1045 lines
414 KiB
Plaintext
1045 lines
414 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from opytex import texenv\n",
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"%matplotlib inline\n",
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"import matplotlib.pyplot as plt\n",
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"plt.style.use(\"seaborn-notebook\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Informations sur le devoir"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'classe': '313', 'date': '15 février 2016', 'titre': 'Brevet Blanc Février'}"
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]
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},
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"execution_count": 30,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ds_name = \"BB_16_02_15\"\n",
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"classe = \"313\"\n",
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"\n",
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"latex_info = {}\n",
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"latex_info['titre'] = \"Brevet Blanc Février\"\n",
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"latex_info['classe'] = \"313\"\n",
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"latex_info['date'] = \"15 février 2016\"\n",
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"latex_info"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Import et premiers traitements"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"notes = pd.ExcelFile(\"./../../../../notes/\"+classe+\".xlsx\")\n",
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"notes.sheet_names\n",
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"notes = notes.parse(ds_name)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"ds_name = \"Brevet blanc Fevrier\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Index(['Brevet blanc Fevrier', 'Présentation', 'Exercice 1',\n",
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" 'Comprendre le programme de calcul', 'Programme à l'envers',\n",
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" 'Calcul literral', 'Exercice 2', 'Construction', 'Pythagore',\n",
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" 'Choix proposition', 'Exercice 3', 'Exercice 4',\n",
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" 'Probabilité « normale »', 'Probabilité « changement »', '2 épreuves',\n",
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" 'Exercice 5', 'Divisibilité', 'PGCD', 'Réduction', 'Divisibilité',\n",
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" 'Utilisation du PGCD', 'Exercice 6', 'Extraire l'information',\n",
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" 'Argumentation', 'Résolution', 'Exercice 7', 'Lecture graphique',\n",
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" 'Moyenne', 'Total', 'Formule tableur (somme)',\n",
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" 'Formule tableur (moiyenne)'],\n",
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" dtype='object')"
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]
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},
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"execution_count": 33,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"notes.index"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"notes = notes.T"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"#notes = notes.drop('av_arrondi', axis=1)\n",
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"#notes = notes.drop('num_sujet', axis=1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"barem = notes[:1]\n",
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"notes = notes[1:]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Brevet blanc Fevrier</th>\n",
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|
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" <th>Présentation</th>\n",
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|
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" <th>Exercice 1</th>\n",
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" <th>Comprendre le programme de calcul</th>\n",
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" <th>Programme à l'envers</th>\n",
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" <th>Calcul literral</th>\n",
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" <th>Exercice 2</th>\n",
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" <th>Construction</th>\n",
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" <th>Pythagore</th>\n",
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" <th>Choix proposition</th>\n",
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" <th>...</th>\n",
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" <th>Exercice 6</th>\n",
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" <th>Extraire l'information</th>\n",
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" <th>Argumentation</th>\n",
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" <th>Résolution</th>\n",
|
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" <th>Exercice 7</th>\n",
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" <th>Lecture graphique</th>\n",
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" <th>Moyenne</th>\n",
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" <th>Total</th>\n",
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" <th>Formule tableur (somme)</th>\n",
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" <th>Formule tableur (moiyenne)</th>\n",
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" </tr>\n",
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" </thead>\n",
|
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" <tbody>\n",
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" <tr>\n",
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" <th>ABDALLAH Touraya</th>\n",
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" <td>15.0</td>\n",
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" <td>3.5</td>\n",
|
|||
|
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" <td>3.5</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
|
|||
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" <td>1.0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>...</td>\n",
|
|||
|
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" <td>0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>4.0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
|
|||
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" </tr>\n",
|
|||
|
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" <tr>\n",
|
|||
|
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" <th>ABDOU Mariam</th>\n",
|
|||
|
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" <td>31.0</td>\n",
|
|||
|
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" <td>4.0</td>\n",
|
|||
|
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" <td>4.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>4.0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>...</td>\n",
|
|||
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" <td>0</td>\n",
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|||
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" <td>NaN</td>\n",
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|||
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
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|||
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" <td>5.0</td>\n",
|
|||
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
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|||
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" <td>NaN</td>\n",
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|||
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" <td>NaN</td>\n",
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|||
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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|||
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" <th>ABTOIHI SAID Yasmina</th>\n",
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" <td>24.5</td>\n",
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|||
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" <td>3.5</td>\n",
|
|||
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" <td>4.0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>3.5</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
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|||
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" <td>NaN</td>\n",
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|||
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" <td>...</td>\n",
|
|||
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" <td>0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
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|||
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" <td>6.5</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>AHAMED Anssuifidine</th>\n",
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|||
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" <td>22.0</td>\n",
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|||
|
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" <td>3.5</td>\n",
|
|||
|
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" <td>5.0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>3.5</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>...</td>\n",
|
|||
|
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" <td>0</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>6.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
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" </tr>\n",
|
|||
|
|
" <tr>\n",
|
|||
|
|
" <th>AHAMED Issihaka</th>\n",
|
|||
|
|
" <td>23.0</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>3.5</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>5.0</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
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" <td>NaN</td>\n",
|
|||
|
|
" <td>NaN</td>\n",
|
|||
|
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" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
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"</table>\n",
|
|||
|
|
"<p>5 rows × 31 columns</p>\n",
|
|||
|
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"</div>"
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|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" Brevet blanc Fevrier Présentation Exercice 1 \\\n",
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|||
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"ABDALLAH Touraya 15.0 3.5 3.5 \n",
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|
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"ABDOU Mariam 31.0 4.0 4.5 \n",
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"ABTOIHI SAID Yasmina 24.5 3.5 4.0 \n",
|
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"AHAMED Anssuifidine 22.0 3.5 5.0 \n",
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"AHAMED Issihaka 23.0 3.0 2.0 \n",
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"\n",
|
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|
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" Comprendre le programme de calcul Programme à l'envers \\\n",
|
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|
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"ABDALLAH Touraya NaN NaN \n",
|
|||
|
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"ABDOU Mariam NaN NaN \n",
|
|||
|
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"ABTOIHI SAID Yasmina NaN NaN \n",
|
|||
|
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"AHAMED Anssuifidine NaN NaN \n",
|
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|
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"AHAMED Issihaka NaN NaN \n",
|
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"\n",
|
|||
|
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" Calcul literral Exercice 2 Construction Pythagore \\\n",
|
|||
|
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"ABDALLAH Touraya NaN 1.0 NaN NaN \n",
|
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|
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"ABDOU Mariam NaN 4.0 NaN NaN \n",
|
|||
|
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"ABTOIHI SAID Yasmina NaN 3.5 NaN NaN \n",
|
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"AHAMED Anssuifidine NaN 3.5 NaN NaN \n",
|
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"AHAMED Issihaka NaN 3.5 NaN NaN \n",
|
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"\n",
|
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" Choix proposition ... \\\n",
|
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|
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"ABDALLAH Touraya NaN ... \n",
|
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|
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"ABDOU Mariam NaN ... \n",
|
|||
|
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"ABTOIHI SAID Yasmina NaN ... \n",
|
|||
|
|
"AHAMED Anssuifidine NaN ... \n",
|
|||
|
|
"AHAMED Issihaka NaN ... \n",
|
|||
|
|
"\n",
|
|||
|
|
" Exercice 6 Extraire l'information Argumentation \\\n",
|
|||
|
|
"ABDALLAH Touraya 0 NaN NaN \n",
|
|||
|
|
"ABDOU Mariam 0 NaN NaN \n",
|
|||
|
|
"ABTOIHI SAID Yasmina 0 NaN NaN \n",
|
|||
|
|
"AHAMED Anssuifidine 0 NaN NaN \n",
|
|||
|
|
"AHAMED Issihaka 0 NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Résolution Exercice 7 Lecture graphique Moyenne \\\n",
|
|||
|
|
"ABDALLAH Touraya NaN 4.0 NaN NaN \n",
|
|||
|
|
"ABDOU Mariam NaN 5.0 NaN NaN \n",
|
|||
|
|
"ABTOIHI SAID Yasmina NaN 6.5 NaN NaN \n",
|
|||
|
|
"AHAMED Anssuifidine NaN 6.0 NaN NaN \n",
|
|||
|
|
"AHAMED Issihaka NaN 5.0 NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Total Formule tableur (somme) \\\n",
|
|||
|
|
"ABDALLAH Touraya NaN NaN \n",
|
|||
|
|
"ABDOU Mariam NaN NaN \n",
|
|||
|
|
"ABTOIHI SAID Yasmina NaN NaN \n",
|
|||
|
|
"AHAMED Anssuifidine NaN NaN \n",
|
|||
|
|
"AHAMED Issihaka NaN NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
" Formule tableur (moiyenne) \n",
|
|||
|
|
"ABDALLAH Touraya NaN \n",
|
|||
|
|
"ABDOU Mariam NaN \n",
|
|||
|
|
"ABTOIHI SAID Yasmina NaN \n",
|
|||
|
|
"AHAMED Anssuifidine NaN \n",
|
|||
|
|
"AHAMED Issihaka NaN \n",
|
|||
|
|
"\n",
|
|||
|
|
"[5 rows x 31 columns]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 37,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes.head()\n",
|
|||
|
|
"#barem"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## Supression des notes inutiles "
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 38,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes = notes[notes[ds_name].notnull()]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 39,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes = notes.astype(float)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"## Traitement des notes"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 40,
|
|||
|
|
"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": 40,
|
|||
|
|
"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": 41,
|
|||
|
|
"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": 41,
|
|||
|
|
"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": 42,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"autres_notes = [\"Présentation\"]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 43,
|
|||
|
|
"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": 44,
|
|||
|
|
"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": 44,
|
|||
|
|
"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": 45,
|
|||
|
|
"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": 46,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
|
|||
|
|
"#notes"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 19,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"ename": "ValueError",
|
|||
|
|
"evalue": "Columns must be same length as key",
|
|||
|
|
"output_type": "error",
|
|||
|
|
"traceback": [
|
|||
|
|
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
|||
|
|
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
|
|||
|
|
"\u001b[1;32m<ipython-input-19-fe35b34416df>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0meleves\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\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[0meleves\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0msous_exo\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0msous_exo\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapplymap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtoRepVal\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/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__setitem__\u001b[1;34m(self, key, value)\u001b[0m\n\u001b[0;32m 2292\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2293\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mIndex\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-> 2294\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_setitem_array\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2295\u001b[0m \u001b[1;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2296\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_setitem_frame\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
|||
|
|
"\u001b[1;32m/home/lafrite/.virtualenvs/enseignement/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_setitem_array\u001b[1;34m(self, key, value)\u001b[0m\n\u001b[0;32m 2316\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2317\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2318\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Columns must be same length as key'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2319\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mk2\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2320\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk1\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk2\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
|
|||
|
|
"\u001b[1;31mValueError\u001b[0m: Columns must be same length as key"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"eleves = notes.copy()\n",
|
|||
|
|
"eleves[sous_exo] = notes[sous_exo].applymap(toRepVal)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 47,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"31"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 47,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"len(notes.T.index)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {},
|
|||
|
|
"source": [
|
|||
|
|
"# Preparation du fichier .tex"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 57,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"#eleves"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
|
|||
|
|
"with open(\"./bilan\"+classe+\".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": 48,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"count 28.000000\n",
|
|||
|
|
"mean 23.285714\n",
|
|||
|
|
"std 5.583422\n",
|
|||
|
|
"min 15.000000\n",
|
|||
|
|
"25% 18.625000\n",
|
|||
|
|
"50% 23.250000\n",
|
|||
|
|
"75% 26.125000\n",
|
|||
|
|
"max 37.500000\n",
|
|||
|
|
"Name: Brevet blanc Fevrier, dtype: float64"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 48,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes[ds_name].describe()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 49,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.text.Text at 0x7f2f9d7fe208>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 49,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA7cAAAG5CAYAAABV8cNaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJr++ZNeb/PqS3fwobgE
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7f2f9d841128>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"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": 50,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x7f2f9d79ccf8>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 50,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA78AAAGrCAYAAAAIOCA+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzeX5Z5/HaDBy9c5V9p3
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7f2f9d7e12e8>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"# Normalisation des notes de chaque exo\n",
|
|||
|
|
"notes_exo_norm = notes[list_exo] / barem[list_exo].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": 55,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA6AAAAHsCAYAAADMwMCPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nudDMJjLWdUBzrzSBY/5
|
|||
|
|
"text/plain": [
|
|||
|
|
"<matplotlib.figure.Figure at 0x7f2f9c210a20>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"ax = notes[list_exo+[\"Présentation\"]].hist(figsize = (16,8))"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 65,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"BOINA HASSANI Nahimi 0.0\n",
|
|||
|
|
"ABDALLAH Touraya 0.5\n",
|
|||
|
|
"HALIBOU Nafilati 0.5\n",
|
|||
|
|
"HOUMADI Himida 0.5\n",
|
|||
|
|
"IBRAHIM Laoura 0.5\n",
|
|||
|
|
"MOENY MOKO Nadjma 0.5\n",
|
|||
|
|
"AHMED ABDOU El-Karim 1.0\n",
|
|||
|
|
"BACO ABDALLAH Moustadirane 1.0\n",
|
|||
|
|
"HOUMADI Antufati 1.0\n",
|
|||
|
|
"Name: Exercice 4, dtype: float64"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 65,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes[notes[\"Exercice 4\"] < 1.5][\"Exercice 4\"].sort_values()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 66,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"text/plain": [
|
|||
|
|
"YOUSSOUF Asma 0.0\n",
|
|||
|
|
"AHMED ABDOU El-Karim 0.5\n",
|
|||
|
|
"IBRAHIM Laoura 0.5\n",
|
|||
|
|
"ABDALLAH Touraya 1.5\n",
|
|||
|
|
"AHAMED Anssuifidine 1.5\n",
|
|||
|
|
"BOINA HASSANI Nahimi 1.5\n",
|
|||
|
|
"HALIBOU Nafilati 1.5\n",
|
|||
|
|
"MOENY MOKO Nadjma 1.5\n",
|
|||
|
|
"ANLI Koudoussia 2.0\n",
|
|||
|
|
"HOUMADI Himida 2.5\n",
|
|||
|
|
"HOUMADI ABDALLAH Abdallah 2.5\n",
|
|||
|
|
"DJADAR Ifrah 3.0\n",
|
|||
|
|
"HOUMADI Antufati 3.0\n",
|
|||
|
|
"Name: Exercice 5, dtype: float64"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 66,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"notes[notes[\"Exercice 5\"] < 3.5][\"Exercice 5\"].sort_values()"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 53,
|
|||
|
|
"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>Comprendre le programme de calcul</th>\n",
|
|||
|
|
" <th>Programme à l'envers</th>\n",
|
|||
|
|
" <th>Calcul literral</th>\n",
|
|||
|
|
" <th>Construction</th>\n",
|
|||
|
|
" <th>Pythagore</th>\n",
|
|||
|
|
" <th>Choix proposition</th>\n",
|
|||
|
|
" <th>Probabilité « normale »</th>\n",
|
|||
|
|
" <th>Probabilité « changement »</th>\n",
|
|||
|
|
" <th>2 épreuves</th>\n",
|
|||
|
|
" <th>Divisibilité</th>\n",
|
|||
|
|
" <th>...</th>\n",
|
|||
|
|
" <th>Divisibilité</th>\n",
|
|||
|
|
" <th>Utilisation du PGCD</th>\n",
|
|||
|
|
" <th>Extraire l'information</th>\n",
|
|||
|
|
" <th>Argumentation</th>\n",
|
|||
|
|
" <th>Résolution</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>count</th>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>...</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" <td>0</td>\n",
|
|||
|
|
" </tr>\n",
|
|||
|
|
" </tbody>\n",
|
|||
|
|
"</table>\n",
|
|||
|
|
"<p>1 rows × 24 columns</p>\n",
|
|||
|
|
"</div>"
|
|||
|
|
],
|
|||
|
|
"text/plain": [
|
|||
|
|
" Comprendre le programme de calcul Programme à l'envers \\\n",
|
|||
|
|
"count 0 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Calcul literral Construction Pythagore Choix proposition \\\n",
|
|||
|
|
"count 0 0 0 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Probabilité « normale » Probabilité « changement » 2 épreuves \\\n",
|
|||
|
|
"count 0 0 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Divisibilité ... Divisibilité \\\n",
|
|||
|
|
"count 0 ... 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Utilisation du PGCD Extraire l'information Argumentation Résolution \\\n",
|
|||
|
|
"count 0 0 0 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Lecture graphique Moyenne Total Formule tableur (somme) \\\n",
|
|||
|
|
"count 0 0 0 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
" Formule tableur (moiyenne) \n",
|
|||
|
|
"count 0 \n",
|
|||
|
|
"\n",
|
|||
|
|
"[1 rows x 24 columns]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"execution_count": 53,
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "execute_result"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"# J'aimerai récupérer le nom des questions qui ont été le moins répondus\n",
|
|||
|
|
"notes_analysis[:1]"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "markdown",
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": true
|
|||
|
|
},
|
|||
|
|
"source": [
|
|||
|
|
"## Bilan à remplir"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 21,
|
|||
|
|
"metadata": {
|
|||
|
|
"collapsed": false
|
|||
|
|
},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
|
|||
|
|
"with open(\"./fill_bilan.tex\",\"w\") as f:\n",
|
|||
|
|
" f.write(bilan.render(eleves = [(\"Nom\",, barem = barem, ds_name = ds_name, latex_info = latex_info, nbr_questions = len(barem.T)))"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"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
|
|||
|
|
}
|