{"id":922,"date":"2023-11-09T02:45:38","date_gmt":"2023-11-09T02:45:38","guid":{"rendered":"https:\/\/lasstatistique.com\/?p=922"},"modified":"2024-08-14T08:03:34","modified_gmt":"2024-08-14T08:03:34","slug":"cours-3-python","status":"publish","type":"post","link":"https:\/\/lasstatistique.com\/?p=922","title":{"rendered":"Cours 3 : Python"},"content":{"rendered":"<p><span style=\"color: #0000ff;\"><b>CHAPITRE IV : VISUALISATION DES DONNEES<\/b><\/span><\/p>\n<p>On peut d\u00e9finir la <strong><span style=\"color: #0000ff;\">visualisation <\/span><\/strong>comme la repr\u00e9sentation de l\u2019information \u00e0 travers des graphes. On communique l\u2019information par des images, ce qui est tr\u00e8s pratique en analyse de donn\u00e9es.<\/p>\n<ul>\n<li>Python offre plusieurs<span style=\"color: #0000ff;\"> framework<\/span> pour la visualisation. On peut citer :<span style=\"color: #0000ff;\"> Matplotlib<\/span>,<span style=\"color: #0000ff;\"> Pandas visualisation<\/span>,<span style=\"color: #0000ff;\"> Seaborn<\/span>,<span style=\"color: #0000ff;\"> ggplot<\/span>, <span style=\"color: #0000ff;\">plotly<\/span>, <span style=\"color: #0000ff;\">Brokeh<\/span>,<span style=\"color: #0000ff;\"> Altair<\/span>.<\/li>\n<li><span style=\"color: #0000ff;\">Matplotlib<\/span> est la librairie la plus populaire pour la visualisation de donn\u00e9es en python. Elle est rapide et puissante, portable, produit des graphiques de bonnes qualit\u00e9, permet de faire une bonne mise en forme.<\/li>\n<li>Pour utiliser <span style=\"color: #0000ff;\">matplotlib<\/span>, il faut l\u2019importer. Pour le faire, la syntaxe est :<span style=\"color: #0000ff;\"> import matplotlib.pyplot as plt<\/span>. Il y\u2019a beaucoup de sous module dans<span style=\"color: #0000ff;\"> matplotlib<\/span>, nous utilisons<span style=\"color: #0000ff;\"> pyplot<\/span>.<\/li>\n<\/ul>\n<ol>\n<li><span style=\"color: #0000ff;\"><b><i> Les graphiques<\/i><\/b><\/span><\/li>\n<\/ol>\n<p>Les graphes de<span style=\"color: #0000ff;\"> matplotlib<\/span> ont deux parties principales :<\/p>\n<ul>\n<li>Les axes : les lignes qui d\u00e9limitent la surface du graphique.<\/li>\n<li>O\u00f9 nous dessinons les axes, le titre et les autres \u00e9l\u00e9ments qui sortent de la zone de l&rsquo;axe.<\/li>\n<\/ul>\n<p>On distingue 5 types de graphiques sur <span style=\"color: #0000ff;\">matplotlib<\/span>. Le choix de l\u2019un ou l\u2019autre se faisant par rapport au type de la variable dont on souhaite faire la repr\u00e9sentation.<\/p>\n<p>On a : le<span style=\"color: #0000ff;\"> scatter plot<\/span> (nuage de point),<span style=\"color: #0000ff;\"> line plot<\/span> (graphique en ligne),<span style=\"color: #0000ff;\"> Histogram<\/span> (Histogramme),<span style=\"color: #0000ff;\"><span style=\"color: #000000;\"> le<\/span> bar plot<\/span> (Diagramme en bar) et le <span style=\"color: #0000ff;\">pie plot<\/span> (Diagramme en secteur).<\/p>\n<ul>\n<li><strong><span style=\"color: #000000;\">L\u2019histogramme<\/span><\/strong><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">Il est utilis\u00e9 pour visualiser la distribution d\u2019une variable continue. Il est repr\u00e9sent\u00e9 par des rectangles dont la largeur d\u00e9pend de l\u2019intervalle et la longueurs l\u2019effectif.<\/span><\/p>\n<p><span style=\"color: #000000;\">On utilise la m\u00e9thode<span style=\"color: #0000ff;\"> hist<\/span> de<span style=\"color: #0000ff;\"> matplotlib.pyplot <\/span>qui prend en param\u00e8tre la variable.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-923\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-6-1-300x198.png\" alt=\"\" width=\"720\" height=\"475\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-6-1-300x198.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-6-1.png 732w\" sizes=\"auto, (max-width: 720px) 100vw, 720px\" \/><\/p>\n<p>La on voit la distribution des notes de Maths des individus de la base<span style=\"color: #0000ff;\"> exam_scores<\/span>.<\/p>\n<p>On peut remarquer qu\u2019on a plus d\u2019individus ayant plus de 50\/100 que ceux ayant moins de 50\/100<\/p>\n<ul>\n<li><b>Le <\/b><b>scatter<\/b><b> plot <\/b>(nuage de point)<\/li>\n<\/ul>\n<p>Il est utilis\u00e9 pour visualiser la relation entre deux variables continues. Pour cr\u00e9er un nuage de point, on utilise la m\u00e9thode <span style=\"color: #0000ff;\">scatter()<\/span> de <span style=\"color: #0000ff;\">matplotlib.pyplot<\/span>.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-924\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-7-1-300x203.png\" alt=\"\" width=\"723\" height=\"489\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-7-1-300x203.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-7-1-768x521.png 768w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-7-1.png 823w\" sizes=\"auto, (max-width: 723px) 100vw, 723px\" \/><\/p>\n<p><span style=\"color: #0000ff;\">plt.xlabel()<\/span> et<span style=\"color: #0000ff;\"> plt.ylabel()<\/span> permettent d\u2019ajouter les axes de abscisses et ordonn\u00e9es.<\/p>\n<p><span style=\"color: #0000ff;\">plt.title()<\/span> permet de mettre un titre au graphique.<\/p>\n<p><span style=\"color: #0000ff;\">plt.show()<\/span> permet d\u2019afficher le graphique<\/p>\n<ul>\n<li><b>Le line plot <\/b><\/li>\n<\/ul>\n<p>Un graphique lin\u00e9aire est utilis\u00e9 pour repr\u00e9senter des variables continues. Il est g\u00e9n\u00e9ralement utilis\u00e9 pour montrer la tendance de la variable dans le temps. Les valeurs des donn\u00e9es sont repr\u00e9sent\u00e9es sous forme de points reli\u00e9s par des segments de ligne.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-925\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-8-1-300x169.png\" alt=\"\" width=\"758\" height=\"427\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-8-1-300x169.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-8-1-768x432.png 768w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-8-1.png 844w\" sizes=\"auto, (max-width: 758px) 100vw, 758px\" \/><\/p>\n<p>On peut \u00e9galement tracer deux line plots sur un m\u00eame graphique dans le but de faire des comparaisons.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-926\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-9-1-300x164.png\" alt=\"\" width=\"717\" height=\"392\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-9-1-300x164.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-9-1-768x419.png 768w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-9-1.png 949w\" sizes=\"auto, (max-width: 717px) 100vw, 717px\" \/><\/p>\n<p>Ici, <span style=\"color: #0000ff;\">color <\/span>nous permet de mettre une couleur pour chaque pays, et<span style=\"color: #0000ff;\"> label<\/span> permet de marquer chaque graphique pour la l\u00e9gende.<\/p>\n<ul>\n<li><b>Bar plot <\/b><\/li>\n<\/ul>\n<p>Le<span style=\"color: #0000ff;\"> bar plot<\/span> est utilis\u00e9 pour repr\u00e9senter des variables qualitatives ou discr\u00e8te. Les barres ont la m\u00eame largeur et la longueur repr\u00e9sente l\u2019effectif de la modalit\u00e9<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-927\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-10-1-300x248.png\" alt=\"\" width=\"719\" height=\"594\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-10-1-300x248.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-10-1.png 623w\" sizes=\"auto, (max-width: 719px) 100vw, 719px\" \/><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-928\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-11-1-300x235.png\" alt=\"\" width=\"721\" height=\"565\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-11-1-300x235.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-11-1.png 646w\" sizes=\"auto, (max-width: 721px) 100vw, 721px\" \/><\/p>\n<ul>\n<li><b>pie plot <\/b><\/li>\n<\/ul>\n<p>Le bar plot est utilis\u00e9 pour repr\u00e9senter des variables qualitatives ou discr\u00e8te. Les modalit\u00e9s sont repr\u00e9sent\u00e9es par diff\u00e9rentes couleurs et la surface de secteur repr\u00e9sente l\u2019effectif.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-929\" src=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-12-1-300x164.png\" alt=\"\" width=\"721\" height=\"394\" srcset=\"https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-12-1-300x164.png 300w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-12-1-768x420.png 768w, https:\/\/lasstatistique.com\/wp-content\/uploads\/2023\/11\/Capture-12-1.png 774w\" sizes=\"auto, (max-width: 721px) 100vw, 721px\" \/><\/p>\n<p>Dans cet exemple, <span style=\"color: #0000ff;\">explode<\/span> permet de s\u00e9parer le graphique par modalit\u00e9 et <span style=\"color: #0000ff;\">autopct<\/span> permet d\u2019arrondir les effectifs \u00e0 l\u2019unit\u00e9.<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>CHAPITRE IV : VISUALISATION DES DONNEES On peut d\u00e9finir la visualisation comme la repr\u00e9sentation de l\u2019information \u00e0 travers des graphes.<\/p>\n","protected":false},"author":1,"featured_media":906,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_container_layout":"default_layout","colormag_page_sidebar_layout":"default_layout","footnotes":""},"categories":[40,46],"tags":[],"class_list":["post-922","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cours","category-python"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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