{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from IPython.display import Markdown, display\n", "\n", "\n", "donnees=pd.read_csv(\"results-survey669838(3).csv\")" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def histogramme(colonne):\n", " tableau_colonne = donnees.loc[:,colonne].value_counts().sort_values(ascending=False)\n", " tableau_colonne.plot(kind=\"bar\")\n", " plt.title(colonne)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "Vidéo_de_cours=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Vidéos de cours]\"\n", "Interview=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Interviews]\"\n", "Quiz=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Quiz]\"\n", "Exercices_pratiques_evalues=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Exercices pratiques évalués (Module 1, 2 et 3)]\"\n", "Exercices_evalues_pairs=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Exercice évalué par les pairs (Module 3)]\"\n", "Ressources_complementaires=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Ressources complémentaires]\"\n", "liste_satisfactions=[Vidéo_de_cours,Interview,Quiz,Exercices_pratiques_evalues,Exercices_evalues_pairs,Ressources_complementaires]\n", "\n", "dico_satisfactions={}\n", "for satisfaction in liste_satisfactions:\n", " dico_satisfactions[(satisfaction.split(\" \"))[2].strip(\"[\").strip(\"]\")]=np.mean(donnees.loc[:,satisfaction])\n", " \n", "\n", "pd.Series(dico_satisfactions).plot(kind=\"barh\",xticks=np.arange(0,round(max(dico_satisfactions.values()),1),1))\n", "plt.grid(axis=\"x\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "### Vidéo_de_cours=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Vidéos de cours]\"\n", "Interview=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Interviews]\"\n", "Quiz=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Quiz]\"\n", "Exercices_pratiques_evalues=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Exercices pratiques évalués (Module 1, 2 et 3)]\"\n", "Exercices_evalues_pairs=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Exercice évalué par les pairs (Module 3)]\"\n", "Ressources_complementaires=\"Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Ressources complémentaires]\"\n", "liste_satisfactions=[Vidéo_de_cours,Interview,Quiz,Exercices_pratiques_evalues,Exercices_evalues_pairs,Ressources_complementaires]\n", "\n", "dico_satisfactions_Rstudio={}\n", "for satisfaction in liste_satisfactions:\n", " dico_satisfactions_Rstudio[(satisfaction.split(\" \"))[2].strip(\"[\").strip(\"]\")]=np.mean(donnees.loc[donnees.loc[:,\"Quel(s) parcour(s) avez-vous suivi ? [RStudio]\"]==\"Oui\",satisfaction])\n", " \n", "dico_satisfactions_Jupyter={}\n", "for satisfaction in liste_satisfactions:\n", " dico_satisfactions_Jupyter[(satisfaction.split(\" \"))[2].strip(\"[\").strip(\"]\")]=np.mean(donnees.loc[donnees.loc[:,\"Quel(s) parcour(s) avez-vous suivi ? [Jupyter]\"]==\"Oui\",satisfaction])\n", "\n", "dico_satisfactions_OrgMode={}\n", "for satisfaction in liste_satisfactions:\n", " dico_satisfactions_OrgMode[(satisfaction.split(\" \"))[2].strip(\"[\").strip(\"]\")]=np.mean(donnees.loc[donnees.loc[:,\"Quel(s) parcour(s) avez-vous suivi ? [Org-mode]\"]==\"Oui\",satisfaction])\n", "\n", "pd.DataFrame({\"Orgmode\":dico_satisfactions_OrgMode,\"Jupyter\":dico_satisfactions_Jupyter,\"RStudio\":dico_satisfactions_Rstudio}).plot(kind=\"barh\",xticks=np.arange(0,round(max(dico_satisfactions.values()),1),1))\n", "plt.grid(axis=\"x\")\n", "plt.show()" ] } ], "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 4 }