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61cbc2a4c93a3237a08f8b8e6c523229
mooc-rr
Commits
0ebecc30
Commit
0ebecc30
authored
Apr 03, 2020
by
61cbc2a4c93a3237a08f8b8e6c523229
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Stats MOOC RR.ipynb
Projet Maman 2/Stats MOOC RR.ipynb
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Projet Maman 2/Stats MOOC RR.ipynb
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0ebecc30
...
...
@@ -16,7 +16,7 @@
},
{
"cell_type": "code",
"execution_count":
4
2,
"execution_count":
23
2,
"metadata": {},
"outputs": [
{
...
...
@@ -54,18 +54,19 @@
"27 QuizP 36 12 OrgMode\n",
"28 Exercices 195 1 Module 1\n",
"29 Exercices 117 2 Module 2\n",
"30 Exercices 85 3 Module 3\n"
"30 Exercices 85 3 Module 3\n",
"31 ExoEvalPair 11 4 ExoEval\n"
]
}
],
"source": [
"## Tableau\n",
"\n",
"Type_init= list(donnees.columns[3:19])+list(donnees.columns[20:32])+list(donnees.columns[34:37])\n",
"Type_init= list(donnees.columns[3:19])+list(donnees.columns[20:32])+list(donnees.columns[34:37])
+[\"ExoEvalPair\"]
\n",
"Type=[i.split()[0] for i in Type_init]\n",
"Id=[int(i.split()[1]) for i in Type_init]\n",
"Id=[int(i.split()[1]) for i in Type_init
[:-1]]+[4
]\n",
"Num=[(sum(donnees.loc[:,type]>0)) for type in Type_init]\n",
"Label=[\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 3\",\"Module 3\",\"Module 4\",\"Module 4\",\"Module 4\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Module 1\",\"Module 2\",\"Module 3\"]\n",
"Label=[\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 1\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 2\",\"Module 3\",\"Module 3\",\"Module 4\",\"Module 4\",\"Module 4\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Jupiter\",\"R\",\"OrgMode\",\"Module 1\",\"Module 2\",\"Module 3\"
,\"ExoEval\"
]\n",
"tableau=pd.DataFrame({'Type':Type,\"Id\":Id,\"Num\":Num,\"Label\":Label})\n",
"col=[\"Type\",\"Num\",\"Id\",\"Label\"]\n",
"tableau = tableau.loc[:, col]\n",
...
...
@@ -74,7 +75,7 @@
},
{
"cell_type": "code",
"execution_count": 2
15
,
"execution_count": 2
33
,
"metadata": {},
"outputs": [
{
...
...
@@ -139,6 +140,36 @@
" \n",
"Graphique('inria_41016_self-paced_grade_report_2020-04-02-1234.csv','inria_41016_self-paced_grade_report_2020-03-27-0806.csv')"
]
},
{
"cell_type": "code",
"execution_count": 245,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nombre d'élèves qui on commencé les exercices : 326\n",
"Nombre d'élèves qui on au dessus de la moyenne : 116\n",
"Nombre d'élèves qui on fait ExoEvalPair : 11\n",
"Moyenne ExoEvalPair : 0.8295454545454546\n"
]
}
],
"source": [
"## Données supplémentaires\n",
"\n",
"exos=sum(donnees.loc[:,\"grade\"]>0)\n",
"moyenne=sum(donnees.loc[:,\"grade\"]>0.5)\n",
"Pair=sum(donnees.loc[:,\"ExoEvalPair\"]>0)\n",
"moyenne_Pair=np.mean(donnees.loc[donnees.loc[:,\"ExoEvalPair\"]>0,\"ExoEvalPair\"])\n",
"\n",
"print(f\"Nombre d'élèves qui on commencé les exercices : {exos}\")\n",
"print(f\"Nombre d'élèves qui on au dessus de la moyenne : {moyenne}\")\n",
"print(f\"Nombre d'élèves qui on fait ExoEvalPair : {Pair}\")\n",
"print(f\"Moyenne ExoEvalPair : {moyenne_Pair}\")"
]
}
],
"metadata": {
...
...
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