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2015-2016/5e/DS/DS_16_02_08/Bilan.ipynb
Benjamin Bertrand 25a2e9a4a7 import work from year 2015-2016
2017-06-16 09:48:54 +03:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 41,
"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": 42,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"{'classe': '510', 'date': '8 février 2016', 'titre': 'DS 5'}"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds_name = \"DS_16_02_08\"\n",
"classe = \"510\"\n",
"\n",
"latex_info = {}\n",
"latex_info['titre'] = \"DS 5\"\n",
"latex_info['classe'] = \"510\"\n",
"latex_info['date'] = \"8 février 2016\"\n",
"latex_info"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import et premiers traitements"
]
},
{
"cell_type": "code",
"execution_count": 43,
"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": 44,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Index(['DS_16_02_08', 'Exercice 1', 'Opération 1', 'Opération 2', 'Exercice 2',\n",
" 'Durée', 'Horaire', 'Exercice 3', 'Distance', 'Temps',\n",
" 'Distance (fraction)', 'Exercice 4', 'nbr virgule', 'Dixieme 1',\n",
" 'Dixieme 2', 'Cinquième', 'Demi', 'Exercice 5', 'Symétrie axiale',\n",
" 'Symétrie centrale', 'Codage', 'Précision'],\n",
" dtype='object')"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes.index"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"notes = notes.T"
]
},
{
"cell_type": "code",
"execution_count": 46,
"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": 47,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"barem = notes[:1]\n",
"notes = notes[1:]"
]
},
{
"cell_type": "code",
"execution_count": 48,
"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>DS_16_02_08</th>\n",
" <th>Exercice 1</th>\n",
" <th>Opération 1</th>\n",
" <th>Opération 2</th>\n",
" <th>Exercice 2</th>\n",
" <th>Durée</th>\n",
" <th>Horaire</th>\n",
" <th>Exercice 3</th>\n",
" <th>Distance</th>\n",
" <th>Temps</th>\n",
" <th>...</th>\n",
" <th>nbr virgule</th>\n",
" <th>Dixieme 1</th>\n",
" <th>Dixieme 2</th>\n",
" <th>Cinquième</th>\n",
" <th>Demi</th>\n",
" <th>Exercice 5</th>\n",
" <th>Symétrie axiale</th>\n",
" <th>Symétrie centrale</th>\n",
" <th>Codage</th>\n",
" <th>Précision</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>7.5</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>2.5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0.666667</td>\n",
" <td>0</td>\n",
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" <td>0</td>\n",
" <td>2</td>\n",
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" <td>0</td>\n",
" <td>0</td>\n",
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" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>2.0</td>\n",
" <td>0.666667</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.000000</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>15.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.333333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>9.5</td>\n",
" <td>3.333333</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>2</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>13.0</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2.0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.333333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>11.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>3.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>16.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>13.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.333333</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>2.166667</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>6.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>2.500000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>9.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.333333</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.166667</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>20.0</td>\n",
" <td>4.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>18.0</td>\n",
" <td>2.666667</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.333333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>11.5</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.666667</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>5.5</td>\n",
" <td>1.333333</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.333333</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>10.0</td>\n",
" <td>2.000000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.000000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>9.5</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1.666667</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.500000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>15.5</td>\n",
" <td>3.333333</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2.000000</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>5.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>8.0</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>0.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2.166667</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>7.0</td>\n",
" <td>2.666667</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>1.666667</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>14.5</td>\n",
" <td>2.000000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2.333333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>4.333333</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>9.0</td>\n",
" <td>2.000000</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.000000</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3.833333</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>5.5</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0.000000</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>NaN</td>\n",
" <td>2.166667</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>4.5</td>\n",
" <td>1.333333</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.333333</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.666667</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>17.5</td>\n",
" <td>3.333333</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>4.000000</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>5.0</td>\n",
" <td>0.666667</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1.333333</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2.000000</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>5.5</td>\n",
" <td>4.000000</td>\n",
" <td>3</td>\n",
" <td>3</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>0</td>\n",
" <td>...</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.500000</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>27 rows × 22 columns</p>\n",
"</div>"
],
"text/plain": [
" DS_16_02_08 Exercice 1 Opération 1 Opération 2 \\\n",
"ABDOU ALI Nassim 7.5 2.666667 3 1 \n",
"ABDOUL-KADER Toura 2.0 0.666667 0 1 \n",
"AHAMADI Djelane 15.0 2.666667 3 1 \n",
"AHMED Laine 9.5 3.333333 3 2 \n",
"AHMED Hamza 13.0 2.000000 2 1 \n",
"AHMED Aicha 11.0 2.666667 3 1 \n",
"ALI Naima 16.0 2.666667 3 1 \n",
"ANSSURDINE Zaidou NaN 0.000000 NaN NaN \n",
"ARBABI Idiamine 13.0 2.666667 3 1 \n",
"ATTOUMANI Mtahida 6.0 2.666667 3 1 \n",
"BACAR Natacha 9.0 2.666667 3 1 \n",
"BACAR Musbahou 20.0 4.000000 3 3 \n",
"BAHEDJA Rachma 18.0 2.666667 3 1 \n",
"CHAHARANE Djawadi 11.5 2.000000 2 1 \n",
"CHARIF Nassuria 5.5 1.333333 1 1 \n",
"COMBO Danil 10.0 2.000000 3 0 \n",
"HOUMADI Naima 9.5 2.000000 2 1 \n",
"IBRAHIM Yanick 15.5 3.333333 3 2 \n",
"IBRAHIM Hakim 8.0 2.000000 2 1 \n",
"MADI Himidati 7.0 2.666667 2 2 \n",
"MARI Ismaël 14.5 2.000000 3 0 \n",
"MOHAMED Yousra 9.0 2.000000 0 3 \n",
"MOUHOUDHOIRE Nithaou 5.5 2.000000 2 1 \n",
"SAINDOU Abdoul Anzize 4.5 1.333333 2 0 \n",
"SAÏD Hakim 17.5 3.333333 2 3 \n",
"SOIFENE Fémida 5.0 0.666667 0 1 \n",
"ZAKARIA Najwa 5.5 4.000000 3 3 \n",
"\n",
" Exercice 2 Durée Horaire Exercice 3 Distance \\\n",
"ABDOU ALI Nassim 2.5 3 2 0.666667 0 \n",
"ABDOUL-KADER Toura 0.0 0 0 0.666667 2 \n",
"AHAMADI Djelane 0.0 0 0 2.333333 3 \n",
"AHMED Laine 0.0 0 0 3.000000 3 \n",
"AHMED Hamza 2.0 1 3 0.666667 2 \n",
"AHMED Aicha 1.5 1 2 3.000000 3 \n",
"ALI Naima 1.5 0 3 3.000000 3 \n",
"ANSSURDINE Zaidou 0.0 NaN NaN 0.000000 NaN \n",
"ARBABI Idiamine 3.0 3 3 1.333333 3 \n",
"ATTOUMANI Mtahida 0.0 0 0 0.666667 2 \n",
"BACAR Natacha 0.0 0 0 1.333333 1 \n",
"BACAR Musbahou 3.0 3 3 3.000000 3 \n",
"BAHEDJA Rachma 3.0 3 3 2.333333 3 \n",
"CHAHARANE Djawadi 0.0 0 NaN 1.000000 3 \n",
"CHARIF Nassuria 0.0 0 0 1.333333 3 \n",
"COMBO Danil 0.0 0 0 1.000000 3 \n",
"HOUMADI Naima 3.0 3 3 1.666667 0 \n",
"IBRAHIM Yanick 1.0 0 2 2.000000 3 \n",
"IBRAHIM Hakim 0.0 NaN 0 0.666667 2 \n",
"MADI Himidati 1.0 0 2 1.666667 2 \n",
"MARI Ismaël 3.0 3 3 2.333333 3 \n",
"MOHAMED Yousra 0.0 0 0 1.000000 3 \n",
"MOUHOUDHOIRE Nithaou 1.5 3 0 0.000000 NaN \n",
"SAINDOU Abdoul Anzize 0.0 0 0 0.333333 1 \n",
"SAÏD Hakim 3.0 3 3 3.000000 3 \n",
"SOIFENE Fémida 0.0 0 0 1.333333 2 \n",
"ZAKARIA Najwa 0.0 0 0 0.000000 0 \n",
"\n",
" Temps ... nbr virgule Dixieme 1 Dixieme 2 \\\n",
"ABDOU ALI Nassim 2 ... 0 2 2 \n",
"ABDOUL-KADER Toura 0 ... 2 0 0 \n",
"AHAMADI Djelane 3 ... 3 3 3 \n",
"AHMED Laine 3 ... 2 3 2 \n",
"AHMED Hamza 0 ... 3 3 3 \n",
"AHMED Aicha 3 ... 3 0 3 \n",
"ALI Naima 3 ... 3 3 3 \n",
"ANSSURDINE Zaidou NaN ... NaN NaN NaN \n",
"ARBABI Idiamine 0 ... 3 3 3 \n",
"ATTOUMANI Mtahida 0 ... 0 NaN NaN \n",
"BACAR Natacha 3 ... NaN 3 3 \n",
"BACAR Musbahou 3 ... 3 3 3 \n",
"BAHEDJA Rachma 3 ... 3 3 3 \n",
"CHAHARANE Djawadi 0 ... 3 3 3 \n",
"CHARIF Nassuria 1 ... 3 0 NaN \n",
"COMBO Danil 0 ... 3 0 0 \n",
"HOUMADI Naima 3 ... 0 2 2 \n",
"IBRAHIM Yanick 2 ... 3 3 3 \n",
"IBRAHIM Hakim 0 ... 2 2 2 \n",
"MADI Himidati 3 ... 0 0 3 \n",
"MARI Ismaël 3 ... 3 3 3 \n",
"MOHAMED Yousra NaN ... 0 3 3 \n",
"MOUHOUDHOIRE Nithaou NaN ... 0 NaN NaN \n",
"SAINDOU Abdoul Anzize 0 ... 3 0 NaN \n",
"SAÏD Hakim 3 ... 3 0 3 \n",
"SOIFENE Fémida 0 ... 0 0 3 \n",
"ZAKARIA Najwa 0 ... 3 0 0 \n",
"\n",
" Cinquième Demi Exercice 5 Symétrie axiale \\\n",
"ABDOU ALI Nassim 0 0 0.500000 1 \n",
"ABDOUL-KADER Toura 0 0 0.000000 0 \n",
"AHAMADI Djelane 3 3 5.000000 3 \n",
"AHMED Laine NaN 2 0.000000 NaN \n",
"AHMED Hamza 3 3 3.333333 3 \n",
"AHMED Aicha 3 3 0.000000 NaN \n",
"ALI Naima 3 0 5.000000 3 \n",
"ANSSURDINE Zaidou NaN NaN 0.000000 NaN \n",
"ARBABI Idiamine 0 3 2.166667 0 \n",
"ATTOUMANI Mtahida 0 NaN 2.500000 3 \n",
"BACAR Natacha 3 3 1.166667 1 \n",
"BACAR Musbahou 3 3 5.000000 3 \n",
"BAHEDJA Rachma 3 3 5.000000 3 \n",
"CHAHARANE Djawadi 3 3 3.666667 3 \n",
"CHARIF Nassuria NaN NaN 1.666667 2 \n",
"COMBO Danil 3 0 5.000000 3 \n",
"HOUMADI Naima 0 0 1.500000 2 \n",
"IBRAHIM Yanick 3 0 5.000000 3 \n",
"IBRAHIM Hakim 2 2 2.166667 2 \n",
"MADI Himidati 0 0 0.500000 1 \n",
"MARI Ismaël 0 0 4.333333 3 \n",
"MOHAMED Yousra 0 0 3.833333 2 \n",
"MOUHOUDHOIRE Nithaou NaN NaN 2.166667 3 \n",
"SAINDOU Abdoul Anzize NaN NaN 1.666667 2 \n",
"SAÏD Hakim 3 3 4.000000 3 \n",
"SOIFENE Fémida 0 0 2.000000 2 \n",
"ZAKARIA Najwa 0 0 0.500000 1 \n",
"\n",
" Symétrie centrale Codage Précision \n",
"ABDOU ALI Nassim 0 0 0 \n",
"ABDOUL-KADER Toura 0 0 0 \n",
"AHAMADI Djelane 3 3 3 \n",
"AHMED Laine NaN NaN NaN \n",
"AHMED Hamza 3 1 0 \n",
"AHMED Aicha NaN NaN NaN \n",
"ALI Naima 3 3 3 \n",
"ANSSURDINE Zaidou NaN NaN NaN \n",
"ARBABI Idiamine 3 0 2 \n",
"ATTOUMANI Mtahida 0 0 3 \n",
"BACAR Natacha 0 2 0 \n",
"BACAR Musbahou 3 3 3 \n",
"BAHEDJA Rachma 3 3 3 \n",
"CHAHARANE Djawadi 3 0 2 \n",
"CHARIF Nassuria 0 0 2 \n",
"COMBO Danil 3 3 3 \n",
"HOUMADI Naima 1 0 0 \n",
"IBRAHIM Yanick 3 3 3 \n",
"IBRAHIM Hakim 1 0 2 \n",
"MADI Himidati 0 0 0 \n",
"MARI Ismaël 3 1 3 \n",
"MOHAMED Yousra 3 2 2 \n",
"MOUHOUDHOIRE Nithaou 0 0 2 \n",
"SAINDOU Abdoul Anzize 0 0 2 \n",
"SAÏD Hakim 3 3 0 \n",
"SOIFENE Fémida 2 0 0 \n",
"ZAKARIA Najwa NaN NaN NaN \n",
"\n",
"[27 rows x 22 columns]"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes\n",
"#barem"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Supression des notes inutiles "
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes = notes[notes[ds_name].notnull()]"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes = notes.astype(float)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Traitement des notes"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Index(['DS_16_02_08', 'Exercice 1', 'Opération 1', 'Opération 2', 'Exercice 2',\n",
" 'Durée', 'Horaire', 'Exercice 3', 'Distance', 'Temps',\n",
" 'Distance (fraction)', 'Exercice 4', 'nbr virgule', 'Dixieme 1',\n",
" 'Dixieme 2', 'Cinquième', 'Demi', 'Exercice 5', 'Symétrie axiale',\n",
" 'Symétrie centrale', 'Codage', 'Précision'],\n",
" dtype='object')"
]
},
"execution_count": 51,
"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": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Exercice 1', 'Exercice 2', 'Exercice 3', 'Exercice 4', 'Exercice 5']"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nbr_exo = 5\n",
"list_exo = [\"Exercice \"+str(i+1) for i in range(nbr_exo)]\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": 53,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"autres_notes = []"
]
},
{
"cell_type": "code",
"execution_count": 54,
"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>Exercice 1</th>\n",
" <th>Exercice 2</th>\n",
" <th>Exercice 3</th>\n",
" <th>Exercice 4</th>\n",
" <th>Exercice 5</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>2.666667</td>\n",
" <td>2.5</td>\n",
" <td>0.666667</td>\n",
" <td>1.333333</td>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>0.666667</td>\n",
" <td>0.0</td>\n",
" <td>0.666667</td>\n",
" <td>0.666667</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>2.666667</td>\n",
" <td>0.0</td>\n",
" <td>2.333333</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>3.333333</td>\n",
" <td>0.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>2.000000</td>\n",
" <td>2.0</td>\n",
" <td>0.666667</td>\n",
" <td>5.000000</td>\n",
" <td>3.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>2.666667</td>\n",
" <td>1.5</td>\n",
" <td>3.000000</td>\n",
" <td>4.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>2.666667</td>\n",
" <td>1.5</td>\n",
" <td>3.000000</td>\n",
" <td>4.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>2.666667</td>\n",
" <td>3.0</td>\n",
" <td>1.333333</td>\n",
" <td>4.000000</td>\n",
" <td>2.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>2.666667</td>\n",
" <td>0.0</td>\n",
" <td>0.666667</td>\n",
" <td>0.000000</td>\n",
" <td>2.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>2.666667</td>\n",
" <td>0.0</td>\n",
" <td>1.333333</td>\n",
" <td>4.000000</td>\n",
" <td>1.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>4.000000</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>2.666667</td>\n",
" <td>3.0</td>\n",
" <td>2.333333</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>2.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000</td>\n",
" <td>5.000000</td>\n",
" <td>3.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>1.333333</td>\n",
" <td>0.0</td>\n",
" <td>1.333333</td>\n",
" <td>1.000000</td>\n",
" <td>1.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>2.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>2.000000</td>\n",
" <td>3.0</td>\n",
" <td>1.666667</td>\n",
" <td>1.333333</td>\n",
" <td>1.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>3.333333</td>\n",
" <td>1.0</td>\n",
" <td>2.000000</td>\n",
" <td>4.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>2.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.666667</td>\n",
" <td>3.333333</td>\n",
" <td>2.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>2.666667</td>\n",
" <td>1.0</td>\n",
" <td>1.666667</td>\n",
" <td>1.000000</td>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>2.000000</td>\n",
" <td>3.0</td>\n",
" <td>2.333333</td>\n",
" <td>3.000000</td>\n",
" <td>4.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>2.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>3.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>2.000000</td>\n",
" <td>1.5</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>1.333333</td>\n",
" <td>0.0</td>\n",
" <td>0.333333</td>\n",
" <td>1.000000</td>\n",
" <td>1.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>3.333333</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>4.000000</td>\n",
" <td>4.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>0.666667</td>\n",
" <td>0.0</td>\n",
" <td>1.333333</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>4.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.500000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Exercice 1 Exercice 2 Exercice 3 Exercice 4 \\\n",
"ABDOU ALI Nassim 2.666667 2.5 0.666667 1.333333 \n",
"ABDOUL-KADER Toura 0.666667 0.0 0.666667 0.666667 \n",
"AHAMADI Djelane 2.666667 0.0 2.333333 5.000000 \n",
"AHMED Laine 3.333333 0.0 3.000000 3.000000 \n",
"AHMED Hamza 2.000000 2.0 0.666667 5.000000 \n",
"AHMED Aicha 2.666667 1.5 3.000000 4.000000 \n",
"ALI Naima 2.666667 1.5 3.000000 4.000000 \n",
"ARBABI Idiamine 2.666667 3.0 1.333333 4.000000 \n",
"ATTOUMANI Mtahida 2.666667 0.0 0.666667 0.000000 \n",
"BACAR Natacha 2.666667 0.0 1.333333 4.000000 \n",
"BACAR Musbahou 4.000000 3.0 3.000000 5.000000 \n",
"BAHEDJA Rachma 2.666667 3.0 2.333333 5.000000 \n",
"CHAHARANE Djawadi 2.000000 0.0 1.000000 5.000000 \n",
"CHARIF Nassuria 1.333333 0.0 1.333333 1.000000 \n",
"COMBO Danil 2.000000 0.0 1.000000 2.000000 \n",
"HOUMADI Naima 2.000000 3.0 1.666667 1.333333 \n",
"IBRAHIM Yanick 3.333333 1.0 2.000000 4.000000 \n",
"IBRAHIM Hakim 2.000000 0.0 0.666667 3.333333 \n",
"MADI Himidati 2.666667 1.0 1.666667 1.000000 \n",
"MARI Ismaël 2.000000 3.0 2.333333 3.000000 \n",
"MOHAMED Yousra 2.000000 0.0 1.000000 2.000000 \n",
"MOUHOUDHOIRE Nithaou 2.000000 1.5 0.000000 0.000000 \n",
"SAINDOU Abdoul Anzize 1.333333 0.0 0.333333 1.000000 \n",
"SAÏD Hakim 3.333333 3.0 3.000000 4.000000 \n",
"SOIFENE Fémida 0.666667 0.0 1.333333 1.000000 \n",
"ZAKARIA Najwa 4.000000 0.0 0.000000 1.000000 \n",
"\n",
" Exercice 5 \n",
"ABDOU ALI Nassim 0.500000 \n",
"ABDOUL-KADER Toura 0.000000 \n",
"AHAMADI Djelane 5.000000 \n",
"AHMED Laine 0.000000 \n",
"AHMED Hamza 3.333333 \n",
"AHMED Aicha 0.000000 \n",
"ALI Naima 5.000000 \n",
"ARBABI Idiamine 2.166667 \n",
"ATTOUMANI Mtahida 2.500000 \n",
"BACAR Natacha 1.166667 \n",
"BACAR Musbahou 5.000000 \n",
"BAHEDJA Rachma 5.000000 \n",
"CHAHARANE Djawadi 3.666667 \n",
"CHARIF Nassuria 1.666667 \n",
"COMBO Danil 5.000000 \n",
"HOUMADI Naima 1.500000 \n",
"IBRAHIM Yanick 5.000000 \n",
"IBRAHIM Hakim 2.166667 \n",
"MADI Himidati 0.500000 \n",
"MARI Ismaël 4.333333 \n",
"MOHAMED Yousra 3.833333 \n",
"MOUHOUDHOIRE Nithaou 2.166667 \n",
"SAINDOU Abdoul Anzize 1.666667 \n",
"SAÏD Hakim 4.000000 \n",
"SOIFENE Fémida 2.000000 \n",
"ZAKARIA Najwa 0.500000 "
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes[list_exo]"
]
},
{
"cell_type": "code",
"execution_count": 55,
"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>Exercice 1</th>\n",
" <th>Exercice 2</th>\n",
" <th>Exercice 3</th>\n",
" <th>Exercice 4</th>\n",
" <th>Exercice 5</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>2.67</td>\n",
" <td>2.5</td>\n",
" <td>0.67</td>\n",
" <td>1.33</td>\n",
" <td>0.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>0.67</td>\n",
" <td>0.0</td>\n",
" <td>0.67</td>\n",
" <td>0.67</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>2.67</td>\n",
" <td>0.0</td>\n",
" <td>2.33</td>\n",
" <td>5.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>3.33</td>\n",
" <td>0.0</td>\n",
" <td>3.00</td>\n",
" <td>3.00</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>2.00</td>\n",
" <td>2.0</td>\n",
" <td>0.67</td>\n",
" <td>5.00</td>\n",
" <td>3.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>2.67</td>\n",
" <td>1.5</td>\n",
" <td>3.00</td>\n",
" <td>4.00</td>\n",
" <td>0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>2.67</td>\n",
" <td>1.5</td>\n",
" <td>3.00</td>\n",
" <td>4.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>2.67</td>\n",
" <td>3.0</td>\n",
" <td>1.33</td>\n",
" <td>4.00</td>\n",
" <td>2.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>2.67</td>\n",
" <td>0.0</td>\n",
" <td>0.67</td>\n",
" <td>0.00</td>\n",
" <td>2.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>2.67</td>\n",
" <td>0.0</td>\n",
" <td>1.33</td>\n",
" <td>4.00</td>\n",
" <td>1.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>4.00</td>\n",
" <td>3.0</td>\n",
" <td>3.00</td>\n",
" <td>5.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>2.67</td>\n",
" <td>3.0</td>\n",
" <td>2.33</td>\n",
" <td>5.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>2.00</td>\n",
" <td>0.0</td>\n",
" <td>1.00</td>\n",
" <td>5.00</td>\n",
" <td>3.67</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>1.33</td>\n",
" <td>0.0</td>\n",
" <td>1.33</td>\n",
" <td>1.00</td>\n",
" <td>1.67</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>2.00</td>\n",
" <td>0.0</td>\n",
" <td>1.00</td>\n",
" <td>2.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>2.00</td>\n",
" <td>3.0</td>\n",
" <td>1.67</td>\n",
" <td>1.33</td>\n",
" <td>1.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>3.33</td>\n",
" <td>1.0</td>\n",
" <td>2.00</td>\n",
" <td>4.00</td>\n",
" <td>5.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>2.00</td>\n",
" <td>0.0</td>\n",
" <td>0.67</td>\n",
" <td>3.33</td>\n",
" <td>2.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>2.67</td>\n",
" <td>1.0</td>\n",
" <td>1.67</td>\n",
" <td>1.00</td>\n",
" <td>0.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>2.00</td>\n",
" <td>3.0</td>\n",
" <td>2.33</td>\n",
" <td>3.00</td>\n",
" <td>4.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>2.00</td>\n",
" <td>0.0</td>\n",
" <td>1.00</td>\n",
" <td>2.00</td>\n",
" <td>3.83</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>2.00</td>\n",
" <td>1.5</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>2.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>1.33</td>\n",
" <td>0.0</td>\n",
" <td>0.33</td>\n",
" <td>1.00</td>\n",
" <td>1.67</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>3.33</td>\n",
" <td>3.0</td>\n",
" <td>3.00</td>\n",
" <td>4.00</td>\n",
" <td>4.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>0.67</td>\n",
" <td>0.0</td>\n",
" <td>1.33</td>\n",
" <td>1.00</td>\n",
" <td>2.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>4.00</td>\n",
" <td>0.0</td>\n",
" <td>0.00</td>\n",
" <td>1.00</td>\n",
" <td>0.50</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Exercice 1 Exercice 2 Exercice 3 Exercice 4 \\\n",
"ABDOU ALI Nassim 2.67 2.5 0.67 1.33 \n",
"ABDOUL-KADER Toura 0.67 0.0 0.67 0.67 \n",
"AHAMADI Djelane 2.67 0.0 2.33 5.00 \n",
"AHMED Laine 3.33 0.0 3.00 3.00 \n",
"AHMED Hamza 2.00 2.0 0.67 5.00 \n",
"AHMED Aicha 2.67 1.5 3.00 4.00 \n",
"ALI Naima 2.67 1.5 3.00 4.00 \n",
"ARBABI Idiamine 2.67 3.0 1.33 4.00 \n",
"ATTOUMANI Mtahida 2.67 0.0 0.67 0.00 \n",
"BACAR Natacha 2.67 0.0 1.33 4.00 \n",
"BACAR Musbahou 4.00 3.0 3.00 5.00 \n",
"BAHEDJA Rachma 2.67 3.0 2.33 5.00 \n",
"CHAHARANE Djawadi 2.00 0.0 1.00 5.00 \n",
"CHARIF Nassuria 1.33 0.0 1.33 1.00 \n",
"COMBO Danil 2.00 0.0 1.00 2.00 \n",
"HOUMADI Naima 2.00 3.0 1.67 1.33 \n",
"IBRAHIM Yanick 3.33 1.0 2.00 4.00 \n",
"IBRAHIM Hakim 2.00 0.0 0.67 3.33 \n",
"MADI Himidati 2.67 1.0 1.67 1.00 \n",
"MARI Ismaël 2.00 3.0 2.33 3.00 \n",
"MOHAMED Yousra 2.00 0.0 1.00 2.00 \n",
"MOUHOUDHOIRE Nithaou 2.00 1.5 0.00 0.00 \n",
"SAINDOU Abdoul Anzize 1.33 0.0 0.33 1.00 \n",
"SAÏD Hakim 3.33 3.0 3.00 4.00 \n",
"SOIFENE Fémida 0.67 0.0 1.33 1.00 \n",
"ZAKARIA Najwa 4.00 0.0 0.00 1.00 \n",
"\n",
" Exercice 5 \n",
"ABDOU ALI Nassim 0.50 \n",
"ABDOUL-KADER Toura 0.00 \n",
"AHAMADI Djelane 5.00 \n",
"AHMED Laine 0.00 \n",
"AHMED Hamza 3.33 \n",
"AHMED Aicha 0.00 \n",
"ALI Naima 5.00 \n",
"ARBABI Idiamine 2.17 \n",
"ATTOUMANI Mtahida 2.50 \n",
"BACAR Natacha 1.17 \n",
"BACAR Musbahou 5.00 \n",
"BAHEDJA Rachma 5.00 \n",
"CHAHARANE Djawadi 3.67 \n",
"CHARIF Nassuria 1.67 \n",
"COMBO Danil 5.00 \n",
"HOUMADI Naima 1.50 \n",
"IBRAHIM Yanick 5.00 \n",
"IBRAHIM Hakim 2.17 \n",
"MADI Himidati 0.50 \n",
"MARI Ismaël 4.33 \n",
"MOHAMED Yousra 3.83 \n",
"MOUHOUDHOIRE Nithaou 2.17 \n",
"SAINDOU Abdoul Anzize 1.67 \n",
"SAÏD Hakim 4.00 \n",
"SOIFENE Fémida 2.00 \n",
"ZAKARIA Najwa 0.50 "
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes[list_exo].applymap(lambda x:round(x,2))"
]
},
{
"cell_type": "code",
"execution_count": 56,
"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": 57,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Opération 1',\n",
" 'Opération 2',\n",
" 'Durée',\n",
" 'Horaire',\n",
" 'Distance',\n",
" 'Temps',\n",
" 'Distance (fraction)',\n",
" 'nbr virgule',\n",
" 'Dixieme 1',\n",
" 'Dixieme 2',\n",
" 'Cinquième',\n",
" 'Demi',\n",
" 'Symétrie axiale',\n",
" 'Symétrie centrale',\n",
" 'Codage',\n",
" 'Précision']"
]
},
"execution_count": 57,
"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": 58,
"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": 59,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
"#notes"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"eleves = notes.copy()\n",
"eleves[sous_exo] = notes[sous_exo].applymap(toRepVal)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"22"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(notes.T.index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Preparation du fichier .tex"
]
},
{
"cell_type": "code",
"execution_count": 247,
"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": 62,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"count 26.000000\n",
"mean 10.326923\n",
"std 4.766429\n",
"min 2.000000\n",
"25% 6.250000\n",
"50% 9.500000\n",
"75% 14.125000\n",
"max 20.000000\n",
"Name: DS_16_02_08, dtype: float64"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes[ds_name].describe()"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7fafa4388940>"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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0bmEMK7cwD+EWAACA6Qm3wAI6fzCKzi2MYeUW5iHcAgAAMD3hFlhA5w9G0bmFMazcwjzO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\ngg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fafa509c208>"
]
},
"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": 64,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fafa4363b70>"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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ubnxy+P3ZcEsgSRLlT8upbKhcoLNydXElKSqJ9IT0Nf/7EawNS1EZLcZa1Ebm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KY+EkWRucU5U1iVbFKGsHbj4eToRFRIFDFhMUSGROJoxg5i8YtiXncblQQnE09SlFMEWEOprOwu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k4bktF/z7oTQCZ9jZ9z/+MybzMlcu/Wr9vbHvrLUy26wIVhuCJDpbmW02ZFFEFgSXtzJvxej0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t8Ts8tztA62s7ylrktPSKU0q4Tw4LBj//o+vg7G5sZ53VaLWqXiTtWtfU0f7sTd+iOL1crr\njlqmFj4+QIgOiyIjMZ30hNRDe+31JgOv294yv7pAcEAwV8triA77dLNAkiTqexrpnxwkIiScO5U3\n8XdR3egJzBYzY3PjTM5P8X/8n//DV/yCrfj9X//3P5Odlul9Jx9egLeqkH6uf8L86iIA96puExfl\nnlbjlY1VHr77GX+1H9/XfHugXbKN5XmePv8zQUEh3P7d/0DuhSmfJ43ZbKK+8QUjo32O26IiYykt\nriY5OcP3M+iE1Wrh2fO/ML8wjUKh4DcP/jdCQo5+AWixWPjp0b+g2VjjxrXvdwzXOhFMJuR63cdF\nr0oFAZ4rXCRJ4uf6pyys2d5bZDIZ31/8hnAXN2N0Bh2P6p6gN+o5X1hNTor3pOYDNPY10zPWt+vn\nlQolaqXqUOofV7AK1q0NRg3Xyi+TGp9ypOfbzujsGO+66rAKAoXp+ZzJKfPa9xSraKVjqIuByUFM\nFjNgC/JKiIqnKr+CcDf8rB9pfYJA50gXXSM9iJJIStwpqvMr3NaWvheSJDG9NEPbYAcrG6vIkJGR\nmEZJVjFhXtIq7uPzZmh6hNrO9wSo/blbfdujip6j6o/saqKR2TFGZ8ccm2ghgcFkJp12qImOwtzK\nPK/b3mIwG0mJO8XF4vN7rlOSJBp6m+ibGCA8OJw7VTcIOKFNR61ex8jMKDNLs6zp1h3qJoA//OEP\nvuIXbMXvH/7wB1QqFaU5xcRH++Y1t+OtKiS7AkkG/O7q3xLopovkjuEuWgfbyUhM43LppQM9tqn9\nHeMDHZTknSGn+qotjMfHJ8zNTzE80ktxYQVhHpgr+xyRJImHj/+V5S3P9X4qJFd5++4JwyM9FOSV\nU1lxxQ0rPSImI/LNTWQWM1jMtqLX3w88vHMsCAI/1D50tKXaZ89T4pK5VHzB5ZCkdZ2Gx/VPMJlN\nXC69REZi2jGu2jUm56d43fEWq2BrW1YqlKTGpxAZGkFUaCRRoZHHHgIF8K6rjsGpYfJSc6guqHTb\n8wqiQFNfC30TA6iUKi4WnSPNS1qJXWFqcZrmgbaPFFohgcGUZpWQmXSym1PrOg3vu+pZWFtEqVBS\nnl1KXlrOsQdige09cHJxmrbBDta0a8hkMjKTMijJLNrRV+rDx0HoGx+gvreRIP9A7p27TXCA5w4s\nDqo/2k1NBBDoF0BN6UXiI+OOPHInSRKdI920DXaA7GBZCZIk0dDXTN94P+HBYdypuumRAnhxbYnR\n2THmVubR6nWfjOco5ApCg0KIj4jj9//7f/EVv2Arfv/n//U/P0idg0M5W1hOoLfrPjyMN6qQBEHg\nfz37E4LoXgWSKIo8rn/C0voyV8pqDjSPZbKY+MvzP+On03L/ygP8klKRQnw71T4OjrPaKCYmYV8V\n0kGeMyoqjvt3fo/iBOepZUYDss1NZFYLmM1IFiuin9rjRS/YXJA/vnuEsKXYyU/Lo/h0Aa/a3zK/\nskBIYAjXyi+73B63rFnhl4ZnWAUr189c5VSs+5zMB0FvMPCo/heH0gKgKCOfs7lnPL6W0dlxXre/\nJTI0gvvn7rrNi7xp2ORl2xuW1pcJDw7jWvllwj7TFlmdXkdjXzNTi9OIW9dHSoWSrOTTlOeUolae\nTMq9LRBrhOb+FkwWM1GhkZwvqt6xBfK4vv7E/CRtQx2s6zTIZDKykk9Tklnk0YLFx5dH50g3LQNt\nhASGcK/61qFbhA+Kq/qjndREtvcBCbPVQmpcCjWlF93yfmo0m3jTUcvM0iyB/oFcKbvkmv3ECUmS\naOxrpne8n7CtAtidYyeiKDK5MMX4/ARL68tsGvSfON/VShXhIeEkxyRxOjHd4Vr3zfw6L0Imk5pe\n1NE/Nsjo9LijfSA5LpGSnCKvbZk6CbxRhaQ3GPi3l/+BBAT6B/L7a+5RINmdnkqFku8vfXOgN8S+\niQEauuopDI+jqrASMSYWKTT8UDoWH18nO6mN9lIhuYJmY40fH/4LMpmMB/f/kVAPzjk5IzMakOl0\nyAQrmM2IFiuSvx+cUEpkz1g/jX1NtrUh42bldZK20shFUaR1sJ2u0R4UcgXni6pdPombX13gaeNz\nAI8niwqCwKv2t0w6zYHFhsdwp+qmWx3pruKs+Xhw4Z7bitPZ5Tletb/FZDaRkZjG+cLqYw9n8gSi\nKNI52k3feD/GrYwEgPjIOCrzK4g6oZ9do8lIY38LIzOjyJCRl5ZDeXapx/7NRUlkfG6C9qFONJsb\nyGVysk9lUny60CPt2D6+TFoH2+kY7iI8OIy71bc8Fti0m/5Iq9dtqYnGWdOuAR/URNFhUXQMd2Gy\nmBwqI3cErC6uLfGq7Q2bRj1J0YnUlF449L+DJEk09bfQM9ZHWFCorQA+5KaCyWxmZHaUqcVpVjdW\nP3o/tBPgF0B0aBQp8cmkJaTuuknoK36dF+EUeGW2mGnpbWd5zRa0oJDLyT+dR1qSe+eSPne8TYW0\nsLLI4wabAikuIpZ752675XntLTHJMUncOHvV5TcYURT5ofYh6xtr/KboAlHB4UjRMYgRkeDbTPHh\nArupjXZTIe2HIFh5+PMfWV1d5PKle2TsE97kdiTpQ9ErCmA0IooSkp8fqE/O2fyk8Vdml+cACFD7\n89ua7z7SGNmZWJjibcc7LFYLOSnZVOWddamInF6a4XnzKxQKBXeqbnrkpKx3rJ/G/mbHRq6/2p87\nlTeIOKGCSRAFHtc9YVmzsucJx0GQJImukW5aBzuQyWRU5p0lNzX7i0zZn12epam/ldWNNcdtwQFB\nlGQWkX3qZMaPZpfnqOtuYEOvJdA/kOr8CrfPb++FKImMzo7TPtSJVq9FIZeTnZJNcUaBx07ufHw5\nOJ9WRoZGcqfq5oHncA+LXX8UFRpJZlIGY/MTu6qJ5pbnHSqjyvyz5Kcd/fe4JEn0jvfR1N8KEpRm\nF1Nyusgt7dPNA610j/YSGhTKXRcLYI1ug+GZEWaX59DoNB8FT4JtHCk4IJi4iBjSE9JIdNFRDL7i\n9+NF7JD2vKZZo6W3HYPJ1lMf4BfAmYIyIkI/z1aq48DbVEgDk4O877Z9H3NSsjnvqqpoDyRJ4mnT\nc2aX57hQVH2gC42ZpVmeNj0nPiKWe3mVyC0WpOhoxMhoOIGTFx+fD7pNLX/+6/+zq9pouwrp4vlb\n+7YvNzS9pLevjazMAi6ed8/mkEtIEjKD3tbeLAo2R68oIvn5g+rkTugMZgN/ef2jI2joVGwyN85e\n3fMxG5sbvGh9w5p2jeiwKK6WX3YpqXhsbpxXbW/xU/txr/r2saXWrmhWedL4KyaLbWdcJpNRnV/h\ntjT8w9LY10LPWC+nkzKoKTm6o9pkMfO24x1Ti9ME+gdytayG2K/AAa436mnsa2ZifsrhUlYqFGQk\nplORe8YjM9vOWAWBrpFuOke7EUWRlLhkqvIr3Z7evReiKDIyM0r7cCc6wyYKuYLc1GyKMgpOLGzH\nx+eJJEkOZ21sRAy3Kq4fe0eD2WJmcmGK5oE2DCaD4/ad1ET9EwPU9zQhl8u5UnbJLenrJouZ2s73\nTC5MEaD2p6b0IolbXU/uQJIkWgba6BrtITQwhDvVtwhyKoBFUWRxbZGR2XEWVhfQGnSI4seeeKVC\nQWhQKAlR8ZxOOn2krhdf8eu8iD1UR+Mzk/SM9Dm+GdERUZzJL/X4LxlvxdtUSO+7GxiYHATgfGEV\nOSnZR37OTcMmf337E6Ik8f2lbw4UsvFr8wumFme4Vn6ZtOAI5PpNpMhIxMiYEz3t8uHdvH77mNGx\n/j3VRs4qpPi4ZK5deYDfLrOyk1MjPH/5A2FhkXx77x9ReaLolCRk+k3bf6KIZDQiSdKJF71gC396\n3vrK8fFB3iusgpX33Q2MzIzip/LjculFl5Rog1NDvOuqJ9A/kHvVtwlxYxK8WTDztP5XljQftGFp\n8anUlFw4kRZnZ6YWZ/i1+QWhgSE8uHj/yBeTKxurvGx9jVavIzEqnsull7xKqeEJRFGkZ6yPnvFe\nxwY9QGxEDJX5FcR4aA7XzrpOQ113A/OrCx8CsVJzPDoyJogCw9OjdAx3smnUo1QoyE3NpSgj32ud\noz68D1ESedvxjtHZcRKi4rlx9prbsgnsWAWB6aUZxmbHmFqccYQzyWVyREnkankNafEfcmZsJ6ht\ndI/24K/248bZa8SERx95HcuaFV61vUGr1xEfGcfl0ovH0jUhSRKtg+10jnQT5B9EYUY+86sLLK0v\nYzDq2V4FqlVqIkMibPO6SeluXZOv+HVexD6eX1EU6RjoYnph1n5/MpLTyE3P9s0D430qpMd1Txya\nkvvnbhN7wGH9nbC3pcRFxHKn+qbLKZcanYa/vP2J4IBgfnPpW5RmE3LtBlJYGGJ07IkE+/jwbhaX\nZnn08x+Jiorj23v/sGfrkdVq4U3tz0xMDhMWFsmt678leJuuQbep5cef/hmr1cI39/+ByOM+IRNF\nW8Fr0CMTBCSjAQkZUkCgV3Q8vOuqZ3BqCMCmj7r4LSEHdBxLksTA5BANfU2IokhZdolLbWLdo700\n9be4NVhlu7ooNDCEe+due8Wp16ZRzw+1D7FYLXxz/i5RoUdLdR+aHqGuuwFBFCg+XUhZdolHEoe9\nmfmVBZr6WxxOXLBlXxRlFJCb4rlrFEmSGJ4ZpamvBZPFZAvEKqz2+LWAIAgMTg/TOdyF3mRAqVCS\nn5ZLYXo+fieUKeDj80IURV62vWZyYZpTsUlcK79y5J8ju5pobG6c8fnJDwG7QaE2F29iGkaT8RP9\nkVUQqO18x9jcBKFBodyquHbklHNJkhiYGqKxtwlBFG3vpVklx/JeYTQbGZ4eZXpxmsX15U9SmMGW\nVB0dHk1qfAppcSnH2kHqK36dF7FP8WtHbzTQ3N2KRmfTYKiUKkpzC4mPjj/uJXo93qZC+tPz/0Rv\ncp8CSZIkXra9YWJ+korcMxRm5Lv82IbeJnrH+zmbW05RRoHNZapZQxYcghgd41Mh+XAgSRKPfv7/\nWFqe597t3xMXt39CsCiKNLe8oaev9RMVkiiK/PL031lYnOFc1XVyc0qOb/H2otd+0msyIkl4TdEr\nCAJ/ffsTG3otABEhEXx7/u6RTkaX1pd52fqaTaOe5Jgkakov7OsFtwerRISEc7fq1qEvyHdSF10r\nqyHphFKltyNKIk8afmV+dYGq/IojzaZZBYGG3kYGp4ZRK9XUlFzgVFyyG1f7+WM0G2nsbWZ8fsKR\nWK6QK0hPSKUi74zHTj+NZiNNfa0Mz4wgQ0ZuWg7lWSUn0pI9ODVI53A3BrMRlVJFQXoeBWl5vs49\nH/siCAK/trxkdnmOtIRULpdePPBG225qokD/QDIS08hITCcyJOKjTVNn/VF1fiUvWl+zsLZIbEQM\n189cxf+IGzgWq4X33fWMzo7jp1JTU3KRZDf+zljXaj7M625uYN0+r4sMCQmlQsn5oirS49M8eojo\nK36dF+Fi8WtnfnmR9oFOLBbbzk1oUAhnC8sJCvi6Qxa8SYXkrEBSKhT8w42jK5CMJiN/efsTZquZ\nBxfuERHi2tyByWLiP1/9gCiJ/M3l72wnMlYL8rVVZP4BtgLYp0Lywcdqoys19w/02J6+1k9USK3t\n7+jobCAtNYsrNd8cTxiQIHw46RXFDye9gUFeE+62olnl4fufHXOS7lT9GM1GXrfXMrs8R3BAMNfK\nLxO1h7dakiQaepvomxggJjya25U3DtQK7E3qor1oH+qkbaiDlLhkrpVfOfRrT6vX8bL1NSsbq0SG\nRnCt/LLP77oHoijSPzlA10gPeqcZwpiwaCryzxxYW3JY5lbmed/dwMbmBoF+AVQVVJIad8rjgWRW\nwUr/xCBdo90YzSbUSjWFGfnkp+V+EangPo4Pq2DlaeNzFtYWyUw6zcXicy69fndSE/mp/EhLSCUj\nMY24iNhdn8dZfxTgF4DBZCAtPpVLJReO3H69pl3nZetrNJsbxIRHc6Ws5kjz+aIoMr86z+jsBAur\ni+gMOsfvWDtKhZKwoFASYxLITDxNeEgYbUMdtA91EhwQxJ2qW24dAdoPX/HrvIgDFr9g+6YPjg8z\nPDXqSNRMjEmgLK/4q26F9iYVkt5g4E8v/wOAIP9AfucGBdLkwhTPW14RGRrJN+fvoJC79mbUNzFA\nfU8j2acyuVB0znajINgKYJXSVgD7VEhfNTupjQ6KswopP6+Mnt5WgoNCefDtP+Hn7pMfQUC2qbMl\nOAsCktlkO+kNCvaq13HXaA/N/a2AbWTlTuUN4qPc260jSiLtQ510DHehkMupLqgi+1TmrveXJIm3\nne8ZmRl1ea7M29RFezG/usAv9c8I9A/gu4vfHPp0e3pxhtcdtZgtZrKST1NdUInyBL3UnxuLa0s0\n9bWwuL7kuC3AL4DCdFvxd9zXKoIg0DnaTeeILRDrVGwy1QWeDcSyY7Fa6JsYoHu0B5PFjJ/Kj8KM\nfPJSc3xFsI9dMVvMPGn8lWXNCnmpOVTlV+xYuO6lJspITCfpAInEE/OTvGh9DUBWciYXiqqPvGk0\nPDNKXXc9VkEgPy2Xs7nlLl+/2rFarYzPTzCxMMXy+vJHm2t2/FR+RIZGkBybRGZSxq4dJ+3DnbQN\ndhDkH8Td6pse29D0Fb/OizhE8WvHbLXQ1tvO4uoyAHK5nLyMHDKS09y4ws8Pb1EhOSuQ4iPjuFt9\n68jPWdv5nqHpEUoyiyjPLnXpMQ71kU7Dg4v3P8y+iSLy9VVbK0hUtE+F9BWzm9rooNhUSH/FtBWE\nc+/O74lzZyus1YpMr0NuMID9pFeusJ30elHRC/Bz/RPmV23z/wF+Afy25sGxtjxOLU7zpv0dZquZ\n7FOZVOVX7lrUOs+VpcSd4mpZza4XR96mLtoLo9nED7UPMZgM3K26RVzkwU8aRUmkY6iL9uHOrc2E\nyhNT+nwJmMxmmvpbGJ0d+xCuI5eTFp9CZe5ZAvyPdz5co9Pw3ikQqyyrxCPF906YLWZ6J/rpGe3D\nbDXjr/ajKKOQ3NRs38aKjx0xmU383PCUNe06xacLOZNTBoDBZGB8bpLRubGP1ERJMYlkJNrURAd9\nTU0tTPOq/Y1jnN5uC6cAACAASURBVCUmPJp71bcP/bNiFaw09DYxODWMSqniYvF50lxUkumNekZm\nRplanGFNt455y4xgR4athTs6PJq0+BRS4k+hlLv+9+0Y7qJ1sJ0g/0DuVt/ySAHsK36dF3GE4teO\nRquhuacdvVEPgL+fP2fyS4kM876LE0/hLSok+6krQG5qDucKKo/0fGaLmR9qH7Jp1HP/3G1iwl0L\nEHKojyLjuFN188NOniQh29AgN5t9KqSvlP3URgdBkiR+fvpvLCzMALisQtoXqxXZpha50QiC1aYs\nkiuRgrxvZt1gMvDn1z9ittp+WafGp3Ct/LJHvrZWr+VF6xtWN1aJCo3kannNrr/UrYLAr80vmFuZ\n53RSBpeKz3+0w++t6qLdkCSJ5y2vmFqcpjy7lJLMogM/h9Fs5E37O2aWZwkOCOJq+WWPuJG/BkRR\nZGh6mI7hbjaNm47bo0IjOZt7hsRjzC+RJImRmVEatwKxIkMjOF9Y7ZbU2sNgspjpHeujZ7wPi9VC\ngF8AxacLyD6V7fZ0Xx+fPwaTgcd1T9jQa0mNT8FqtTK7MufYkNxJTXRQtquMxuYmGJ0dO9BBizOa\nzQ1etb5hVbtGZGgkV8tqCN0j3HFlY42R6RHmVubRbG58Ek4ll8sJCQgmPiqOjIR0YiNijryB1TnS\nTctAG4H+gdyturXn+g6DJElYrBbMVgtmixmzyUzV/fO+4hfcU/zamZybonuoz/GiiQqP5Ex+GX5f\nqdbGW1RIzgmv5wvPkZOye0uiK8ytzPNLwzNCg0L57uJ9l3f3nNVHqdt232Q67QcVUlTsietgfHgO\nV9RGrtLd00xTyxvi4pIRRcElFdKeWCzIN7XITKatotdsO+n1wqIXPm4ZA7hYfI6s5KP9vB8Uq2Cl\nvqeRoekR1Co1l/cIFbFYLTxp/JWl9WVHW51FtHitumgvesb6aOxrJiEqnluV1w8cEGMLEHvDpnHT\nFiBWcsGX0HtMrGhWaOhtdpgRwNZRkJ+WS1FGwbGdyhrNRpr7WxmaHgEgLzWH8uyT00eazCa6x3rp\nHe/HKlgJ9A+k5HQhWcmZXv2z5sNz2NVEQ1PDTC/NOG6PDouyJTUnpB4puX83lZHjoMWg5071TeIj\n41x+zvG5CWq76rBYLeScyqIyv+KjTR1RFJlZnmVsboLFtUV0hk2212MqhZLw4HASoxPITM4gNOh4\nsmnso0mB/oHcqbpJ2NbXkSQJq2DFbLVgsZg/FLBW89ZtFtv/b33OYjVjdty29fFWqrYzf/jDH3zF\nL7i3+AXbi6prqIfJuWnb8wPpyWnkZXjWe+cteIsK6dH7XxyzT+5QIDX2NtMz3kdeWi7V+RUuPWa7\n+mj7L1eZQY98Q4MUEYEYFeNTIX0FHERttB9Ly/M8+vmP+PsH8N03/4RKpd5XhbQrZjNyvc5W9Fot\nSCYzolIFgd4b7Pe24x3DM6OAbd7qNzXfEhzguTCN7QxODVHf04ggipRmFlOSVbRjQWgym3hc/5R1\n3TrRYVEfaWu8SV20F8uaFR69/wW1SsV3F7850MWgXb3R0LuljsoqoSRzf3WUj6Njtppp7m9lZGbM\nkcwql8k5FZdMdX7FsXg/waZoet9dj8YeiJVfQWp8yol9z41mI12jvfRP9GMVBIL8gyjJLCIr+fRX\ned32tbObmigkMBiDyYhVsHKhqPrI4xiCIPC28z1jc+M7qowWVhc/0R/t+XyiQFN/K33j/SgVCs4X\nVnM6KQOz1czY7ASTC1OsbKx85Ae346/2Iyo0klOxtjnloxzaSZKEIAo7FK7bi1TbbSuaFdZ1GmQy\nGQF+AQhbRe9hakS1UoVKqUatUqHe+lOlVNtuV6j4m//+d77iF9xf/NoxGo009bSyrtUAtouxkpxC\nEmMT3P61vB1vUSH98fl/YDAZkCHj99f/5kgXlFbByo/vHqPRabhdeYPEaNe+r5+oj7bjUyF9NRxG\nbbQbZrOJHx7+Czqdhts3/obExFRgbxXSjphMtqLXbN4qei2IKhUcURd2nAiCwJ/f/OhI1owKi+R+\n9R2vOLlZ1qzwsvU1OsMmSdGJ1JRe3FFXMTQ1RG1XveNjb1MX7YXFauGH2kdo9VpuVlwjOcb1NVsF\nK++7GxiZGcVP5cfl0oskxSQe42p97Mbw9AhtQ50fJYlHhIRzNucMybHu/54IgkDXaA+dI10Iokhy\nTBLVBZUeTX/djsFkoGukh/7JQQRRIDggmNLMIk4nZfiK4C8ch5pobpzx2fFd1UQanYbH9U8xWUxc\nLr1IRmL6ob6eyWziecurfVVGzvqjy6WXdt0g0hl0vGx9w7JmhdDAEJJiElnZWGVNu+4o3u3IZDKC\n/AOJCY8hPSGFU7GnPnp9C6Lw4WTVuXDddgJrsVo+KWTtJ66iKG5fosuEBIYQ4OePSrlVwCpVqFVb\nBezWn7bCVm27j/1zStWeG2i+mV/nRRxT8WtncXWZtr4Ox7B4cGAwZwvKCAk6uTf4k8AbVEjuViAt\nr6/wsO5nAvwC+P7St/vuysEu6qPtWMy2JOiAQJ8K6QvmKGojZyRJ4tWbR4xPDFJcVMmZsouf3Gcn\nFdJHmEzIN3XILGawmJHMVkQ/tdd3HyyvL/Oo7olDseAcSOItmMwmXnfUMrM0S5B/ENfKLzu6X3ZS\nFwFuOVXwBJIk8abjHaOzYxRmFFCRW+7yYzc2N3jR+oY17RrRYVFcLa850ZN6HzbWtGs09DYzvzKP\n/QrNT+VHXmo2JZnuN1podBvU9TQwtzKPUqGgNKuEgrS8Ey029UY9nSPdDEwNIYoiIYEhlGUVk56Y\nduB2fh/ejV1NNDY3jlbvmppoWbPCk4ZnWAQrV8svkxp36kBfU6vX8qzpBZrNjX1VRs76o0vF58lM\nPv3JfbrHemnpb0OURGTA9spKLpPjr/YnJDCY0OBQ1Er1JyewzrOx2+d9XUEhVziKUEdR6nQCq1Jt\nL2Ttt324f//EAA29zQT4BXCn6ibhwWEHXsde+Ipf50Ucc/FrZ3B8mMGJ4Q8D8tFxlOYVf1UJg9tV\nSNkxWdypuOnRNegMm/z7yz8DEBwQxN9d/e2Rns/uLDudlEFNiWspvTuqj7ZjtSJfX/OpkL5Q3KE2\nsjM41MW7umfExiRy9/bvdr1odFYhnau6Tk52MZiMyHU6ZFbLh6JXrYJjToB1B3aXLNh2su9V3zry\nOMNxIUkSHcNdtA11IJfLqcgpZ2514RN1UXV+BU+anmO2mLlcdon0hNQTXPX+DE2PUNv5/sCppBML\nU7zteIfFaiE3JZvKvLNecVLv4wNWq5WWwTaGpkccJ0cymYxTMUlU5le49YRWkiRGZsdo7GvGZDYR\nGRLB+aIqlwMlj4tNwyadI90MTg0jSiJhQaGUZhWTnpDma8v/jHGHmmhhbZGnjc8RJZEbZ6663LGy\nvL7Cs+YXGM1GCtPzOZtb7ngtfRLQZDVjsVjY0G/QPNAGEpxOTGfTqEezuYHBbDjSCasduVz+6Wnq\nHoWr82mr/eODqpN2o3e8n4beJgLU/rYCOCTcLc8LvuL340V4qPgF2y+T1r4OFlZsIRNymZzc9GxO\npxyubeJz5aRVSPMr8/zc8AyA+Kg47lYdXoEkiiKP6n5hWbOyY5DVbo/ZUX306R19KqQvFHepjdbW\nl/np0b+iUCj47pv/um8RbVMh/YCg26A0o4CSvHJkFguixYrk7wefScDQo/c/s7huU8wF+Qfy/eVv\nUSu8P1hwemmGFy2vP9pZ364uWl5f4ZfGZwiCwPWzVw7URuxJ1nUafnr3CLlMzoOL911SVYiiSOtg\nO12jPSjkCs4XVZOZlLHv43ycLKOzY7QNdrCh1zpuCwsO40x2GanxBzv12guj2bQViDUMQG5KNmdy\nyk4sEMuOVq+jc6SLoekRJEkiPDiMsqySE51T9nEwjkNNNLs8x6/NLwAZNyuuER0W9UnhanY6YV3R\nrDCxMOV4Dfmp/D76/Pb25IMgl9tOd4P9g/D389sqWp1bhLcK2U8KV7XXJZzbD4j81X7cqbpJRIh7\nzDm+4td5ER4sfu1s6LQ097SxabDpBvzUfpzJKyEq4utROpy0Cql3rJ+GviYA8lJzqS5wLbRqJ9Z1\nGn6sfYRKqeT7S9+6NEu8q/poO5KEXLOOzGJBio5BjIzyqZA+c9ylNrJaLfz0+F9ZX1/h2pUHpO6X\nYi5JyIwGdAszvHn1EJ1OQ1JKJlXlNSg+g5NesLUJ//ntD46LhPSEVK6U1Zzwqlxju7oIIFAdwN1z\ntz9RPMyvLPC06TkAtytvHMqXe5xYBSsP3//CmnaNK2U1Lp1QG0wGXrW/ZX5lgZDAEK6VXybSC13F\nPnZHo9ugobeJ2eU5pK3mSrVSTU5KFqXZxQfyfO7F/OoC77sb0Og0BGwFYqV5QaG5samlY7iLkZlR\nJCQiQyIozS4hJTb5xNfm41PMFjOTC1OMzo7vqSZyDmiytQDbC9Lt861mp/vYClaD0eCYDz4MzkWo\nemtm1Wg2YTQbMVvMjpEeZxRyBZIkIUoiKbHJXCq5cOIbRO6mf3KQuu4G/NR+3Km86ZbfFb7i13kR\nJ1D82pman6FrqAdhS2gdGRbBmYKyHYfev0ROWoX0rrOOwa0d5gtF58g+dXglil3zkRKXzLXyKy79\nItxLfbQdmU6L3KDfSoL2qZA+Z9ylNnpX94zBoS7yckqprrq2+x0lCZlBj2xzE5koIJlMGI16nvU2\nsrixSnxkHNfOXD60n9BTjM6M8bqj1vHx5ZKLZCR5f9eMWTB/oi5KjUtBqVAyMjuKWqniUskFUrbN\njU0tTvO85RVKhZK7VbeICtulQ+QEqOtuoH9ykJxTWZwvqt73/gtri7xqfYPeZCAl7hSXis9/cRdr\nXxNWq5X24U4GJgcdOhGZTEZiVAJV+RWEHWGMw44gCnSP9tIx3Ok1gVh2NLoN2oc7GZ0dA2yu5LLs\nUpJjEn1F8AlgD2gyWc0YTUZml+eYWZ5lRbOCuFVn+Kv9CQ4IQq3yQ5LED4Xs1gntTkXmfigVSsf7\nmN6oRy6TkRCdQHBA8NaJqy1peHp5hunFGdRKFdUFVcRFxqLeahVe3lhhZGaU+dVFtHrtJ23MCrmC\n0KBQEqLiORWTzMu2V5itFmQyGRW5Z8hPy/1iX3MDk0O8767HT+XHnaobRO7WJekivuLXeREnWPyC\nrQ2se7iPidlJx21piSkUZJ5s4IOnOGkVknP75P1zd4mNiD7U80iSxC8Nz5hfXeBi8Xmydggl2M5+\n6qPtfKxCigU/7y5WfHyKu9RGY+MDvHrziMiIGO7f+y87t2tJEjL9JjK93lb0Go1IkoTk5w8qFVbB\nypv2d0wsTBIWHMatimteGzj0uu0to3PjAKgUKr6v+ZbgAO9PQm/sa6ZnrM/x8XZ10dD0CHXdDQii\nQPHpQsqySz4K1BmdHeN1ey3+aj/uVd8mzM0BIIdhfH6Sl62vCQ8O59sLd/dsFZQkib6Jfhr7WkCC\nMzllFGbkf7EXa18jE/MTtAy0o9nccNwWGhhKeXYJ6YlpR37+jc0N6robmF2ZRyFXUJZVQkG6d1wf\nres0tA91MDY3AUBMeDRlWSUkRif4XuMuIoqi4xTVvC1hePsJrGWX9OHDBDQpFQrHaesnc6zOc67b\nWodVjj9VH71X2/MPAtT+3K2+TVhw6CcqoxtnrrC6scb4/CRL68vojXpHB4UdtVJNREg4yTGJZCaf\ndujGjCYjrztqmV2eA2zF/G8vf+dS0OrnzODUEO+66vFTqblddXP3MUEX8BW/zos44eLXjtFkpLmn\njbWNdQAUCgXF2QUkH0F/8rlw0iokdymQdAYdf337EIDvL33jUiGxr/poO3YVUkioLQgrwHu9qz4+\nxl1qI612nR8e/guSJPHg/j8Stv1EUBRtJ736TWSCgGQ0ICGzvVa2bbCIkkhzXys9430E+AVw4+xV\nosO8Z/zCLJj56+uf2DTqAYgNj+b++bsnvKr9mZyf4nXHW6xbXT17qYtWNlZ52foarV5HYlQ8l0sv\n4e+Usm1v/wryD+TeuTsnWvRr9Tp+rH2EIAo8uHBvzzASi9XCu646xuYm8Ff7c6XsEglR8R5crQ9P\notVraehtZnppxtFeqlKqyErO5Ex26ZHGmiRJYnQrEMtoNhEREs75wmpiI042EMvO6sYa7UOdTCzY\nDjFiI2IcRfCXjCRJO7pbP1LgfFK42k9bbR/b/dIHQS6Xo1LYTk7FrVNc+8mtUqEkMjSCmPCYrbla\n58L2w+zrcWye9I0PUN/bSJB/IDfOXuV9VwNLmuWtQlmGacv64kygXwDRYVGkxJ0iPSFtx5+ThdVF\nXrW/RW/UkxyTRHhwGN1jvfvqj74UhqaGqe2qQ61Sc7vyxqGvUXzFr/MivKT4tbO8tkJrXwcms20u\nLCggiLMFZYQG7x8m8jlzkiokmwLpjwiiiFKh5B9u/O7QyaP2H9L4qDjuVO4xy7uFS+qj7dhVSIFB\ntgL4C39tfCm4Q20kCAKPf/kjyysLXLpwh8zT+R8+KYq2gtegtxW9JiOSxI5F73bsbftKhZIrZTWc\n8gK/7OLaMo/rf3FcSJdmlVCWVXzCq9qbndRFRRn5nM09s+fjTBYzbzveMbU4TaB/INfKaz5Kuu0a\n6aF5oPWTk2NPIooij+ufsrS+tK+KaV2n4UXrazQ6DbERMVwtq3GcYPj4srGKVjqHuumfHHBc7MuQ\nER8VR1X+2SOF15jMJpoHWhmc+hCIVZ5T5jWnXyuaVdqGOphanAYgPjKOsuwS4iP3cKufEJIkYRWs\nH7X/mi0fF7IWp5lX2+csmJwK2cMENMlksk9OUe1JwnsHNNlu2zTqmZifPJCayFNodBredzcwv7qw\n4+flMhnBAcHERsSSkZhGQlT8nkW4JEk2jdFW0nN5TilFGQVIkrSv/uhLw36yrlaquV11uALYV/w6\nL8LLil87w5OjDIwNOXaz4qJiKc8r8WgolKc5SRXSxwqkYP7u6m8O9TySJPG85RVTi9NU5p2lID1v\n38e4pD7ajk+F9FnhLrVRU/NruntbOJ2RR83FrRNQUUS2qbMVvaL4oegNDDpQOvjE/CSv22sRJZFz\nBZXkpGQfao3uoHWgnY6RLsCWyHn/3G2iww83kuAJBEHgVfvbT9RFd6puuryRJkkSnSPdtA12IJPJ\nqMw/S25KtuNCrmWgjc6RbiJDIrhTfcvjF/z2r5+ekMbl0ou7XmCOzY1T21mHVbCSn5ZLRe4Zr2hR\n9eF5phdnaB5oZU277rgtOCCYsqziI12wL6wu8r67nvWtQKzKvLOkJ6R6zQnY8voKbUMdTC/NAJAY\nFU9ZdqnbTqodAU329t+PTl53drd+VMhuFa4HvQaXIdsqRvcoXLf+/OjzjttUKBXKA3+f3KEmcjei\nKLKwtsjo7BgLq4to9bod54YjgsNJikkkMynDkejvCiaLibcd75lanCbAL4ArpZeIj/qwiaLVa/mh\n9hGSJPHdxW8+CU38EhmZGeVtx3tUShW3Kq8Tc8BrAl/x67wILy1+wZao2d7XydyybRdJJpORnZZJ\ndurhg5k+B05KhTS3PM8vjTYFUkJ0PHcqD1d4G0wG/vL2J6xWKw8u3t9X1O2y+ujTB35QIUXHIIZH\n+FRIXoo71EbTM2M8e/4XQkPCefDNP6GSK2xFr9FgO+k1mw5V9DqzuLbEry0vMZlNFJ8upDy71KMX\nlIIg8Lj+Cctb4VDBAcH8tuaBVztge8f6aexvdlxIblcXHZTZ5Tletb/FZDZxOjGdc4VVqJQqJEmi\nvqeR/slBYiNiuFVxHZXSM8F39nT6kMBgHly4v2NYlSiKNPW30Dvej1Kh5GLxOdIT0jyyPh/ezaZh\nk4a+ZqYWpj9qT81MyuBMbhlq5cE3cj4EYnUhiAJJMYmcK6h0SbnlKRbXlmgb6nDMaSbFJFKWVUJk\nSMSHItSpWN21kHVoc44W0KTaKkDVzqep+xauKsdsrGorjdgTHIea6ChYrVbGFyaZnJ9kSbOCfmsU\nxxmlQokgWJGAmPAYltaXiAyN5E7VzQNtVi6vr/Cy7TU6wyYJUfFcLr24Y7fPyMwobzreHdiz/jkz\nMjPG2453qJRKblXeOFAB7Ct+nRfhxcWvHe2mjuaeVnR6mxpJrVJTnldCTKT3noQclZNSITkrkPLT\n8qjKP1zr9cT8JC9aXxMdFsX9c3f2fVNyWX20HZ8Kyetxh9pIr9fx15/+GYvFzDc3/47ogEBkRuOH\nmV65wlb0uuHCZGNzg6dNL9DqtWQkpnGx6LxHik+dQcdf3vzkmAHLTMrgUsnhHcjHzXZ1kUwmozq/\ngtzUnCM/t86wyau2NyytLxMeHM618suEBYciSRJvOmoZnR0nMTqBG2euHvv3Rm8y8MPbh5gtZu6f\nu7NjIKHeqOdl2xsW15YICwrl2pkr+276+fj6EEWRrtEeesf7MJo/KL/iImKpyj9L1CFaGTc2tdT1\nNDC7PIdCrqA0q5jC9HyPFAK2mVczJrMJo9mEyWLCtPWn7WPb57R6LZrNjUPNt9rZHtD0IZTJ6eNt\nDlfnQnZ7QJM34qqayBMYjAaGZ0eZXpxhTbu287yufyAxYVGkxKdgNpto7GtBLpdzpewSp2KTed9d\nz+DUsMublZIk0T85SGNfM6IoUpJZRGlW8Z7ft9fttYzOjlGSWUR5dumR/96fA6OzY7xpf4dSqeRW\nxXWXOyp8xa/zIj6D4tfOzMIsnYM9jjfQ8JAwKgrKPaoH8iQnpUKq7XjP0MwIABeLz5GVfLiT9jcd\n7xiZGaUsq4RSF2YVD6I+2o5DhRQZiRgZ41MheRFHVRuJosiTX/+ThZlxzhdUkZeaBaLo9qLXGaPZ\nyK/Nr1haX/KICml4eoS3ne8dH18tryEtfn937Emwk7ooLT6VmpILbi1EBVGgsa+F/okBVEoVl4rP\nkxqfgiiKvGh9xdTiDKnxKVwpvXRsF/qSJPG06Tmzy3NU5J6hMCP/k/vMrczzqu0tRvP/z96bxsaR\np2l+v4i8M3klyUzeFC9d1EmJOkpSSXVXtbqO7p7e9YyxX2ZhGIZh2PB+WCxsrNuGjQF2YBg25pPt\nXewuMNheb8/0dB2qrqtLpfuiSFEUL0m8jyQzSSbJvI+I8IdIBpN38kgeUj4FFfNiZJDMjIzn/77v\n8wtTXbKPi8fe2LaKdEZ7V6MTYzR1PWZydkq7zWa2caLuKPvL69b1mlYUhT5XPw86mghHw+Rl5XHx\n2PoCsSRZ0oxrJBolnGRkF5jbueuxCNFodEla70oyJNA2khwnFp83wXMoGzWkqQCryTqfPpzUMvyq\nVvXiksSIZ4Te0T6G3CNacnNhbgE1pdVUl+zblrwA76yXlyO9uCbHmAnMaGGFcxIFkWxrFkX5TmpK\nqymyOxFFEUVRaOpu4VlvO2ajifca39GqkbIic6v1Dr2j/ZQUFPNe4zvoV/iMUAMC79Pn6sdkNHHl\nxCXKHKVr7nc0FuXz218RCAX56Pz7u3K+PB3qHe3nZutt9LrUDXDG/CbvxB4yv6CeCHf0dNE3MqDd\nVllSwbH927PSud3aKRTSV3e+1k5uP7nwsw3NG0ZiUf5w60tCkRAfX/jZmgP660UfLZYQDCD6ZjMo\npF2krUAbtTbfpuPRDfY5yrh07h2IRFF0ehRbelN/twuFdL35Bv1jakqqUW/gV6kGv+2A1kIXpUM9\nI73cabuPJEscrTnC6QMnkRWZ7x/9yNjUOHVltVw6/kZa2hGf9jzjcXcL5Y4y3mt8e8FzKIrCs95E\nGIvAK8+czCg9CoaDPOx8zMD4oMY41Yk6akqrOXPoNCZj6p0ykViEpq75QKx9iZlQSZYXVGXnzGty\nlTbVqqwgCJgMRkwGEyajCZPBhDnxdcH1BbcZ0Ynzn+fRWJTRCRfDnhGGPaOEIiFt2848B+XOMsod\nZdiz817J95Msy7gmx+hz9dM/NqgFZ+XaclTDW1pFrm3zrOjVnn90Qn1+t9eNP+TXeMBz0uv05GXl\nUlpYQl1ZzbKYucUoow/OvLOk7V6WZa633GBwfJgKZxnvnHprybn61KyX6y03mQ3M4rQ7eOvkm9jW\nkeo/PuXmj/e/w2q28tmbH++aALh0q881wI0nt9CJOj448y5F+c5VH58xv8k7scfM75wi0ShN7c1M\nzajD/zpRx9H9h6ksqdjhPdt67RQK6T/+8DtC0TCCkEAgGdd/gjs64eLbhz+Qm5XLpxevrjmjsm70\n0SIJ4TDC7HQGhbQLtGm0UTSKp/85N77/eyxmKx9e+jl6iw2s2/c3TScKKSpF+YefviCYOPErsju5\n+saHW7LtrdZ60EXp0NSsl+vNN5gN+ijOL+KthjfR6/R88+B7JmYmqa86xNnDjVt6ouz2evj6/rdY\njGY+u/TxAvxSNBbl1tO7DI4PYTVZeKvh8ponHhlltJpkWaa9v5P2vk7NDIJaATxaXY/VbF3RuM4b\nW7XNONV5WJ2ow2Q0YZ4zqcmXF5jZebNr1Bu39H2mKAqTs1OqEXaP4Jme0O6zmq2UO8ood5ZRWlC8\npzsqFEXBMz1Br6uf/tF+QtEwoP6MNaVV1JRUk59jT4vZj8fj9Ln6GRgfYmJmcsHra04mo4mC7Hwq\nisqoKa3GbFy9yzASjfCnxz8x7nXjtDt49/TbmI3LFxwkSeKHx9cZnXBRVbKPKycvaa3Myaz3I9X1\nNB5s2FAhq+V5K09ePn1t8Edz6ncN8FPCAL9/5p1VK98Z85u8E3vU/M5pcsZLc8cTwpHEgcRipbG+\ngdzs9K2a7YR2AoW0VQik++0P6Rzo5kj1Yc6usc8bQh8tVgaFtCu0YbRRNIoY8BHxzfLt939HIBrh\n7Usf4SzZuTbgrUYhjU+6+ePD77SZrsaDDRyrPboVu7ql2ii6KB1KNpwWk4W3Gy6Tm5XLH+9/y7R/\nJuXxilQUiUX4/NY1guEgH557bwGfd2rWy4/NN/AlGfHdWqnPaPcoLsWXmYcNJxnZqHa/PxggFF1q\nUFaTMVGNureEVQAAIABJREFUnavCGg1G/EE/npkJFEXBnp3H0ep68nPsmpHdzsCkVBWOhhnxjDLs\nHmF4YpRoYtZUFEWK84s0M5zOyuhWyuubpne0b1vRRMFwkJfDPQx7RvH6ponGF87rCgjqvG5eIVUl\n+6goKkMvpv5a8AV9fP/oR2YCs1QV7+PNExdXbGeeU1yK893DPzHudVNXVsv5I2d40PGIF8M9GPUG\nLp24yL6ijRevZFl+7fBHcxoYG+R6y801DXDG/CbvxB43v3PqGeqjq++51jbkzHdwun5zYPndpp1A\nIflDfn53/R+AjSOQ4lKcz29fYzYwy8/OfbAgrn45bQh9tORJ46oBNhqQHU6U7NwMCmkbtSG0USSC\nGPAjxKIo0Sg3Hv5I74yHE/WnOVm383zbrUIhNXU109bbDqhzVB9f+BkFuSkmnG+TtgJdlA5p3Meu\n+VbjquJKvr7/Hf6QP2W82lrPcb35JgPjg5ysO07DgRPafckt2MdqjnDqwMlXctwmo5WlhjzFiETD\nCSMbXbmlOOny3CznWhIFUWsVNugNBMNBguGQNlsrCgJOu5OjVfVkZ2VjThjdlV6HvqCPe88eMjIx\nqgZi1R3jSE39gjbk3SpZlvHMTKhG2DPC1KxXuy/bmk1Foj26OL9oVyXibzeaaHJmkpcjfbgmx5gN\nzC55rYmiSLY1m+J8J7VlNTjzHBs23BPTk3zf9CPhaJij1fU0HjqV8raisSjfPvyBiZlJTAYjkViU\ngpx83j51eUtSyl9H/NGcBsaH+Kn5JqIo8F7jOwsWbOeUMb/JO/GKmF9QTVZrVxujnjFAnR/ZX1nL\nwer0twhvp7YbhTQy4eK7hz8AUFpYwodn31v3NjzTHq7d/Rabxcpnlz5eFhUypw2jj5ZuCNE7iSCK\nCRRSfsYAb5PWhTaKhBH9foR4DGJRlGic9rE+7r98SklBMR+cfXfXpHRuBoUkSRJf3f2GKZ8acJNt\nzd7QbHu6tdXoonRoccjUidpjfPvoT4QiIS4dv8D+Taz6dw10c6/9IUX5Tj46+z6iKCJJEg87m+ga\nfL4gfCujvS1ZlpcEO2mV2WXbitUKbarnbga9YcF87PItxQsvL8eBlWWZrsHntPW2L0DMFOYWcObQ\n6TUXlOcCsR52NBGKhsnLyuXC0fN7rlU/EA4y4hlhyD3C6IRLm1PW63SUFJRos8JZ65gX3SptF5pI\nlmWGJ0bpH+1n3OshEA4seT0a9AbysnIpKyyhrrx2y/BXQ+PD/PTkJpIkc7a+kfqqQ+veRvfgC+4+\nuw9AQU4+V9/4aM2q8Xr0OuKPQB3R6h8f4HrLTQCunLpEUb4TGQVZkZAVGSkuc+bt8xnzC6+W+Z2T\nPxigqb0FX8AHqO1ADYeO4SzYWwf61bTdKKT2vg4edj4G4GjNYc4cWn/LdfPzJ7S+bGN/eR2Xjq9e\n0d0w+mixklFIDieyPT+DQkqzUkUbCeEQQiCgmt5oFDkWRzEZmQgHuHbvG4x6A59d+nhbki7Xo42g\nkHwBH3+4/aU2M3ugvI6La7wHtlvpRBelQwvwQlm5NB5s4PbTu0RjMd46dZmqDZjTqdkpvrr7R/Q6\nA59d+jk2iw1/KMD15htMzExiz7bz9qnLe6bl8nWRoihqW/FaxjVRpQ1Hw0RiUS1oaC0JCBiNxgXm\ndXHI07y5nTe76aiuerweHnY+xj3t0W6zmMwcqarnSPXhVU/2I7Eoj7tb6B58DsCBijoaD53aNnzO\nVkqSJMa9bm1WeCYwq91nz87T2qOdeY60GaDtQBNF41H6RvsZHB9mYmaScGJWOFlmo5mCnHwqisqp\nKaleV0haquoa6OZ++yMNZVS5zhZlSZJ42KWm9+t1Ogw6A6FomFMHTnKi7tiW7uurgD9SFAUZGUmR\nkBUFBVk1sIqcdFlCRkFJmvEfnXBx++k99fP7yFkK8/KRFEntG5Hg3Y8+yJhfeDXN75xcnjFau9u0\nWP3crBwaj57Can415rO2G4V0q/UOL0d6AXjz+EXqymvW9f2SnKh8zU7x7um31jx4bgZ9tFgZFNL2\naVW0kaLMm14pPm96zWYwGonFY3xx+xqzQR/vn3mHcsf2BCqtV+tBIXUPvuTus3va9XdPvUVl8e4J\n5tsudFE6JMsyj7oe09HfhV6n53jtUZ72PEOWZd5rfDslVMacYvEYX975mpnALO+dfpuKonJGPKPc\neHKbSCxCbVkNF46e25Vzkq+SZEUmmph/XW4eNhwNJ5nYefzO3MjTWloS8pSUSJxsaJMvb3XI01Yo\nEo3S1P2Y3tE+bVFNFEX2FVVw9nDjqouGbq+Hu8/u4/VNYzaaOXu4kZrSql33M65HswFfIj16hLHJ\nMaTE68GoN1LqKKHCUUaZo3TT8/mro4mqqC6p2tSCrS/op2eklxHPKF7/9JIFGkEQsJmtOO0Oqoqr\nqHCWpbW6uRrKKFX5gj5+arnFxMwkeVl5vH3qMnqdnj/e/xZ/KLAl4yrJ2q34I1lRTauMjKwkKrJL\nLqsGlySEmKIo6u1y4vsTlVwFEBARAAHU0QhFYHJ6itaONgRB4OzR0xTnFyEIAkpcofG9TOVX3YlX\n2PxCol2o7zm9w/3aqlx5USknDh57JdohthuF9OWdr5lInCR/evEqBetMvvX6vHxx52tMeiO/uPzJ\nqomCm0UfLZYQDCD6fSh5eRkUUpq0ItpIURBCQdX0yhJKJIIiySgmEyRWqRVF4VbrHXpG+zhaU8+Z\nHQhVWo9SQSH90HSdIfcwACaDkV9e+XRDqenp0k6gi9Kh3tF+7rTdIy7F2VdcydD4EKIo8sHZ9yiy\np9bxc/vpXV4M92jJ0a0v22h50YooipyrP8PBiv172hzshOKStGI78eLU4uS24lRl1Bs145paavHu\nDHnajGRZ5sVwD0972vCHAtrt+Tl2zhw6RWnh8gtAsizT3tdJy4tWJFmitLCEN46cJecV6GqIS3Fc\nE2MMJ1qkA+H530thboHWHl2YW5DSezqdaCK310PvqDqv6wv6l8zrqhzkbIrzi6ktrcKxDnbzZpUK\nymgtDY4Pcav1LtF4lLqyGt5IWkCcDczy9f3vCEVCXDx2ngMVWzeiuF34I60Cq8goKNrluYrsXHVW\nXsbQSopEXJZRFBlZVh8HCUMrKImHCwiKgIiIKIroBR2iKCIirvradU95eNTWDMCZY6dw5jsy5nfB\nTrzi5ndO0ViUxx1PmPCqxk0nitTXHqaqbO/PbW03Cum3P/yO8CYQSG297TR1NbOvuJK3Gy6v+gbe\nLPposYRwGGHGi5CTm0EhbbGWRRstNr3hMIqioJjMS6rvL4Z7uP30LoW5BVx948O9EciyAgopGo3y\n+5ufaziLkoIiPjr3wQ7v7bx2Gl2UDk37pvmx+QYzgVlys3KZ8c9g1Bv52fn3yV8jN2BuTqwgJ5/3\nTr/NnWf3GfaMYDPbePvU5XVXOl41zYc8LTMbu4qRnXt9rSVBEDAbzZqJXb2t2LRmyNPrqsmZSR52\nPmZsaly7zWw0cbjqEMdrji77+/IFfdxrf8iIZxSdKHKi7jhH90ggVipSFIVp/4zWHj3udS/IMyh3\nlKoopcLSBQYpHWgiWZYZHB+if2wQz7SHQCioBZnNyag3kJdo264trSbLuvVs+VQUiUb4U/NPjE+t\njTJaTrIs87i7hWd9HehEHeePnOVARd2Sx037pvn6/ndEYhGunLxETWn1lv0MG8EfzbUbL20xXr3d\nGNCqs5IsoySZYEEQQBEQEn9rRVHrtaIgohNF9IIeURC3PNvEMzXBw2ePQYHGo6dw5hZmzK+2E6+J\n+Z2Td8bL444nhBJoJIvJwukjDdhzlgK895K2E4UUlaL89vvfIcsyBp2ev1gnAklWZL65/z3jXjeX\nT1yktmzl9uktQR8tViyKOO1FsFgzKKQt1AK00ZtXEYIB9Z+UML2AYrbAMrPpM/4ZvrhzDUEQ+ezS\nz7csoGO7lIxCOl57lJYXrdoJ1tnDpzlSXb/De6hqN6GL0qFYPMbtp/foHxvAoDcQi8cwG81cfePD\nFSszM4FZvrh9DYDLJy7ysLMJfyhAaWEJV05eWpN3udcky3IKvFh1Pjb5/lTPV/Q6/RLjuvJ1dT7W\noDdkqupbqGg8SnP3E14M92ihUKIgUuEs41z9GWyLAqEURaF/bIAHHU2EIiFys3K5cPTcrmkX3UpF\nY1FGJ1wMuUcY8YxoplYQBJx2B4U5BcSkGK6JMXyhzaGJItEoPaO9DLuHmZydIhyNLHmMxWSmIKeA\nfcUVVJXsw6hPT4VyPdoIyihZgVCAn57cwu31kGPN5u1TV8hfJTBxYmaSbx58T1yK8/apK5tCHiVr\nDn807nVz8dh5qsuqVm03XmxoF7YbK8hKPFHBVRuN1VdB4rioCJqB1Qs61dgKuh0/rnm8EzxsewyK\nwunDDfz8H3+aMb/w+pnfOfWPDNLe06nNCTnshZyqP7FqCvFu13aikHwBH3934w+Amlr767d+sb7v\nD/r4w62vEAWBX7z5yZIP42TNo4/2c/HY+U3tt6Z4XE2CNpuRCwozKKRNSkMbBQP8+sP/jCxRlzC9\nIRQEtcK+wodnXJL46u4f8fq8vNVwmeod5PluRgNjg/zYfEO7Looin138OXnZeTu4V6p2K7ooHVIU\nhY7+Lh51PdYMm9Vk5ecXPlqSAitJEtfufcPk7BT7y+voHe1FkmVO1h3nxP5juyZlfDmtFPKkzcMu\nxu8kLm8m5Gm+AptcoTXPhzwZTK/c62mv6+VIL09etGqMWYC87DwaDzZQ4Sxf8NhILEpzdwtdyYFY\nB09hWkfFby9JURQmZ6foGeljYGyAQFKSNqjnNjWlVRypOpzS72A2MMvL4V5GJ1xM+6eJJRYe5iQI\nAlkWG067k+qSfZQVlu667oXNoIxADSu90XqbSDRCVck+Lh49n9J59bjXzXcPf0BWFN47vXZew9z8\nrBrmpCypyM5d9gVn+ebhDyiKwodn3yPLYlul3ViHIMhL2o0FUcAg6FNqN96NmvBO8qBNJTj85je/\nyZhfeH3NL6irQk+62xgZHwXUA1NNeTWHqvfvugPSerRdKKQRzwjfPfoRgDJHKR+ceXdd3z8XeV9a\nWMIHZ95d8YAyhz6a8c/y6aWra7YwpqwMCmnL1NJ8m46mm5yoO8aJ+tMokTCKwqqmd0732h/SNdC9\ntYsb2yxJkvji7tdM+6a12zZy4pAO7QV0UTo0PuXmestNQpEQsPw889xYRY41m9mgD6PByOUTl6jY\n5vZvRVEWhDqtXZVVv0rrDHmaq7aqhta8JOTJtKiteKdfuxltnaZ9MzzoeIRrckxrtTUZjByqPMDx\n/cfQi/MdOWog1gO8Pi9moykRiFX9Sr0elkcTCeRl29GJOqZ908QkdaFIJ4oU5xdT7iyl3FFGji0H\nWZbVeV1XH2OT4/hC/iWhazpRR64th5KCYmrLqtedkbLdSkYZnas/w+Gq1JP+ZUWm9UUbT14+RRRE\nzh5u5NC+Aym/ZhRFYXhihB+afkRG4d3Gt3DYC5MCohJmF3nZdmNZkYlLy7cbuzyjPH3ejj0rj3NH\nz6DT6dLabrwbNeGd5GHbY/7l//QvM+YXXm/zO6dgKEhTewszfjUq36A3cPLQMYoL927Lz3ahkJ71\ndvCoS0Ugrbd9UlEUfmi6zrBnhPNHznJ4FaTKlqGPlu6EikKKx1UDnEEhrU+SRNAzxjd/+HcYDQau\nXvkUnd6IYrVBCgtIc9XSvKw8Prn4sz0ZRjPjn+Xz219pQSU1pVV4pifXhUJKh/YauigdCkZC/NRy\nk/EpNwA5thw+ufAzjAYjg+ND/OnxT4iiiCzLFOTk8/apK2RvcsZOSoQ8rTUPG45GiUTDGwh5MmjG\ndT3s2IwyArVDrPn5E54Pv9S6AARBoNxRxrn6Rm3kRJZl2vs7efKilbgkUVJQzBtHz+1pzNd60ESy\nLOOZntBCs7w+r7YdQRCWHQMwGozYs/KocJZRW1az6zB9q2kzKKNQJMSNJ7dxTY6RZbHxVoOakzAX\n6rRcurGCvCQcCmDU4+JW2130oo5LJy6Sm5WrtRsnpxuDgoCAorCk3Xg5Q9vc0cqIe5T9+2o5VH1g\ny35ve0kTk5N8+GdXM+YXMuY3WWMTbp50PdU+EHJs2TQePYVtj4YibRcK6WbrbXpG+gDWnOFdrGA4\nyB9uqfzTz978eNUP1q1EHy2WikIKoRQkUEhpZCa/EpIkhIAfIRzi/r3v6R/p43TDm9TWHUm5eu4P\n+fn81jUkWeKTi1ex74L24PVqriUf1Cmg9xvfocxZti4U0lZrL6OL0iFZlmnqbtZSrXNsObzX+DZf\n3L6mzUMeqKjjXP3ZBXNtiqIQi8dWnoedM67RCOGkqm18UavjShIEYU3jutDcqq3Fe7krKaPdpb7R\nfppftDKbxMjNteVw+uBJ9hWr4ye+oJ/77Q8Z9oygE0WO1x3jWPWRPXMs2SiaKBwN83Kkl2H3CFOz\nXm0RcbEEBOw5edSV11JVVLnqCNdu1HpRRovbjV1TY9xovU0wGqS0sIRzR86g1+uXTTeWFZmYLKEo\ncqI1WTW8C9ONYdzj4enzZxh1Ri6cOEdedu6m241j8Rg3mu4QCoe4cPIcBXlb1EG4h5RJe07eiYz5\nXSBZlnne/4KXQ33ayl6ps4SGQ8f35EnHdqGQvrh9jcnZKQA+vfhzCnJTP7D0ufr5qeUWjrxCrp7/\ncMXf81ajjxZLQyHZ7aoBzqCQlioeRwj6EUMhkGU8Y0Nce/wTuQVFfHLp5yl/OMmyzNf3v8Mz7dly\nxMF26ftHf2LYo45MmIwmfn35FxiN87NNqaCQtlqvCrooHepz9XPjye1E65x6AiwApYWl2Ew2jS0b\njUWJxtSwp/WEPK1sXI1J182ZkKeMdp1mA7M86GhiZGJUe80b9QYOVh7gZN1xdDodA2OD3O94pAZi\n2XK4cOz8rg3EkhWZsclxekf7UkYTTftmeDnSw+iEi5nA7JJFLFEQybJkUZTvZF9RJYIAIxOjDHtG\nFywe5GfbNZSSI69wV583SpLEzdY79I71kW3N5t3GK1gt1kU82uXbjRVFoWOgm2e97QDUVx2kurRK\nXfwWSARAqY9bnG6sE/To1mg3HnIN86S7DZPByIWG82RZN7+oMDXj5U7LfSwmM1caL2FYRJx41ZUx\nv8k7kTG/yyoaj9Hc8QTP1ASghtfU1xykurxqZ3dsA9ouFNJvf/hPhKMRBEHgP3/3Hy8wAmvpRsst\nel39nD5wkuN1x1Z83FajjxZLCIcRZqchJwel0KmmE2cEsZhqesNhkOIokQiyqOOr1lt4pie4ev5D\nivJT46kCPO5u4WnPM6pLqrhy8tKeMgHRaJS/u/kHIonkztXm3VdCIW21XkV00Vbr8fMWWvpaCUpL\n8SLJMogGjEYjFqNFDXZKMq7mBaFP5sS8rBm9Tocw958gJHJAE/8XBK1qkfyYjDLabYrLcZ68aKN7\n8DnRRCu+gKBW9OrPYDGZefz8CV0D3QDsL6+l8dDpdSFw0qX1oIlkWWZsapze0X7Gp9z4Q/5EpXJe\nep2eXFsOpYUl1JZVY89eOSNhNjCbQCmNMjY1ps3iGw1GygpVlFJ5YSlm0/Ykx8/hetS24uQW4/nL\n4WiYG09v4572UJhbwKXjFzHpDcumGyuAIIgICoBCLBbj2YtOJryTmA1mTh8+SWFewZbPz/aNDPDs\nRQdmk5mLDeexbsH5WHffC54PvKTUUcKp+hOv1bE4Y36TdyJjflfVjG+GpvYWgmE1NMVsMtNYfxJ7\n7t4Ki9kOFFJUivLb736HrMgYdAb+4r1/lHJ1NhKN8IdbXxKORvj44s8oWCHUKi3oo8XKoJDmFYsh\nBnwIkUjC9EaRdXqwWjU2anXJPt5quJzyJkcnXHz78AeyrVl8evHneyphfcQzwvePrmvm6Vz9WepT\nCAVJRiG91XB5ywKVXnV00WY1OTPJj09vMO5za9VeEREj6or/XMqnssxXg95AlsWG1WLFZrVhsyT+\nmS2IwiKjKwiJ1j0BnbjwvpVPrpIeo15bxiCrl8VFty8214vvyxjsjDarwbEhHj9vYdo/o92WY82m\nYf8Jsm3Z3G27z5TPi8lo4uyh09SW1ezIa87rm6Z3tI8+V7+WaL0YTSRJEv1jgwyMDzIxPUEwEYKX\nLJPBRH6OWrWtK6vZMOIsFo/hmhxj2DPKsHt4QYK0I6+QckcZ5c4yCnLy18cIXibdWDW4idTixOVU\n2o19IT+POpoJhoKUFpRwfL/axi4gIipqurFe0KETdUvajb2z0zxubyEUCVNoL+DU4RNpTQN/OdhD\nZ+9zrGYrFxvObXoBQZZl7j55gHd2mpOHjlNR/PosEGfMb/JOZMxvShp0DfHsRac2L1KQl09jfcO6\nqps7re1AISUjkHKs2fzZOhBIw54Rvn/0I3lZeXx68eqKxjkt6KPFWoxCytl786ibUjSqmt5oFOIx\nlEgMWa+aXlA/4H9/8wsi0TC/uvJZyu28oUiIz299RSQW5eobH646W7TbNJdKDWqK52eXfk5uVup8\n8IGxQa3t9o0jZzlYufHQjdcJXbReSZLE/a5HtA91EJbDmqE1YqSsoJTGww0Y9UYURWHCO8mgawjX\nxDiKoqaD2ixW9HoD0WhEW/RMlgBYrQlDbLWq/yw2rBYLoiiqKeeKgiIoKLKCepqhwNxMW+K0Y+6i\nAigKIKh7Ki5jhufMNYJ6v7hBgy0K4rLmeiUTnaleZ+QL+nnY2cSQe1hriTbo9dSV1WIxWXna83Q+\nEOvIOXKz0h+I5Qv66XP10zvarwVR6XV6KosqqCmtxp6VS59rgGHPCFM+r1bFnpMAWMxWHHmFVBVV\nUllckZZQOEVRmPZPM+weZcgzjNvrWZC6X+YoodRRQlFBEXq9btl2Yxk1KCpZWrqxLKPIkladnWs3\nnpuf1dqNEdHp1HZjn8/Ho2fNRGNRaiuqOVxzMKX3sqIo9I8M0N7ThaIoHKiq48C+um05DnT1PefF\nQA9Z1iwunDyHaZPn3cFQkBtNd1BQuNJ4cc/NaW9UGfObvBMZ85uyZFmm7UU7g65hQD0tqC7fx+Ga\ng7t6rmOx0o1CGnGP8F2TikAqd5Tx/pl3Uv7eu88e0D34nGM1R2g8dGrZx6QNfbRYkoQ4PfV6oZAi\nEcSAHyGWZHoNBrAsrLC3PG/lycunHK89yumDDSltWlEUvnv0J0YnXJw5dJqjNfXp+Am2XJIkqa+3\nxFzXWoszq8nt9fDD4+tEohGO1x7l1IGT6z55eF3RRWtpdGKUG89uMxGcREZtOxQRyTXlcrLuGKWO\nkhW/NxKNMDw+yqBrCH8wAIDVbKG8uIyCXDuxeBx/MIA/6Ne+zrWYJ8tsMpNltZFlzUp8VS+bjaZ1\nIT+0/5T5WrR2Uiwn36ckGWcFreKjmdfENhP/n9vactXmTPU6o9UkyzKtL5/SOfB8PkEecOQ5EESB\n8Sk3oihyovYYx2q2PhBreTSRSJmjFKfdSTAcYNzrZjYwu+S9KYoi2ZYsivKLqC2twml3puWcba12\n41A0zOiki5GJEUYnxwjH1NZsAQFHXiFOu5MiuwObxYrMXLuxgKDMLZORmKVVF7H0og5dUsLxWhqf\ncPO44wmSLHF0fz3VZftS+rli8Rit3c9wecYwGoycOnwCR/72LVwrikJ7Txd9w/3kZOVw4cTZTc/r\nDo+P0NL5lLzsXC42nN9T5/AbVcb8Ju/EIvMrSRLDoyM7uEfbp/LSsg0doEPhEE3tLUz71HYgvV7P\niQNHKXWufHK125RuFFJbbztNXc0AqxrZxYrFY3x++xq+oG/VOdK0oY8WS1EQZ7wIcenVRiFFwoiB\ngGp6Y1HV9JqMsMyMjT8U4Pc3PsdoMPJnVz7DoE/tQ+hpzzMed7dQ7ijjvca398SJ7bRvmi/uXNNm\nuOqrDnOufnPjArOBWb579OO6UUgZdNFSRaUot9ru8ML1kogyP6NoEkxUFlVwav+JdR3jFUXBOzvN\noGuYUbdL6/QpKnBQWVKBM9+RqO4qRKIRzQj7koxxOBJesl2dTrfEEGdb1ZZqnbj9x5M546xVjJi/\nLivyrq1ei6uY60z1evs07B6hqbsZbxLX3Gw0I8kSsXhMDcQ6ep7igs0FYmloIlc/oxPzaKL8bDs6\nnY5QJEwgHFgSTGfQ6cnNyqW0sIS6stpNVaOXr8ZurN14Ia5HYcY3g8c7yYR3Cp/fp70ubUYbRQVO\nigucFNgLFqTQb1T9IwO0vehAFEVO159MGeU545/lcXsLgVCQ/Fw7p+pPYtmm2eVkKYrC0+fPGHQN\nY8/J4/yJM5uu1r9u+KM9a34FQfgI+D8BEfg3iqL8q0X3//fAfwHEAA/wTxVFGVqyoYXfs8D8DgwN\nYnVkU11dva5922vq6+sj6PGxr2LjyBz31AQtna1aS022NYvGo6e2JJVuO5RuFNJciBXAlZNvUlNa\nldL3jU+5+fr+t2Rbs/js0scrmqt0oo8WS/DNIobDrxwKSQiHEAIBhHgMolGUWFw1vat8uN14cove\n0X4uHb/A/vLalJ7H7fXw9f1vsRjNfHbp420L/tiM5uZ0QT19fv/su5QVbs0C13pQSBl00VL1uHq5\n03GPmcisVuXVocNuzaPxQAMFW5BoH4vHGHW7GHQNawudJqOJiuIyKovLsa1wnI/H4/hDyVVi9XIg\nGEBe5jPfZrEuqharX/fSLPxibUX1es7YattM/H+nqtfLGe/XvXodDAe53/GIofFhLTAqmYFbV1bL\nmcOn1jU/uxKayKg3oCgQk2JLvsdsNJGfk0+Fs5ya0qo1n0/jyyoyCsoC3qy84PJCQ7tcu7GMOi4x\n124sKAKywpJ2YzFp8WU5RaIR3FMTuCfduKcmtLRpURApsOdTlO/EWeBYN3pTURQ6e7vpGerDaDBy\n9thp7CmMcSmKwtDYMG0vOpBlmbqKGg5W79/RCqmiKLR0tjLidlGYV8DZY6c39Rn4uuGP9qT5FQRB\nBJ4NTkU+AAAgAElEQVQD7wKjwCPgzxVF6Up6zBXggaIoYUEQ/ivgLUVR/nyN7S4xv0fOHufAgVd7\nFeT58+e0P3y6KfOrbav/Jc8HXs4D0x3FnDx0LC0zJFutdKOQPr91jSnf+hFITV3NtPW2c7BiPxdW\nmOtNN/posRagkAqcsIfmvRdLCIcQ/H4EKQ7RKHIsjmI2r/kzub0ert37hoKcfD65eDWlE7tILMIX\nt6/hDwX46Nz7lBQUb9WPkTZ9+/B7RifGALAYzfzq8mdbPt+fCgopgy6aVzAS5HrrTQYmBomhngAL\nCJhFM/vLaqmvOpS2Y8CMf5Yh1zDD4yPE4upJaUFePpUl5ZQUFqf0vIqiEAwHFxjiua/R2NITeqPB\nuGwLtdVseaUNVaraiuq1kvi6V6rX2sz2LjPXsizzrLed9v4uwtGFnQ8GvYFz9WeoWyUQawGayDVA\nbBVWtoA6l+/IK6SqeB+VRRVqgvOiFmM5wZGdvywhoyzA9cw9d1xKfJ8iJQKltrbdeL2SZRnv7DTu\nKQ/jkx58AZ92n81io6jAgbPAQUFu/qpmVJIlnnS1Mep2YbPYOHe8MSXzHJfitD3vYHh8BIPewMlD\nx1KuFKdbsizT1N7C+KSbogIHjUdObcqQv074o71qfs8Dv1EU5WeJ6/8CUBZXf5MefxL4G0VR3lxj\nuxnzuwWKx+M0d7YyPukG1A+pQ9UHqK3c/RX0dKOQ/sP3/4lIbH0IJEmS+PLu13h907zf+A7lK6Tj\npht9tFh7GoWkKPOmV5YgHFYrMCZTSkZeURSu3ftmXWgjRVG43nKTgbFBTtYdp+HAia34SdKmUDTE\nP9z4gkiim6PCWc57jW+n7flWQiFl0EXzetbfwaMXj/HFfFrVT4cOR7aDs4dOkW3bvjR2SZJwTYwz\n6Bpiclpd1DPo9ZQVlVFZUr7h9spINEogtNAQ+4MBAqHgkseKgohNM8NJ5thi29LRldddO129FoWN\nB5stZ5BV2712a/hmq9euyTEedT5mcnZqwe3Z1mzePXVFyyaYQxO193cxND6kVXjnpNZUlcTr3ary\ndUsqKcgtUKuzSQZ3uXZjFdcja5Xc+Xbj+b8EioBO0CEIK6cb7waFwiHGpzy4Jz1MeCe135VOp8Nh\nL8SZ76CowLGgoyoai/LoWTNTM17sOXbOHjuVUjeJL+DncXsLvqCfvOxcTtefxLrOanO6JckSj9qa\n8XgnKHUUc6p+/dkZyXpd8Ed71fz+GfChoij/ZeL6PwHOKory367w+L8BXIqi/NUa282Y3y3UrN9H\nU3uzdtJiMpo4XX9y17dTpBOFtACBpDfwF++mhkCamp3iyzt/xGQ08cs3P1k2Tn9b0EeLFY2oKCSr\nDdnhRLGllnS8Y1IUhFBQbW+WJZRIBEWWUUxmWMcq50bQRl0Dz7nX/oAiu5OPzr2/q0MlBseG+FPz\nT9r1C0fPbSqReT2aRyHp0OsMC6onryO6aNY/y49PbzAyPUI8gSgSELDpbRyqOMjBfXU7vIcQCAYY\nHBtmaGxEYz7nZudSWVJOmbMk5Vn41STJEsFQcMFM8Zw5llYJ3Mpe1EJtWkfgVkbbp7mApGRzvdur\n1+KK5nhh9TocjtD8vIWBsaEFZt9msiGIAv6QHwkJZdF/OlFHTlY2xQXFVBVXkmWxoShqa3JcTszO\nytKSduPF6caiKKIX12433muSJInJmSnckx7cU54FC2Q5Wdk4853kZmXT3f8CfzBAiaOYhkPHUzrn\nGh4f5Wn3MyRZorpsH4drD+5IJkEqiksSD54+YmrGS0VxGScOHtvw3/h1wR/tVfP7a+CDReb3jKIo\n/90yj/0nwH8NXFEUZWk/1cLHrml+4/GVW1A2oq1anf7yyy/p7Ozkn//zf77u702X+Z3TkGuEtpft\n2glKfq6d00cadgUMfiWlE4U045/l9zc/ByDHls2fXUkNgfT0ZRuPnz+huqSKtxqWb2LYFvTRYsXj\niN4pBLMJucCBkpM68mbbpCgIwYD6T5ZRQiH15Gidphc2hjaamvXy1d2v0ev0fHbp412NE7jz9D7P\nh18AoNfp+MWlT7a9ovj1/W+ZSJrrfd3QRZIk0dzTytO+NgJSQDthNmCgOK+IM4dP70jQylqSZRn3\nlIdB17DW+aMTdZQ6i6ksqcCek7flJ96KohCORpYY4pUCt/QLArfm26htFtuuXpDKaHPabPV6/nW7\nvup1NB4nEAoQCAWYCczimhwjEA6suJ9mg5nC3HxqK2vJtmat2G6sE0X0gj5t7cZ7Uf5gINEe7WZq\nempBrkCW1UZdZQ3OfOeqeCBJkmh/2cmAawi9TseJg8f2RIBrLB7jXusjZnwzVJXt42jd4Q0fa18H\n/NFeNb/ngf9ZUZSPEteXbXsWBOE94P8CLiuKMrl0S0u2u2An/vEv/hH/67/63zTzG4/HGRqStuwE\nTJIkKip0O96elW7zC4k5mJcdDIzOZ45VlVZypO7wrj7hSBcKadA9wp8SCKQKZxnvNa6NQJJlma/v\nf4dn2rNiaNa2oY8WS5LUJGhBQHE4kXPtuwOFJMuq4Q0FESQJJRxSKwhW24aTqteLNorFY3x552tm\nArO8e/otKosqNvS86ZYkSfzDrS/xBdWZKnu2nU8u/GxbDedidNGcNopC2mvyTHu4/vQWbr8bKVHl\nFRHJNmRztKaeqpL0htltpUKRMMNjIwy6hjRGcJbVRmVJBeVFpct2r2y11hO4JSBgtViWzBXv9cCt\njNIvRVEIhUP4An5mgz58QX8i+dxPNB5FSbLJi7+KqOc/SbVjtTqbMNBGgxGbxUpedi6F9gIK7QW7\ntgK5mzTqdtHS+RRZkdHr9QsKV/acPJz56qxwblaO9rkSCAVoan/CrH+WHFs2p4807JnQVlDbu+8+\neYAv4KeusobDNRunH7yK+KP/+9/+v/w///5fL7htr5lfHdCNGnjlAh4Cf6EoSmfSYxqA36G2R/ek\nuN1VK7/xeJzR0a2r1sbjcUpL197ewMAAH330EefPn+fu3bucOXOGv/zLv+Q3v/kNHo+Hv/3bv6Wj\no4Ompib+5m/+hr/8y78kJyeHpqYmxsfH+eu//mt+9atfrbj97TC/cwpHwjS1t+CdVbEAep2e4wfq\nKSvava0V6UIhzVVygZSN1Exgli9uf4VO1PGLNz/Bal46f7Jt6KPFWoxCyi+AnTpgyjJCwK+aXllG\niYRV02uxbgrPtBG00e2nd3kx3EN91SHO1Z/Z8HOnU5MzU3x1949aSul2txevhC4qLSzZEAppL0mS\nJO52PKBzpJOwHNFOjI0YKXeUcfbQ5lI8d1qKojA5PcWgawiXZwxZUatoxYVFVJaU47AXbvuixkqB\nW76An1g8E7iV0fKSJCkxj74U6yXL8pLHGxNdRckhbvm5dsqLyihxFGv3AwTDIdyTHiZnVNRPKBLW\nUo4XSxRFzEYTWdYs7Ll5OO0OcrKyXwmDshVajDIqKnDiC/gZn3TjnvLgnZnWjrMmowlnvgODwcDg\n6BBxKU5lSTlH6+r35HE3HIlw98l9AqEgh6oPsH9fahSK5fQq4492S+V3XU5CURRJEIT/BviOedRR\npyAI/wvwSFGUr4C/BmzA7wT102lAUZTU+kt3oXp6evj7v/976uvraWxs5Le//S23b9/miy++4K/+\n6q/45S9/ueBDeGxsjDt37tDZ2cmnn366qvndTplNZi6deoMJ7yTNna1EohGaO5/S3d/DmaMN29pe\nmaounXiDthc5PBvpwBf38a+/+3dbgkI6XneMKZ+XPtcAT3ueUZCbT1Xx6qD1XFsOZw6d5l77Q263\n3eP9xneWnHyVOUqpcJYx5B5hcHwo7egjTYKAnGtH8PsQPeOIsoScX7i9KCRJmq/0yjJKOISMoFZ6\nt+DE4HF3M5IscfpgQ0rGt2ekjxfDPRTk5NN4MDW+83arraedpm6VQy0IAh+dfY/ibUqhTgVd9PGF\nj/ih6Sd6R/sJhkOropD2koY8I9x6dpvJ0JSGKBIRsZvzaNh/YtNc0N0iQRC0ilU0FmV4fFQzwi7P\nGBaThcqSMiqKy7FsU2ieIAjYLLZEWuzC+yLR6LIt1FMzXqZmvAseu2LgltW2JwgHGS2vha+B+a9z\nHQzJEkVxnlVttiDJMrMBH1MzXs305mXnUuYsodRZsiLazmq2UFVWSVXZ/Oe1nNjWnGHzB/2EoxFk\nWSYYDqmGecpDd9/cmIoei8lMdlY2Bbn5OAscWPdSEOUmtRrKKCcrm5ysbPbvqyUai+HxTuCeVFuk\nh8aGtW3YEu/jYDhEltW25xa3zCYTb5w4y52WB3T1PUen01FTXrWhbR07UM/UrJcXAz047IW7Pq9n\nL2rdnxKKonwDHFx022+SLm/NgOYuUXV1NfX19QAcOXKEd999F4Bjx47R39+/5PG/+IXq8w8fPozb\n7d62/UxVhfYCPrjwDi8Heujuf0kgFOCnR7cpLnDScPjEjreCL9ax/UfIzsrmfvdDIkT4Nz/++y1B\nIb3VcJlp/1d4fV6uN9/kF5c+1hIgV9LBygMMjA8x4hnl+dCLZYOIzhw6zbBnlEddzZQ7yrZvBVMQ\nULJzkEURccKDKMW3B4UkSWqlNxxS25sjYWRBRLFlb1n7tdvroXe0n4KcfOrKatZ8/GxglrvP7qPX\n6bnS8OauXEX+471vGfOqxweLycKv3voUo257WjxTRReZjWY+OveehkK6du/bZVFIe0HRWJQbbbd4\nOd5LVFFTtAUEzIKZ6qIqTuw/uitfJ1slo8FITXkV1WX7mPbNMOgaYmTcRXf/S7r7X+LMd1BZUk5R\ngXPHqlgmoxGTMX/JiZ5a9Qsua4yT8StzygRu7W6p1f/QsiZ3JdxWQW7+/EKHLYssaxZmo4nJ6SlG\n3KP0jQxq1dosq40yZymlzpINt86Kokhedi552QtzNGRZZsI7gcc7ybRvhkAoSDQWJS7F8SXarUfd\nLnihTigbDEasFiu5WTkU5uXjzHfsunOszWo9KCOjwUCZs4T8nDwCoQDe2WmMegNGowl/0E9HTxcd\nPV1YzBaKEu3RhXkFe+bYbDFbeOPEGe48eUD7y050oo59pesftzLoDZw6fII7Lfdp6Wx95fFHO6FX\n612YBplM85UOURS166IoLhvClfz49bSUb7fq9tVSVbaPlq6njE2MMzbp5ps7P3Cgqo4DuyDFNFlV\nJZXkWrM1FNJ/vPu7LUEh/eLNj/kP3/9/RGJRPr9zbU0EkiAIXDr2Bn+49RUPOx9TWlhCtnVhxTw3\nK5fD+w7S0d9Fx0DXtqCPkqXYspB1OsSpKURJSh8KKR5HCPoRQyGYq/SKui01vaC+hx52NgFwrv7M\nmievkiTxU8st4lKcyycukWvbGPYlXQpFQvz+xhdE46oB21dcyTunrmzLc28EXaTX6Xnr1JsaCumr\nu99oKKS9oBcjL7nb9YDZyKxW5dWhw26z03igIWXm96siQRCw5+Rhz8njSO1hRj0uBl3DuKfU1Faj\nwUhFsYpMyrLujkUOnU6nVY+SpSgK4Uh4WWbxhHeSCe/CuBG9Tr9sC7XNYs20raZBcUkiEFyKzvKH\nlm9Vtlms2HPsq859K4rCtG+G3qE+Rj1jWsK52WRmX2kFZc5ScrKy07bIIYoizgInzoKFiL1INJpo\nnZ5k1u8jGA4Ri8eIxqJEY1GmZ6cZGB1UtyGImIxGbFYbedm5OO2F2HPte/I1uBGU0fikh5bOVmLx\nGGXOEo4fOIperycSjWhMYc/UBP2jg/SPDiKKIoV5BTgLHBTlO3Yd8mixbFabaoBbHvD0+TP0Oh1l\nRaXr3k5+rp0D++p4PvCSp8/bX2n80U4oY37X0GYM7G42v6DOPJ85egpfwEdTewv+YIDuvhf0Dw/Q\nUH8Ch71wp3dRkz3XzqfnrmoopG+e/sCUb2bTKKRfv/NLDYH0u59+z5+vgUCyWWycP3KWm623udV6\nl4/Ov78k8fHk/uP0jPTR+rKNurKa7UEfJUkxW5BEEXHaiyjJyIWOrUMhxeMIAR9iOAxSXEUWiXqU\n7PQkTfeO9uGZnqC6ZF9KTN+m7mYmZ6fYX15Lbdnu4lv3jw1yvfmGdv3S8TfYX57+haZgKMS1+9/g\nD/m129YzWywKImfrG7FZbDzsbOKP97/jrYbLVOxS3m8wHOTH1hsMTg4RQ60kCQhYdVYOlNVxuOrg\nnjzR3Grp9XoqSyqoLKlg1u9jcGyY4bEReob66BnqIz/XTmVJBSWOYvS7sPIiCAIWswWL2YIjf+Fn\nVTweX2KI/cEAs/5Zpn0zC7eDgNViXaaFOmvBbGhGS6UoCtFYdGE1PvE1tEyrsk7UJSry8wsQ2bYs\nrBbrqmFSvoCPkXEXI+5RrQXaoDdohjc/176jxsBkNFJRUkZFycJjoi/gxz3lYWrGiy/gJxwNI0kS\noUiYUCTMhHeSl4O9gLrIYzaaybFlYc+148x3kL2LEYbBUJAHbU0po4xkWeZ5/0teDPYgCgLH9h9h\nX2mF9nczGU1UFJdTUVyOLMt4Z6e1WeG5f89QK/vOfCdFBQ7yd+miQbYtm/MnznDvyUNaOp+i0+ko\nLlz/OM3+fbV4vBOMelw4xx2vLP5oJ7RnzO9yPMHNbSu1D/PkA+rig+t6r+9WZduyefvsZUbGR3n6\nvJ1ILMr91kfk5eRx5kjDirMy2y2LxcIvL32ioZAe9D3E6/duCoVk1Bn5xZuf8PubnxONx/j89lf8\n6spnq35PTWkVg+OD9I8N0t7XuaS6azKYaDhwgvvtD2l+3rp96KNkGU3I+QWIXi+ie2zzKKRYDDHg\nQ4hEEqY3iiLq0mZ6QU1rbupuQSeKNB5ae253cHyIjv4ucm05uy7g6lbrHV6OqCc5ep2eX17+JO3t\nw5Ik8dOTWwyOzye9bwZddKT6MFkWGzee3OZPj6/zxpGz28YgTkVPe9t53PMYX8yvharo0OHMdnD2\ncOOeSg/dbuVkZXO07jCHaw4wNuFm0DXEhHeSqRkvz150UF5USmVJOblpfL9vpfR6PXk5ueTlLG1b\nDYVDi8yaenl8MsD4IjbF0sAtdcbU8poFbmlBZYGlJne5oDKT0URBXr72e5trQTebzCn/3oLhEKPu\nUUbGXcwm2tt1oo4yZyllRSU47IW70vgkK9uWRbYti9qK+YVYWZbxznjxeCfw+mYIBANEolEt1CsQ\nCuCaGKejpwtQTb7VbCEnK5uCXLUCuhoyaDs0PTvDw7YmIrEotRXVHK45uOrfNRyJ0Nz5hMnpKaxm\nC6ePNCxpKU+WKIoU5KkjEPW1h7RQMveUhwnvJL3DffQO96HX6Si0F1JU4MCZ79g156qgzpufO97I\n/dZHPG5v4eyxxiWLdGtJFEVOHT7BjaY7tL1oJz8375XEH+2E1pX2nLad2MOc381oO9OeU5Usy7T3\ndNE/MqDdVllSwbH99bvqg2arUUiDY0P8qfknACqLKnj39FurPj4cDfOHm18SiUf59OJV7NkL54V3\nDH20WJKEOD2FoNOpSdDrRSFFo6rpjUYhHkOJxJD1erCmv/VoPWijQCjA57evEZdifHzhKvlrzG9v\nlyRJ4vc3v9CqroW5BVw9/2HaZ5gWo4vMRjMfnX1vzbn2VOT2evjh8XUi0ciOo5CmfTNcf3qDkZlR\nDVEkIGDT2zhSdYi68o0nbr7uCoSCDI0NM+QaJpxoL83NyqGypJwyZ+krN4O2UuBWMBxc8lhRFMmy\nLA3bsu3xwK24FF+2jXxlRJV14Xy1LYssi23Dr41INILLM8bwuAvvrBpyJggCznwHZUWlFBU4d2UX\nwlYoHo+r5m56ihn/LMFQkFgsynJn6ItRTA57AQXbhGIan3DzuOMJkixxdH891WWrh4VOeCdp7nhC\nJBaluLCIkwePberYIUkSkzNTidAsz4L3Z05WjmaE08E234g83gkePn0MApw/fmZD4VWvEv5ot6Q9\n7xnz+ypqN5rfOUWiUZram7WUTZ1Ox7G6eipKynd4z+a11Sik1hdtNL9QEUgnao9x6uDJVR8/ND7M\nD4+vk59j5+MLP1vywbNj6KPFkmXE2WkESVYNsD1/7QTmSAQx6E8yvVFkgxEs29PCvR60kSzLfPPw\ne8an3Lxx5CyH9m2csbeVmpie4Nq9bzWMUSqvqc1qJXTRVv9OZgOzO4ZCkiSJRy8e0zbQTkgKaVVe\nAwZK7cWcOXR6QfZCRpuTLMt4vBMMuoYZn3CrjFRRpNRRQmVJ+Y63nKZbqwVuSfLSjjSLybwss3i3\nBG7NtSr7AksDp0KR8JLH63Q6reKdXAHfqlnpWDzG2ISbEfcoE1OT2vu5MK+AUmfJEjTR66bdhGJa\njDJarZVXURReDvbS1fccQRA4XHOQmvKqLX0PKIpCIBTEPelmfMrD5PSUtuBr0Bs0prAzv3BHmeHj\nE24etTejE0XeOHFuSUdKKnpV8EcZ85u8Exnzu9O7sqImZ7w0dzwhnPhQtFmsnK5vIDd7dwQJtb1o\n59lIBzIyJkybRiFdb75B/5gaTPHOqStr4orutN3j+dDLFauTPzT9yJB7JKVtpVWKoqKQwiGUgsKV\nUUiRMGIggBCLQiyKEo0jm4ywze1EN57cone0n0vHL7B/jerdXIV4X3Elbzdc3hUnmE9ePKXlRSug\nGtCr5z/AaV97ZnmjSgVdtNUKR8P80PQTnmkPxflFaUchub1urrfdxOOf0Kq8IiI5xhyO19ZTUbT+\nVM2M1qdwJMzQ2AiDrmGt4mKz2KgsKaeiuAyT8fVZdFgYuLXQGM9VypO13YFbc1ie5VKVY8t00s2Z\npgX7aFNTlbf6mCpJEu4pDyNuF+OTbi0AKxU0UUaro5iW02ZRTKuhjJZTNBalpfMp7ikPZpOZ0/Un\nyc9NfzdWPB7H451UZ4Qn3Qveh/acvERoljOtoWgradTt4nHHEwx6AxdOnlsS4LeWYvEYN5ruEAqH\nuHDy3J7FH2XMb/JOZMzvTu/KmuoZ6qOr77l2cHXmOzhdf3JXtI/3uwa53/0QCQk9+k2jkP7h1pdM\n+6YB+OWbn5CXvfJBPhaP8YdbXxIIBbn6xoc47Y4F98/4Z/iHW1+SZcnil29+suOR/ULAjxgMoNjt\nyPmOeRRSJIzo9yPEYxCNosR2xvSC2lZ77d43FOTk88nFq6t+SLkmx/j2wQ/YLFY+vfTzXcGhvXb3\nj7inJwCwma384sonacUYpYouSofiUlxDIeVm5W45CkmSJG6136V75DkRJYKCgoCAESMVjjIaD53a\n8ffU6yhFUZicnmLQNYzLM4asyAiCQFGBk8qSCpz5hbtiEWqnFIvHCGjzxPPGMxAKLAnC3Gzg1nLh\nXr6VnksQsFmsS2aYbVZbSvz0zUhRFCa8k4y4R3F5xrcUTZSRqpVQTMud56eKYloPyghgasbL40TB\nxGEvpOHwiR2ZUVYURV0gSLRHz7XRg7rQM1cVdtgLt+08dsg1zJPuNkwGIxcazq/79T414+VOy30s\nJvOexR9lzG/yTgiCcu13X1PsUA1LxvzuTsWlOK1dbYx6xgD1g3R/ZS0HqzeHHNoKeWe8GgpJh25T\nKCRJkviPP/4d0VgUQRDWRCCNTY7zxwffkWPN5rM3P14y8/Wg4xEd/V00Hjq17eij5SSEQ4gz0yh5\neSi5doRwGEGKQzSKHIujmE2wQxUcRVG4du8bPNMTXD3/4aoJz+FImM9vf0UoGubq+aULD9utYCjE\n729+TkxSA2BqSqq40vBm2p5vI+iidEhWZA2FZDFZtgSFNDg+yK2Oe0yFpjREkYhInjmX0wdO4kwh\n+Tuj7VE0FmNkfJRB15AWTGQ2maksLqeipHxdFaZXXUursfOmddngKINRqw6bTWZEUURRZCJawnJA\n68pK1tIqcxbZNhtW8/ZinebQRCPjo0vQRGXOkrSjiTJStRKKaTklo5hybFl4vJP4Av41UUaKotA3\n3E9HbzeKonCwaj/799Xumr9tNBbFMzWhJUfPMaUFQdCq4c58B1lWW1r3uW94gGcvOzCbzFxsOL/u\n42N33wueD7yk1FGyJ/FHGfObvBOCoPyzf/a/o9Mp5Oda0AsxPv311Yz53aXyBwM0tbfgS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Z7JkXZSSKIj2Dvdzs6UZEpKasmsqS8i23obVVtFQUk0wqQ61UJVBMeWYLqiRqQjL+aHdV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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fafa43a4128>"
]
},
"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": 65,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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Ty3WncbMPaLvYB1SSBGsr39cXmSkzvwo8v8wXSJIkSZIExZ8Dqr4jb9bSLm1eNvBZktPM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\nAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fafa446fac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = notes[list_exo].hist(figsize = (16,8))"
]
},
{
"cell_type": "code",
"execution_count": 66,
"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>Opération 1</th>\n",
" <th>Opération 2</th>\n",
" <th>Durée</th>\n",
" <th>Horaire</th>\n",
" <th>Distance</th>\n",
" <th>Temps</th>\n",
" <th>Distance (fraction)</th>\n",
" <th>nbr virgule</th>\n",
" <th>Dixieme 1</th>\n",
" <th>Dixieme 2</th>\n",
" <th>Cinquième</th>\n",
" <th>Demi</th>\n",
" <th>Symétrie axiale</th>\n",
" <th>Symétrie centrale</th>\n",
" <th>Codage</th>\n",
" <th>Précision</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>26.000000</td>\n",
" <td>26.000000</td>\n",
" <td>25.000000</td>\n",
" <td>25.00</td>\n",
" <td>25.000000</td>\n",
" <td>24.000000</td>\n",
" <td>23.000000</td>\n",
" <td>25.000000</td>\n",
" <td>24.000000</td>\n",
" <td>22.000000</td>\n",
" <td>22.000000</td>\n",
" <td>22.000000</td>\n",
" <td>24.000000</td>\n",
" <td>23.000000</td>\n",
" <td>23.000000</td>\n",
" <td>23.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>2.269231</td>\n",
" <td>1.307692</td>\n",
" <td>1.040000</td>\n",
" <td>1.28</td>\n",
" <td>2.240000</td>\n",
" <td>1.583333</td>\n",
" <td>1.043478</td>\n",
" <td>2.040000</td>\n",
" <td>1.750000</td>\n",
" <td>2.409091</td>\n",
" <td>1.590909</td>\n",
" <td>1.409091</td>\n",
" <td>2.166667</td>\n",
" <td>1.739130</td>\n",
" <td>1.173913</td>\n",
" <td>1.652174</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>1.002305</td>\n",
" <td>0.884047</td>\n",
" <td>1.398809</td>\n",
" <td>1.40</td>\n",
" <td>1.051982</td>\n",
" <td>1.442120</td>\n",
" <td>1.223938</td>\n",
" <td>1.337909</td>\n",
" <td>1.421879</td>\n",
" <td>1.053750</td>\n",
" <td>1.501082</td>\n",
" <td>1.469016</td>\n",
" <td>1.007220</td>\n",
" <td>1.421184</td>\n",
" <td>1.370208</td>\n",
" <td>1.300654</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.00</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.750000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>3.000000</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.00</td>\n",
" <td>3.000000</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.500000</td>\n",
" <td>3.000000</td>\n",
" <td>2.500000</td>\n",
" <td>1.000000</td>\n",
" <td>2.500000</td>\n",
" <td>3.000000</td>\n",
" <td>0.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>3.000000</td>\n",
" <td>1.750000</td>\n",
" <td>3.000000</td>\n",
" <td>3.00</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>2.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.00</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Opération 1 Opération 2 Durée Horaire Distance Temps \\\n",
"count 26.000000 26.000000 25.000000 25.00 25.000000 24.000000 \n",
"mean 2.269231 1.307692 1.040000 1.28 2.240000 1.583333 \n",
"std 1.002305 0.884047 1.398809 1.40 1.051982 1.442120 \n",
"min 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 \n",
"25% 2.000000 1.000000 0.000000 0.00 2.000000 0.000000 \n",
"50% 3.000000 1.000000 0.000000 0.00 3.000000 2.000000 \n",
"75% 3.000000 1.750000 3.000000 3.00 3.000000 3.000000 \n",
"max 3.000000 3.000000 3.000000 3.00 3.000000 3.000000 \n",
"\n",
" Distance (fraction) nbr virgule Dixieme 1 Dixieme 2 Cinquième \\\n",
"count 23.000000 25.000000 24.000000 22.000000 22.000000 \n",
"mean 1.043478 2.040000 1.750000 2.409091 1.590909 \n",
"std 1.223938 1.337909 1.421879 1.053750 1.501082 \n",
"min 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"25% 0.000000 0.000000 0.000000 2.000000 0.000000 \n",
"50% 1.000000 3.000000 2.500000 3.000000 2.500000 \n",
"75% 2.000000 3.000000 3.000000 3.000000 3.000000 \n",
"max 3.000000 3.000000 3.000000 3.000000 3.000000 \n",
"\n",
" Demi Symétrie axiale Symétrie centrale Codage Précision \n",
"count 22.000000 24.000000 23.000000 23.000000 23.000000 \n",
"mean 1.409091 2.166667 1.739130 1.173913 1.652174 \n",
"std 1.469016 1.007220 1.421184 1.370208 1.300654 \n",
"min 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"25% 0.000000 1.750000 0.000000 0.000000 0.000000 \n",
"50% 1.000000 2.500000 3.000000 0.000000 2.000000 \n",
"75% 3.000000 3.000000 3.000000 3.000000 3.000000 \n",
"max 3.000000 3.000000 3.000000 3.000000 3.000000 "
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes_questions = notes[sous_exo]\n",
"notes_analysis = notes_questions.describe()\n",
"notes_analysis"
]
},
{
"cell_type": "code",
"execution_count": 67,
"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>Opération 1</th>\n",
" <th>Opération 2</th>\n",
" <th>Durée</th>\n",
" <th>Horaire</th>\n",
" <th>Distance</th>\n",
" <th>Temps</th>\n",
" <th>Distance (fraction)</th>\n",
" <th>nbr virgule</th>\n",
" <th>Dixieme 1</th>\n",
" <th>Dixieme 2</th>\n",
" <th>Cinquième</th>\n",
" <th>Demi</th>\n",
" <th>Symétrie axiale</th>\n",
" <th>Symétrie centrale</th>\n",
" <th>Codage</th>\n",
" <th>Précision</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>24</td>\n",
" <td>23</td>\n",
" <td>25</td>\n",
" <td>24</td>\n",
" <td>22</td>\n",
" <td>22</td>\n",
" <td>22</td>\n",
" <td>24</td>\n",
" <td>23</td>\n",
" <td>23</td>\n",
" <td>23</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Opération 1 Opération 2 Durée Horaire Distance Temps \\\n",
"count 26 26 25 25 25 24 \n",
"\n",
" Distance (fraction) nbr virgule Dixieme 1 Dixieme 2 Cinquième \\\n",
"count 23 25 24 22 22 \n",
"\n",
" Demi Symétrie axiale Symétrie centrale Codage Précision \n",
"count 22 24 23 23 23 "
]
},
"execution_count": 67,
"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
}
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