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import work from year 2015-2016
2017-06-16 06:48:54 +00:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"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": [
"# Information sur la classe"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"classe = \"510\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Import et premiers traitements"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Remarques',\n",
" 'notes',\n",
" 'Calcul_Mental',\n",
" 'DS_15_09_20',\n",
" 'DS_15_10_30',\n",
" 'DS_15_11_20',\n",
" 'DM_15_12_07',\n",
" 'DS_16_01_18',\n",
" 'DM_16_01_25',\n",
" 'DS_16_02_08',\n",
" 'DS_16_03_21',\n",
" 'DM_16_04_01',\n",
" 'DS_16_04_11']"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"all_notes = pd.ExcelFile(classe+\".xlsx\")\n",
"all_notes.sheet_names"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2e trimestre"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Bilan DS_16_02_08"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"ds_name = \"DS_16_02_08\"\n",
"notes = all_notes.parse(ds_name)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"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>Barème</th>\n",
" <td>4.000000</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.0</td>\n",
" </tr>\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>0.5</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>0.0</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>5.0</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>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Exercice 1 Exercice 2 Exercice 3 Exercice 4 Exercice 5\n",
"Barème 4.000000 3.0 3.000000 5.000000 5.0\n",
"ABDOU ALI Nassim 2.666667 2.5 0.666667 1.333333 0.5\n",
"ABDOUL-KADER Toura 0.666667 0.0 0.666667 0.666667 0.0\n",
"AHAMADI Djelane 2.666667 0.0 2.333333 5.000000 5.0\n",
"AHMED Laine 3.333333 0.0 3.000000 3.000000 0.0"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes_exo = notes.T.filter(regex='Exercice').astype('float')\n",
"notes_exo.head()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"barem = notes_exo.iloc[0]\n",
"notes_exo = notes_exo.drop('Barème')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": true
},
"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>count</th>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>2.296296</td>\n",
" <td>1.074074</td>\n",
" <td>1.456790</td>\n",
" <td>2.617284</td>\n",
" <td>2.506173</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.948833</td>\n",
" <td>1.268734</td>\n",
" <td>1.000633</td>\n",
" <td>1.777600</td>\n",
" <td>1.846966</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>0.000000</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.666667</td>\n",
" <td>1.000000</td>\n",
" <td>0.833333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>2.666667</td>\n",
" <td>0.000000</td>\n",
" <td>1.333333</td>\n",
" <td>3.000000</td>\n",
" <td>2.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.666667</td>\n",
" <td>2.250000</td>\n",
" <td>2.333333</td>\n",
" <td>4.000000</td>\n",
" <td>4.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>4.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>5.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Exercice 1 Exercice 2 Exercice 3 Exercice 4 Exercice 5\n",
"count 27.000000 27.000000 27.000000 27.000000 27.000000\n",
"mean 2.296296 1.074074 1.456790 2.617284 2.506173\n",
"std 0.948833 1.268734 1.000633 1.777600 1.846966\n",
"min 0.000000 0.000000 0.000000 0.000000 0.000000\n",
"25% 2.000000 0.000000 0.666667 1.000000 0.833333\n",
"50% 2.666667 0.000000 1.333333 3.000000 2.166667\n",
"75% 2.666667 2.250000 2.333333 4.000000 4.166667\n",
"max 4.000000 3.000000 3.000000 5.000000 5.000000"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes_exo.describe()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f9013c9f358>"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x7f9013c9f208>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"notes_exo_norm = notes_exo / barem\n",
"\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": 21,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x7f9008cdeb38>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = notes_exo.hist(figsize = (16,8))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Bilan du 2e trimestre"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"ds_name = \"notes\"\n",
"notes = all_notes.parse(ds_name)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"trim2 = notes[7:].T\n",
"trim2.columns = ['DS_15_11_20', 'DM_15_12_07', 'DS_16_01_18', 'DM_16_01_25', 'DS_16_02_08', 'CM']"
]
},
{
"cell_type": "code",
"execution_count": 6,
"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_15_11_20</th>\n",
" <th>DM_15_12_07</th>\n",
" <th>DS_16_01_18</th>\n",
" <th>DM_16_01_25</th>\n",
" <th>DS_16_02_08</th>\n",
" <th>CM</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Barème</th>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>NaN</td>\n",
" <td>11.5</td>\n",
" <td>9</td>\n",
" <td>13</td>\n",
" <td>7.5</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>6.5</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>12</td>\n",
" <td>2</td>\n",
" <td>3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>15.5</td>\n",
" <td>14</td>\n",
" <td>13.5</td>\n",
" <td>18.5</td>\n",
" <td>15</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>12.5</td>\n",
" <td>13.5</td>\n",
" <td>12.5</td>\n",
" <td>14</td>\n",
" <td>9.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DS_15_11_20 DM_15_12_07 DS_16_01_18 DM_16_01_25 \\\n",
"Barème 20 20 20 20 \n",
"ABDOU ALI Nassim NaN 11.5 9 13 \n",
"ABDOUL-KADER Toura 6.5 5 3 12 \n",
"AHAMADI Djelane 15.5 14 13.5 18.5 \n",
"AHMED Laine 12.5 13.5 12.5 14 \n",
"\n",
" DS_16_02_08 CM \n",
"Barème 20 20 \n",
"ABDOU ALI Nassim 7.5 5 \n",
"ABDOUL-KADER Toura 2 3.5 \n",
"AHAMADI Djelane 15 15 \n",
"AHMED Laine 9.5 10 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trim2.head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"barem = trim2[:1]\n",
"notesT2 = trim2[1:28]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"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_15_11_20</th>\n",
" <th>DM_15_12_07</th>\n",
" <th>DS_16_01_18</th>\n",
" <th>DM_16_01_25</th>\n",
" <th>DS_16_02_08</th>\n",
" <th>CM</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>NaN</td>\n",
" <td>11.5</td>\n",
" <td>9</td>\n",
" <td>13</td>\n",
" <td>7.5</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>6.5</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>12</td>\n",
" <td>2</td>\n",
" <td>3.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>15.5</td>\n",
" <td>14</td>\n",
" <td>13.5</td>\n",
" <td>18.5</td>\n",
" <td>15</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>15.5</td>\n",
" <td>0</td>\n",
" <td>13</td>\n",
" <td>14</td>\n",
" <td>11</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>8</td>\n",
" <td>7</td>\n",
" <td>10.5</td>\n",
" <td>5</td>\n",
" <td>13</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>12.5</td>\n",
" <td>13.5</td>\n",
" <td>12.5</td>\n",
" <td>14</td>\n",
" <td>9.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>12</td>\n",
" <td>13</td>\n",
" <td>12</td>\n",
" <td>13.5</td>\n",
" <td>16</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <td>4</td>\n",
" <td>5.5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>15</td>\n",
" <td>16</td>\n",
" <td>16.5</td>\n",
" <td>13.5</td>\n",
" <td>13</td>\n",
" <td>13.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>8.5</td>\n",
" <td>18</td>\n",
" <td>10</td>\n",
" <td>18.5</td>\n",
" <td>6</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>18.5</td>\n",
" <td>17</td>\n",
" <td>15.5</td>\n",
" <td>18.5</td>\n",
" <td>20</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>15.5</td>\n",
" <td>14</td>\n",
" <td>10</td>\n",
" <td>11</td>\n",
" <td>9</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>15.5</td>\n",
" <td>16</td>\n",
" <td>10</td>\n",
" <td>16.5</td>\n",
" <td>18</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>13.5</td>\n",
" <td>12.5</td>\n",
" <td>12.5</td>\n",
" <td>16</td>\n",
" <td>11.5</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>13.5</td>\n",
" <td>14</td>\n",
" <td>4.5</td>\n",
" <td>10</td>\n",
" <td>5.5</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>5</td>\n",
" <td>13.5</td>\n",
" <td>11.5</td>\n",
" <td>8.5</td>\n",
" <td>10</td>\n",
" <td>7.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>15.5</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>8.5</td>\n",
" <td>9.5</td>\n",
" <td>6.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>7.5</td>\n",
" <td>13</td>\n",
" <td>6.5</td>\n",
" <td>12</td>\n",
" <td>8</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>16</td>\n",
" <td>13.5</td>\n",
" <td>16.5</td>\n",
" <td>17.5</td>\n",
" <td>15.5</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>12</td>\n",
" <td>16.5</td>\n",
" <td>11</td>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>11.5</td>\n",
" <td>18.5</td>\n",
" <td>16</td>\n",
" <td>17.5</td>\n",
" <td>14.5</td>\n",
" <td>17.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>15.5</td>\n",
" <td>10</td>\n",
" <td>11</td>\n",
" <td>9.5</td>\n",
" <td>9</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>8.5</td>\n",
" <td>14.5</td>\n",
" <td>9.5</td>\n",
" <td>15</td>\n",
" <td>5.5</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>10</td>\n",
" <td>0</td>\n",
" <td>10.5</td>\n",
" <td>0</td>\n",
" <td>4.5</td>\n",
" <td>1.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>9.5</td>\n",
" <td>11.5</td>\n",
" <td>15.5</td>\n",
" <td>12.5</td>\n",
" <td>17.5</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>11</td>\n",
" <td>16</td>\n",
" <td>8.5</td>\n",
" <td>11.5</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>11</td>\n",
" <td>13.5</td>\n",
" <td>12</td>\n",
" <td>12</td>\n",
" <td>5.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DS_15_11_20 DM_15_12_07 DS_16_01_18 DM_16_01_25 \\\n",
"ABDOU ALI Nassim NaN 11.5 9 13 \n",
"ABDOUL-KADER Toura 6.5 5 3 12 \n",
"AHAMADI Djelane 15.5 14 13.5 18.5 \n",
"AHMED Aicha 15.5 0 13 14 \n",
"AHMED Hamza 8 7 10.5 5 \n",
"AHMED Laine 12.5 13.5 12.5 14 \n",
"ALI Naima 12 13 12 13.5 \n",
"ANSSURDINE Zaidou 4 5.5 0 0 \n",
"ARBABI Idiamine 15 16 16.5 13.5 \n",
"ATTOUMANI Mtahida 8.5 18 10 18.5 \n",
"BACAR Musbahou 18.5 17 15.5 18.5 \n",
"BACAR Natacha 15.5 14 10 11 \n",
"BAHEDJA Rachma 15.5 16 10 16.5 \n",
"CHAHARANE Djawadi 13.5 12.5 12.5 16 \n",
"CHARIF Nassuria 13.5 14 4.5 10 \n",
"COMBO Danil 5 13.5 11.5 8.5 \n",
"HOUMADI Naima 15.5 0 8 8.5 \n",
"IBRAHIM Hakim 7.5 13 6.5 12 \n",
"IBRAHIM Yanick 16 13.5 16.5 17.5 \n",
"MADI Himidati 12 16.5 11 4 \n",
"MARI Ismaël 11.5 18.5 16 17.5 \n",
"MOHAMED Yousra 15.5 10 11 9.5 \n",
"MOUHOUDHOIRE Nithaou 8.5 14.5 9.5 15 \n",
"SAINDOU Abdoul Anzize 10 0 10.5 0 \n",
"SAÏD Hakim 9.5 11.5 15.5 12.5 \n",
"SOIFENE Fémida 11 16 8.5 11.5 \n",
"ZAKARIA Najwa 11 13.5 12 12 \n",
"\n",
" DS_16_02_08 CM \n",
"ABDOU ALI Nassim 7.5 5 \n",
"ABDOUL-KADER Toura 2 3.5 \n",
"AHAMADI Djelane 15 15 \n",
"AHMED Aicha 11 16.5 \n",
"AHMED Hamza 13 11 \n",
"AHMED Laine 9.5 10 \n",
"ALI Naima 16 13 \n",
"ANSSURDINE Zaidou 0 15 \n",
"ARBABI Idiamine 13 13.5 \n",
"ATTOUMANI Mtahida 6 11 \n",
"BACAR Musbahou 20 19 \n",
"BACAR Natacha 9 16.5 \n",
"BAHEDJA Rachma 18 16 \n",
"CHAHARANE Djawadi 11.5 9 \n",
"CHARIF Nassuria 5.5 11 \n",
"COMBO Danil 10 7.5 \n",
"HOUMADI Naima 9.5 6.5 \n",
"IBRAHIM Hakim 8 11.5 \n",
"IBRAHIM Yanick 15.5 15 \n",
"MADI Himidati 7 3 \n",
"MARI Ismaël 14.5 17.5 \n",
"MOHAMED Yousra 9 11 \n",
"MOUHOUDHOIRE Nithaou 5.5 13 \n",
"SAINDOU Abdoul Anzize 4.5 1.5 \n",
"SAÏD Hakim 17.5 17 \n",
"SOIFENE Fémida 5 5 \n",
"ZAKARIA Najwa 5.5 10 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notesT2.sort_index()\n",
"#barem"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notesT2 = notesT2.astype(float)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Un peu de statistiques"
]
},
{
"cell_type": "code",
"execution_count": 10,
"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_15_11_20</th>\n",
" <th>DM_15_12_07</th>\n",
" <th>DS_16_01_18</th>\n",
" <th>DM_16_01_25</th>\n",
" <th>DS_16_02_08</th>\n",
" <th>CM</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>26.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" <td>27.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>11.807692</td>\n",
" <td>11.759259</td>\n",
" <td>10.703704</td>\n",
" <td>11.944444</td>\n",
" <td>9.944444</td>\n",
" <td>11.240741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.800202</td>\n",
" <td>5.378680</td>\n",
" <td>3.986176</td>\n",
" <td>5.125977</td>\n",
" <td>5.078865</td>\n",
" <td>4.842461</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>8.750000</td>\n",
" <td>10.750000</td>\n",
" <td>9.250000</td>\n",
" <td>9.750000</td>\n",
" <td>5.750000</td>\n",
" <td>8.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>12.000000</td>\n",
" <td>13.500000</td>\n",
" <td>11.000000</td>\n",
" <td>12.500000</td>\n",
" <td>9.500000</td>\n",
" <td>11.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>15.500000</td>\n",
" <td>15.250000</td>\n",
" <td>12.750000</td>\n",
" <td>15.500000</td>\n",
" <td>13.750000</td>\n",
" <td>15.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>18.500000</td>\n",
" <td>18.500000</td>\n",
" <td>16.500000</td>\n",
" <td>18.500000</td>\n",
" <td>20.000000</td>\n",
" <td>19.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" DS_15_11_20 DM_15_12_07 DS_16_01_18 DM_16_01_25 DS_16_02_08 \\\n",
"count 26.000000 27.000000 27.000000 27.000000 27.000000 \n",
"mean 11.807692 11.759259 10.703704 11.944444 9.944444 \n",
"std 3.800202 5.378680 3.986176 5.125977 5.078865 \n",
"min 4.000000 0.000000 0.000000 0.000000 0.000000 \n",
"25% 8.750000 10.750000 9.250000 9.750000 5.750000 \n",
"50% 12.000000 13.500000 11.000000 12.500000 9.500000 \n",
"75% 15.500000 15.250000 12.750000 15.500000 13.750000 \n",
"max 18.500000 18.500000 16.500000 18.500000 20.000000 \n",
"\n",
" CM \n",
"count 27.000000 \n",
"mean 11.240741 \n",
"std 4.842461 \n",
"min 1.500000 \n",
"25% 8.250000 \n",
"50% 11.000000 \n",
"75% 15.000000 \n",
"max 19.000000 "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notesT2.describe()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f9a02bc7358>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x7f9a02b78a90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Normalisation des notes de chaque exo\n",
"notes_exo_norm = (notesT2 / barem.values[0,:]).astype(float)\n",
"#notes_exo_norm.describe()\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": 90,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
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"text/plain": [
"<matplotlib.figure.Figure at 0x7f5f8a355b38>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = notesT2.hist(figsize = (16,8))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Analyse par élève "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from ipywidgets import interact, interactive\n",
"from IPython.display import display, HTML"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"DS_15_11_20 NaN\n",
"DM_15_12_07 11.5\n",
"DS_16_01_18 9.0\n",
"DM_16_01_25 13.0\n",
"DS_16_02_08 7.5\n",
"CM 5.0\n",
"Name: ABDOU ALI Nassim, dtype: float64"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<function __main__.f>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA7QAAAGrCAYAAADw2NvJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhUAkgEA4gGAkiEA4gEA
"text/plain": [
"<matplotlib.figure.Figure at 0x7f99efaad048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Normalisation des notes de chaque exo\n",
"notes_exo_norm = (notesT2 / barem.values[0,:]).astype(float)\n",
"def f(x):\n",
" #notes_exo_norm\n",
" display(notesT2.loc[x])\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)\n",
" notes_exo_norm.loc[x].plot(ax=ax, color=\"red\", alpha = 1)\n",
"\n",
" \n",
"interact(f, x = list(notesT2.index))"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# 3e trimestre"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## DS_16_03_21"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"ds_name = \"DS_16_03_21\"\n",
"notes = all_notes.parse(ds_name)"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Barème</th>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <th>AHAMADI Djelane</th>\n",
" <th>AHMED Laine</th>\n",
" <th>AHMED Hamza</th>\n",
" <th>AHMED Aicha</th>\n",
" <th>ALI Naima</th>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <th>ARBABI Idiamine</th>\n",
" <th>...</th>\n",
" <th>IBRAHIM Yanick</th>\n",
" <th>IBRAHIM Hakim</th>\n",
" <th>MADI Himidati</th>\n",
" <th>MARI Ismaël</th>\n",
" <th>MOHAMED Yousra</th>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <th>SAÏD Hakim</th>\n",
" <th>SOIFENE Fémida</th>\n",
" <th>ZAKARIA Najwa</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>DS_16_02_08</th>\n",
" <td>20</td>\n",
" <td>9.5</td>\n",
" <td>3.5</td>\n",
" <td>10.5</td>\n",
" <td>10.5</td>\n",
" <td>11.000000</td>\n",
" <td>18.000000</td>\n",
" <td>9.5</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>...</td>\n",
" <td>14.5</td>\n",
" <td>11.5</td>\n",
" <td>0</td>\n",
" <td>13.000000</td>\n",
" <td>8.5</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>4.5</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Exercice 1</th>\n",
" <td>5</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.333333</td>\n",
" <td>4.333333</td>\n",
" <td>3.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>0</td>\n",
" <td>3.333333</td>\n",
" <td>2.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 1</th>\n",
" <td>1</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 2</th>\n",
" <td>1</td>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 3</th>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 28 columns</p>\n",
"</div>"
],
"text/plain": [
" Barème ABDOU ALI Nassim ABDOUL-KADER Toura AHAMADI Djelane \\\n",
"DS_16_02_08 20 9.5 3.5 10.5 \n",
"Exercice 1 5 4.0 1.0 3.0 \n",
"Opération 1 1 3.0 3.0 3.0 \n",
"Opération 2 1 3.0 0.0 3.0 \n",
"Opération 3 1 0.0 0.0 0.0 \n",
"\n",
" AHMED Laine AHMED Hamza AHMED Aicha ALI Naima \\\n",
"DS_16_02_08 10.5 11.000000 18.000000 9.5 \n",
"Exercice 1 4.0 4.333333 4.333333 3.0 \n",
"Opération 1 3.0 3.000000 3.000000 3.0 \n",
"Opération 2 3.0 3.000000 3.000000 3.0 \n",
"Opération 3 3.0 3.000000 3.000000 0.0 \n",
"\n",
" ANSSURDINE Zaidou ARBABI Idiamine ... \\\n",
"DS_16_02_08 0 8 ... \n",
"Exercice 1 0 2 ... \n",
"Opération 1 NaN 3 ... \n",
"Opération 2 NaN 3 ... \n",
"Opération 3 NaN 0 ... \n",
"\n",
" IBRAHIM Yanick IBRAHIM Hakim MADI Himidati MARI Ismaël \\\n",
"DS_16_02_08 14.5 11.5 0 13.000000 \n",
"Exercice 1 4.0 4.0 0 3.333333 \n",
"Opération 1 3.0 0.0 NaN 3.000000 \n",
"Opération 2 3.0 3.0 NaN 3.000000 \n",
"Opération 3 3.0 3.0 NaN 3.000000 \n",
"\n",
" MOHAMED Yousra MOUHOUDHOIRE Nithaou SAINDOU Abdoul Anzize \\\n",
"DS_16_02_08 8.5 0 4 \n",
"Exercice 1 2.0 0 1 \n",
"Opération 1 3.0 NaN 0 \n",
"Opération 2 3.0 NaN 3 \n",
"Opération 3 0.0 NaN 0 \n",
"\n",
" SAÏD Hakim SOIFENE Fémida ZAKARIA Najwa \n",
"DS_16_02_08 0 4.5 11.5 \n",
"Exercice 1 0 1.0 2.0 \n",
"Opération 1 NaN 0.0 3.0 \n",
"Opération 2 NaN 3.0 3.0 \n",
"Opération 3 NaN 0.0 0.0 \n",
"\n",
"[5 rows x 28 columns]"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes = notes.drop(notes.index[1])\n",
"notes.head()"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <th>AHAMADI Djelane</th>\n",
" <th>AHMED Laine</th>\n",
" <th>AHMED Hamza</th>\n",
" <th>AHMED Aicha</th>\n",
" <th>ALI Naima</th>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <th>ARBABI Idiamine</th>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <th>...</th>\n",
" <th>IBRAHIM Yanick</th>\n",
" <th>IBRAHIM Hakim</th>\n",
" <th>MADI Himidati</th>\n",
" <th>MARI Ismaël</th>\n",
" <th>MOHAMED Yousra</th>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <th>SAÏD Hakim</th>\n",
" <th>SOIFENE Fémida</th>\n",
" <th>ZAKARIA Najwa</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>DS_16_02_08</th>\n",
" <td>9.5</td>\n",
" <td>3.5</td>\n",
" <td>10.5</td>\n",
" <td>10.5</td>\n",
" <td>11.000000</td>\n",
" <td>18.000000</td>\n",
" <td>9.5</td>\n",
" <td>0</td>\n",
" <td>8</td>\n",
" <td>8.5</td>\n",
" <td>...</td>\n",
" <td>14.5</td>\n",
" <td>11.5</td>\n",
" <td>0</td>\n",
" <td>13.000000</td>\n",
" <td>8.5</td>\n",
" <td>0</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>4.5</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Exercice 1</th>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>4.333333</td>\n",
" <td>4.333333</td>\n",
" <td>3.0</td>\n",
" <td>0</td>\n",
" <td>2</td>\n",
" <td>2.0</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>4.0</td>\n",
" <td>0</td>\n",
" <td>3.333333</td>\n",
" <td>2.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 1</th>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 2</th>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Opération 3</th>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.000000</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>3.000000</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 27 columns</p>\n",
"</div>"
],
"text/plain": [
" ABDOU ALI Nassim ABDOUL-KADER Toura AHAMADI Djelane \\\n",
"DS_16_02_08 9.5 3.5 10.5 \n",
"Exercice 1 4.0 1.0 3.0 \n",
"Opération 1 3.0 3.0 3.0 \n",
"Opération 2 3.0 0.0 3.0 \n",
"Opération 3 0.0 0.0 0.0 \n",
"\n",
" AHMED Laine AHMED Hamza AHMED Aicha ALI Naima \\\n",
"DS_16_02_08 10.5 11.000000 18.000000 9.5 \n",
"Exercice 1 4.0 4.333333 4.333333 3.0 \n",
"Opération 1 3.0 3.000000 3.000000 3.0 \n",
"Opération 2 3.0 3.000000 3.000000 3.0 \n",
"Opération 3 3.0 3.000000 3.000000 0.0 \n",
"\n",
" ANSSURDINE Zaidou ARBABI Idiamine ATTOUMANI Mtahida \\\n",
"DS_16_02_08 0 8 8.5 \n",
"Exercice 1 0 2 2.0 \n",
"Opération 1 NaN 3 3.0 \n",
"Opération 2 NaN 3 3.0 \n",
"Opération 3 NaN 0 0.0 \n",
"\n",
" ... IBRAHIM Yanick IBRAHIM Hakim MADI Himidati \\\n",
"DS_16_02_08 ... 14.5 11.5 0 \n",
"Exercice 1 ... 4.0 4.0 0 \n",
"Opération 1 ... 3.0 0.0 NaN \n",
"Opération 2 ... 3.0 3.0 NaN \n",
"Opération 3 ... 3.0 3.0 NaN \n",
"\n",
" MARI Ismaël MOHAMED Yousra MOUHOUDHOIRE Nithaou \\\n",
"DS_16_02_08 13.000000 8.5 0 \n",
"Exercice 1 3.333333 2.0 0 \n",
"Opération 1 3.000000 3.0 NaN \n",
"Opération 2 3.000000 3.0 NaN \n",
"Opération 3 3.000000 0.0 NaN \n",
"\n",
" SAINDOU Abdoul Anzize SAÏD Hakim SOIFENE Fémida ZAKARIA Najwa \n",
"DS_16_02_08 4 0 4.5 11.5 \n",
"Exercice 1 1 0 1.0 2.0 \n",
"Opération 1 0 NaN 0.0 3.0 \n",
"Opération 2 3 NaN 3.0 3.0 \n",
"Opération 3 0 NaN 0.0 0.0 \n",
"\n",
"[5 rows x 27 columns]"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"barem = notes['Barème']\n",
"notes = notes.drop('Barème', axis=1)\n",
"notes.head()"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"DS_16_02_08 20.0\n",
"Exercice 1 5.0\n",
"Opération 1 1.0\n",
"Opération 2 1.0\n",
"Opération 3 1.0\n",
"Opération 4 1.0\n",
"Opération 5 1.0\n",
"Exercice 2 2.0\n",
"Unité temps 2.0\n",
"Exercice 3 6.0\n",
"Durée 2.0\n",
"Horaire 2.0\n",
"Fraction de temps 2.0\n",
"Exercice 4 5.0\n",
"Placer fraction axe 2.0\n",
"Comparaison denom 1.5\n",
"Comparaison num 1.5\n",
"Name: Barème, dtype: float64"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"barem"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Absents"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"['ANSSURDINE Zaidou',\n",
" 'HOUMADI Naima',\n",
" 'MADI Himidati',\n",
" 'MOUHOUDHOIRE Nithaou',\n",
" 'SAÏD Hakim']"
]
},
"execution_count": 87,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(notes.T[notes.iloc[0] == 0].index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Présents"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"notes = notes.T[notes.iloc[0] != 0].T"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"count 22.000000\n",
"mean 10.136364\n",
"std 4.282250\n",
"min 3.500000\n",
"25% 8.125000\n",
"50% 10.500000\n",
"75% 12.625000\n",
"max 20.000000\n",
"Name: DS_16_02_08, dtype: float64"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total = notes.iloc[0]\n",
"total.describe()"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f5b2f26d4a8>"
]
},
"execution_count": 90,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAeAAAAFXCAYAAAB6G51YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nI0e0tbX1xEsNm76+7bb
"text/plain": [
"<matplotlib.figure.Figure at 0x7f5b2f26d048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"total = notes.iloc[0]\n",
"total.hist()"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {
"collapsed": true
},
"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",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>4.000000</td>\n",
" <td>1.333333</td>\n",
" <td>2.000000</td>\n",
" <td>1.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>1.000000</td>\n",
" <td>0.666667</td>\n",
" <td>0.000000</td>\n",
" <td>1.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>3.000000</td>\n",
" <td>1.333333</td>\n",
" <td>2.000000</td>\n",
" <td>3.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>4.000000</td>\n",
" <td>1.333333</td>\n",
" <td>2.000000</td>\n",
" <td>2.166667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>4.333333</td>\n",
" <td>1.333333</td>\n",
" <td>2.666667</td>\n",
" <td>1.500000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Exercice 1 Exercice 2 Exercice 3 Exercice 4\n",
"ABDOU ALI Nassim 4.000000 1.333333 2.000000 1.333333\n",
"ABDOUL-KADER Toura 1.000000 0.666667 0.000000 1.333333\n",
"AHAMADI Djelane 3.000000 1.333333 2.000000 3.333333\n",
"AHMED Laine 4.000000 1.333333 2.000000 2.166667\n",
"AHMED Hamza 4.333333 1.333333 2.666667 1.500000"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes_exo = notes.T.filter(regex='Exercice').astype('float')\n",
"barem_exo = barem.T.filter(regex='Exercice').astype('float')\n",
"notes_exo.head()"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"Exercice 1 5\n",
"Exercice 2 2\n",
"Exercice 3 6\n",
"Exercice 4 5\n",
"Name: Barème, dtype: float64"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"barem_exo"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from ipywidgets import interact, interactive\n",
"from IPython.display import display, HTML"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"DS_16_02_08 10.500000\n",
"Exercice 1 4.000000\n",
"Opération 1 3.000000\n",
"Opération 2 3.000000\n",
"Opération 3 3.000000\n",
"Opération 4 3.000000\n",
"Opération 5 0.000000\n",
"Exercice 2 1.333333\n",
"Unité temps 2.000000\n",
"Exercice 3 2.000000\n",
"Durée 1.000000\n",
"Horaire 1.000000\n",
"Fraction de temps 1.000000\n",
"Exercice 4 2.166667\n",
"Placer fraction axe 1.000000\n",
"Comparaison denom 3.000000\n",
"Comparaison num 0.000000\n",
"Name: AHMED Laine, dtype: float64"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA78AAAGrCAYAAAAIOCA+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYtHyK1K1VMRiMepq67D
"text/plain": [
"<matplotlib.figure.Figure at 0x7f5b2d877d68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Normalisation des notes de chaque exo\n",
"notes_exo_norm = (notes_exo / barem_exo).astype(float)\n",
"def f(x):\n",
" #notes_exo_norm\n",
" display(notes[x])\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)\n",
" notes_exo_norm.loc[x].plot(ax=ax, color=\"red\", alpha = 1)\n",
"\n",
" \n",
"interact(f, x = list(notes_exo.index))"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Bilan 3e trimestre"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"ds_name = \"notes\"\n",
"notes = all_notes.parse(ds_name)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Index(['3e trimestre', 'DS_16_03_21', 'DM_16_04_01', 'DS_16_04_11'], dtype='object')"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"notes[15:].index"
]
},
{
"cell_type": "code",
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"source": [
"trim3 = notes[15:].T\n",
"trim3.columns = ['Calcul mental', 'DS_16_03_21', 'DM_16_04_01', 'DS_16_04_11']"
]
},
{
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{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Calcul mental</th>\n",
" <th>DS_16_03_21</th>\n",
" <th>DM_16_04_01</th>\n",
" <th>DS_16_04_11</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Barème</th>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>13.5</td>\n",
" <td>9.5</td>\n",
" <td>NaN</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>4</td>\n",
" <td>3.5</td>\n",
" <td>4.5</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>16</td>\n",
" <td>10.5</td>\n",
" <td>14</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>8</td>\n",
" <td>10.5</td>\n",
" <td>12</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>9</td>\n",
" <td>11</td>\n",
" <td>4.5</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>17.5</td>\n",
" <td>18</td>\n",
" <td>17</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>17</td>\n",
" <td>9.5</td>\n",
" <td>13.5</td>\n",
" <td>15.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <td>12.5</td>\n",
" <td>7</td>\n",
" <td>NaN</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>13</td>\n",
" <td>8</td>\n",
" <td>15.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>9</td>\n",
" <td>8.5</td>\n",
" <td>18.5</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>14</td>\n",
" <td>4.5</td>\n",
" <td>14</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>19</td>\n",
" <td>20</td>\n",
" <td>18.5</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>16</td>\n",
" <td>10.5</td>\n",
" <td>16.5</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>13</td>\n",
" <td>13</td>\n",
" <td>12</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>12</td>\n",
" <td>13</td>\n",
" <td>11</td>\n",
" <td>14.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>14</td>\n",
" <td>5.5</td>\n",
" <td>7</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>5</td>\n",
" <td>10.5</td>\n",
" <td>16.5</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>12</td>\n",
" <td>14.5</td>\n",
" <td>18.5</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>10</td>\n",
" <td>11.5</td>\n",
" <td>10.5</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>5</td>\n",
" <td>10.5</td>\n",
" <td>11.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>14</td>\n",
" <td>13</td>\n",
" <td>17.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>8.5</td>\n",
" <td>8.5</td>\n",
" <td>18</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>7.5</td>\n",
" <td>5</td>\n",
" <td>15.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>9</td>\n",
" <td>4</td>\n",
" <td>NaN</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>17.5</td>\n",
" <td>20</td>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>6.5</td>\n",
" <td>4.5</td>\n",
" <td>17</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>6.5</td>\n",
" <td>11.5</td>\n",
" <td>9</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Unnamed: 28</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>moyenne</th>\n",
" <td>11.4444</td>\n",
" <td>10.2222</td>\n",
" <td>13.8125</td>\n",
" <td>11.6923</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4</td>\n",
" <td>3.5</td>\n",
" <td>4.5</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>q1</th>\n",
" <td>8.25</td>\n",
" <td>7.5</td>\n",
" <td>11.375</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Me</th>\n",
" <td>12</td>\n",
" <td>10.5</td>\n",
" <td>14.75</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Q3</th>\n",
" <td>14</td>\n",
" <td>12.25</td>\n",
" <td>17.125</td>\n",
" <td>15.25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>19</td>\n",
" <td>20</td>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Calcul mental DS_16_03_21 DM_16_04_01 DS_16_04_11\n",
"Barème 20 20 20 20\n",
"ABDOU ALI Nassim 13.5 9.5 NaN 10.5\n",
"ABDOUL-KADER Toura 4 3.5 4.5 8\n",
"AHAMADI Djelane 16 10.5 14 16.5\n",
"AHMED Laine 8 10.5 12 9.5\n",
"AHMED Hamza 9 11 4.5 10.5\n",
"AHMED Aicha 17.5 18 17 16.5\n",
"ALI Naima 17 9.5 13.5 15.5\n",
"ANSSURDINE Zaidou 12.5 7 NaN 8\n",
"ARBABI Idiamine 13 8 15.5 10\n",
"ATTOUMANI Mtahida 9 8.5 18.5 8\n",
"BACAR Natacha 14 4.5 14 11.5\n",
"BACAR Musbahou 19 20 18.5 16.5\n",
"BAHEDJA Rachma 16 10.5 16.5 16.5\n",
"CHAHARANE Djawadi 13 13 12 9\n",
"CHARIF Nassuria 12 13 11 14.5\n",
"COMBO Danil 14 5.5 7 11.5\n",
"HOUMADI Naima 5 10.5 16.5 NaN\n",
"IBRAHIM Yanick 12 14.5 18.5 17\n",
"IBRAHIM Hakim 10 11.5 10.5 9\n",
"MADI Himidati 5 10.5 11.5 10\n",
"MARI Ismaël 14 13 17.5 9.5\n",
"MOHAMED Yousra 8.5 8.5 18 10.5\n",
"MOUHOUDHOIRE Nithaou 7.5 5 15.5 9.5\n",
"SAINDOU Abdoul Anzize 9 4 NaN 10\n",
"SAÏD Hakim 17.5 20 19 19\n",
"SOIFENE Fémida 6.5 4.5 17 5.5\n",
"ZAKARIA Najwa 6.5 11.5 9 11.5\n",
"Unnamed: 28 NaN NaN NaN NaN\n",
"moyenne 11.4444 10.2222 13.8125 11.6923\n",
"min 4 3.5 4.5 5.5\n",
"q1 8.25 7.5 11.375 9.5\n",
"Me 12 10.5 14.75 10.5\n",
"Q3 14 12.25 17.125 15.25\n",
"max 19 20 19 19"
]
},
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}
],
"source": [
"trim3"
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},
{
"cell_type": "code",
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"metadata": {
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},
"outputs": [],
"source": [
"barem = trim3[:1]\n",
"notesT3 = trim3[1:28]"
]
},
{
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{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Calcul mental</th>\n",
" <th>DS_16_03_21</th>\n",
" <th>DM_16_04_01</th>\n",
" <th>DS_16_04_11</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>ABDOU ALI Nassim</th>\n",
" <td>13.5</td>\n",
" <td>9.5</td>\n",
" <td>NaN</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABDOUL-KADER Toura</th>\n",
" <td>4</td>\n",
" <td>3.5</td>\n",
" <td>4.5</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHAMADI Djelane</th>\n",
" <td>16</td>\n",
" <td>10.5</td>\n",
" <td>14</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Aicha</th>\n",
" <td>17.5</td>\n",
" <td>18</td>\n",
" <td>17</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Hamza</th>\n",
" <td>9</td>\n",
" <td>11</td>\n",
" <td>4.5</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Laine</th>\n",
" <td>8</td>\n",
" <td>10.5</td>\n",
" <td>12</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI Naima</th>\n",
" <td>17</td>\n",
" <td>9.5</td>\n",
" <td>13.5</td>\n",
" <td>15.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ANSSURDINE Zaidou</th>\n",
" <td>12.5</td>\n",
" <td>7</td>\n",
" <td>NaN</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ARBABI Idiamine</th>\n",
" <td>13</td>\n",
" <td>8</td>\n",
" <td>15.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ATTOUMANI Mtahida</th>\n",
" <td>9</td>\n",
" <td>8.5</td>\n",
" <td>18.5</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Musbahou</th>\n",
" <td>19</td>\n",
" <td>20</td>\n",
" <td>18.5</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BACAR Natacha</th>\n",
" <td>14</td>\n",
" <td>4.5</td>\n",
" <td>14</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>BAHEDJA Rachma</th>\n",
" <td>16</td>\n",
" <td>10.5</td>\n",
" <td>16.5</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHAHARANE Djawadi</th>\n",
" <td>13</td>\n",
" <td>13</td>\n",
" <td>12</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CHARIF Nassuria</th>\n",
" <td>12</td>\n",
" <td>13</td>\n",
" <td>11</td>\n",
" <td>14.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>COMBO Danil</th>\n",
" <td>14</td>\n",
" <td>5.5</td>\n",
" <td>7</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HOUMADI Naima</th>\n",
" <td>5</td>\n",
" <td>10.5</td>\n",
" <td>16.5</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Hakim</th>\n",
" <td>10</td>\n",
" <td>11.5</td>\n",
" <td>10.5</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IBRAHIM Yanick</th>\n",
" <td>12</td>\n",
" <td>14.5</td>\n",
" <td>18.5</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MADI Himidati</th>\n",
" <td>5</td>\n",
" <td>10.5</td>\n",
" <td>11.5</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MARI Ismaël</th>\n",
" <td>14</td>\n",
" <td>13</td>\n",
" <td>17.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOHAMED Yousra</th>\n",
" <td>8.5</td>\n",
" <td>8.5</td>\n",
" <td>18</td>\n",
" <td>10.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MOUHOUDHOIRE Nithaou</th>\n",
" <td>7.5</td>\n",
" <td>5</td>\n",
" <td>15.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAINDOU Abdoul Anzize</th>\n",
" <td>9</td>\n",
" <td>4</td>\n",
" <td>NaN</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SAÏD Hakim</th>\n",
" <td>17.5</td>\n",
" <td>20</td>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SOIFENE Fémida</th>\n",
" <td>6.5</td>\n",
" <td>4.5</td>\n",
" <td>17</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ZAKARIA Najwa</th>\n",
" <td>6.5</td>\n",
" <td>11.5</td>\n",
" <td>9</td>\n",
" <td>11.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Calcul mental DS_16_03_21 DM_16_04_01 DS_16_04_11\n",
"ABDOU ALI Nassim 13.5 9.5 NaN 10.5\n",
"ABDOUL-KADER Toura 4 3.5 4.5 8\n",
"AHAMADI Djelane 16 10.5 14 16.5\n",
"AHMED Aicha 17.5 18 17 16.5\n",
"AHMED Hamza 9 11 4.5 10.5\n",
"AHMED Laine 8 10.5 12 9.5\n",
"ALI Naima 17 9.5 13.5 15.5\n",
"ANSSURDINE Zaidou 12.5 7 NaN 8\n",
"ARBABI Idiamine 13 8 15.5 10\n",
"ATTOUMANI Mtahida 9 8.5 18.5 8\n",
"BACAR Musbahou 19 20 18.5 16.5\n",
"BACAR Natacha 14 4.5 14 11.5\n",
"BAHEDJA Rachma 16 10.5 16.5 16.5\n",
"CHAHARANE Djawadi 13 13 12 9\n",
"CHARIF Nassuria 12 13 11 14.5\n",
"COMBO Danil 14 5.5 7 11.5\n",
"HOUMADI Naima 5 10.5 16.5 NaN\n",
"IBRAHIM Hakim 10 11.5 10.5 9\n",
"IBRAHIM Yanick 12 14.5 18.5 17\n",
"MADI Himidati 5 10.5 11.5 10\n",
"MARI Ismaël 14 13 17.5 9.5\n",
"MOHAMED Yousra 8.5 8.5 18 10.5\n",
"MOUHOUDHOIRE Nithaou 7.5 5 15.5 9.5\n",
"SAINDOU Abdoul Anzize 9 4 NaN 10\n",
"SAÏD Hakim 17.5 20 19 19\n",
"SOIFENE Fémida 6.5 4.5 17 5.5\n",
"ZAKARIA Najwa 6.5 11.5 9 11.5"
]
},
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