{"id":18387,"date":"2020-11-18T10:51:09","date_gmt":"2020-11-18T10:51:09","guid":{"rendered":"https:\/\/datascientest.com\/?p=18387"},"modified":"2024-07-31T15:27:13","modified_gmt":"2024-07-31T15:27:13","slug":"data-cleaning","status":"publish","type":"post","link":"https:\/\/datascientest.com\/data-cleaning","title":{"rendered":"La programmation Python pour les nuls- Episode 3"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"18387\" class=\"elementor elementor-18387\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5a185b1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5a185b1\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ad5819d\" data-id=\"ad5819d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ac90202 elementor-widget elementor-widget-text-editor\" data-id=\"ac90202\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<h3><span style=\"color: #000000;\">Table des mati\u00e8res:<\/span><\/h3><ol><li><span style=\"color: #000000;\"><a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmer-en-python\">Episode 1<\/a> &#8211; <a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmer-en-python#introductionpython\">Introduction<\/a> &#8211;<a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmer-en-python#variables\">Variables<\/a> &#8211;<a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmer-en-python#types\">types<\/a>\u00a0<\/span><\/li><li><span style=\"color: #000000;\"><span style=\"text-decoration: underline;\"><span><a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmation-python-fonctions-operateurs-boucles\" target=\"_blank\" rel=\"noopener\">Episode<\/a><\/span><\/span><a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmation-python-fonctions-operateurs-boucles\" target=\"_blank\" rel=\"noopener\"> 2<\/a>&#8211;<a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmation-python-fonctions-operateurs-boucles#operateurs\" target=\"_blank\" rel=\"noopener\">Op\u00e9rateurs<\/a>&#8211;<a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmation-python-fonctions-operateurs-boucles#boucles\" target=\"_blank\" rel=\"noopener\">Boucles<\/a>&#8211;<a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/programmation-python-fonctions-operateurs-boucles#fonctions\" target=\"_blank\" rel=\"noopener\">Fonctions<\/a><\/span><\/li><li><span style=\"color: #000000;\"><strong><span style=\"text-decoration: underline;\"><span>Episode 3<\/span><\/span><\/strong><\/span><ol><li><a href=\"#importdesdonnees\">Import des donn\u00e9es<\/a><\/li><li><a href=\"#datacleaning\">Data Cleaning<\/a><\/li><li><a href=\"#dataprocessing\">Data processing<\/a><\/li><\/ol><\/li><li><span style=\"color: #000000;\"><u><a style=\"color: #000000;\" href=\"https:\/\/datascientest.com\/la-programmation-python-pour-les-nuls-episode-4\">Episode 4 <\/a>&#8211;<\/u>\u00a0<a style=\"color: #000000;\" href=\"https:\/\/datascientest.com\/exemple-programme-python#bibliothequepython\"><span style=\"text-decoration: underline;\">Import des biblioth\u00e8ques Python<\/span> &#8211;<\/a><span style=\"text-decoration: underline;\"><a style=\"text-decoration: underline; color: #000000;\" href=\"https:\/\/datascientest.com\/exemple-programme-python#donneespython\">Import des donn\u00e9es<\/a><\/span> &#8211;<a style=\"color: #000000;\" href=\"https:\/\/datascientest.com\/exemple-programme-python#valeursmanquantes\"><span style=\"text-decoration: underline;\">Gestion des valeurs manquantes<\/span>\u00a0<\/a><\/span><\/li><li><span style=\"color: #000000;\"><u><a style=\"color: #000000;\" href=\"https:\/\/datascientest.com\/la-programmation-python-pour-les-nuls-episode-4#cheatsheet\">Cheat Sheet Python<\/a><\/u><\/span><\/li><\/ol>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-9abba6b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9abba6b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9446aa9\" data-id=\"9446aa9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d672687 elementor-widget elementor-widget-heading\" data-id=\"d672687\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Bienvenue dans le troisi\u00e8me \u00e9pisode dans notre dossier d\u2019introduction \u00e0 la programmation sur Python. Vous avez vu dans l\u2019\u00e9pisode pr\u00e9c\u00e9dent les diff\u00e9rents op\u00e9rateurs sur Python ainsi que le fonctionnement des boucles et diff\u00e9rentes fonctions utiles sur Python. Dans cette partie vous allez d\u00e9couvrir deux \u00e9tapes indispensables \u00e0 tout projet de machine learning: le data cleaning et le data processing<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-288e69d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"288e69d\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c7847a1\" data-id=\"c7847a1\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a025376 elementor-widget elementor-widget-menu-anchor\" data-id=\"a025376\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\nbody.elementor-page .elementor-widget-menu-anchor{margin-bottom:0}<\/style>\t\t<div id=\"importdesdonnees\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-b4c677a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b4c677a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-cc01e24\" data-id=\"cc01e24\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fa3ca6a elementor-widget elementor-widget-heading\" data-id=\"fa3ca6a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Import des donn\u00e9es:<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1c34fa7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1c34fa7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-19a5f0b\" data-id=\"19a5f0b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2c9bf02 elementor-widget elementor-widget-text-editor\" data-id=\"2c9bf02\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Pr\u00e9alablement aux op\u00e9rations li\u00e9es aux donn\u00e9es en <a href=\"https:\/\/datascientest.com\/python-tout-savoir\">Python<\/a>, telles que le nettoyage, la transformation et la visualisation, il est n\u00e9cessaire de les importer.<\/span><\/p><p><span style=\"font-weight: 400;\">Pour cela, nous utilisons le module <\/span><a href=\"https:\/\/pandas.pydata.org\/docs\/\" target=\"_blank\" rel=\"noopener\"><i>Pandas<\/i><\/a><span style=\"font-weight: 400;\">. D\u00e9velopp\u00e9 pour apporter \u00e0 <\/span><span style=\"font-weight: 400;\"><strong>Python<\/strong> les outils n\u00e9cessaires pour manipuler de gros volumes de donn\u00e9es. Ce module a pour objectif de devenir le meilleur outil de manipulation de donn\u00e9es : \u00e0 la fois performant, facile d&rsquo;utilisation et flexible. <strong>Pandas<\/strong> est aujourd&rsquo;hui le module le plus utilis\u00e9 pour g\u00e9rer des bases de donn\u00e9es aux formats : CSV, Excel, \u2026<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-176e6c7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"176e6c7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1d50b6b\" data-id=\"1d50b6b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-619a1c8 elementor-widget elementor-widget-text-editor\" data-id=\"619a1c8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"text-decoration: underline;\"><strong>Fichier csv :\u00a0<\/strong><\/span><\/p><p><span style=\"font-weight: 400;\">L&rsquo;un des types de donn\u00e9es les plus courants est le format <\/span><strong><i>CSV<\/i><\/strong><span style=\"font-weight: 400;\">, qui est un acronyme pour <strong><em>comma separated value<\/em><\/strong> (<\/span><i><span style=\"font-weight: 400;\">valeurs s\u00e9par\u00e9es<\/span><\/i><span style=\"font-weight: 400;\"> par des <\/span><i><span style=\"font-weight: 400;\">virgules<\/span><\/i><span style=\"font-weight: 400;\">).<\/span><\/p><p><span style=\"font-weight: 400;\">La structure g\u00e9n\u00e9rale des fichiers CSV utilise des lignes comme observations et des colonnes comme attributs.<\/span><\/p><p><span style=\"font-weight: 400;\">Voici la proc\u00e9dure \u00e0 suivre pour lire des fichiers CSV :<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-630be4c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"630be4c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7a1b40e\" data-id=\"7a1b40e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-977ea17 elementor-widget elementor-widget-shortcode\" data-id=\"977ea17\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/YOHANCOHENCODES\/75efefe51f29e0e3638b43194a09af58.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-d9bc9b3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"d9bc9b3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2cddfa9\" data-id=\"2cddfa9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-48dd1d9 elementor-widget elementor-widget-text-editor\" data-id=\"48dd1d9\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Il est \u00e9galement possible d\u2019ajouter d\u2019autres arguments \u00e0 la fonction<strong> pd.read_csv<\/strong> :<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">&#8211; \u00a0 <\/span> <span style=\"font-weight: 400;\">L\u2019argument <\/span><strong><i>sep <\/i><\/strong><span style=\"font-weight: 400;\">dans la fonction permettant de pr\u00e9ciser le type de s\u00e9paration pour la lecture de nos donn\u00e9es (ex : , \/ ; \/ &#8211; \u2026).<\/span><\/p><p><span style=\"font-weight: 400;\">&#8211; \u00a0 <\/span> <span style=\"font-weight: 400;\">L&rsquo;argument <strong>header<\/strong> d\u00e9termine le num\u00e9ro de la ligne qui contient les noms des variables ; par d\u00e9faut, header = 0.<\/span><\/p><p><span style=\"font-weight: 400;\">&#8211; \u00a0 <\/span> <span style=\"font-weight: 400;\">L&rsquo;argument<strong> index_col<\/strong> permet de d\u00e9finir une colonne du DataFrame comme index.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-489b72c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"489b72c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f9000f3\" data-id=\"f9000f3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-21cd886 elementor-widget elementor-widget-text-editor\" data-id=\"21cd886\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"text-decoration: underline;\"><strong>Fichier Excel :<\/strong><\/span><\/p><p><span style=\"font-weight: 400;\">Les donn\u00e9es <a href=\"https:\/\/datascientest.com\/formation-excel\">Excel<\/a> sont avec les fichiers CSV les plus couramment utilis\u00e9s.<\/span><\/p><p><span style=\"font-weight: 400;\">\u00a0<\/span><span style=\"font-weight: 400;\">Voici la proc\u00e9dure \u00e0 suivre avec la fonction <\/span><strong>pd.ExcelFile()<\/strong><span style=\"font-weight: 400;\">:<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4514061 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4514061\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-db422c5\" data-id=\"db422c5\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-95bf994 elementor-widget elementor-widget-shortcode\" data-id=\"95bf994\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/YOHANCOHENCODES\/c2efdb868122f41f4191bc2742bc37c3.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-97abe9e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"97abe9e\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-08d21e5\" data-id=\"08d21e5\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-68caf25 elementor-widget elementor-widget-text-editor\" data-id=\"68caf25\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Si nous ne sp\u00e9cifions pas de nom de feuille, c\u2019est la premi\u00e8re qui est affich\u00e9e par d\u00e9faut. Si nous voulons afficher une feuille en particulier nous pouvons le faire en utilisant la derni\u00e8re ligne de code ci-dessus en pr\u00e9cisant le nom de la feuille.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-245a7ae elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"245a7ae\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-aab65db\" data-id=\"aab65db\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fa56da8 elementor-widget elementor-widget-text-editor\" data-id=\"fa56da8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Avant de proc\u00e9der \u00e0 la mod\u00e9lisation des donn\u00e9es il est n\u00e9cessaire de passer par un nombre d\u2019\u00e9tapes pr\u00e9liminaires qui sont essentielles \u00e0 un projet de <strong>machine Learning<\/strong>. Bien que fastidieuses, il ne faut surtout pas les mettre de c\u00f4t\u00e9 car elles sont garantes de la qualit\u00e9 de notre mod\u00e9lisation. On parle souvent de <strong>\u00ab garbage in \u2013 garbage out \u00bb<\/strong>. Un mod\u00e8le dont la qualit\u00e9 des donn\u00e9es n\u2019est pas optimale, ne pourra pas r\u00e9aliser de bonnes pr\u00e9dictions.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Les \u00e9tapes pr\u00e9liminaires, aussi appel\u00e9es \u00e9tapes de <strong>data pre-processing<\/strong>, recouvrent ainsi les \u00e9tapes de v\u00e9rification de l\u2019\u00e9tat, du nettoyage &#8211; <strong>data cleaning<\/strong> &#8211; et de la pr\u00e9paration de donn\u00e9es.\u00a0 <\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a35aa63 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a35aa63\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f906307\" data-id=\"f906307\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b678882 elementor-widget elementor-widget-heading\" data-id=\"b678882\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">V\u00e9rification:<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a027890 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a027890\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-caa0eec\" data-id=\"caa0eec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c93b263 elementor-widget elementor-widget-text-editor\" data-id=\"c93b263\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Avant toute chose il est important d\u2019avoir une vision d\u2019ensemble sur les donn\u00e9es. Par exemple, la pr\u00e9paration de nos donn\u00e9es va d\u00e9pendre du type de <strong>variables<\/strong>. En pr\u00e9sence de donn\u00e9es num\u00e9riques il est int\u00e9ressant de conna\u00eetre l\u2019intervalle des valeurs, leur moyenne, leur <strong>\u00e9cart-type<\/strong> et autre statistique de base. Cette \u00e9tape de v\u00e9rification comprend \u00e9galement la v\u00e9rification de l\u2019existence de duplicatas.\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8b37ac0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8b37ac0\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2f27a8f\" data-id=\"2f27a8f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0977616 elementor-widget elementor-widget-shortcode\" data-id=\"0977616\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/08dd0cc049f5cbd5fae13238e0ea9204.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fb9fd95 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fb9fd95\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b3afdab\" data-id=\"b3afdab\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d42daec elementor-widget elementor-widget-menu-anchor\" data-id=\"d42daec\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"datacleaning\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-cbf5aa0 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"cbf5aa0\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-169897d\" data-id=\"169897d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7ae189f elementor-widget elementor-widget-heading\" data-id=\"7ae189f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Data Cleaning<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a8e3cee elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a8e3cee\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8841552\" data-id=\"8841552\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7e33dd5 elementor-widget elementor-widget-heading\" data-id=\"7e33dd5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Traitement des donn\u00e9es manquantes<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-77c9869 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"77c9869\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ff21c91\" data-id=\"ff21c91\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-40ae25f elementor-widget elementor-widget-text-editor\" data-id=\"40ae25f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400; color: #000000;\">Les bases de donn\u00e9es auxquelles nous sommes confront\u00e9s au quotidien comprennent tr\u00e8s souvent des donn\u00e9es manquantes. Nombreuses sont les raisons derri\u00e8re cette probl\u00e9matique : des erreurs de typographie qui ont donn\u00e9 lieu \u00e0 des retraits de donn\u00e9es, une absence initiale de donn\u00e9es etc.\u00a0<\/span><\/p><p><span style=\"font-weight: 400; color: #000000;\">La suppression de donn\u00e9es sera la m\u00e9thode utilis\u00e9e en dernier recours car elle engendre une perte importante d\u2019informations. Plus on poss\u00e8dera d\u2019informations, meilleure sera la qualit\u00e9 de pr\u00e9diction de notre mod\u00e8le.\u00a0<\/span><\/p><p><span style=\"font-weight: 400; color: #000000;\">N\u00e9anmoins dans certains cas, on optera tout de m\u00eame pour cette strat\u00e9gie. En r\u00e8gle g\u00e9n\u00e9rale, on fera le choix de supprimer une ligne de donn\u00e9es lorsque celle-ci est truff\u00e9e de donn\u00e9es manquantes, en particulier si les variables les plus importantes sont manquantes, la target par exemple. On pourra d\u00e9cider de supprimer une variable en entier, si la grande majorit\u00e9 des donn\u00e9es sont absentes et que cette variable a peu de poids sur la variable pr\u00e9dite.\u00a0<\/span><\/p><p><span style=\"font-weight: 400; color: #000000;\">On pr\u00e9f\u00e8rera \u00e0 la suppression de ces donn\u00e9es, l\u2019imputation de valeur. Cette [cm_tooltip_parse] m\u00e9thode [\/cm_tooltip_parse] permet de r\u00e9duire la perte d\u2019information. Plusieurs m\u00e9thodes s\u2019offrent \u00e0 nous. On pourra par exemple imputer pour les variables num\u00e9riques la valeur m\u00e9diane ou moyenne de cette variable (on fera attention aux valeurs extr\u00eames si l\u2019on impute la moyenne). Si l\u2019on a \u00e0 faire \u00e0 une variable cat\u00e9gorielle, on pourra imputer la valeur majoritaire au sein de la variable, en utilisant le mode.\u00a0<\/span><\/p><p><span style=\"font-weight: 400; color: #000000;\">Une m\u00e9thode d\u2019imputation plus fine sera d\u2019imputer en tenant compte des valeurs au sein des autres variables. On pourra ainsi calculer la moyenne, la m\u00e9diane, le mode par groupes d\u2019individus au sein d<\/span><span style=\"font-weight: 400;\">u <\/span><span style=\"font-weight: 400;\"><strong>DataFrame<\/strong><\/span> <span style=\"font-weight: 400; color: #000000;\">pour affiner la valeur \u00e0 imputer.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2503ec4 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2503ec4\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-69b964d\" data-id=\"69b964d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a023e0c elementor-widget elementor-widget-shortcode\" data-id=\"a023e0c\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/776a9a6f9405c1442343334b0060173d.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f41fa5a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f41fa5a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-35feb65\" data-id=\"35feb65\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6d1a860 elementor-widget elementor-widget-heading\" data-id=\"6d1a860\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Valeurs aberrantes \/Outliers<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-91ec1d8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"91ec1d8\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7aeca2a\" data-id=\"7aeca2a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-92ce5e2 elementor-widget elementor-widget-text-editor\" data-id=\"92ce5e2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Un outlier ou valeur aberrante correspond \u00e0 une valeur \u00e9loign\u00e9e de la distribution de la variable. Cela pourra \u00eatre d\u00fb \u00e0 une <strong>erreur de typographie<\/strong> ou \u00e0 une <strong>erreur de mesure<\/strong> mais cela pourra \u00e9galement \u00eatre une valeur extr\u00eame. On parle couramment de valeur extr\u00eame, pour d\u00e9signer une valeur non erron\u00e9e qui s\u2019\u00e9loigne n\u00e9anmoins fortement du reste des valeurs de la variable.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Une fa\u00e7on assez simple de d\u00e9tecter ces valeurs est de r\u00e9aliser un <strong>box-plot <\/strong>pour chacune des variables. Un<strong> box plot<\/strong> est un graphique sous forme de rectangle o\u00f9 sont d\u00e9crites les statistiques de la variables (les quartiles (Q1, m\u00e9diane, Q3). Les bornes du graphique d\u00e9limitent les valeurs selon la distribution de la variable. Au-del\u00e0 de ces extr\u00e9mit\u00e9s, ces valeurs sont consid\u00e9r\u00e9es comme des valeurs aberrantes.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-107ac05 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"107ac05\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-fa6cba8\" data-id=\"fa6cba8\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c4c7422 elementor-widget elementor-widget-shortcode\" data-id=\"c4c7422\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/2f9c35b9d3bec0b0d478b21dc0889721.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-50a2d03 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"50a2d03\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7b30824\" data-id=\"7b30824\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-384ee40 elementor-widget elementor-widget-text-editor\" data-id=\"384ee40\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Dans le cadre d\u2019un projet de<strong> Machine Learning<\/strong> on fera souvent le choix de supprimer une valeur aberrante. En effet, pour obtenir une meilleure qualit\u00e9 de pr\u00e9diction il est n\u00e9cessaire de traiter ces donn\u00e9es car un mod\u00e8le pourra \u00eatre tr\u00e8s sensible aux donn\u00e9es extr\u00eames ce qui va biaiser les pr\u00e9dictions.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f1831f6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f1831f6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-3811546\" data-id=\"3811546\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-b657d75 elementor-widget elementor-widget-shortcode\" data-id=\"b657d75\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/fa5572ebd71c7b1b6e81dcb28aa21415.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1319584 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1319584\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d45a063\" data-id=\"d45a063\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4201770 elementor-widget elementor-widget-menu-anchor\" data-id=\"4201770\" data-element_type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"dataprocessing\" class=\"elementor-menu-anchor\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-af26bbe elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"af26bbe\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1da01a5\" data-id=\"1da01a5\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6ecbbc1 elementor-widget elementor-widget-heading\" data-id=\"6ecbbc1\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Data processing<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c9b1a70 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c9b1a70\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-4072b43\" data-id=\"4072b43\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-894c30f elementor-widget elementor-widget-heading\" data-id=\"894c30f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Encodage binaire<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-42c1a12 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"42c1a12\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-895682c\" data-id=\"895682c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6701705 elementor-widget elementor-widget-text-editor\" data-id=\"6701705\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Lorsque l\u2019on est en pr\u00e9sence de donn\u00e9es <strong>cat\u00e9gorielles textuelles<\/strong>, il est n\u00e9cessaire d\u2019encoder nos variables. On parle d\u2019<strong>encodage binaire<\/strong> lorsque l\u2019on encode une variable en deux cat\u00e9gories, en g\u00e9n\u00e9ral en 0, 1. Par exemple, une variable d\u00e9crivant le sexe d\u2019une personne pourra \u00eatre encod\u00e9 en 0, 1. Une<strong> variable cat\u00e9gorielle<\/strong> (avec plus que deux cat\u00e9gories) pourra \u00e9galement \u00eatre encod\u00e9, selon le nombre de cat\u00e9gories qui la compose.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">La strat\u00e9gie habituellement adopt\u00e9e est n\u00e9anmoins celle de la cr\u00e9ation de <strong>dummies<\/strong>. A partir d\u2019une variable, pour les n-cat\u00e9gories qui la compose, on cr\u00e9era n-1 colonnes encod\u00e9es de fa\u00e7on binaire (0-1) correspondant, chacune correspondant \u00e0 une des cat\u00e9gories comprises dans la variable. On retire une colonne car cette colonne peut \u00eatre d\u00e9duite des autres. Il est important que les variables ne soient pas corr\u00e9l\u00e9es pour la qualit\u00e9 de la pr\u00e9diction.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2f2f966 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2f2f966\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-bbb7f45\" data-id=\"bbb7f45\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-938d7f4 elementor-widget elementor-widget-shortcode\" data-id=\"938d7f4\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/8e3a27b17de4e0e56483a3261575b140.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-27ea407 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"27ea407\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-032cb06\" data-id=\"032cb06\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-25fffa9 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"25fffa9\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9marer en Python<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7dbba3f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7dbba3f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d1925aa\" data-id=\"d1925aa\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-15480dd elementor-widget elementor-widget-heading\" data-id=\"15480dd\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Feature Scaling : Normalisation et standardisation<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4c2e97c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4c2e97c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-56fb839\" data-id=\"56fb839\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3af6200 elementor-widget elementor-widget-text-editor\" data-id=\"3af6200\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: left;\"><span style=\"font-weight: 400;\">Les variables qui composent un <strong>DataFrame<\/strong> ne sont pas toujours \u00e0 la m\u00eame \u00e9chelle. L\u2019\u00e2ge et la taille par exemple n\u2019ont pas la m\u00eame mesure. Ainsi, pour \u00e9quilibrer le poids de chacune des variables au sein du DataFrame, il conviendra de \u00ab <strong>scaler<\/strong> \u00bb les variables autrement dit les mettre \u00e0 la m\u00eame \u00e9chelle. Cette \u00e9tape est tr\u00e8s importante notamment dans les mod\u00e8les qui utilisent des mesures de distance lin\u00e9aire et qui seront fortement impact\u00e9es par ce genre de d\u00e9s\u00e9quilibre.<\/span><\/p><p style=\"text-align: left;\"><span style=\"font-weight: 400;\">Deux cas de figure se pr\u00e9sentent \u00e0 nous :<strong> lorsque la distribution d\u2019une variable suit une loi normale et lorsqu\u2019elle ne suit pas une loi normale.<\/strong>\u00a0<\/span><\/p><p style=\"text-align: left;\"><span style=\"font-weight: 400;\">Si elle ne suit pas une loi normale il convient d\u2019appliquer un<strong> \u00ab min-max scaling \u00bb<\/strong>, ses valeurs seront dans un intervalle [0,1].<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-bb0a30a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bb0a30a\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8ffca01\" data-id=\"8ffca01\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e5b5104 elementor-widget elementor-widget-text-editor\" data-id=\"e5b5104\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\"><span style=\"font-weight: 400;\">X&rsquo;=(X-X_min)\/(X_max\u00a0 &#8211; X_min)<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c49f589 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c49f589\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5c6248a\" data-id=\"5c6248a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e0d4405 elementor-widget elementor-widget-shortcode\" data-id=\"e0d4405\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-45ab561 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"45ab561\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a88ffa3\" data-id=\"a88ffa3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d87cde3 elementor-widget elementor-widget-text-editor\" data-id=\"d87cde3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Si la variable suit une distribution normale, on parlera de standardisation. Pour ce faire <strong>on soustrait la moyenne et on divise par l\u2019\u00e9cart type.<\/strong><\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6a51b29 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6a51b29\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-851424b\" data-id=\"851424b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c42e677 elementor-widget elementor-widget-text-editor\" data-id=\"c42e677\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p style=\"text-align: center;\"><span style=\"font-weight: 400;\">X&rsquo;=(X &#8211; \u03bc)\/\u03c3<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-71de96c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"71de96c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-97bcd71\" data-id=\"97bcd71\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-41c12fc elementor-widget elementor-widget-text-editor\" data-id=\"41c12fc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\"><span style=\"color: #000000;\">O\u00f9<strong> \u00b5<\/strong> ou <strong>\u03c3<\/strong> sont la moyenne et l\u2019\u00e9cart type de la distribution.<\/span> <\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-21dedff elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"21dedff\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6988b62\" data-id=\"6988b62\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c95527f elementor-widget elementor-widget-shortcode\" data-id=\"c95527f\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-shortcode\"><script src=\"https:\/\/gist.github.com\/Lara-datascientest\/085b75fe6b96aa7f8cd81db0484b5683.js\"><\/script><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-bb86716 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"bb86716\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8a01738\" data-id=\"8a01738\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-fd7cc95 elementor-widget elementor-widget-heading\" data-id=\"fd7cc95\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusion:<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-9d247d6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9d247d6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-be73a2c\" data-id=\"be73a2c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-25d1b31 elementor-widget elementor-widget-text-editor\" data-id=\"25d1b31\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Voici donc les jalons principaux de l\u2019\u00e9tape de data pre-processing. Il existe \u00e9videmment d\u2019autres proc\u00e9dures que vous pourrez appliquer \u00e0 vos bases de donn\u00e9es de fa\u00e7on plus sp\u00e9cifique ! Plus les variables de notre DataFrame sont bien trait\u00e9es et plus faciles seront les \u00e9tapes de cr\u00e9ation de variables et de mod\u00e9lisation. <\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ea8f64d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ea8f64d\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a0184aa\" data-id=\"a0184aa\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f78544b elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"f78544b\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir nos formations <\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Table des mati\u00e8res: Episode 1 &#8211; Introduction &#8211;Variables &#8211;types&nbsp; Episode 2&#8211;Op\u00e9rateurs&#8211;Boucles&#8211;Fonctions Episode 3 Import des donn\u00e9es Data Cleaning Data processing Episode 4 &#8211;&nbsp;Import des biblioth\u00e8ques Python &#8211;Import des donn\u00e9es &#8211;Gestion des valeurs manquantes&nbsp; Cheat Sheet Python Bienvenue dans le troisi\u00e8me \u00e9pisode dans notre dossier d\u2019introduction \u00e0 la programmation sur Python. Vous avez vu dans l\u2019\u00e9pisode [&hellip;]<\/p>\n","protected":false},"author":78,"featured_media":19220,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data cleaning, data processing : L&#039;essentiel pour d\u00e9marrer en Python<\/title>\n<meta name=\"description\" content=\"Le data cleaning et le data processing , deux \u00e9tapes cl\u00e9s de tout projet data science: d\u00e9couvrez comment y proc\u00e9der dans cet article !\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/data-cleaning\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"La programmation Python pour les nuls- Episode 3\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/data-cleaning\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2020-11-18T10:51:09+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-31T15:27:13+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2020\/11\/illu_progpython_3_blog-22.png\" \/>\n\t<meta property=\"og:image:width\" content=\"4268\" \/>\n\t<meta property=\"og:image:height\" content=\"2343\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"J\u00e9r\u00e9my Robert\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"J\u00e9r\u00e9my Robert\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/data-cleaning\",\"url\":\"https:\/\/datascientest.com\/data-cleaning\",\"name\":\"Data cleaning, data processing : L'essentiel pour d\u00e9marrer en Python\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2020-11-18T10:51:09+00:00\",\"dateModified\":\"2024-07-31T15:27:13+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/7af2361c48e24e79a8aa2360e6e74925\"},\"description\":\"Le data cleaning et le data processing , deux \u00e9tapes cl\u00e9s de tout projet data science: d\u00e9couvrez comment y proc\u00e9der dans cet article !\",\"inLanguage\":\"fr-FR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/datascientest.com\/data-cleaning\"]}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/datascientest.com\/#website\",\"url\":\"https:\/\/datascientest.com\/\",\"name\":\"Formation Data Science | DataScientest.com\",\"description\":\"Leader de la formation en Data Science\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/datascientest.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"fr-FR\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/7af2361c48e24e79a8aa2360e6e74925\",\"name\":\"J\u00e9r\u00e9my Robert\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"fr-FR\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/jeremyrobert.jpeg\",\"contentUrl\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/jeremyrobert.jpeg\",\"caption\":\"J\u00e9r\u00e9my Robert\"},\"description\":\"J\u00e9r\u00e9my Robert est actuellement Directeur p\u00e9dagogique B2B chez DataScientest.com. 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