 'Réduction',\n",
|
|||
|
|
" 'Divisibilité',\n",
|
|||
|
|
" 'Utilisation du PGCD',\n",
|
|||
|
|
" \"Extraire l'information\",\n",
|
|||
|
|
" 'Argumentation',\n",
|
|||
|
|
" 'Résolution',\n",
|
|||
|
|
" 'Lecture graphique',\n",
|
|||
|
|
" 'Moyenne',\n",
|
|||
|
|
" 'Total',\n",
|
|||
|
|
" 'Formule tableur (somme)',\n",
|
|||
|
|
" 'Formule tableur (moiyenne)']"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 16,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"item_avec_note = list_exo + [ds_name] + autres_notes\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": 17,
|
|||
|
|
"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": 18,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
|
|||
|
|
"#notes"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 20,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"31"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 20,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"len(notes.T.index)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Un peu de statistiques"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"count 30.000000\n",
|
|||
|
|
"mean 16.616667\n",
|
|||
|
|
"std 6.729609\n",
|
|||
|
|
"min 5.000000\n",
|
|||
|
|
"25% 11.500000\n",
|
|||
|
|
"50% 16.000000\n",
|
|||
|
|
"75% 21.375000\n",
|
|||
|
|
"max 29.500000\n",
|
|||
|
|
"Name: Brevet blanc Fevrier, dtype: float64"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes[ds_name].describe()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 22,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.text.Text at 0x7fc141e23550>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 22,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA60AAAG5CAYAAABlfdJ7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XuwbndZH/Dvk0QucpNGxUpqwNgE0VJAoSCd5qCOUHTA\nXhg1UqtVeyORFGWQdiAHWjvtH2CdE53OKFKqoFbqBawUL5hjlQEiIVwayKHHoEaFOmkopc5YPPz6\nx353ziG8Ode19l7PXp/PzJm13332Xu9vv9937XOetd7v3jXGCAAAACzRRfu9AAAAALgvhlYAAAAW\ny9AKAADAYhlaAQAAWCxDKwAAAItlaAUAAGCxLpn7Dqrqw0n+d5JPJfnkGOPJc98nAAAAB8PsQ2t2\nhtVDY4y79+C+AAAAOED24uXBtUf3AwAAwAGzF8PkSPKWqrq5qr57D+4PAACAA2IvXh78VWOMj1TV\n5yX51ar6wBjjt+7rg6tq7MGaAAAA2AdjjDqXj599aB1jfGSz/ZOq+vkkT05yn0Pr5mPnXhYzqCrZ\nNSa/vubK7tixY7nqqiS5cuo95/bbkyuvnHq/PTn2epNfX7LrTX59VZ3TvJpk5pcHV9VnV9WDN28/\nKMnXJXn/nPcJAADAwTH3ldZHJPn5zUt+L0nyujHGr8x8nwAAABwQsw6tY4w7kjx+zvtgOW644Yb9\nXgIXQH59ya43+fUmv75k15v81qWW9lrwqhpLWxPAGum0AgBT2/SRz6nY6venMpnDhw/v9xK4APLr\nS3a9ya83+fUlu97kty6GVgAAABbLy4MB2MrLgwGAqXl5MAAAAAeKoZXJ6Bb0Jr++ZNeb/HqTX1+y\n601+62JoBQAAYLF0WgHYSqcVAJiaTisAAAAHiqGVyegW9Ca/vmTXm/x6k19fsutNfutiaAUAAGCx\ndFoB2EqnFQCYmk4rAAAAB4qhlcnoFvQmv75k15v8epNfX7LrTX7rYmgFAABgsXRaAdhKpxUAmJpO\nKwAAAAeKoZXJ6Bb0Jr++ZNeb/HqTX1+y601+62JoBQAAYLF0WgHYSqcVAJiaTisAAAAHiqGVyegW\n9Ca/vmTXm/x6k19fsutNfutiaAUAAGCxdFoB2EqnFQCYmk4rAAAAB4qhlcnoFvQmv75k15v8epNf\nX7LrTX7rYmgFAABgsXRaAdhKpxUAmJpOKwAAAAeKoZXJ6Bb0Jr++ZNeb/HqTX1+y601+62JoBQAA\nYLF0WgHYSqcVAJiaTisAAAAHiqGVyegW9Ca/vmTXm/x6k19fsutNfutiaAUAAGCxdFoB2EqnFQCY\nmk4rAAAAB4qhlcnoFvQmv75k15v8epNfX7LrTX7rYmgFAABgsXRaAdhKpxUAmJpOKwAAAAeKoZXJ\n6Bb0Jr++ZNeb/HqTX1+y601+62JoBQAAYLF0WgHYSqcVAJiaTisAAAAHiqGVyegW9Ca/vmTXm/x6\nk19fsutNfutiaAUAAGCxdFoB2EqnFQCYmk4rAAAAB4qhlcnoFvQmv75k15v8epNfX7LrTX7rYmgF\nAABgsXRaAdhKpxUAmJpOKwAAAAeKoZXJ6Bb0Jr++ZNeb/HqTX1+y601+62JoBQAAYLF0WgHYSqcV\nAJiaTisAAAAHiqGVyegW9Ca/vmTXm/x6k19fsutNfutiaAUAAGCxdFoB2EqnFQCYmk4rAAAAB4qh\nlcnoFvQmv75k15v8epNfX7LrTX7rYmgFAABgsXRaAdhKpxUAmJpOKwAAAAeKoZXJ6Bb0Jr++ZNeb\n/HqTX1+y601+62JoBQAAYLF0WgHYSqcVAJiaTisAAAAHyp4MrVV1UVXdUlVv3Iv7Y3/oFvQmv75k\n15v8epNfX7LrTX7rsldXWl+Q5LY9ui8AAAAOiNk7rVV1WZLXJPmBJC8cYzz7DB+v0wqwADqtAMDU\nltpp/cEkL0piEgUAAOCcXDLnzqvq65N8dIxxa1UdSnJWE3XVyQ+7+uqrc+jQoXtet2673O2p3YIl\nrMdWfmvZ7r499X6PHDmy2fvu9vBE22smXWf37e7b+70O2/Pb7r693+uwPfftTTfdlJtuumnf12Er\nv4O+PXToUI4ePZoLMevLg6vqXyd5XpI/T/LAJA9J8nNjjG87zed4eXBThw8fvufJST/y62uu7Lw8\neG849nqTX1+y601+fZ3Py4P37Pe0VtXVSb5XpxWgB0MrADC1pXZaAQAA4Lzs2dA6xjh6pqus9OYl\nGr3Jry/Z9Sa/3uTXl+x6k9+6uNIKAADAYu1Zp/Vs6bQCLINOKwAwNZ1WAAAADhRDK5PRLehNfn3J\nrjf59Sa/vmTXm/zWxdAKAADAYum0ArCVTisAMDWdVgAAAA4UQyuT0S3oTX59ya43+fUmv75k15v8\n1sXQCgAAwGLptAKwlU4rADA1nVYAAAAOFEMrk9Et6E1+fcmuN/n1Jr++ZNeb/NbF0AoAAMBi6bQC\nsJVOKwAwNZ1WAAAADhRDK5PRLehNfn3Jrjf59Sa/vmTXm/zWxdAKAADAYum0ArCVTisAMDWdVgAA\nAA4UQyuT0S3oTX59ya43+fUmv75k15v81sXQCgAAwGLptAKwlU4rADA1nVYAAAAOFEMrk9Et6E1+\nfcmuN/n1Jr++ZNeb/NbF0AoAAMBi6bQCsJVOKwAwNZ1WAAAADhRDK5PRLehNfn3Jrjf59Sa/vmTX\nm/zWxdAKAADAYum0ArCVTisAMDWdVgAAAA4UQyuT0S3oTX59ya43+fUmv75k15v81sXQCgAAwGLp\ntAKwlU4rADA1nVYAAAAOFEMrk9Et6E1+fcmuN/n1Jr++ZNeb/NbF0AoAAMBi6bQCsJVOKwAwNZ1W\nAAAADhRDK5PRLehNfn3Jrjf59Sa/vmTXm/zWxdAKAADAYum0ArCVTisAMDWdVgAAAA4UQyuT0S3o\nTX59ya43+fUmv75k15v81sXQCgAAwGLptAKwlU4rADA1nVYAAAAOFEMrk9Et6E1+fcmuN/n1Jr++\nZNeb/NbF0AoAAMBi6bQCsJVOKwAwNZ1WAAAADhRDK5PRLehNfn3Jrjf59Sa/vmTXm/zWxdAKAADA\nYum0ArCVTisAMDWdVgAAAA4UQyuT0S3oTX59ya43+fUmv75k15v81sXQCgAAwGLptAKwlU4rADA1\nnVYAAAAOFEMrk9Et6E1+fcmuN/n1Jr++ZNeb/NbF0AoAAMBi6bQCsJVOKwAwNZ1WAAAADhRDK5PR\nLehNfn3Jrjf59Sa/vmTXm/zWxdAKAADAYum0ArCVTisAMDWdVgAAAA4UQyuT0S3oTX59ya43+fUm\nv75k15v81sXQCgAAwGLN2mmtqvsn+c0k90tySZI3jDFefobP0WkFWACdVgBgaufTab1krsUkyRjj\nz6rq6WOMP62qi5P8dlW9eYzxzjnvFwAAgINh9pcHjzH+dPPm/bMzJLuMekDpFvQmv75k15v8epNf\nX7LrTX7rMuuV1iSpqouSvCvJFUl+eIxx89z3CWfjxIkTOX78+Cz7vuKKK3LxxRfPsm/m5XkBALAs\nsw+tY4xPJXlCVT00yS9U1WPHGLed7nOqTr7E+eqrr86hQ4fuOZtiu9zt7p/9XsfZbo8fP56rrnpF\nkocnuS47jmy2F3L77tx++8ty5ZVXLuLrPNttt/zm2t5111258cZvSPLoTPN82L19R6699kguvfTS\nRXydZ7M9cmR3/bvbwxNtr9nXr8vW1tZ2d7trv9dhe37bXfu9DtvTbw8dOpSjR4/mQsz6g5g+486q\nXpbkE2OMV53mY/wgJvaEHzLDNp4XJ3ksAICpnc8PYpq101pVn1tVD9u8/cAkX5vkg3PeJ/vn3me9\n6EV+fcmuN/n1Jr++ZNeb/Nblkpn3/xeTvHbTa70oyc+MMX555vsEAADggNjTlwefDS8PZq946SPb\neF6c5LEAAKa2uJcHAwAAwIUwtDIZ3YLe5NeX7HqTX2/y60t2vclvXQytAAAALJZOK6ulr8c2nhcn\neSwAgKnptAIAAHCgGFq
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7fc141f5d908>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"#notes_seules = notes[ds_name]\n",
|
|||
|
|
"ax = notes[ds_name].hist(bins = barem[ds_name][0], range=(0,barem[ds_name][0]), figsize = (16,7), )\n",
|
|||
|
|
"ax.set_xlabel(\"Notes\")\n",
|
|||
|
|
"ax.set_ylabel(\"Effectif\")\n",
|
|||
|
|
"#notes_seules.hist()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 24,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x7fc12ae5fa20>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 24,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA8QAAAGrCAYAAAAGkV5RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n42WbjC3ehuyQ8RX78BZ
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7fc12b1549e8>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"# Normalisation des notes de chaque exo\n",
|
|||
|
|
"notes_exo_norm = notes[list_exo + autres_notes] / barem[list_exo + autres_notes].values[0,:]\n",
|
|||
|
|
"#notes_exo_norm\n",
|
|||
|
|
"ax = notes_exo_norm.T.plot(color = \"gray\", legend = False, figsize = (16, 7))\n",
|
|||
|
|
"d_norm = notes_exo_norm.describe()\n",
|
|||
|
|
"d_norm.T[[\"min\", \"25%\", \"50%\", \"75%\", \"max\"]].plot(ax=ax, kind=\"area\", stacked = False, alpha=.1)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 25,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA6YAAAHsCAYAAADB3rDIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWk/Xcg1zoQ9MzczMzKw
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7fc12b1a94a8>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"ax = notes[list_exo+autres_notes].hist(figsize = (16,8))"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 30,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"Index(['AHAMADI Faina', 'ALI Mardhuia', 'ALSENE ALI MADI Stela',\n",
|
|||
|
|
" 'ANLI Emeline', 'CHANFI Nadhrati', 'HAMZA Samianti',\n",
|
|||
|
|
" 'HOUMADI Mouslimati', 'HOUMADI Dhoirfia', 'LOUTOUFI Nachima',\n",
|
|||
|
|
" 'MALIDE El-Anzize', 'SOILIHI Soifia', 'SOUFIANI Laila',\n",
|
|||
|
|
" 'YOUSSOUF Sitirati'],\n",
|
|||
|
|
" dtype='object')"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 30,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes[notes[\"Exercice 4\"] < 1].index"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"source": [
|
|||
|
|
"## Bilan à remplir"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"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": "3.5.1"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 0
|
|||
|
|
}
|