diff --git a/Projet Maman 2/Stats MOOC RR.ipynb b/Projet Maman 2/Stats MOOC RR.ipynb index ed43a4c34c63fa1721388c93db0648d8336f430b..41161b287b4314219afad2eef25b17b293585c85 100644 --- a/Projet Maman 2/Stats MOOC RR.ipynb +++ b/Projet Maman 2/Stats MOOC RR.ipynb @@ -66,7 +66,7 @@ "Type=[i.split()[0] 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\",\"ExoEval\"]\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\",\"ExoEvalPair\"]\n", "tableau=pd.DataFrame({'Type':Type,\"Id\":Id,\"Num\":Num,\"Label\":Label})\n", "col=[\"Type\",\"Num\",\"Id\",\"Label\"]\n", "tableau = tableau.loc[:, col]\n", diff --git a/Projet Maman 3/Untitled.ipynb b/Projet Maman 3/Untitled.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5f884928f16e22f8a6c13eb020eec86d72d243d8 --- /dev/null +++ b/Projet Maman 3/Untitled.ipynb @@ -0,0 +1,145 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 23, + "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": 67, + "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\",grid=True,xticks=np.arange(0,round(max(dico_satisfactions.values()),1),1))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "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\")\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 +} diff --git a/Projet Maman 3/results-survey669838(3).csv b/Projet Maman 3/results-survey669838(3).csv new file mode 100644 index 0000000000000000000000000000000000000000..7fa854ad0d1125e1926a3dbdcc73b5813cf33fd6 --- /dev/null +++ b/Projet Maman 3/results-survey669838(3).csv @@ -0,0 +1,51 @@ +"ID de la réponse","Date de soumission","Dernière page","Langue de départ","Tête de série","Date de lancement","Date de la dernière action","URL référente","Question cachée pour enregistrer l'ID anonymisé des apprenants. ","Le MOOC a-t-il satisfait vos attentes ?","Pour quelle raison ?","Avez-vous eu la possibilité de vous investir dans ce MOOC comme vous l’aviez prévu ?","Si non, quels ont été les éléments bloquants ? [Des éléments personnels]","Si non, quels ont été les éléments bloquants ? [Des éléments techniques]","Si non, quels ont été les éléments bloquants ? [ Des difficultés dans la gestion de mon temps]","Si non, quels ont été les éléments bloquants ? [ Une mauvaise évaluation de l’effort à fournir par semaine selon vous]","Si non, quels ont été les éléments bloquants ? [Autre]","L’effort à fournir était-il conforme à ce qui était annoncé ?","Quel est votre niveau de connaissance sur le sujet après avoir suivi ce MOOC ?","Combien d'heures par semaine avez-vous passé sur le MOOC ?","Compte tenu du temps investi, êtes-vous satisfait(e) de ce que vous avez appris ?","Pourquoi n'êtes-vous pas satisfait(e) de ce que vous avez pu apprendre en suivant ce MOOC ?","Avez-vous contribué aux activités collaboratives du MOOC (forum, wiki, vidéos en direct, évaluation par les pairs, projets de groupe...) ?","Allez-vous conseiller ce MOOC à des amis ou à des collègues ?","Allez-vous pouvoir mettre en pratique ce que vous avez appris ?","Avez-vous satisfait les conditions d'obtention d'une attestation de suivi avec succès gratuite pour ce MOOC ?","Avez-vous finalement passé un certificat payant sur ce MOOC ?","Que pensez-vous faire de votre certificat et/ou de votre attestation ?","Avez-vous l’intention de suivre un autre MOOC ?","Avez-vous l’intention de suivre un autre MOOC ? [Autre]","Pour quelle raison ?","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [edx.org]","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [ Coursera]","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [ FutureLearn]","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [ MiriadaX]","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [ OpenClassrooms]","Si vous suivez des MOOC sur d'autres plateformes, quelles sont-elles ? (question facultative) [Autre]","Avez-vous trouvé la plateforme agréable à utiliser ?","Pour quelle raison ?","Etes-vous satisfait(e) du catalogue de cours disponibles ?","Pourquoi ?","Quelles sont les thématiques qui vous intéressent le plus ? [Agronomie et agriculture]","Quelles sont les thématiques qui vous intéressent le plus ? [Arts, création et design]","Quelles sont les thématiques qui vous intéressent le plus ? [Chimie]","Quelles sont les thématiques qui vous intéressent le plus ? [Communication]","Quelles sont les thématiques qui vous intéressent le plus ? [Cultures et civilisations]","Quelles sont les thématiques qui vous intéressent le plus ? [Découverte de l'Univers]","Quelles sont les thématiques qui vous intéressent le plus ? [Développement durable]","Quelles sont les thématiques qui vous intéressent le plus ? [Droit et juridique]","Quelles sont les thématiques qui vous intéressent le plus ? [Économie et finance]","Quelles sont les thématiques qui vous intéressent le plus ? [Education et formation]","Quelles sont les thématiques qui vous intéressent le plus ? [Enjeux de société ]","Quelles sont les thématiques qui vous intéressent le plus ? [Entrepreneuriat]","Quelles sont les thématiques qui vous intéressent le plus ? [Environnement]","Quelles sont les thématiques qui vous intéressent le plus ? [Géographie]","Quelles sont les thématiques qui vous intéressent le plus ? [Histoire]","Quelles sont les thématiques qui vous intéressent le plus ? [Informatique]","Quelles sont les thématiques qui vous intéressent le plus ? [Innovation]","Quelles sont les thématiques qui vous intéressent le plus ? [Langues]","Quelles sont les thématiques qui vous intéressent le plus ? [Lettres]","Quelles sont les thématiques qui vous intéressent le plus ? [Management]","Quelles sont les thématiques qui vous intéressent le plus ? [Mathématiques et statistiques]","Quelles sont les thématiques qui vous intéressent le plus ? [Médias]","Quelles sont les thématiques qui vous intéressent le plus ? [Numérique, technologie]","Quelles sont les thématiques qui vous intéressent le plus ? [Orientation]","Quelles sont les thématiques qui vous intéressent le plus ? [Outils, méthodes et enjeux de la recherche]","Quelles sont les thématiques qui vous intéressent le plus ? [Philosophie]","Quelles sont les thématiques qui vous intéressent le plus ? [Physique]","Quelles sont les thématiques qui vous intéressent le plus ? [Programmation]","Quelles sont les thématiques qui vous intéressent le plus ? [Relations internationales]","Quelles sont les thématiques qui vous intéressent le plus ? [Réseaux et télécommunications]","Quelles sont les thématiques qui vous intéressent le plus ? [Santé]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences cognitives]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences de la Terre et de l'Univers]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences de la vie]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences humaines et sociales]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences Politiques]","Quelles sont les thématiques qui vous intéressent le plus ? [Sciences pour l'ingénieur]","Quelles sont les thématiques qui vous intéressent le plus ? [Sport]","Quelles sont les thématiques qui vous intéressent le plus ? [TPE-PME]","Quelles sont les thématiques qui vous intéressent le plus ? [Vie de l'entreprise]","Quelles sont les thématiques qui vous intéressent le plus ? [Autre]","Auriez-vous souhaité bénéficier de services complémentaires, éventuellement payants ?","Lesquels ?","Ce MOOC a-t-il répondu à vos besoins spécifiques d'accès aux contenus (accessibilité numérique, par exemple : sous-titrage, versions adaptées du document...) ? []","Avez-vous trouvé des informations relatives à l’accessibilité au sein du MOOC ?","Avez-vous des suggestions ou un avis concernant l’accessibilité du MOOC ?","J'autorise FUN à publier mon témoignage :","Avez-vous d'autres commentaires, remarques ou suggestions d'amélioration à nous communiquer ?","Bienvenue dans le groupe ""Questions de l'équipe du MOOC"" ! Vous pouvez ajouter jusqu'à 5 questions à la suite de celle-ci. Ne supprimez pas cette question car elle vous permet de prévisualiser le questionnaire avant de l'activer ! Pour ajouter des questions, vous pouvez vous référer au guide suivant : https://www.reseau-fun.help/hc/fr/articles/360000333858 Pour toute demande relative aux questionnaires de début et fin de cours, veuillez contacter le D2RP en cliquant sur « Envoyer une demande » en haut à droite du centre d’aide www.reseau-fun.help. ","Quel(s) parcour(s) avez-vous suivi ? [Jupyter]","Quel(s) parcour(s) avez-vous suivi ? [RStudio]","Quel(s) parcour(s) avez-vous suivi ? [Org-mode]","Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Vidéos de cours]","Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Interviews]","Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Quiz]","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)]","Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Exercice évalué par les pairs (Module 3)]","Dans quelle mesure avez-vous apprécié les éléments suivants du cours ? (1= pas satisfait ; 4= très satisfait) [Ressources complémentaires]","Quels outils comptez-vous utiliser ? [Markdown]","Quels outils comptez-vous utiliser ? [Pandoc]","Quels outils comptez-vous utiliser ? [Gitlab]","Quels outils comptez-vous utiliser ? [DocFetcher]","Quels outils comptez-vous utiliser ? [ExifTool]","Quels outils comptez-vous utiliser ? [Jupyter]","Quels outils comptez-vous utiliser ? [RStudio]","Quels outils comptez-vous utiliser ? [Emacs]","Quels sont, selon vous, les points positifs de ce cours ?","Avez-vous quelques suggestions et/ou points d'amélioration ? N'hésitez pas à préciser ce que vous auriez aimé voir dans ce cours qui n'y est pas, ce qui aurait pu être approfondi, ce qui vous a manqué ... ","Avez-vous des retours à nous faire sur le forum ? N'hésitez pas à nous dire comment vous l'avez utilisé et ce que vous en avez pensé.","Temps total :","Durée pour le groupe : Codification","Durée pour la question: code","Durée pour le groupe : Objectifs apprentissages","Durée pour la question: F01FUN","Durée pour la question: F01FUNC01","Durée pour la question: F02FUN","Durée pour la question: F02FUNC01","Durée pour la question: F03FUN","Durée pour la question: F04FUN","Durée pour la question: F05FUN","Durée pour la question: F06FUN","Durée pour la question: F06FUNC01","Durée pour la question: F07FUN","Durée pour la question: F08FUN","Durée pour la question: F09FUN","Durée pour la question: F10FUN","Durée pour la question: F11FUN","Durée pour la question: F1011FUNC01","Durée pour le groupe : Vos attentes","Durée pour la question: F12FUN","Durée pour la question: F12FUNC01","Durée pour la question: F13FUN","Durée pour la question: F14FUN","Durée pour la question: F14FUNC01","Durée pour la question: F15FUN","Durée pour la question: F16FUN","Durée pour la question: F17FUN","Durée pour la question: F18FUN","Durée pour la question: F18FUNC01","Durée pour le groupe : Accessibilité","Durée pour la question: F19FUN","Durée pour la question: F20FUN","Durée pour la question: F21FUN","Durée pour la question: F21FUNC01","Durée pour le groupe : Commentaires additionnels","Durée pour la question: F22FUN","Durée pour le groupe : Questions de l'équipe du MOOC","Durée pour la question: F00EM","Durée pour la question: DILLparcours","Durée pour la question: DILLsatisfaction","Durée pour la question: DILLoutils","Durée pour la question: DILLpositifs","Durée pour la question: DILLproposition","Durée pour la question: DILLforum" +"17","2020-03-23 00:45:29","6","en","1608630492","2020-03-23 00:40:39","2020-03-23 00:45:29","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","217ba8a7fafa77ac394998c6998cc603","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","1h à 2h","Oui, plutôt","","Non, pas du tout","Oui, probablement","Oui, tout à fait","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Peut-être","","","Non","Oui","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","","Non","","Non concerné","Non","","","","","Oui","Non","Non","3","2","3","3","2","4","Oui","Non","Oui","Non","Non","Oui","Non","Non","","","","284.63","","","156.84","","","","","","","","","","","","","","","","50.88","","","","","","","","","","","19.12","","","","","8.77","","49.02","","","","","","","" +"24","2020-03-23 17:50:18","6","en","70578783","2020-03-23 17:48:39","2020-03-23 17:50:18","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","315f358433aa0886134e9d72427a8d82","Non, pas du tout","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Débutant","2h à 3 h","Oui, complètement","","Oui, tout à fait","Oui, certainement","Oui, probablement","Oui, tout à fait","Oui","","Peut-être","","","Oui","Oui","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Eventuellement","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","3","3","3","3","3","3","Oui","Non","Oui","Non","Non","Oui","Non","Non","","","","81.69","","","31.85","","","","","","","","","","","","","","","","22.73","","","","","","","","","","","7.48","","","","","3","","16.63","","","","","","","" +"28","2020-03-24 09:45:36","6","fr","2033350482","2020-03-24 09:37:24","2020-03-24 09:45:36","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","57b9d1400938c1a73c89812eb7af6bdc","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, plutôt","Avancé","Plus de 5h","Oui, complètement","","Non, pas du tout","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Oui","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","","Non","","Oui, tout à fait","Oui","Eventuellement de l'audiodescription ? +","Oui","Merci infiniment pour ce mooc c'était super et comble un gros manque de formation pratique à la recherche dans le système français. +Je vais profiter du confinement pour repenser mes outils de thèse de ce pas, et je n'ai qu'un regret c'es de ne pas avoir connu ce mooc plus tôt ce qui m'aurait fait gagner bien du temps !","","Oui","Non","Non","4","3","3","2","","4","Oui","Non","Oui","Non","Non","Oui","Non","Non","Très peu de pré-requis, l'essentiel est bien mis en valeur dans les vidéos comme ""sommaire de luxe"", et le choix est laissé grâce aux docs complémentaires d'approfondir les outils qui nous paraissent utiles.","Il y a deux ou trois questions de quiz où ce sont des carrés au lieu des ronds (ou inversement). +Des fois, le nombre de réponses attendues est précisé et d'autre fois pas, ce qui peut induire en erreur. +Regarder les questions où la réussite est la plus faible devrait pouvoir vous aider à traquer ces cas!","","492.16","","","43.72","","","","","","","","","","","","","","","","45.97","","","","","","","","","","","118.6","","","","","105.55","","178.32","","","","","","","" +"68","2020-03-27 15:37:34","6","fr","15819038","2020-03-27 15:23:46","2020-03-27 15:37:34","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","3fc2553edccc8ce04ff4284658a43487","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Avancé","Plus de 5h","Oui, plutôt","","Non, pas vraiment","Oui, probablement","Oui, tout à fait","Ce n'était pas mon but initial mais l'ai eue et j'en suis satisfait(e)","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","2","3","3","2","4","Non","Non","Oui","Non","Non","Oui","Non","Non","","Pour le TD du module 3: j'aurais aimé la possibilité de ne pas review (via un lien par exemple) un de mes pair car je n'arrivais pas a estimer si celui-ci avait réalisé le travail ou non. +Je m'explique, l'étudiant n'a fourni aucune information sauf un lien vers un fichier sur son espace personnel (à convertir en espace gitlab). Ce fichier était vide et j'ai donc regardé le dernier fichier modifié qui était un fichier orgmode (que je ne maitrise pas du tout). J'ai donc passé un peu de temps pour tenter de reproduire son travail pour finalement conclure que la personne n'a pas réalisé l'exercice demandé. C'est très frustrant. +Le deuxième pair était plus aisé à corriger car le lien vers le pdf fonctionnait (mais pas celui du notebook). J'ai cependant passé un peu de temps pour tester son script car la copie depuis un fichier pdf ne conserve pas le format python. + +Le processus de reviewing prend du temps (et encore plus dans un cadre réel), peut être trop dans le cadre d'un MOOC.","","822.73","","","75.47","","","","","","","","","","","","","","","","71.86","","","","","","","","","","","37.46","","","","","15.15","","622.79","","","","","","","" +"76","2020-03-27 19:12:51","6","en","814956595","2020-03-27 19:09:28","2020-03-27 19:12:51","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","b0d8849cabfd978d26bf972a065187ab","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, plutôt","Avancé","Plus de 5h","Oui, plutôt","","Non, pas du tout","Oui, probablement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","4","4","4","","3","Oui","Non","Oui","Non","Non","Oui","Non","Non","","","","198.45","","","90.45","","","","","","","","","","","","","","","","42.81","","","","","","","","","","","22.89","","","","","5.81","","36.49","","","","","","","" +"79","2020-03-27 23:30:41","6","fr","1169283907","2020-03-27 23:24:27","2020-03-27 23:30:41","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","754f45c6a8f0b015f5e6ca7cf5ef80b6","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","1h à 2h","Oui, complètement","","Non, pas du tout","Oui, probablement","Oui, tout à fait","Ce n'était pas mon but initial mais l'ai eue et j'en suis satisfait(e)","Non, le MOOC n'en proposait pas","","Autre","gestionnaire de version","","Oui","Non","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Non","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","3","4","4","2","2","Oui","Oui","Oui","Non","Non","Oui","Non","Oui","Bonne qualité des vidéos, exercices abordables","quelques quizz ne sont pas exactement en rapport avec les vidéos, les exercices de la fin sont plus complexes (trop ?)","Continuez, il y a encore plein de choses à expliquer et faire découvrir.","374.69","","","99.78","","","","","","","","","","","","","","","","83.92","","","","","","","","","","","15.88","","","","","11.18","","163.93","","","","","","","" +"84","2020-03-29 14:19:46","6","fr","831676245","2020-03-29 14:03:10","2020-03-29 14:19:46","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","f7761dbf5e688ce6ed562c39d3e11475","Oui, complètement","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","2h à 3 h","Oui, plutôt","","Non, pas vraiment","Oui, certainement","Oui, probablement","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","tous mes moods concernant la recherche reproductible et les statistiques m'intéressent grandement.","","Non","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","","","","","J'ai trouvé le Mooc vraiment très bien, tant dans les contenus que dans la construction avec alternance de cours, quizz et exercices. J'ai été heureuse qu'il concerne des aspects pratiques et réponde à certaines de mes questions. Je vais me mettre de ce pas à l'utilisation de certaines plateformes (très heureuse notamment de découvrir les bases de Git). Je n'ai pas encore réalisé le travail d'évaluation par pairs par manque de temps, mais je le ferai peut être ultérieurement. Je n'ai pas vraiment réussi à investir le journal. j'ai été étonnée que l'on ne parle pas dans ce Mooc de tous les aspects ""pré-enregistrement"" (plateforme OSF notamment). Peut-être qu'il serait intéressant d'ajouter cela? +Merci aux formateurs pour leur excellent travail.","","Non","Oui","Non","4","2","3","4","","4","Oui","Non","Oui","Non","Non","Non","Oui","Non","- très utile, très pratique. Abord des points non abordés lors des études et pourtant indispensables au métier de chercheur.","- approfondir la différence entre GitLab et GitHub ; formation à GitHub aussi? (mais peut etre très proche de Gitlab?) +- parler des procédures de pré-enregistrement et de la plateforme OSF par exemple","","991.92","","","406.13","","","","","","","","","","","","","","","","103.76","","","","","","","","","","","30.68","","","","","278.59","","172.76","","","","","","","" +"103","2020-03-31 17:02:11","6","en","947628490","2020-03-31 16:59:15","2020-03-31 17:02:11","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","2386bd0a28a48d17116638ec221d560d","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","2h à 3 h","Oui, complètement","","Non, pas du tout","Oui, probablement","Oui, probablement","Ce n'était pas mon but initial mais l'ai eue et j'en suis satisfait(e)","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Oui","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Oui","Non","Non","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","3","3","3","4","4","4","Oui","Non","Oui","Non","Non","Oui","Non","Non","","","","171.66","","","56.74","","","","","","","","","","","","","","","","64.86","","","","","","","","","","","13.93","","","","","5.95","","30.18","","","","","","","" +"108","2020-04-01 13:49:30","6","fr","93915182","2020-04-01 13:46:23","2020-04-01 13:49:30","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/1?activate_block_id=block-v1%3Ainria%2B41016%2Bself-paced%2Btype%40vertical%2Bblock%402048947c5dc44a0697d765ab7698e9f3","c1be096ce5a0b3b0084e344aef021f79","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","2h à 3 h","Oui, complètement","","Non, pas du tout","Oui, probablement","Oui, probablement","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Oui","Non","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Non","Oui","Non","4","3","4","4","3","2","Oui","Non","Non","Non","Non","Non","Oui","Non","","","","179.39","","","49.91","","","","","","","","","","","","","","","","77.53","","","","","","","","","","","11.75","","","","","5.93","","34.27","","","","","","","" +"116","2020-04-02 10:54:25","6","fr","1395599532","2020-04-02 10:50:24","2020-04-02 10:54:25","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","561f29363a95279df3290b2b9e82d6e0","Oui, plutôt","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","Plus de 5h","Oui, plutôt","","Oui, en partie","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","","","","","","Oui","Non","Non","4","4","3","2","3","4","Oui","Oui","Oui","Non","Non","Oui","Oui","Non","","","","240.69","","","93.52","","","","","","","","","","","","","","","","77.05","","","","","","","","","","","19.32","","","","","3.42","","47.38","","","","","","","" +"119","2020-04-02 12:18:33","6","fr","911881138","2020-04-02 12:15:00","2020-04-02 12:18:33","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","d1af2f3d870f239fa7c72309ea99362a","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","2h à 3 h","Oui, complètement","","Non, pas vraiment","Oui, certainement","Oui, tout à fait","Ce n'était pas mon but initial mais l'ai eue et j'en suis satisfait(e)","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Oui","","Oui, plutôt","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Non","Oui","Non","4","3","4","4","4","3","Oui","Oui","Oui","Non","Non","Non","Oui","Oui","","","","211.66","","","70.49","","","","","","","","","","","","","","","","63.46","","","","","","","","","","","21.7","","","","","3.68","","52.33","","","","","","","" +"126","2020-04-03 10:22:21","6","fr","1149057960","2020-04-03 10:18:18","2020-04-03 10:22:21","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","8c3ac72a29d8d0dc1be9d4e0d7a9044e","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, complètement","Débutant","Moins d'1h","Oui, complètement","","Non, pas du tout","Oui, probablement","Non, pas vraiment","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Oui","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","3","4","3","3","3","Non","Non","Non","Non","Non","Non","Non","Non","","","","237.72","","","67.73","","","","","","","","","","","","","","","","97.92","","","","","","","","","","","19.4","","","","","6.36","","46.31","","","","","","","" +"130","2020-04-03 12:44:09","6","en","1262715192","2020-04-03 12:42:16","2020-04-03 12:44:09","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","ec9afc2f389140fd3f1bffb60bd86a40","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Débutant","4h à 5h","Oui, plutôt","","Non, pas vraiment","Oui, probablement","Non, pas vraiment","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","","","Non","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Non concerné","Non","","","","","Oui","Non","Non","1","1","1","1","","","Non","Non","Non","Non","Non","Non","Non","Non","","","","110.13","","","25.74","","","","","","","","","","","","","","","","41.73","","","","","","","","","","","17.38","","","","","3.08","","22.2","","","","","","","" +"132","2020-04-03 14:01:23","6","fr","519902585","2020-04-03 13:48:13","2020-04-03 14:01:23","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","db689cfbd0b4e3bd8e301c603975e6c8","Oui, plutôt","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Intermédiaire","2h à 3 h","Oui, complètement","","Oui, en partie","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Non","Non","Oui","4","4","3","3","","2","Oui","Oui","Oui","Non","Oui","Oui","Non","Oui","Bonne présentation des outils","De manière générale une plus grande comparaison des outils me parait utile. +J'utilise Jupyter, Rmd, et org-mode, je trouve que les trois outils sont complémentaires et que il est utile de présenter aussi des cas ou l'un des outils est plus efficace que l'autre. +Je ne vois pas aussi l'intérêt d'introduire markdown, si une utilisation de org permet d'introduire facilement les tags (sans mettre de chunk de code, pour ne pas empieter sur emacs org-mode)","","745.19","","","99.77","","","","","","","","","","","","","","","","80.69","","","","","","","","","","","23","","","","","5.37","","536.36","","","","","","","" +"137","2020-04-03 16:37:54","6","fr","1479471003","2020-04-03 16:01:54","2020-04-03 16:37:54","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","74770e64a71b0b5f820b020426051f03","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Intermédiaire","Plus de 5h","Oui, complètement","","Non, pas du tout","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","éthique de la recherche","","Non","Oui","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","4","4","4","1","1","Oui","Non","Oui","Non","Non","Oui","Oui","Non","Comprendre l'intérêt de se poser la question de la reproductibilité. Avoir des idées de solutions pour être outillé. Mettre en pratique et pouvoir vérifier que l'on a bien compris.","","","635.78","","","167.54","","","","","","","","","","","","","","","","188.46","","","","","","","","","","","28.33","","","","","24.23","","227.22","","","","","","","" +"142","2020-04-03 18:06:11","6","fr","1456591281","2020-04-03 18:01:29","2020-04-03 18:06:11","https://www.fun-mooc.fr/","ea207563bd2097b8bc663c0fd8f8e38a","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Débutant","Plus de 5h","Oui, complètement","","Non, pas du tout","Oui, probablement","Oui, probablement","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","spectroscopie","","Oui","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","","Non","","Oui, tout à fait","Non","","","","","Oui","Non","Non","4","3","3","3","","4","Oui","Oui","Oui","Oui","Non","Oui","Non","Non","Beaucoup de détails mais cours très accessible ","","","281.75","","","65.53","","","","","","","","","","","","","","","","90.01","","","","","","","","","","","37.2","","","","","6.18","","82.83","","","","","","","" +"153","2020-04-04 16:15:27","6","fr","2050520555","2020-04-04 16:11:48","2020-04-04 16:15:27","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","2bee89fcead0b44bf5febf8e2fed610d","Non, pas du tout","Trop d'informations ce qui noie complètement le fil conducteur de ce MOOC. +Les modules 2 et 4 sont les seuls avoir un intérêt","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","2h à 3 h","Non, pas vraiment","","Oui, en partie","Non, pas du tout","Oui, probablement","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","2","1","2","4","1","1","Non","Non","Oui","Non","Non","Oui","Non","Non","","","","219.07","","","148.88","","","","","","","","","","","","","","","","26.44","","","","","","","","","","","6.85","","","","","4.32","","32.58","","","","","","","" +"155","2020-04-04 16:28:04","6","fr","1009208363","2020-04-04 16:11:54","2020-04-04 16:28:04","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","5da49e44873587b02454888c63deb52f","Non, pas vraiment","Je m'attendais à apprendre plus comment utiliser les outils de Notebook, ce qui dans mon cas m'est le plus utile en pratique. Je trouve que l'introduction est trop longue (module 1) et que le module 4 est trop exhaustif vis à vis des formats de fichiers et des méthodes d'archivages.","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Débutant","1h à 2h","Non, pas vraiment","","Non, pas du tout","Non, pas du tout","Non, pas vraiment","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Autre","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","J'aurais aimé avoir plus d'exercices et de vidéos sur l'utilisation des Notebooks. La possibilité de suivre plusieurs parcours avec plusieurs langages est très appréciable. +Selon moi l'introduction (module 1) est trop longue. +De nombreuses ressources sont disponibles pour ceux qui voudraient aller plus loin mais le nombre important de liens peut être déstabilisant. Malgré tout ils permettent d'aller plus loin sur les sujets de son choix. +Les modules qui évoquent les formats de fichiers et des méthodes d'archivages sont selon moi trop exhaustifs, une synthèse pourrait aider à mieux retenir ce qui est essentiel. ","","Oui","Non","Non","2","","2","2","","","Non","Non","Non","Non","Non","Oui","Non","Non","La possibilité de suivre plusieurs parcours avec plusieurs langages est très appréciable. +De nombreuses ressources sont disponibles pour ceux qui voudraient aller plus loin sur les sujets de son choix.","J'aurais aimé avoir plus d'exercices et de vidéos sur l'utilisation des Notebooks. +Selon moi l'introduction (module 1) est trop longue. +De nombreuses ressources sont disponibles pour ceux qui voudraient aller plus loin mais le nombre important de liens peut être déstabilisant. Malgré tout ils permettent d'aller plus loin sur les sujets de son choix. +Les modules qui évoquent les formats de fichiers et des méthodes d'archivages sont selon moi trop exhaustifs, une synthèse pourrait aider à mieux retenir ce qui est essentiel. ","","967.14","","","357.95","","","","","","","","","","","","","","","","61.58","","","","","","","","","","","24.74","","","","","397.7","","125.17","","","","","","","" +"162","2020-04-05 14:22:43","6","fr","1519669575","2020-04-05 14:20:38","2020-04-05 14:22:43","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","2460667c2082b0c9c8f5890689ef7d39","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","2h à 3 h","Oui, plutôt","","Non, pas vraiment","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Oui, sur ce sujet","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Non","","","","","Oui","Non","Non","4","4","4","4","2","4","Non","Non","Non","Non","Non","Oui","Non","Non","","","","114.1","","","51.2","","","","","","","","","","","","","","","","29.38","","","","","","","","","","","10.26","","","","","2.78","","20.48","","","","","","","" +"173","2020-04-06 09:14:43","6","fr","817759389","2020-04-06 09:09:27","2020-04-06 09:14:43","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","71e3f5c4e1466adde86b3c709811ce86","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, plutôt","Avancé","2h à 3 h","Oui, complètement","","Non, pas du tout","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Peut-être","","","Non","Non","Non","Non","Oui","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","3","4","4","4","4","Non","Non","Oui","Non","Oui","Oui","Non","Non","","","","311.95","","","117.83","","","","","","","","","","","","","","","","92.6","","","","","","","","","","","10.52","","","","","3.99","","87.01","","","","","","","" +"174","2020-04-06 11:07:12","6","fr","908896466","2020-04-06 09:32:01","2020-04-06 11:07:12","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","639fe20eabd06f996a7db5869873ab64","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Intermédiaire","2h à 3 h","Oui, complètement","","Oui, en partie","Oui, probablement","Oui, tout à fait","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Non","Oui","Non","3","2","3","4","3","3","Oui","Non","Oui","Non","Non","Non","Oui","Non","Très bonne pédagogie, aspect très pratiques","La première partie ""poser le décor"" relève plus de la culture générale que du sujet du cours à mon avis elle n'est pas essentielle (du moins elle devrait être présentée comme facultative)","","173.6","","","43.55","","","","","","","","","","","","","","","","32.7","","","","","","","","","","","17.06","","","","","4","","76.29","","","","","","","" +"179","2020-04-06 14:24:51","6","fr","121164472","2020-04-06 14:20:15","2020-04-06 14:24:51","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","903ba28f62ed8331f61b08d02bfc7573","Oui, plutôt","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","Plus de 5h","Oui, complètement","","Non, pas vraiment","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Oui","Oui","Non","Non","Oui","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","","","","","Non","Oui","Non","4","4","4","4","","4","Oui","Non","Oui","Non","Non","Non","Oui","Non","","","","267.64","","","92.16","","","","","","","","","","","","","","","","95.34","","","","","","","","","","","19.3","","","","","5.65","","55.19","","","","","","","" +"185","2020-04-06 15:59:23","6","en","2091093870","2020-04-06 15:53:47","2020-04-06 15:59:23","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","08a9fcb34c53440c2ff49b6094ef9c5a","Oui, complètement","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","4h à 5h","Oui, complètement","","Oui, en partie","Oui, certainement","Oui, probablement","Oui, tout à fait","Non, le MOOC n'en proposait pas","","Autre","Big data","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Non","","Non","","Oui, tout à fait","","","","","","Oui","Non","Non","4","4","4","4","4","4","Oui","Non","Oui","Non","Non","Oui","Oui","Non","Vidéos très bien réalisées. Cours clair et bien structuré. Supports de cours fournis. Exercices intéressant et abordables mêmes avec un niveau relativement faible en programmation/statistiques.","","","278.6","","","34.01","","","","","","","","","","","","","","","","54.49","","","","","","","","","","","34.64","","","","","5.52","","149.94","","","","","","","" +"189","2020-04-06 17:59:51","6","en","510364875","2020-04-06 17:46:56","2020-04-06 17:59:51","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","ced38cde67fec1edb24638c4c3b98dd3","Oui, plutôt","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","4h à 5h","Oui, plutôt","","Oui, en partie","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Oui","Matlab onramp","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","A peu près","Non","L’accès aux vidéos depuis ma tv connectée est impossible.","Oui","","","Oui","Non","Non","4","3","3","3","","4","Oui","Oui","Oui","Oui","Oui","Non","Non","Non","Accessibilité. Explications détaillées. Réactivité.","Utilisation de git dans un terminal. +Makefile, Dockerfile, ...","Plutôt réactif.","753.51","","","121","","","","","","","","","","","","","","","","98.52","","","","","","","","","","","109.24","","","","","18.11","","406.64","","","","","","","" +"191","2020-04-06 18:02:15","6","fr","138365987","2020-04-06 17:57:55","2020-04-06 18:02:15","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","ef43fa481d86f164e9cae5ed6b8625cd","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Intermédiaire","Plus de 5h","Oui, complètement","","Non, pas du tout","Oui, certainement","Oui, tout à fait","Ce n'était pas mon but initial mais l'ai eue et j'en suis satisfait(e)","Non, l'attestation gratuite me convenait","","Autre","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Non concerné","Non","","","","","Non","Oui","Non","4","3","4","4","","4","Oui","Non","Oui","Non","Non","Non","Oui","Non","","","","169.73","","","46.07","","","","","","","","","","","","","","","","63.46","","","","","","","","","","","13.92","","","","","7.56","","38.72","","","","","","","" +"193","2020-04-06 19:07:09","6","en","568261143","2020-04-06 18:58:35","2020-04-06 19:07:09","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","04c8a5ac9846a6fce5bd1f72743e4ee8","Oui, complètement","","Oui, plutôt","N/A","N/A","N/A","N/A","","Oui, plutôt","Intermédiaire","2h à 3 h","Oui, plutôt","","Non, pas vraiment","Oui, probablement","Oui, probablement","Oui, tout à fait","Non, pour des raisons financières","","Autre","","","Oui","Non","Non","Non","Non","","Oui, plutôt","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Oui, tout à fait","Oui","Faire de meilleurs quizz, avec moins de réponses posssibles, et surtout des choix plus clairs (le caractère VRAI ou FAUX de plusieurs propositions de réponses pourrait être contesté) ","Non","","","Non","Oui","Non","4","3","1","2","3","3","Oui","Non","Oui","Non","Non","Non","Oui","Non","","","","504.47","","","78.1","","","","","","","","","","","","","","","","148.29","","","","","","","","","","","228.71","","","","","8.37","","41","","","","","","","" +"197","2020-04-07 12:03:03","6","fr","1526838324","2020-04-07 11:58:27","2020-04-07 12:03:03","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","08746c38508e5f7e5cd043e919a322cd","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","4h à 5h","Oui, complètement","","Non, pas du tout","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Autre","","","Non","Oui","Non","Non","Non","","Oui, tout à fait","","Oui, tout à fait","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Oui","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Non","","Non concerné","","","","","","Oui","Non","Oui","4","4","4","4","","4","Oui","Oui","Non","Oui","Non","Oui","Non","Oui","Obtention d'une vision synthétique du sujet","Org-mode reste complexe ... peut-être plus de description sur le sujet ?","","269.09","","","62.83","","","","","","","","","","","","","","","","63.93","","","","","","","","","","","27.57","","","","","5.59","","109.17","","","","","","","" +"199","2020-04-07 14:08:27","6","fr","478650226","2020-04-07 14:02:14","2020-04-07 14:08:27","https://www.fun-mooc.fr/courses/course-v1:inria+41016+self-paced/courseware/7bf2267c336246f9b6518db624692e14/aec41b9dd3424191a187915ce92af393/","209e6fa51d4c3fee4545b21fdd7eca8b","Oui, complètement","","Oui, tout à fait","N/A","N/A","N/A","N/A","","Oui, complètement","Avancé","Plus de 5h","Oui, complètement","","Non, pas vraiment","Oui, certainement","Oui, tout à fait","Oui, tout à fait","Non, l'attestation gratuite me convenait","","Peut-être","","","Non","Non","Non","Non","Non","","Oui, tout à fait","","Oui, plutôt","","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","Oui","Non","Non","Oui","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Oui","Non","Non","Non","Non","Non","Non","Non","Non","Non","Non","","Eventuellement","","Oui, tout à fait","Oui","","","","","Oui","Non","Non","4","3","4","4","3","2","Oui","Non","Non","Non","Non","Oui","Non","Non","Le sujet abordé","","","367.95","","","104.37","","","","","","","","","","","","","","","","169.67","","","","","","","","","","","16.41","","","","","6.14","","71.36","","","","","","","" + diff --git a/Projet Maman/Untitled.ipynb b/Projet Maman/Untitled.ipynb index 8510738ac345c47a2580db0b2206875a0ae4b183..86d0b9eb716abdb222d709083e78ca9341b64817 100644 --- a/Projet Maman/Untitled.ipynb +++ b/Projet Maman/Untitled.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -44,12 +44,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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FSAWddZjrACIiJUzT3G1Q9gWdu8JwuOscIiIlTAXdBmVf0MDeaHMMEZFC2jMM/F6uQxQbFbTOP4uIFJoB9nMdotiooFXQIiIdYV/XAYpNWRd0biH3PV3nEBEpAyroVirrggYOQrtXiYh0hLow8KtchygmrSpoY8ynxpi3jTFv5L6K/V9E2vtZRKRjVAF1rkMUk7YsYn6gtXbu+n5gjIlba9PtzNSR9nYdQESkjOwLTHIdoli0e4rbGDPcGDPOGHM38HbusYeMMVOMMe8aY85t9NylxpjfG2PeNMa8ZIzpnXu8tzHmwdzjb64amRtjTjfGvJIbrV9vjMnbdHQY+B6g1W1ERDqI1aCoVdoygh5njEkDK6y1e+Ue2xMYZK39JPffZ1tr5xtjaoDJxpjR1tp5QGfgJWvtFcaYvwDnAL8D/gFMsNYekyvhjYwxOwAnAUOttaEx5jrgNOD2Nn/aNe0EVObpWCIi0oiFMFVhpi3o4c35bLNqO2Ngde3Xvat2u9h1sCKSrynuVxqVM8CPjDHH5L7fDNgGmAesBB7NPT6F1bc4HQScCZCbIl9kjDkDGEK24AFqgK/bkHdDdsvjsUREypaFMOWZjxd09+auKuPZvau2ylSY7YHtGz/3mgXX9Lqk+yX5/F1esvK1kfayVd8YY4aTvfhqH2vtcmPMeKA69+PQWmtz36ebeX8D3GatvTxPGdemixVERFrJwsrQM9NzI2NmDqiund2naqtM3OzQwkMMAR4vZMZSka+CbqwrsCBXztvTsnMOzwIXAFfnprg75x572Bjzd2vt18aYHkAXa+2MPOXUCFpEpAm5Mp62oIc3d60yXmdk3AoFK2hjzKfALGvt/o0eewOosNYW3TVHhSjoJ4DzjTFvAR8AL7XgNZcANxhjfkB2ZH2BtXaSMeZK4CljTAwIgYuAdhd0GPgxYNf2HkdEpFTkyvjjXBmbGQNrar/uXdmakXFLDcnz8dbWxRizmbV2Vu5aplaJ0t1IZvWMc/kIA39r4CPXOUREXLCwotHI2MwYWNMzV8ZeB7z9J5d0v2TLQhw4N4K+AVhprf2bMea3ZE/BnmGtHWSMGQjcQXaWFuBia+2LuVOzCeBLYLC1dkdjzI+Bs3PPG2GtvTr3HmcCPwEs8Ja19oxCfBYozAi6GOzoOoCISEdYVcbzN8mW8cwB35Sxq9+DA65ZcE31Jd0vaSjQ8UcBtwJ/A44me/fPqhL9GjjUWttgjNkGuAfYPfezb+5GMsYMAc4C9iJ7PdTLxpgJZC90voLs3UVzc6deC0YFLSJSIhqX8azNq83MATW95vSq3NJhGa9PDNgOeLNAx58PLDDGnAy8Dyxv9DMPuNYYM5js6dRtG/2s8d1I+wEPWmuXARhjHgD2JztqHrXqTiZr7fwCfQZABS0iUpQsNISVZtr8Ht68CJfxhmxP4Qoa4D7gX8D313r8MmA22WuQYkDjUfyyRt+bDRzXkC3pDlGuBZ3vix5ERArGQsPKSjNt/ibevNw5415zelVuZWNmJ9fZ2qitV4C31INAX+BJoF+jx7sCn1lrM8aY77HhzZImArcaY/5EtpSPITtNvhJ4MHd30TxjTI9CjqLLrqDDwDcU/i+HiEibrKeMe8/pVbllEZfx+mzb/FPazlq7BPgzQG6hq1WuA0YbY04AxrHmqLnx618zxtwKvJJ7aIS19vXc8X4PTMitqPk6647S86bsruIOA39z8nCrlohIe1moz5Zx5fxZm1fHZg6o7pUr41IfPL18SfdLtC53M0r9L8H6lMXo+ZpJU7j5tXcwwKDetYz4zreYOnc+Fz/6DA2pNBWxGP888iD22LTvOq8956EneezD6fTs3Ik3LvreN49f/vREnvzoU3bt05Nbjj0CgDvffI8F9Q38cG8tzCbSlFVlPK+2ct5nm1XHZwys7j23Z+UWNmaKbgGNPNjKdYBiUI4F3a/5pxS3zxcv4V8vv86bF32PGs/jlJGPMvKdD7j37alcOXwfDt9mCx7/cDqXP/0cz5x14jqvP3PwTly452DOevCJbx5b1LCCl2Z9yWsXnsmZox/j7dlz2LpHN+54410ePf3Yjvx4IpGXK+OP59VWzm9UxluWaRmvT+01C67Z+JLulyx2HSTKyrGge7kO0BFSmQz1YQovFqc+DOnbpTPGwOIVKwFYtGIlfbt0Xu9r9x+4KZ8uWLTGYzFjWJlOY6395rjJF17lor12w4vnbRdQkaLTeGQ8a/Pq+MwB35Txzq6zRdyWwBuuQ0RZORZ0b9cBCq3/xl24bN/d2ervI6jxKjhkqwEcuvVANu3ahaPueIBfPDWBjLVM+MEpLT5ml6pKjtlhG/b4z50ctOXmdK2u5NUvZnPl8H0K+ElEouXsB59Ijf1wuunSuXrFXXde9lqjMh4EsHzhcu754Z3M/WQuXrXHKf84hb479mXp3KXcdMZN1C+q53+u+B92OXIXAEacNoIT/nYCXft2dfq5HFFBN6McC7rkR9AL6hsYM3UaH176A7pVV3HyyEe56833ePXzr/jr4cM4dsdtuf+dDzjv4ad44nvHt/i4P9lvD36y3x4AnPfwUyQO3Jebp7zN09NmsHPvWn45TNd8SOmwsGxllZk2t7ZyQXZkXNOne92BW5zd5Yj4XRfc1WnKnl33W/s1T1/1NP0H9ecHd/yA2R/OZtTPRnHRQxcxZfQU9jx5T3Y7djeuP+F6djlyF9554h023WXTci1nKIPTje1VjgVd8iPoZ6fPZGD3jenZuRMA391hG16a9SX3vP0+Vx1xIADH77Qt5z/ydJuO//qX2a1ct92kO/7j4/jv2Sdx2v1j+WjeArbZpHt+PoRIB1pPGfed29PbAmN2afy8rXptw7yZ8zZ4nNkfzOaQyw4BoPe2vZk/cz5Lvl5C3IuzsmElqZUpTMyQTqWZ8J8JnHP3OYX9YNHWx3WAqCvHgi75EfTmXbvw8mdfsXxlSI1XwbhPZjKkX2/6dtmIiZ9+xrAtNmPcJ7PYepNubTp+8N8XuO7oQwnTadK52/RiBpaHqXx+DJGCsLBsRVVs2rxab8GszasrZg6s6TO3dt0ybot+g/rx5pg32XLvLZkxZQYLZi1g4RcLGXL8EO445w5eve9Vjk4czfM3Pc8eJ+1BZafKfHykYqWCboYKugTtuWlfjt1xG/a8/k4qYjEG9+3F/w7ZmcF9evHjJ8aRymSorqjg30cfCsAXi5dy/iNP8UjuauzTR41l4qefMXd5PVskb+DXB+7DWXXZ610efv9jhvTvQ7+NNwJg7037stt1t7Fz757s2qenmw8ssgGNynjhzAHZaep5eSrj9TnkkkN44PIH+MsBf6Hfjv3ov0t/YhUxajau4dz7zgWy56mfveZZzr79bO695F7qF9Yz/KLhbLHnFoWIFGUq6GaU1UIluVXEVlKe/zARKWkWlq6oik2b29NbOGvz6opGZRzL5/vMmzmPG0++kV+8+Ium81jLbwf/lp8/93OqN67+5vEHf/kgOx+5M3M+nkMmk2HIcUMYcfoILn7k4nzGjC5LBlhgrPfyjza58EjXcaKs3IqqB+X3mUVKjoUlK6pj0+fWegtnDaipmDmguu+8TbyBGLOry1zLFy2nsqaSisoKXrr9Jbbad6s1ynnOtDks+moRWw/dms/f/hyv2gMDYUPoMHU7WZaAWWhsfHHMestjtnJlLFOdiqerqch0isXTnarimU418XTNRvFMddeYrepmMJsAg9jEdfhoK7eyKvkLxERKzXrKuN+8TbwBLsr4tv+9jWkvTGPpvKUkdkpwxC+OIJ1KAzD0rKHM/mA2d114F7F4jD7b9eHkf5y8xuvH/m4sR16ZHTTWHVfHTaffxMTrJ3LE5Ud09EdZP8sKMAsMscXGViyLZSobYpmqlfFMDfFMjalId/LimU7V8XRN53impms8U9XdEO8CdGnDuxWsno0xnwJLyG4pGQeutNY+3ILX7L5qK8kNPOe3wERr7TP5S9tEpjKb4h5OdoF0EYkgC0saqmPT5vb0Fs3aPFvG87Mj4w1t/ycbkptKhtiimK1YYqzXEM9UroxlajLxTA0V6U4V2dFtTad4pmbjeKa6W8x6G3Vwyppjt+vb0PzTWqdx2RpjtgOestYOaOlr8p2nrTSCFhEnLCxuqI5Nn9uzctHMAdXerAHVfef38AZizGDX2SLJsjg3lbxkzankGioyNfF4ulPl6qnkmm4xW9k1N5Uc5YnkHsAXBX6PjYEFq/7DGHM68COgEngZuNBam278AmPMr4DTgFnAXGCKtfZvuR2uHrXWjjLGHA5cnfv5a8CW1tqjjDG/AZZaa/+WO9Y7wFHW2k9b8t6NlVtBl/wV3CJRpDJey5pTyUtzU8mpeKbGNppKrslNJW+cm0remGzZlJK2TI231DiTnXnZEjgRwBizA3ASMNRaGxpjriNbxLevepExZnfgOGA3sh35GjCl8YGNMdXAjcBBwMfAfc2Facl7r00FLSJ5ZWFRQ3Vs+pxelYtnDaj2Zm5e029Bj4oBpVLGd198N+899R4b1W6UvZI7O5U8PzeVvGzyfa9WP/G3R/sbYjYer+DkX130yW4HDF+x+KulXf5+nr/FimX1Fade9ouqvQ45og/Q508Xfp9zE3+iR++yvOuokFPqB+amuLcCnjXGjAcOBoYAk3NnTWqAr9d63X7Aw9baegBjzJj1HHt74BNr7Ue559wJnNtMnpa89xrKraBrXQcQKSXrKeP+C3pUbI4xu7nO1mZrTyVnclPJmexU8n6HnNDj8GM28W782W8H9pvznaW5qeRacr9feux9KN957P8wxvDpB++RvPS8nfd7/HuMHzOCQ48/g/3+5zv83zmnstchRzD5v0+x5Y47l2s5Q2ELGgBr7TRjzGxgR8AAt1lrL2/iJS293mFDF3ClgMa39q26jL8l772Gcivocvu8InljYVFDTWz6nOw0deWsATX9F3SPeBlbGtZzVXIqnqnJVGRqYvF1ppKrexhiTU4lD913Z77+bBYVFVXEbdU6a9vWdF69S9yK5cu/ub4t7nmsbKgnDFcQi8VIp1KMvX0El//71vx/7uLRqdBvYIzpBWwBzACWAg8bY/5urf3aGNMD6GKtndHoJc8D1xtj/ki2M44kO53d2FRgC2PMVtbaaUDjnYc+BY7KvXdd7r0Bnm3Be69BhSUi61i7jGcOqNl0YfeKzZyWsSXN6quSlxnrLY9nqsJYpjpTka4hnll1VXKnzvFM9aqrkjsDfXNfHeblpx/nzqv+wOL58/jlf7KnGPc/6hiu/slFTHh4FKf/5AqeuPtWhn3neKpqCt5RUVZTwGOPM8akAQ/4hbV2NjDbGHMl8JTJLmATAheRLW8ArLWTjTGPAG/mHn8VWGP/XWttgzHmXGCsMWYu2VJftdf3aOBMY8wbwGTgw9xr3mvuvddWbrdZ3QCU9er0ImuzsKi+JjZtTq/KxTMHVFfN2rym38LsyLiwtzZZFoFZtPZUckWmxubKtjKeqWl8VXI3QzRut/r6s1n84YIzuXpM03dtvjv5Je6/7ip+c8vINR5fumghV112Pj/9503c+qcESxct4ttnncd2u+1eyNhRdPqx2/W9y3WItRljNrLWLjXGdAImAudaa19r4vnDgZ9Ya4/KZw6NoEXKiIWF9TWx6XN6VS6ZOaCmcuaA6v6LunubA3XtPPA6U8nxTHUqlqm2FZkaE0939uLpTjUVmZrOsUx113imursh1hUo6b0Wd9pjb66dOYPFC+axcffVdzvdf93fOe78S3h+7ENsudMu7H/UMfzpwrP47e2jHKZ1osp1gA24wRizI9nzx7c1Vc6FpIIWKVGNynjxzAE1VS0u4+xU8nyILY7ZiqXGevXxTFUYz1Sn4+lOsXimZtVUcqd4pnrjeLqmW4wKJ1PJUfTljE/os3l2bZXp775FKgzp0q3HNz//4tPpzP/6K3bacx8+mfoulVXVGAzhihUOUzuT13XS88Vae2ornz8eGJ/vHOVW0OUzny9lxcKC+k6x6V9nR8ZVszav3nRRd28zoK7xVcnxtPdKdunGqnR2+cZO8Xi6U2VFplOneLpmo1imetUCFz0BbU+2Hlf9+ALenTyJJQvmc86wIZz0Q590KrvV6rfaXoBqAAAarElEQVROPpOXnhrL+IdHUVFRQWVVDT/++7/XOFtw99V/5tRLfw7A/kd+lz9fdBZj7xjByT/8qZPP41gkCzoqyu0c9PU0f6+aSNRlUj27v7a0W6c5c3p3WfFF/84Vi7p1qojZKmLpmng8U1MRz1RXm3R1TcxWbWSIl/WmwxJdGUvwrW02u9l1jqgqtxG0SCmIeZ07VdQetN/WPSsqttmx8U+8Vd+kgWW5L5HIqoDNXGeIrHKbXiif6QIpafbTzwenbhi5ZfrNqROttYuaf4VIJG1wHWopv4IWKR3WxjPPTzkgdcsDYebrec9ZazOuI4m0kv7ONkEFLVLs6htq0/c/sX/6oWem2pXhu67jiLSCRtBNKLeC1hS3lCz7xdc7pm4cuWP6lbeet9bOcZ1HpAVU0E0ot4IWKXUmM/nt/VIj7q/MfD57grU25TqQSBNU0E1QQYuUopVh1/RDzwxL3//EJ7a+4XXXcUQ2YInrAFFWbgWtf61JWbFz5m+Tunn0bunnXp1kM5kvXOcRWct81wGirNwKep7rACIuZN76YJ/UjSO7ZT75bIK1tizXlJRIUkE3odwKerbrACLOpNKd0o9NGJa6+9Gv7NJlk13HEUEF3SQVtEi5Wbh4QOq2h/ZIPfPiZJtOb3AvWpECs6igm6SCFilT9oNP9kjdOLJPZur0CdZarQkqHW0JtXW6LqgJKmiRcpbOVKWfnTQsdcfDi+2CxS+6jiNlRaPnZqigRQSWLOubunvMvqnHJrxhU6mPXMeRsqCCbkZZFbSXSC4G6l3nEIkq+8lng1M3jNwi/dbUCdqEQwpMBd2MsiroHI2iRZpibUXmuSnDUrc+sNLOmf+cLadN46UjqaCboYIWkfVb3tAzNfLx/dMPP/ueXRm+5zqOlBwVdDNU0CLSJPv57J1SN47cIT357eestXNd55GSob9LzVBBi0hLmMwrb+2fummUl/l89kRrrW6Pkfb61HWAqFNBi0jLrVjZNf3QMwekRz0x3daveMN1HClqH7sOEHUqaBFpNfv1/G1SN48anH5+yos2k/nSdR4pSiroZqigRaTNMm9O3Td14/0bZz79bIK1dqXrPFI0lgPaXa0Z5VjQ+te+SD6lUp3TYycMS90z9gu7dLk24ZCWmE5tnW7fa0Y5FvQHrgOIlKQFiwambntwj9SzkybbdKakNuH4+3/uYqf9TmDQ/idyyrm/pKFhzR07/3rt7QwefgqDh5/CoP1PJN57D+YvWMScuQvY78izGbT/iTz02Lhvnv+dM37MF1/N6eiPESWa3m6BsitoL5Gcgy7vFykYO3X6Hqkb7+uT+eCT8dba5a7ztNfnX37NP268l1efvoN3nhtJOp3m3gefXOM5P734TN4Yfw9vjL+HP155McP2raNH967c88ATfO/ko5j0+C389do7ABjz5ETqdtmefn16uvg4UaGCboGyK+gcLbogUkjpTFX6mReHp+54eKFduHiS6zjtlUqlqW9YQSqVYnl9Q5Ples8DT3DKsd8CwPMqqK9fwYoVK4nFDKlUiquvv5ufXnRGR0WPKhV0C5RrQb/rOoBIWViyrF/qrjH7pB6f+LpNpYryl3L/vr34yYWns/ngI+k76Ft03XgjDjtwn/U+d/nyep747ySOO+pgAE497nCeHDeJw0/6Ib/52Xlcd/P9nHnikXTqVNORHyGKivLvQkcr14LWCFqkA9nps3ZL3TByYPrtD4puE44FCxfz8BMT+GTKGL54+wmWLa/nzvsfW+9zxzz5HEP33JUe3bsC0HXjLoy95x+8+syd1O2yPY8+/RzHHXUw51z2fxx/1s+YNPmtjvwoUaKCbgEVtIh0DGsrMhNfXbUJx/PFsgnHMxNeZovN+9Oztjue53HskQfx4uQ31/vcex968pvp7bX99m83csWlP+CeB59gyK47cPM/fs0vf39tIaNH1QpglusQxaBcC1pT3CKuZDfh2C/9yH/fLYZNODbftA8vTXmb5cvrsdby7MRX2GGbLdZ53qLFS5jw4mt85/Dh6/zso2kz+eKrOQwbOoTlyxuIxWIYY2hYUZa3jn9EbV3GdYhiUJYF7SWSs9GCJSJO2c++GpS6ceT26Vffec5aO891ng3Za8jOHH/0wdQdfBo7H3ASGWs598xj+c+to/jPraO+ed6DY8dx2PC96dx53fPLV/zhX/zu8gsBOOXYw7n13jHsffj3+cmFZXmxmO6VbyFTJLNMeRcG/uPA4a5ziAhQVbkw/j/D3jJ9ew41xsRdx5GCOp/auutdhygGZTmCznnNdQARyVmxslv6wacPSI96cpptWLH+E7xSKl5xHaBYlHNBT3EdQETWZL+et23qplG7pl947UWbyXzlOo/kXT3wtusQxaKcC1ojaJGIyrzx/r6pEfdvlPn08/HahKOkvEZtXcp1iGJRtgXtJZKfAvNd5xCRDQhTG6XHjh+eunfs53bZ8lddx5G8eNl1gGJStgWd87rrACLSjPmLtkjd+uDuqf++9IpNZ2a6jiPtovPPrVDuBa2/LCJFwr4/bc/Ujff1ynz46Xhrbb3rPNImGkG3QrkX9DOuA4hIK6Qz1emnXxieuvPh+XbRkpdcx5FW+Zrauk9dhygm5V7QzwNFvx2eSNlZvKx/6s5H9k49PvE1m0pPcx1HWkQzlq1U1gXtJZIrgQmuc4hI29jps+pSN963efqdDydYaxe7ziNN0vR2K5V1Qec82fxTRCSyMtbLTJg8LHXbgw127oIXimUTjjI00XWAYqOChqdcBxCRPFhW3yt132ND02PGvWPDcKrrOLKGJcAk1yGKTdmuxd1YGPgzgc1c5xCRvMnE9h78fKxux0HGmB6uwwiPUFv3Hdchio1G0FlPuw4gInkVy7z0xgGpm0eZzJdzJlprtb2hW5qpbAMVdJb+8oiUooaV3dMPPHVAevRTH9mGlW+5jlPG9Du2DVTQWc8A+he2SImys+dul7rp/l3Sk15/wWas9oLvWJ9QW/eR6xDFSAUNeInkPLR5hkjJy7z23tDUiJGdMjO/mGCtDV3nKRNj83kwY8wxxhhrjNm+Bc+91BjTKZ/v35FU0KtpCkakHISpLukx44al7ntsll1Wr21nC29Mno93CtlFpk5uwXMvBdZb0MaYeD5DFYIKejXdDy1STuYt3DJ16wND0uNfftlmMp+5jlOilgDj83UwY8xGwFDgB+QK2hgz3BjzaKPnXGuM+b4x5kdAP2CcMWZc7mdLjTG/Nca8DOxjjBlijJlgjJlijHnSGNM397wfGWPeM8a8ZYy5N1/5W0sFvdoksn+ZRKSMZN79eK/UDSM3yXw0Q5tw5N9T1Nblcz/v7wJPWGs/BOYbY+o29ERr7T+AL4ADrbUH5h7uDLxjrd2L7Mpm/wSOt9YOAW4Gfp973i+A3ay1uwDn5zF/q6igc7xEMgTGuc4hIg6k0zXpp54fnrrrkXl28VJtwpE/jzb/lFY5BVg1or0399+tkQZG577fDhgEPG2MeQO4Etg097O3gLuMMacDqXYlbocKV28cUaOBb7sOISKOLFq6aeqOhzc1Ww+YEj9knx4mHt/CdaQiliKPF4gZYzYBDgIGGWMsEAcs8AhrDjarmzhMg7U2veqQwLvW2n3W87wjgQPI9sGvjDE7WWs7vKg1gl7TaGCp6xAi4pb9eMaQ1A33bZp596MJ1lqd+mqbJ6mtm5PH4x0P3G6tHWCtHWit3Qz4JPezHY0xVcaYrsDBjV6zBOiygeN9APQ0xuwDYIzxjDE7GWNiwGbW2nHAz4BuwEZ5/BwtpoJuxEskl7F6+kNEylnGeunxrwxL3fbgcjtv4Quu4xShO/J8vFOAB9d6bDRwKjCS3LQ08Hqjn98APL7qIrHGrLUryZb+n40xbwJvAPuSHZnfaYx5O3esv1trF+b5s7SI1uJeSxj4BwL/dZ1DRKLFbN73rfjhB1QZr2I711mKwGKgN7V1Da6DFDONoNc1HpjhOoSIRIud+eUuqRvu2yb9+nsTrbULXOeJuFEq5/ZTQa/FSyQt+Z+aEZHSEMu8+PoBqZtH28xXc5/TJhwbdLvrAKVABb1+t7kOICIR1rCiR3r0k/unH3j6A7ti5duu40TMDGCi6xClQOegNyAM/OfJrlgjItIUGxuy04uxPXfdxsRML9dhIuAP1NZd4TpEKdAIesM0ihaRljCZKe8OTd10f3Vm5pfahEOnCPNGBb1hIwFd5CAiLbMy3Dg95r/DUvc9NtMury/X3fEmU1s31XWIUqGC3gAvkVwEPOQ6h4gUmXkLt0rd8kBdesIrL5XhJhwaPeeRCrppmuYWkTbJvPPR3qkbRm6SmTZzvLW2HGbjVrJ6nWzJAxV0054GvnQdQkSKVDpdk37iueGpu8bMsYuXvuw6ToHdk+elPcueruJuRhj4fwF+6jqHiBQ/s82AV+MH77NJiW7CsSu1dW+5DlFKNIJu3n/IblEmItIu9qMZu6duGNk/897H4621pbQxz7Mq5/xTQTfDSySnk72iW0Sk/TKZyvS4l4enbn9oqZ2/6EXXcfLkKtcBSpEKumX+SHbfURGR/Fi6vE/qnkf3TT067k0bpj5wHacdpgKPuw5RinQOuoXCwB8DHOU6h4iUIGPSsX13eyG26/a7GGO6uY7TSudTW3e96xClSCPolvu96wAiUqKsjWdeeO2A1C2j05nZRbUJx1y0MUbBaATdCmHgjwOGu84hIqXN9O35fvzI4WlTVTnIdZZm/I7aul+5DlGqNIJunT+6DiAipc9+OWeH1Ij7d0q//OYL1tqo3lu8ArjWdYhSphF0K4WBPxnY3XUOESkTld7i+BEHvG769x5qjKlwHaeRW6mtO8t1iFKmEXTraRQtIh1nZbhx+uFnh6VGPj7D1je87jpOTgZIug5R6lTQrfcg8L7rECJSZuYu2Cp18+jd0hMnT7KZzOeO09xDbd07jjOUPE1xt0EY+N8DbnWdQ0TKVEV8efzQoa+YLTbdxxhT1cHvHgLbU1s3vYPft+xoBN02dwEzXIcQkTKVSndKPz5xeOruMbPtkmWvdPC736hy7hgaQbdRGPgXA/90nUNExGw78NX4QXvXmnh8YIHfahmwNbV1XxX4fQSNoNtjBKC/pCLinP3w091TN4zsl3l/2gRr7bICvtU1KueOoxF0O4SBfy6gJe5EJDo26vRlxbcP+sR077pvno88H9iS2rpFeT6ubIBG0O0zAtAWayISHUuX903d/ei+qbHj37Cp1Ed5PPKfVM4dSyPodgoD/2DgGdc5RETWYUw6NrTuhdgu2+1qjOnajiN9Tvbcc0O+oknzVNB5EAb+I8DRrnOIiKxXTfXc+FHD3zc9eww1xrRl5vRcautuzHsuaZKmuPPDJ3tvoIhI9NQ31Kbvf2L/9EPPTLUrw3db+eoPgZsLEUuaphF0noSB/3fgUtc5RESaYWN77PxCbI+dtzPG9GzB84+itm5swVPJOjSCzp8AiOquMyIiq5jM5Lf3S424vzLz+ewJ1tpUE899WOXsjkbQeRQG/veBW1znEBFpKdOzx0fxow9cZmqqB6/1o+XAjtTWadVERzSCzq/bgOdchxARaSk7Z/42qZtHD04/9+okm8l82ehHv1c5u6URdJ6FgT8IeB2I0r6tIiLNq6hYFj9s6GQzsH8PY8we1NatdB2pnKmgCyAM/CTwY9c5RETawOJVDPd++eeJroOUO01xF0aC7I39IiLF5iaVczSooAvASySXoluuRKT4fAn81HUIyVJBF4iXSI4C7nGdQ0SkFS7yEsmFrkNIlgq6sC4AdBWkiBSDB7xE8kHXIWQ1FXQBeYnkIuAMIO06i4hIExYCF7sOIWtSQReYl0g+B/zJdQ4RkSZc5iWSXzb/NOlIKuiO8RvgFdchRETW4w4vkbzVdQhZlwq6A3iJZAo4FVjqOouISCPvk71WRiJIBd1BvERyGvAj1zlERHKWAyd4ieQy10Fk/VTQHchLJG8B7nedQ0QEuNhLJFu7N7R0IBV0xzsPmOU6hIiUtdtyAwaJMBV0B/MSyQXAmUDGdRYRKUvvARe6DiHNU0E74CWS44G/uM4hImVnGdnzzstdB5HmqaDd+TXwqusQIlJWLvQSyfdch5CWUUE74iWSIXASMNd1FhEpC7d4ieTtrkNIy6mgHfISyenAMcAK11lEpKS9A1zkOoS0jgraMS+RfB74gescIlKylgEneolkvesg0joq6AjwEsm7gMB1DhEpSed5ieT7rkNI6xlrresMkhMG/l1klwQVEcmHX3mJ5O9ch5C20Qg6Ws4GnncdQkRKwr9VzsVNBR0hXiK5guxFY9NcZxGRovYg2t+56GmKO4LCwN8OeAno5jqLiBSd54DDvESywXUQaR+NoCPISyQ/AI4DQtdZRKSovAN8W+VcGlTQEeUlkv8FznedQ0SKxmfAEV4iudB1EMkPFXSEeYnkzcCfXecQkchbAHzLSyQ/cx1E8kcFHX2Xoz2kRWTDGshOa2uN7RKjgo44L5G0wGnAA66ziEjkpIFTcisSSolRQReBRhtrjHKdRUQi5WIvkXzIdQgpDBV0kfASyRRwCnCv6ywiEgm/8xLJ/7gOIYWjgi4iuZI+HbjLdRYRcer3XiL5K9chpLC0UEkRCgM/BtwCnOk6i4h0uJ96ieTfXIeQwlNBF6lcSd9Idv1uESl9GbI7U41wHUQ6hgq6iIWBb4DrgXNcZxGRggqB071EcqTrINJxVNBFLlfS16FVx0RKVT1wnJdIPu46iHQsFXSJCAP/n2j3GpFSsxg4ykskn3MdRDqeruIuEV4i+UPgatc5RCRv5gIHqpzLlwq6hHiJ5GXAH1znEJF2+wzY30skX3MdRNzRFHcJCgP/B8C/Ac91FhFptY+BQ7xEcobrIOKWCrpEhYF/EDAa6OY6i4i02NvAYV4i+ZXrIOKeprhLVG4/6X2A6a6ziEiLjAeGqZxlFRV0CfMSyanAXsALrrOISJOuBQ71EskFroNIdGiKuwyEgV9FdtWxM1xnEZE1rAQu8BLJm10HkehRQZeRMPAvBf4KVLjOIiJ8CRzrJZIvuQ4i0aSCLjO5i8fuA2pdZxEpY68Ax3iJ5Beug0h06Rx0mcldPLYH8IbrLCJl6kbgAJWzNEcj6DIVBn4n4CbgZNdZRMrEcuB8L5G8w3UQKQ4q6DIXBv5FwF+ATq6ziJSwqcDxXiL5rusgUjxU0EIY+NsCdwB7us4iUoLuBc7xEsmlroNIcVFBCwBh4FcAVwBXoqu8RfJhBeB7ieS/XAeR4qSCljWEgb8H2dH0dq6ziBSxl4CzvUTyfddBpHjpKm5Zg5dITgZ2A/4F6F9vIq1TD/jAUJWztJdG0LJBYeAfBtwC9HOdRaQITAD+10skP3YdREqDRtCyQV4i+RQwiOzCJiKyfkuBi4ADVc6STxpBS4uEgX8K2Wnv7q6ziETIU8C52rtZCkEFLS0WBn5/slPeh7rOIuLYQrJXaGuTCykYFbS0Whj4J5Jd3GSA6ywiDowhuyKYluqUglJBS5uEgV9N9mrVy4HOjuOIdIR5wI+8RPJu10GkPKigpV3CwO8H/JHsXtPGcRyRQkgBI4CEl0h+7TqMlA8VtORFboGTq4F9XWcRyaNRwC+9RPIj10Gk/KigJa9yV3v/GdjMdRaRdpgA/NxLJF92HUTKlwpa8i4M/Brgp8DP0S5ZUlzeBn7hJZKPuQ4iooKWgsndlvUn4DR0flqibSbwa+AOL5HMuA4jAipo6QBh4O8F/B442HUWkbXMJ3uR4z+9RHKF6zAijamgpcOEgT+E7LT3cWiZWXGrAfgH8EcvkVzoOozI+qigpcOFgb818BPge0C14zhSXuqB24Dfe4nkZ67DiDRFBS3OhIHfG7gEuADo5jiOlLbPyK4lf4OXSM53HUakJVTQ4lwY+F2A84DL0NaWkl+TyN6f/4CXSKZchxFpDRW0REYY+JXA6WRv0drecRwpXiFwP3C1l0hOdh1GpK1U0BI5YeAb4NtkLyjbx3EcKR5zgOuBf2sjCykFKmiJtDDw64CzgVPRXtSyfm8B1wB3e4lkg+swIvmigpaiEAZ+FfBdsmV9CLpNq9ytAMYC13qJ5DjXYUQKQQUtRScM/M3I3qJ1JrCN4zjScTJk18i+Gxil+5el1KmgpaiFgb87cApwEtDfcRwpjNfIlvK9XiL5ueswIh1FBS0lIQz8GHAA2XPVxwE93CaSdnodGE12pPyB6zAiLqigpeSEge8BhwLfAg5Dt2wVA0v2nuXRZO9Z/tRtHBH3VNBS8nLnrA8lW9YHA7VuE0nOIuA54HHgQS+R/NJxHpFIUUFLWcndY13H6sIeClQ6DVU+5pEt5Am5rze1taPIhqmgpayFgd8JGEa2rA8FdnKbqKTMBiayupDf9RJJ/cIRaSEVtEgjYeD3A4YDg4Fdc1+9XWYqIp+zuowneonkVMd5RIqaClqkGbldt1aV9S65P7cHPJe5HGoAPgTeB6bmviZ7ieQ0p6lESowKWqQNcht77Mi6xV1KF6DNJVu+jYv4fWCGzh2LFJ4KWiSPwsDvQ3bBlL65rz6Nvm/8mOsL01YC83Nf83Jf02hUxF4iOc9dPBFRQYs4EAZ+D9Yt7b5AF6Cq0VflWt+b3CHsWn9CdpvFBWTLdn5Tf3qJ5NICfTQRyRMVtIiISARpRyAREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiSAVtIiISASpoEVERCJIBS0iIhJBKmgREZEIUkGLiIhEkApaREQkglTQIiIiEaSCFhERiaD/B1tX4F1XN4IUAAAAAElFTkSuQmCC\n", + "image/png": 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\n", 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" ] @@ -83,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -119,7 +119,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -151,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -202,7 +202,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -235,12 +235,12 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -266,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -299,7 +299,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -314,7 +314,7 @@ "\u001b[0;31mKeyError\u001b[0m: 'the label [Est-ce le premier MOOC que vous suivez ? ] is not in the [columns]'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m## D009FUN\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0moui\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Oui'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mnon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Non'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m## D009FUN\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0moui\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Oui'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mnon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdonnees\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m'Non'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'Est-ce le premier MOOC que vous suivez ? '\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 1365\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1366\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1367\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1368\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1369\u001b[0m \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 856\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 857\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 858\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 859\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 860\u001b[0m \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m 989\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 990\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_label_like\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 991\u001b[0;31m \u001b[0msection\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 992\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 993\u001b[0m \u001b[0;31m# we have yielded a scalar ?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", @@ -337,7 +337,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -386,12 +386,12 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -416,7 +416,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -461,12 +461,12 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -492,7 +492,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -518,7 +518,7 @@ "for situation in liste_situation:\n", " dico_situation[situation]=len(donnees.loc[donnees.loc[:,'Merci de nous préciser votre situation professionnelle. Vous êtes actuellement : ']==situation,'Merci de nous préciser votre situation professionnelle. Vous êtes actuellement : '])\n", "\n", - "a=pd.Series(d_situation)\n", + "a=pd.Series(dico_situation)\n", "a_clé=list(a.keys())\n", "a_clé[8]='Salarié(e) de la fonction publique'\n", "a_clé[9]=\"Salarié(e) d'une entreprise\"\n", @@ -529,7 +529,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -562,7 +562,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -601,7 +601,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -626,64 +626,27 @@ "dico_python={}\n", "for niveau in liste_niveau_info:\n", " dico_python[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de : [Langage Python]']==niveau,'Quel est votre niveau de connaissance de : [Langage Python]'])\n", - "python=pd.Series(dico_python)\n", "\n", "donnees_R=donnees.loc[:,'Quel est votre niveau de connaissance de : [langage R]']\n", "dico_R={}\n", "for niveau in liste_niveau_info:\n", " dico_R[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de : [langage R]']==niveau,'Quel est votre niveau de connaissance de : [langage R]'])\n", - "R=pd.Series(dico_R)\n", "\n", "donnees_git=donnees.loc[:,'Quel est votre niveau de connaissance de : [Git / Gitlab]']\n", "dico_git={}\n", "for niveau in liste_niveau_info:\n", " dico_git[niveau]=len(donnees.loc[donnees.loc[:,'Quel est votre niveau de connaissance de : [Git / Gitlab]']==niveau,'Quel est votre niveau de connaissance de : [Git / Gitlab]'])\n", - "git=pd.Series(dico_git)\n", "\n", - "pd.DataFrame({\"Git/Gitlab\":git,\"Python\":python,\"R\":R}).T.plot(kind='bar',figsize=(15,7))\n", + "pd.DataFrame({\"Git/Gitlab\":dico_git,\"Python\":dico_python,\"R\":dico_R}).T.plot(kind='bar',figsize=(15,7))\n", "plt.legend(loc='upper center')\n", "plt.show()" ] }, { "cell_type": "code", - "execution_count": 91, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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qETiER3/sxlWPsDL2xAEAAAwi4gAAAAYRcQAAAIOIOAAAgEFEHAAAwCAiDgAAYBARBwAAMIiIAwAAGETEAQAADCLiAAAABhFxAAAAg4g4AACAQUQcAADAICIOAABgEBEHAAAwiIgDAAAYRMQBAAAMIuIAAAAGEXEAAACDiDgAAIBBRBwAAMAgIg4AAGAQEQcAADCIiAMAABhExAEAAAwi4gAAAAYRcQAAAIOIOAAAgEFEHAAAwCAiDgAAYBARBwAAMIiIAwAAGETEAQAADCLiAAAABtm2iKuqH6uqj1fVzVV12Xa9DgAAwE6yLRFXVccl+bUkP57kvCQXV9V52/FaAAAAO8l27Yl7fJKbu/sT3f21JG9KcuE2vRYAAMCOsV0R99Akn163fetiDQAAgCXs2qafWxus9bc8oOrSJJcuNr9cVR/fplnYGqcl+ctVD7FV6j+uegJ2oGPqPZQkeflG/9TDtjnm3kP1095D3OeOrfdRHXPvoYcf7gO3K+JuTfKwddtnJfns+gd09xVJrtim12eLVdW+7t6z6jlgKu8hWI73ECzP++jYsV2HU/7vJOdW1TlVdf8kFyW5epteCwAAYMfYlj1x3X1nVf3rJO9KclyS13X3DdvxWgAAADvJdh1Ome7+gyR/sF0/n/ucQ19hOd5DsBzvIVie99Exorr70I8CAADgqLBdn4kDAABgG4g4AACAQUQcAADAICKOg6qqh1fV0xa3T6iqk1Y9ExztFmfnBYCVqarvr6of32D9WVX191YxE1tHxPEtquqsdbf/RZI3J/mNxdJZSd66irlgmH+26gHgWFBVZ1TVa6vqnYvt86rqklXPBUP8UpIbN1j/6OI+BhNx3NOTq+pnF7efn+RJSb6YJN19U5LTVzUYADvOb2ftO2cfstj+v0letLJpYJYHd/cn77nY3TcnefB9Pw5bScTxLbr7vyb58mLza939tQP3VdWuJL6TAg7te6vqixtcvlRVX1z1cDDIad19VZJvJEl335nkrtWOBGOccJD7TrzPpmBbiDjupbtft7j5vqp6SZITqurpSX43ye+vbjIY4/ruPnmDy0ndffKqh4NBvlJVD87iD4hV9YQkX1jtSDDGH1bVK6qq1i9W1cuT/NGKZmKL+LJvNlVV90tySZIfSVJJ3tXdv7naqeDoV1Uf7u7zVz0HTFdVj0vyq0m+O8lHkuxO8g+7+89WOhgMUFUnJnlNkscnuW6x/Ngk+5L88+7+8mbP5ei3a9UDcFR7QXe/Osk3w62qXrhYAzb3u6seAKZb/CHx+CQ/lOSRWftj4se7++srHQyG6O6vJLm4qh6R5DGL5Ru6+xMrHIst4nBKDmbvBms/fV8PAQPtr6pzk6TW/NbiM3F/ttizABxCd38jya90953dfUN3f0TAweGrqsct/pvzoCSfWVwetG6dweyJ416q6uIkP5nknKq6et1dJyW5YzVTwSgvzNpZ9ZLk4iTfm+ScJOcneXWSH1zNWDDOu6vqOUne0j7/Ad+uXznIfZ3kqffVIGw9EcdGPpDktiSn5Vv/AfhSEp9DgEO7c90eg2cmeX1335G1D5n/pxXOBdP8XNbOondnVf1N1g6pbCcIgkPr7h9e9QxsHyc2AdhiVXVtkmck+XySP0/y1O6+YXHfjd396FXOB8Cxb3FY/y8l+btJrk/y8939mdVOxVbxmTjuparev7j+ku+4giPy77N29q9PJrl6XcD9UBIfKIfDVFXXHM4asKHXJXlHkuckuTZrZ3rlGGFPHMA2qKpdSU7q7s+vWzsxa//uOq0zHERVHZ/kAUnem+QpWTuMMklOTvJOe7Ph0Krquu7+vnXb13a3E5ocI3wmjk1V1d9Jcmt3f7WqnpK1kzO8vrv/erWTwdFt/SEsVfXNQ1gWp3sGDu1nkrwoyUOytgfhgC8m+bWVTATzHF9V5+fuP4KcsH67u6/d9Jkc9eyJY1NVdV2SPUnOTvKuJFcneWR3//1VzgVHu6r6kySvT/LHSZ6V5Ind/Q9WOxXMU1Uv6G6HgMERqKr3Ze0slBvp7nZ2ysFEHJs6sNu9qv5tkr/p7l+tqg939/mrng2OZg5hga1RVT+10Xp3v/6+ngXgaOLEJhzM1xffGbc3ydsXa9+xwnlgiuOr6vx1X6h6wj22gcPz/esuP5jkZVnbuw0cQlX9wrrbz73Hff/hvp+IrWRPHJuqqvOS/Mskf9rdb6yqc5L8RHdfvuLR4KjmEBbYHlX1nUl+p7uFHBzC+qNA7nlEiCNE5nNiEzZUVccleUl3P+/AWnffkkTAwSF091NWPQMco/5fku9a9RAwRG1ye6NthnE4JRvq7ruS7K6q+696FpjGISywNarq96vq6sXlHUk+nuStq54LhuhNbm+0zTAOp2RTVfUbSR6XtbNSfvPU6N39ypUNBQM4hAW2RlX90LrNO7O29+Di7n7+ikaCMarqrqz9/1slOSFre7Kz2D6+u53nYDCHU3Iwn11c7pfkpBXPApM4hAW2QHf/z6r6viQ/meQfJbklye+tdiqYobuPW/UMbB8Rx6a6++VJUlUn+pJi+LY4hAWWUFXfleSiJBcnuSPJf8va0UM/vNLBAI4SDqdkU1X1xCSvTfLA7v7bVfXYJD/T3f9qxaPBUc0hLLCcqvpGkj9Jckl337xY+0R3P2K1kwEcHZzYhIN5VZIfzdpfQdPd/yfJk1c6EQzQ3cd198ndfVJ371rcPrAt4ODQnpPkL5K8t6p+s6ouiEORAb5JxHFQ3f3peyzdtZJBANgxuvu/d/dPJHlUkvcleXGSM6rq16vqR1Y6HMBRQMRxMJ+uqh9I0lV1/6r6+SQ3rnooAHaG7v5Kd7+hu5+Z5Kwk1yW5bMVjAaycz8Sxqao6Lcmrkzwta4exvDvJC7v7jpUOBgAAO5iIY1NVtbu79696DgAA4G4Op+RgPlBV766qS6rqQaseBgAAEHEcRHefm+TfJXlMkmur6u1V9bwVjwUAADuawyk5LIvPx70yyT/u7uNWPQ8AAOxU9sSxqao6uar2VtU7k3wgyW1JHr/isQAAYEezJ45NVdUtSd6a5Kru/tNVzwMAAIg4DqKqqv2CAADAUWXXqgfg6FNVr+ruFyW5uqruFXHd/awVjAUAAETEsbHfWVz/8kqnAAAA7sXhlAAAAIPYE8emqupJSV6W5OFZ+12pJN3dj1jlXAAAsJPZE8emqupjSV6c5ENJ7jqw3t13rGwoAADY4eyJ42C+0N3vXPUQAADA3eyJY1NVdXmS45K8JclXD6x397UrGwoAAHY4Ecemquq9i5sHfkkOfCbuqSsaCQAAdjwRx71U1c8duLm47iT7k7y/u29ZzVQAAECS3G/VA3BUOmlxeeDiclKSPUneWVUXrXIwAADY6eyJ47BV1alJ/rC7H7fqWQAAYKeyJ47D1t1/lbsPsQQAAFZAxHHYquqpST6/6jkAAGAn8z1x3EtVXZ+7z0h5wKlJPpvkp+77iQAAgAN8Jo57qaqH32Opk9zR3V9ZxTwAAMDdRBwAAMAgPhMHAAAwiIgDAAAYRMQBAAAMIuIAAAAGEXEAAACD/H+LjMAwNTwQKwAAAABJRU5ErkJggg==\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Autres :\n", - "\n", - "['LORIA', 'Sustainable Research Unit - REHABS (Nelson Mandela University & Univ. de Lyon)', 'LAAS', 'LEGOS/OBS-MIP', 'IRCGN', 'LAMIH', 'GEPEA', 'SCK-CEN, Belgique', 'VetAgro Sup', 'IMT Atlantique', 'IGF ', 'EPHE (Ecole Pratique des Hautes Etudes)', 'IADI', 'FEMTO-ST', 'CRCA', 'ENSAM', 'Arts et métiers ParisTech', 'National Institute of Standards and Technology ; Centre de Recherche en Automation de Nancy', 'Institut du Cerveau (ICM)', 'CEA/LITEN/LCO GRENOBLE', 'CEA Grenoble', 'Agrocampus', 'Sorbonne Université', 'CEA LETI', 'IRIT', 'ENSAM PARIS', 'CRBM', 'Collège de France', 'PhLAM']\n" - ] - } - ], + "outputs": [], "source": [ "## DILLEPST\n", "\n", @@ -727,22 +690,9 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - 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\n", 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