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recopytex/templates/tpl_evaluation.ipynb

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{
"cells": [
{
"cell_type": "code",
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"execution_count": 1,
"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": true
}
}
}
}
},
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"outputs": [],
"source": [
"from IPython.display import Markdown as md\n",
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"from IPython.display import display, HTML\n",
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"import pandas as pd\n",
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"import ipywidgets as widgets\n",
"import seaborn as sns\n",
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"from pathlib import Path\n",
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"from datetime import datetime\n",
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"from recopytex import flat_df_students, pp_q_scores\n",
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"#import prettytable as pt\n",
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"%matplotlib inline"
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]
},
{
"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
"outputs": [],
"source": [
"cm = sns.light_palette(\"green\", as_cmap=True)"
]
},
{
"cell_type": "code",
"execution_count": 3,
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"metadata": {
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"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": true
}
}
}
},
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"tags": [
"parameters"
]
},
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"outputs": [],
"source": [
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"tribe = \"308\"\n",
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"assessment = \"DM1\"\n",
"date = \"15/09/16\"\n",
"csv_file = Path(f\"../sheets/{tribe}/160915_{assessment}.csv\")"
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]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": false
}
}
}
}
},
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"outputs": [
{
"data": {
"text/markdown": [
"# DM1 (15/09/16) pour 308"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
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"if date is None:\n",
" display(md(f\"# {assessment} pour {tribe}\"))\n",
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"else:\n",
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" display(md(f\"# {assessment} ({date}) pour {tribe}\"))"
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]
},
{
"cell_type": "code",
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"execution_count": 32,
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"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": true
}
}
}
}
},
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"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Trimestre</th>\n",
" <th>Nom</th>\n",
" <th>Date</th>\n",
" <th>Exercice</th>\n",
" <th>Question</th>\n",
" <th>Competence</th>\n",
" <th>Domaine</th>\n",
" <th>Commentaire</th>\n",
" <th>Bareme</th>\n",
" <th>Est_nivele</th>\n",
" <th>Eleve</th>\n",
" <th>Score</th>\n",
" <th>Note</th>\n",
" <th>Niveau</th>\n",
" <th>Normalise</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>DM1</td>\n",
" <td>15/09/16</td>\n",
" <td>1</td>\n",
" <td>1.1</td>\n",
" <td>Cal</td>\n",
" <td>Prio</td>\n",
" <td></td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>ABDOU Asmahane</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>DM1</td>\n",
" <td>15/09/16</td>\n",
" <td>1</td>\n",
" <td>1.2</td>\n",
" <td>Cal</td>\n",
" <td>Prio</td>\n",
" <td></td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>ABDOU Asmahane</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>DM1</td>\n",
" <td>15/09/16</td>\n",
" <td>1</td>\n",
" <td>1.3</td>\n",
" <td>Cal</td>\n",
" <td>Prio</td>\n",
" <td></td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>ABDOU Asmahane</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1</td>\n",
" <td>DM1</td>\n",
" <td>15/09/16</td>\n",
" <td>1</td>\n",
" <td>1.4</td>\n",
" <td>Cal</td>\n",
" <td>Prio</td>\n",
" <td></td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>ABDOU Asmahane</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1</td>\n",
" <td>DM1</td>\n",
" <td>15/09/16</td>\n",
" <td>1</td>\n",
" <td>1.5</td>\n",
" <td>Cal</td>\n",
" <td>Prio</td>\n",
" <td></td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>ABDOU Asmahane</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Trimestre Nom Date Exercice Question Competence Domaine Commentaire \\\n",
"0 1 DM1 15/09/16 1 1.1 Cal Prio \n",
"1 1 DM1 15/09/16 1 1.2 Cal Prio \n",
"2 1 DM1 15/09/16 1 1.3 Cal Prio \n",
"3 1 DM1 15/09/16 1 1.4 Cal Prio \n",
"4 1 DM1 15/09/16 1 1.5 Cal Prio \n",
"\n",
" Bareme Est_nivele Eleve Score Note Niveau Normalise \n",
"0 1.0 1 ABDOU Asmahane 2.0 1.0 2.0 1.0 \n",
"1 1.0 1 ABDOU Asmahane 3.0 1.0 3.0 1.0 \n",
"2 1.0 1 ABDOU Asmahane 2.0 1.0 2.0 1.0 \n",
"3 1.0 1 ABDOU Asmahane 2.0 1.0 2.0 1.0 \n",
"4 1.0 1 ABDOU Asmahane 2.0 1.0 2.0 1.0 "
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
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"source": [
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"stack_scores = pd.read_csv(csv_file, encoding=\"latin_1\")\n",
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"scores = flat_df_students(stack_scores).dropna(subset=[\"Score\"])\n",
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"scores = pp_q_scores(scores)\n",
"scores.head()"
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]
},
{
"cell_type": "code",
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"execution_count": 6,
"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": true
}
}
}
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}
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},
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"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
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" <th></th>\n",
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" <th>Note</th>\n",
" <th>Bareme</th>\n",
" </tr>\n",
" <tr>\n",
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" <th>Exercice</th>\n",
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" <th>Eleve</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
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" <th rowspan=\"5\" valign=\"top\">1</th>\n",
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" <th>ABDOU Asmahane</th>\n",
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" <td>5.0</td>\n",
" <td>6.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>ABOU Roihim</th>\n",
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" <td>0.0</td>\n",
" <td>6.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>AHMED BOINALI Kouraichia</th>\n",
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" <td>2.0</td>\n",
" <td>6.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>AHMED Rahada</th>\n",
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" <td>3.0</td>\n",
" <td>6.0</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>ALI SAID Anchourati</th>\n",
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" <td>0.0</td>\n",
" <td>6.0</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
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" Note Bareme\n",
"Exercice Eleve \n",
"1 ABDOU Asmahane 5.0 6.0\n",
" ABOU Roihim 0.0 6.0\n",
" AHMED BOINALI Kouraichia 2.0 6.0\n",
" AHMED Rahada 3.0 6.0\n",
" ALI SAID Anchourati 0.0 6.0"
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]
},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
],
"source": [
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"exercises_scores = scores.groupby([\"Exercice\", \"Eleve\"]).agg({\"Note\": \"sum\", \"Bareme\": \"sum\"})\n",
"exercises_scores.head()"
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]
},
{
"cell_type": "code",
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"execution_count": 7,
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"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": false
}
}
}
}
},
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"outputs": [
{
"data": {
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" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row0\" class=\"row_heading level0 row0\" >ABDOU Asmahane</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow0_col0\" class=\"data row0 col0\" >6.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow0_col1\" class=\"data row0 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row1\" class=\"row_heading level0 row1\" >ABOU Roihim</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow1_col0\" class=\"data row1 col0\" >0</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow1_col1\" class=\"data row1 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row2\" class=\"row_heading level0 row2\" >AHMED BOINALI Kouraichia</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow2_col0\" class=\"data row2 col0\" >3.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow2_col1\" class=\"data row2 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row3\" class=\"row_heading level0 row3\" >AHMED Rahada</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow3_col0\" class=\"data row3 col0\" >7</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow3_col1\" class=\"data row3 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row4\" class=\"row_heading level0 row4\" >ALI SAID Anchourati</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow4_col0\" class=\"data row4 col0\" >0</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow4_col1\" class=\"data row4 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row5\" class=\"row_heading level0 row5\" >ASSANE Noussouraniya</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow5_col0\" class=\"data row5 col0\" >5.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow5_col1\" class=\"data row5 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row6\" class=\"row_heading level0 row6\" >BACAR Issiaka</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow6_col0\" class=\"data row6 col0\" >0</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow6_col1\" class=\"data row6 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row7\" class=\"row_heading level0 row7\" >BACAR Samina</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow7_col0\" class=\"data row7 col0\" >4</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow7_col1\" class=\"data row7 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row8\" class=\"row_heading level0 row8\" >CHAIHANE Said</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow8_col0\" class=\"data row8 col0\" >6</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow8_col1\" class=\"data row8 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row9\" class=\"row_heading level0 row9\" >COMBO Houzaimati</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow9_col0\" class=\"data row9 col0\" >6</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow9_col1\" class=\"data row9 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row10\" class=\"row_heading level0 row10\" >DAOUD Anzilati</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow10_col0\" class=\"data row10 col0\" >7.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow10_col1\" class=\"data row10 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row11\" class=\"row_heading level0 row11\" >DAOUD Talaenti</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow11_col0\" class=\"data row11 col0\" >8</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow11_col1\" class=\"data row11 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row12\" class=\"row_heading level0 row12\" >DARKAOUI Rachma</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow12_col0\" class=\"data row12 col0\" >8</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow12_col1\" class=\"data row12 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row13\" class=\"row_heading level0 row13\" >DHAKIOINE Nabaouya</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow13_col0\" class=\"data row13 col0\" >1</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow13_col1\" class=\"data row13 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row14\" class=\"row_heading level0 row14\" >DJANFAR Soioutinour</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow14_col0\" class=\"data row14 col0\" >7.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow14_col1\" class=\"data row14 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row15\" class=\"row_heading level0 row15\" >DRISSA Ibrahim</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow15_col0\" class=\"data row15 col0\" >0</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow15_col1\" class=\"data row15 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row16\" class=\"row_heading level0 row16\" >HACHIM SIDI Assani</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow16_col0\" class=\"data row16 col0\" >8.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow16_col1\" class=\"data row16 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row17\" class=\"row_heading level0 row17\" >HAFIDHUI Zalifa</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow17_col0\" class=\"data row17 col0\" >8</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow17_col1\" class=\"data row17 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row18\" class=\"row_heading level0 row18\" >HOUMADI Marie</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow18_col0\" class=\"data row18 col0\" >7.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow18_col1\" class=\"data row18 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row19\" class=\"row_heading level0 row19\" >HOUMADI Sania</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow19_col0\" class=\"data row19 col0\" >5.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow19_col1\" class=\"data row19 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row20\" class=\"row_heading level0 row20\" >MAANDHUI Halouoi</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow20_col0\" class=\"data row20 col0\" >8.5</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow20_col1\" class=\"data row20 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row21\" class=\"row_heading level0 row21\" >MASSONDI Nasma</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow21_col0\" class=\"data row21 col0\" >8</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow21_col1\" class=\"data row21 col1\" >12</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11dlevel0_row22\" class=\"row_heading level0 row22\" >SAIDALI Irichad</th>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow22_col0\" class=\"data row22 col0\" >7</td>\n",
" <td id=\"T_996dd6e8_c3d5_11e9_aaaf_902b34d9e11drow22_col1\" class=\"data row22 col1\" >12</td>\n",
" </tr>\n",
" </tbody></table>"
],
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"text/plain": [
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"<pandas.io.formats.style.Styler at 0x7f92fc46a9d0>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"assessment_scores = scores.groupby([\"Eleve\"]).agg({\"Note\": \"sum\", \"Bareme\": \"sum\"})\n",
"#assessment_scores.style.background_gradient(cmap=cm, subset=[\"Note\"])\n",
"assessment_scores.style.bar(subset=[\"Note\"])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"12.0"
Feat: first analysis and plots
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]
},
Feat: Base for student exploration
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"execution_count": 8,
Feat: first analysis and plots
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
Feat: short summary of student results
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"assessment_scores.Bareme.max()"
Feat: first analysis and plots
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]
},
{
"cell_type": "code",
Feat: Base for student exploration
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"execution_count": 9,
"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": false
}
}
}
}
},
Feat: first analysis and plots
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"outputs": [
{
"data": {
"text/plain": [
Feat: short summary of student results
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"count 23.00\n",
"mean 5.37\n",
"std 3.08\n",
"min 0.00\n",
"25% 3.75\n",
"50% 6.50\n",
"75% 7.75\n",
"max 8.50\n",
"Name: Note, dtype: float64"
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]
},
Feat: Base for student exploration
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"execution_count": 9,
Feat: first analysis and plots
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"metadata": {},
"output_type": "execute_result"
Feat: short summary of student results
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}
],
"source": [
"assessment_scores[\"Note\"].describe()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f92c5d2a450>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
Feat: first analysis and plots
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},
{
"data": {
Feat: short summary of student results
2019-08-21 05:56:00 +00:00
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Feat: first analysis and plots
2019-08-04 21:24:32 +00:00
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
Feat: short summary of student results
2019-08-21 05:56:00 +00:00
"dp = sns.distplot(assessment_scores.Note, bins=int(assessment_scores.Bareme[0])*2)\n",
"dp.set(xlim=(0, assessment_scores.Bareme[0]))\n",
"dp"
Feat: cli to make a report
2019-08-04 14:25:44 +00:00
]
},
{
"cell_type": "code",
Feat: short summary of student results
2019-08-21 05:56:00 +00:00
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>Note</th>\n",
" <th>Bareme</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Exercice</th>\n",
" <th>Eleve</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">1</th>\n",
" <th>ABDOU Asmahane</th>\n",
" <td>5.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ABOU Roihim</th>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED BOINALI Kouraichia</th>\n",
" <td>2.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AHMED Rahada</th>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALI SAID Anchourati</th>\n",
" <td>0.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Note Bareme\n",
"Exercice Eleve \n",
"1 ABDOU Asmahane 5.0 6.0\n",
" ABOU Roihim 0.0 6.0\n",
" AHMED BOINALI Kouraichia 2.0 6.0\n",
" AHMED Rahada 3.0 6.0\n",
" ALI SAID Anchourati 0.0 6.0"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"exercises_scores.head()"
]
},
{
"cell_type": "code",
"execution_count": 79,
Feat: Base for student exploration
2019-08-20 19:15:39 +00:00
"metadata": {
"extensions": {
"jupyter_dashboards": {
"version": 1,
"views": {
"grid_default": {},
"report_default": {
"hidden": true
}
}
}
}
},
Feat: cli to make a report
2019-08-04 14:25:44 +00:00
"outputs": [],
Feat: short summary of student results
2019-08-21 05:56:00 +00:00
"source": [
"def st_results(student):\n",
" html = \"<div class='card'>\"\n",
" html += \"<div class='container'>\"\n",
" \n",
" ass = assessment_scores.loc[student]\n",
" exercices = exercises_scores.xs(student, level=\"Eleve\")\n",
" \n",
" html += f\"<h2> {student} -- {assessment}</h2>\"\n",
" html += f\"<p> {ass.Note} / {ass.Bareme}</p>\"\n",
" for (i, ex) in exercices.iterrows():\n",
" if not ex.Bareme == 0:\n",
" html += f\"<h3> Exercice {i} ({ex.Note}/{ex.Bareme})</h3>\"\n",
" html += scores.loc[(scores.Exercice==i) & (scores.Eleve==student)][[\"Question\", \"Commentaire\", \"Note\", \"Bareme\"]].to_html()\n",
" html += \"</div>\"\n",
" html += \"</div>\"\n",
" return HTML(html)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "788cdf676be445669085d7de593a8eeb",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(Dropdown(description='student', options=('ABDOU Asmahane', 'ABOU Roihim', 'AHMED BOINALI…"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<function __main__.st_results(student)>"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"widgets.interact(st_results, student=list(assessment_scores.index))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
Feat: cli to make a report
2019-08-04 14:25:44 +00:00
"source": []
}
],
"metadata": {
"celltoolbar": "Tags",
Feat: Base for student exploration
2019-08-20 19:15:39 +00:00
"extensions": {
"jupyter_dashboards": {
"activeView": "grid_default",
"version": 1,
"views": {
"grid_default": {
"cellMargin": 10,
"defaultCellHeight": 20,
"maxColumns": 12,
"name": "grid",
"type": "grid"
},
"report_default": {
"name": "report",
"type": "report"
}
}
}
},
Feat: cli to make a report
2019-08-04 14:25:44 +00:00
"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",
Feat: Base for student exploration
2019-08-20 19:15:39 +00:00
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Feat: cli to make a report
2019-08-04 14:25:44 +00:00
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