{"id":171001,"date":"2023-09-22T19:43:56","date_gmt":"2023-09-22T18:43:56","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=171001"},"modified":"2023-10-30T20:08:57","modified_gmt":"2023-10-30T19:08:57","slug":"matplotlib-master-data-visualization-in-python","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/matplotlib-master-data-visualization-in-python","title":{"rendered":"Matplotlib: Master Data Visualization in Python"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"171001\" class=\"elementor elementor-171001\" 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-5fe21058 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5fe21058\" 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-7693c799\" data-id=\"7693c799\" 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-55cf4c35 elementor-widget elementor-widget-heading\" data-id=\"55cf4c35\" 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\">Matplotlib is an open-source Python library for creating data visualizations. Discover everything you need to know: definition, how it works, challenges, and training...<\/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-20e97a9f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"20e97a9f\" 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-17b99161\" data-id=\"17b99161\" 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-3c26cc8 elementor-widget elementor-widget-text-editor\" data-id=\"3c26cc8\" 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<p>Data visualization is a key step in data analysis. After collecting, storing, and analyzing data, it&#8217;s essential to transform the results of these analyses into reports and graphical visualizations. This is because the human brain understands a chart more quickly than a series of statistics in tabular form. Therefore,<a href=\"https:\/\/datascientest.com\/en\/dataviz-definition-objectives-and-uses\"> &#8220;DataViz&#8221; allows sharing the results of an analysis with non-technical<\/a> teams within a company, including its executives.<\/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-4998d3a6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4998d3a6\" 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-3b3bf5bb\" data-id=\"3b3bf5bb\" 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-57abfaaa elementor-widget elementor-widget-heading\" data-id=\"57abfaaa\" 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\">What is Matplotlib ?<\/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-7dbc733c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7dbc733c\" 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-51a57f3c\" data-id=\"51a57f3c\" 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-2475de3a elementor-widget elementor-widget-text-editor\" data-id=\"2475de3a\" 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>Matplotlib is an open-source Python library originally developed by neurobiologist John Hunter in 2002. Its initial purpose was to visualize the brain signals of epileptic individuals. To achieve this, Hunter aimed to replicate the graphic creation<a href=\"https:\/\/datascientest.com\/en\/python-all-you-need-to-know\"> capabilities of MATLAB using Python.<\/a><\/p><p>Following John Hunter&#8217;s passing in 2012, Matplotlib has been continually improved over time by numerous contributors from the open-source community. It is used to create high-quality graphs and charts and serves as an open-source alternative to MATLAB.<\/p><p>For instance, you can create plots, histograms, bar charts, and various types of graphs with just a few lines of code. It&#8217;s a comprehensive tool that enables the generation o<strong>f highly detailed data visualizations.<\/strong><\/p><p>This library is especially valuable for individuals working with Python or <a href=\"https:\/\/datascientest.com\/en\/numpy-the-python-library-in-data-science\">NumPy.<\/a> It finds application in web application servers, Python shells, and scripts. With Matplotlib&#8217;s APIs, developers can also integrate charts into graphical interface applications.<\/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-37feedfc elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"37feedfc\" 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-314c88e8\" data-id=\"314c88e8\" 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-3d1afbc3 elementor-widget elementor-widget-video\" data-id=\"3d1afbc3\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/-29x_deQQus&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.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-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\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-71802381 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"71802381\" 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-6328d06f\" data-id=\"6328d06f\" 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-62b3dd70 elementor-widget elementor-widget-heading\" data-id=\"62b3dd70\" 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\">Matplotlib's main concepts<\/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-3a17d847 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3a17d847\" 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-4dee8965\" data-id=\"4dee8965\" 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-348c8ce9 elementor-widget elementor-widget-text-editor\" data-id=\"348c8ce9\" 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><strong>Matplotlib<\/strong> relies on several key elements. A &#8220;figure&#8221; represents a complete illustration, and each plot within that figure is referred to as an &#8220;axis.&#8221;<\/p><p><strong>&#8220;Plotting&#8221;<\/strong> involves creating a graph, for which you need data in the form of key-value pairs representing the X and Y axes. Functions like &#8220;scatter,&#8221; &#8220;bar,&#8221; and &#8220;pie&#8221; are then used to create the chart.<\/p><p>You can create basic graphs like bar charts or histograms, as well as more complex three-dimensional figures using Matplotlib.<\/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-51c7c116 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"51c7c116\" 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-53862e81\" data-id=\"53862e81\" 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-743b1d39 elementor-widget elementor-widget-image\" data-id=\"743b1d39\" data-element_type=\"widget\" data-widget_type=\"image.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-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"450\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-1024x576.png\" class=\"attachment-large size-large wp-image-171009\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-1024x576.png 1024w, https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-300x169.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-768x432.png 768w, https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-1536x864.png 1536w, https:\/\/datascientest.com\/en\/files\/2023\/09\/matplotlib-graphs-2048x1153.png 2048w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\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-5e3974ec elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5e3974ec\" 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-374c53e9\" data-id=\"374c53e9\" 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-72190d8 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"72190d8\" 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\/en\/data-courses\">\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\">Learn more about Python libraries<\/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<div class=\"elementor-element elementor-element-3d506e9c e-flex e-con-boxed e-con\" data-id=\"3d506e9c\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3400d93f elementor-widget elementor-widget-heading\" data-id=\"3400d93f\" 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\">4 things you need to know about Matplotlib<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-24d3b65d elementor-widget elementor-widget-text-editor\" data-id=\"24d3b65d\" 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>With Matplotlib, you can <strong>enhance the visual appearance<\/strong> of your graphs by adding a title, legends, and by choosing the style and color of visualizations. You can also adjust the size of the figures and choose the layout of the graphs if you decide to display multiple graphs in a single figure.<\/p><p>Matplotlib also offers a function for annotating graphs freely and for saving an image in jpg format.<\/p><p>Additionally, you can <strong>add a digital watermark<\/strong> to a graph to include copyright information.<br \/>Now, let&#8217;s explore some examples of graphs that you can create with Matplotlib along with the few lines of code to plot them.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2c774541 e-flex e-con-boxed e-con\" data-id=\"2c774541\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-57e6fdef elementor-widget elementor-widget-heading\" data-id=\"57e6fdef\" 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\">1. Tracing functions<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5e2a9569 elementor-widget elementor-widget-text-editor\" data-id=\"5e2a9569\" 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><strong>Matplotlib<\/strong> is primarily a library for plotting functions and displaying their curves in graphs. We can visualize trigonometric functions like sine and cosine by specifying the interval over which we want to observe these functions.<\/p><p>Here&#8217;s an example of plotting the sine and cosine functions between 0 and 6. The function used is `plot()`, which is a basic function in Matplotlib.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6a70aed6 elementor-widget elementor-widget-image\" data-id=\"6a70aed6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"512\" height=\"384\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image6.png\" class=\"attachment-large size-large wp-image-171010\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image6.png 512w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image6-300x225.png 300w\" sizes=\"(max-width: 512px) 100vw, 512px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4dcd7c3e elementor-widget elementor-widget-text-editor\" data-id=\"4dcd7c3e\" 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;\">To create this graph, we use two libraries, Matplotlib and NumPy. NumPy is used to calculate the sine and cosine values, and the `arange` function generates a list from 0 to 2 Pi with an interval of 0.1 between each value.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-53f0083 elementor-widget elementor-widget-html\" data-id=\"53f0083\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script src=\"https:\/\/gist.github.com\/Thomas-AH-Heller\/1dfaa426ddec5e3f1877157ae1529e28.js\"><\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-38f3e04e e-flex e-con-boxed e-con\" data-id=\"38f3e04e\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-38309d3b elementor-widget elementor-widget-heading\" data-id=\"38309d3b\" 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\">2. Creating 2D Graphs<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6e8bc7ca elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6e8bc7ca\" 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-4b6e76a2\" data-id=\"4b6e76a2\" 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-5839c0ba elementor-widget elementor-widget-text-editor\" data-id=\"5839c0ba\" 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><strong>Another feature of Matplotlib<\/strong> is the creation of 2D graphs, which is very useful for a Data Scientist in the data visualization step. Indeed, it is possible to display histograms, pie charts, box plots, scatter plots, stack plots (for stacked data visualization), and more.<\/p><p>These graphs can be used, for example, to display data distribution, statistical indicators, trends over a certain period if dealing with time series data, and more.<\/p><p>The main functions used are:<\/p><ul><li>hist() to plot a histogram.<\/li><li>bar() to plot a bar chart.<\/li><li>pie() to plot a pie chart.<\/li><li>box() to plot box plots.<\/li><li>scatter() to plot a scatter plot.<\/li><li>stackplot() to plot a stacked area chart.<\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-408999fe elementor-widget elementor-widget-image\" data-id=\"408999fe\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"799\" height=\"559\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image1-1.png\" class=\"attachment-large size-large wp-image-171011\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image1-1.png 799w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image1-1-300x210.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image1-1-768x537.png 768w\" sizes=\"(max-width: 799px) 100vw, 799px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">exe de pie()<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3f563f7a elementor-widget elementor-widget-text-editor\" data-id=\"3f563f7a\" 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>This example is inspired by the &#8220;Matplotlib &#8211; Box Plots and Pie Charts&#8221; module from our <a href=\"https:\/\/datascientest.com\/en\/data-scientist-job-all-about\">Data Scientist and Data Analyst training!<\/a><\/p><p>Here, we use the labels, colors, and autopct functions of the pie chart. Labels, as the name suggests, allows you to choose the labels for the segments, colors can be used in various ways, either with keywords like &#8220;Yellow&#8221; or &#8220;Red&#8221; or by using Hex codes, as shown in our example.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73832215 elementor-widget elementor-widget-image\" data-id=\"73832215\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"798\" height=\"430\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image3.png\" class=\"attachment-large size-large wp-image-171012\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image3.png 798w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image3-300x162.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image3-768x414.png 768w\" sizes=\"(max-width: 798px) 100vw, 798px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7424f13b elementor-widget elementor-widget-text-editor\" data-id=\"7424f13b\" 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;\">Here, we use two lists, Pda and Pds, which we created beforehand to create our bar chart. First, we create the first bar chart, and then we add the second one by specifying &#8220;bottom=Pda&#8221; to indicate that the second bar chart is stacked on top of the first one.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cc69755 elementor-widget elementor-widget-image\" data-id=\"5cc69755\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"798\" height=\"430\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image9-1.png\" class=\"attachment-large size-large wp-image-171013\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image9-1.png 798w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image9-1-300x162.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image9-1-768x414.png 768w\" sizes=\"(max-width: 798px) 100vw, 798px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">exemple de bar()<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-54e61b8f elementor-widget elementor-widget-text-editor\" data-id=\"54e61b8f\" 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>For this bar chart, we decided to place the two bars side by side. To achieve this, we use two sets of values for the X-axis. First, we use &#8220;x1,&#8221; which ranges from 0 to 11 with a step, and then &#8220;x2,&#8221; which ranges from 0.4 to 11.4 with a step of 1. We do this to offset the second column by 0.4, which will also be the width of our bars.<\/p><p>These two charts are inspired by the &#8220;Matplotlib \u2013 Bar Charts&#8221; module in the Data Scientist and Data Analyst course.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-19e77520 elementor-widget elementor-widget-image\" data-id=\"19e77520\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"474\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image8-1.png\" class=\"attachment-large size-large wp-image-171014\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image8-1.png 800w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image8-1-300x178.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image8-1-768x455.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4cda282f elementor-widget elementor-widget-text-editor\" data-id=\"4cda282f\" 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;\">For this graph, we use lists for the axes. Both groups of scatter plots share the same X-axis but have different values on the Y-axis. We can also see that we use the &#8220;s&#8221; argument to vary the size of our points.<\/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<div class=\"elementor-element elementor-element-6ac9f388 e-flex e-con-boxed e-con\" data-id=\"6ac9f388\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1d4dec5c elementor-widget elementor-widget-heading\" data-id=\"1d4dec5c\" 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\">3. Display 3D graphics<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7c6ba4b8 elementor-widget elementor-widget-text-editor\" data-id=\"7c6ba4b8\" 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>It&#8217;s also possible to create 3D graphs using Matplotlib. To do this, you need to use a special Matplotlib library called <code>mpl_toolkits.mplot3d<\/code> (often renamed to <code>Axes3D<\/code>).<\/p><p>3D graphs can simplify certain visualizations and make a report more enjoyable to read.<\/p><p>In general, the functions used include <code>Axes3D.plot()<\/code>, <code>Axes3D.scatter()<\/code>, <code>Axes3D.plot_wireframe()<\/code>, <code>Axes3D.plot_surface()<\/code>, and <code>Axes3D.bar()<\/code>.<\/p><p>Here&#8217;s an example of what can be displayed using these functions. This example is from the official documentation.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4f23f737 elementor-widget elementor-widget-image\" data-id=\"4f23f737\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"449\" height=\"408\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image2-1.png\" class=\"attachment-large size-large wp-image-171015\" alt=\"\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/09\/image2-1.png 449w, https:\/\/datascientest.com\/en\/files\/2023\/09\/image2-1-300x273.png 300w\" sizes=\"(max-width: 449px) 100vw, 449px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0ebfb3a elementor-widget elementor-widget-html\" data-id=\"0ebfb3a\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script src=\"https:\/\/gist.github.com\/Thomas-AH-Heller\/81d803f0f7c6c7113734e8bbd887466b.js\"><\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-589f4ad8 e-flex e-con-boxed e-con\" data-id=\"589f4ad8\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-3ba1cc6b elementor-widget elementor-widget-heading\" data-id=\"3ba1cc6b\" 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\">4. Creating widgets<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32baec4e elementor-widget elementor-widget-text-editor\" data-id=\"32baec4e\" 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>The last feature of <strong>Matplotlib<\/strong> that we will discuss is the creation of widgets. These are interactive visualizations on which the user can take action. For a data scientist, this can be very useful, for example, to see how changing a parameter influences a function or a <a href=\"https:\/\/datascientest.com\/en\/survival-analysis-beyond-machine-learning\">Machine Learning model.<\/a><\/p><p>All the necessary classes for implementing a widget can be found in the `matplotlib.widgets` module.<\/p><p>Creating a widget requires creating objects and functions that describe the action of one object on another. Objects could be things like a slider (of the Slider class) or a button (of the Button class), which could, for example, cover a range of values that a function&#8217;s parameter might take. Thus, depending on the value of this parameter, the user sees the graph of the function change instantly.<\/p><p>This widget is from the &#8220;<a href=\"https:\/\/datascientest.com\/en\/all-about-deep-learning\">Introduction to Deep Learning with Keras<\/a>&#8221; module in the Data Scientist and Data Analyst tracks.<\/p><p>By adjusting the parameters w1 and w2, we can adjust the red line to find the boundary that separates the green data from the orange data. This is called a classification problem using a linear method: we separate data into two categories using a linear decision boundary.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d1559c9 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"d1559c9\" 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\/en\/data-courses\">\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\">Learn how to use 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\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4c5b209c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4c5b209c\" 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-5af50827\" data-id=\"5af50827\" 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-a2426f4 elementor-widget elementor-widget-heading\" data-id=\"a2426f4\" 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\">What is PyPlot?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-184bae31 elementor-widget elementor-widget-text-editor\" data-id=\"184bae31\" 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>Pyplot is a Matplotlib module that offers several simple functions for adding elements such as lines, images, or text to the axes of a graph. Its interface is very convenient, which is why this module is widely used.<\/p><p>There is also an <a href=\"https:\/\/datascientest.com\/en\/api-the-path-to-seamless-integration\">Object-Oriented (OO) API<\/a> that provides more flexibility and customization by allowing objects to be assembled more freely. However, it is more challenging to use.<\/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-720a4b09 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"720a4b09\" 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-442d5199\" data-id=\"442d5199\" 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-2256d7c elementor-widget elementor-widget-video\" data-id=\"2256d7c\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=UO98lJQ3QGI&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\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-19faf52a elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"19faf52a\" 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-ead9ba2\" data-id=\"ead9ba2\" 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-71c4c033 elementor-widget elementor-widget-heading\" data-id=\"71c4c033\" 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\">Matplotlib, Numpy and Pandas<\/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-6dcae98f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6dcae98f\" 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-5471e8a5\" data-id=\"5471e8a5\" 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-3a452da7 elementor-widget elementor-widget-text-editor\" data-id=\"3a452da7\" 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>Numpy is a Python package dedicated to scientific computing. It is an essential dependency for Matplotlib since Matplotlib uses Numpy functions for numerical data and multi-dimensional arrays.<\/p><p>On the other hand, <a href=\"https:\/\/datascientest.com\/en\/pandas-the-python-library\">Pandas is a Python library<\/a> also used by Matplotlib for data manipulation and analysis. It is not an essential dependency like Numpy, but it is often used in conjunction with Matplotlib.<\/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-703a539c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"703a539c\" 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-31d2df3c\" data-id=\"31d2df3c\" 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-567ac977 elementor-widget elementor-widget-heading\" data-id=\"567ac977\" 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\">Matplotlib and Data Science<\/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-34db3bbf elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"34db3bbf\" 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-7120a4f4\" data-id=\"7120a4f4\" 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-24d6416c elementor-widget elementor-widget-text-editor\" data-id=\"24d6416c\" 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>Python is the most widely used programming language for <a href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-all-about-the-job\">Data Science and Machine Learning.<\/a> As a result, <strong>resources like NumPy and Matplotlib<\/strong> are very valuable for building machine learning models.<\/p><p>Programmers can access these libraries to perform crucial tasks within the Python environment. It is then possible to integrate the results with other elements and functionalities of a machine learning program or neural network.<\/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-6fcf6357 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6fcf6357\" 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-5e0269cd\" data-id=\"5e0269cd\" 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-47f1c615 elementor-widget elementor-widget-video\" data-id=\"47f1c615\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/www.youtube.com\\\/watch?v=DAQNHzOcO5A&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\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-6e131a37 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6e131a37\" 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-9abb9be\" data-id=\"9abb9be\" 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-85ac7ba elementor-widget elementor-widget-heading\" data-id=\"85ac7ba\" 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\">What are the difficulties with Matplotlib?<\/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-23772bac elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"23772bac\" 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-2109ed7b\" data-id=\"2109ed7b\" 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-75393a8c elementor-widget elementor-widget-text-editor\" data-id=\"75393a8c\" 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>Learning Matplotlib can be challenging. There are many tutorials available, but several difficulties may arise for beginners.<\/p><p>Firstly, this library is extremely extensive, comprising over 70,000 lines of code in total. It also hosts multiple different interfaces and has the capability<strong> to interact with various backends for rendering graphics.<\/strong><\/p><p>Moreover, while publicly accessible documentation on Matplotlib is understandable, some documents are simply outdated. This tool continues to evolve over time, and some examples available on the internet can actually be achieved with 70% fewer lines of code on modern versions.<\/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-138eef83 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"138eef83\" 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-20cb7302\" data-id=\"20cb7302\" 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-d448f71 elementor-widget elementor-widget-heading\" data-id=\"d448f71\" 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\">How do I learn Matplotlib?<\/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-14347f89 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"14347f89\" 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-7b989cca\" data-id=\"7b989cca\" 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-79bcb110 elementor-widget elementor-widget-text-editor\" data-id=\"79bcb110\" 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><strong>Matplotlib<\/strong> offers many possibilities for data visualization but can be challenging to master due to its technical complexity and heavy syntax. Learning it on your own can be difficult because much of the online documentation is outdated.<\/p><p>To learn how to use this library effectively, you can consider DataScientest&#8217;s training programs. We offer courses that cover various roles in data science,<a href=\"https:\/\/datascientest.com\/en\/data-analyst-salary-average-salary-revealed\"> including Data Analyst<\/a>, Data Scientist, Data Engineer, ML Engineer, and Data Manager.<\/p><p>Python is the preferred programming language for all our programs, and you will learn to use this language and its various data science libraries, including Matplotlib for data visualization. <strong>This tool is part of the curriculum in our &#8220;data visualization&#8221;<\/strong> module for Data Analyst, Data Scientist, and Data Management training programs.<\/p><p>All our training programs follow a Blended Learning approach, combining an online platform with coaching and in-person masterclasses. They can be completed through Continuous Training or in an intensive BootCamp format in just a few weeks.<\/p><p>Upon completion of these programs, learners receive a diploma certified by the University of Sorbonne and can quickly enter the job market. Over 90% of our graduates secure employment after their training.<\/p><p>Therefore, DataScientest is the best way to learn how to master Matplotlib, Python, and various data science resources. Don&#8217;t wait any longer and explore our training programs today.<\/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<div class=\"elementor-element elementor-element-6e312515 e-flex e-con-boxed e-con\" data-id=\"6e312515\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4ec9e952 elementor-widget elementor-widget-heading\" data-id=\"4ec9e952\" 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<div class=\"elementor-element elementor-element-4caeccc1 elementor-widget elementor-widget-text-editor\" data-id=\"4caeccc1\" 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>Matplotlib allows you to create a wide variety of visualizations, but there are other libraries that can also create impressive visuals. Some of these libraries include Seaborn, Bokeh, and Ggplot, among others.<\/p><p>Data visualization is at the core of all the challenges addressed by Data Scientists and Data Analysts. To learn how to master these techniques, several modules are dedicated to Matplotlib, Bokeh, and <a href=\"https:\/\/datascientest.com\/en\/seaborn_and_data_visualization\">Seaborn in our Data Scientist and Data Analyst training programs.<\/a><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-55d9df74 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"55d9df74\" 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-2088336a\" data-id=\"2088336a\" 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-79734a93 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"79734a93\" 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\/en\/data-courses\">\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\">Data Training Courses<\/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<div class=\"elementor-element elementor-element-229cd218 e-flex e-con-boxed e-con\" data-id=\"229cd218\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Matplotlib is an open-source Python library for creating data visualizations. Discover everything you need to know: definition, how it works, challenges, and training&#8230; Data visualization is a key step in data analysis. After collecting, storing, and analyzing data, it&#8217;s essential to transform the results of these analyses into reports and graphical visualizations. This is because [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":171007,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"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>Matplotlib: Master Data Visualization in Python<\/title>\n<meta name=\"description\" content=\"Discover the power of Matplotlib, the versatile Python library for data visualization. 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