{"id":166377,"date":"2023-01-30T12:27:12","date_gmt":"2023-01-30T11:27:12","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=166377"},"modified":"2023-10-30T18:23:12","modified_gmt":"2023-10-30T17:23:12","slug":"seaborn_and_data_visualization","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/seaborn_and_data_visualization","title":{"rendered":"Seaborn : all about the Data Visualization tool in Python"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"166377\" class=\"elementor elementor-166377\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-74c3964 e-flex e-con-boxed e-con\" data-id=\"74c3964\" 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-9b35037 elementor-widget elementor-widget-text-editor\" data-id=\"9b35037\" 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><b>Seaborn is a Data Visualization tool in Python language. Discover all you need to know: presentation, use cases, benefits, training\u2026<\/b><\/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-524fec2 elementor-widget elementor-widget-text-editor\" data-id=\"524fec2\" 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;\">Data Visualization is a technique allowing Data Scientists to transform raw data into graphs and charts. Such illustrations facilitate the reading and understanding of data, which is why Dataviz is very useful.<\/span><\/p><p><span style=\"font-weight: 400;\">There are many &#8220;<\/span><b>no-code<\/b><span style=\"font-weight: 400;\">&#8221; tools to create <\/span><b>data visualizations<\/b><span style=\"font-weight: 400;\">: Tableau, Power BI, and ChartBlocks&#8230; however, as an alternative, it is also possible to opt for the <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/python-the-most-popular-programming-language\">Python language<\/a><\/strong><\/span><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">This requires <\/span><b>programming skills<\/b><span style=\"font-weight: 400;\"> but offers complete freedom. Using Python, it is possible to manipulate, transform and create data visualizations. Many <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/how-to-become-a-data-scientist\">data scientists<\/a><\/strong><\/span><span style=\"font-weight: 400;\"> are turning to this solution.<\/span><\/p><p><span style=\"font-weight: 400;\">One of the reasons why Python is the <\/span><b>best choice<\/b><span style=\"font-weight: 400;\"> for <\/span><a href=\"https:\/\/datascientest.com\/en\/data-science-definition-issues-and-use-cases\"><span style=\"font-weight: 400;\"><span style=\"text-decoration: underline;\"><strong>Data Science<\/strong><\/span><\/span><\/a><span style=\"font-weight: 400;\"> is its vast ecosystem of libraries. There are many Python libraries for manipulating data: numpy, pandas, matplotlib, and TensorFlow&#8230;<\/span><\/p><p><span style=\"font-weight: 400;\">While Matplotlib is <\/span><b>very popular<\/b><span style=\"font-weight: 400;\"> for creating data visualizations, it can be complex to use. Some developers have created a new library based on Matplotlib: <\/span><b>Seaborn<\/b><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\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2427c3b e-flex e-con-boxed e-con\" data-id=\"2427c3b\" 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-2bb1242 elementor-widget elementor-widget-heading\" data-id=\"2bb1242\" 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><h3 class=\"elementor-heading-title elementor-size-default\">What is Seaborn?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6dd8cb8 elementor-widget elementor-widget-text-editor\" data-id=\"6dd8cb8\" 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;\">Seaborn is a library for <\/span><b>creating statistical graphs in Python<\/b><span style=\"font-weight: 400;\">. It is based on z<\/span><b>Matplotlib<\/b><span style=\"font-weight: 400;\"> and integrates with <\/span><b>Pandas&#8217; structures<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">This library is <\/span><b>as powerful as Matplotlib<\/b><span style=\"font-weight: 400;\"> but brings simplicity and new features. It allows us to quickly explore and understand data.<\/span><\/p><p><span style=\"font-weight: 400;\">Entire <strong>data frames<\/strong> can be captured, and the internal functions for <strong>semantic mapping<\/strong> and statistical aggregation allow the data to be converted into graphical visualizations.<\/span><\/p><p><span style=\"font-weight: 400;\">All the complexity of Matplotlib is <\/span><b>abstracted<\/b><span style=\"font-weight: 400;\"> by Seaborn. However, it is possible to create graphs that meet all your needs and requirements.<\/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-20550a5 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"20550a5\" 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-md\" 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 to use Seaborn<\/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<div class=\"elementor-element elementor-element-f0e9652 e-flex e-con-boxed e-con\" data-id=\"f0e9652\" 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-2181c56 elementor-widget elementor-widget-heading\" data-id=\"2181c56\" 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\">Seaborn and the different types of Dataviz\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8b52c78 elementor-widget elementor-widget-text-editor\" data-id=\"8b52c78\" 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;\">Seaborn provides different styles and default color palettes to <\/span><b>create more attractive graphics<\/b><span style=\"font-weight: 400;\">. The different types of visualizations allow you to highlight the relationships between data. These can be numerical variables or groups, classes, or divisions.<\/span><\/p><p><span style=\"font-weight: 400;\"><strong>Relational graphs<\/strong> are used to understand the relationships between two variables, while categorical graphs are used to visualize variables categorized by category.<\/span><\/p><p><span style=\"font-weight: 400;\">Distribution graphs are used to <\/span><b>examine univariate or bivariate distributions<\/b><span style=\"font-weight: 400;\">. Regression graphs add a visual guide to highlight patterns in a data set for exploratory analyses.<\/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-d0fd8b5 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"d0fd8b5\" 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\t\t\t<img decoding=\"async\" width=\"800\" height=\"370\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/01\/seaborn-graph.webp\" class=\"attachment-large size-large wp-image-166379\" alt=\"seaborn_graph\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/01\/seaborn-graph.webp 960w, https:\/\/datascientest.com\/en\/files\/2023\/01\/seaborn-graph-300x139.webp 300w, https:\/\/datascientest.com\/en\/files\/2023\/01\/seaborn-graph-768x355.webp 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\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-8a41ff7 elementor-widget elementor-widget-spacer\" data-id=\"8a41ff7\" data-element_type=\"widget\" data-widget_type=\"spacer.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-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\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<div class=\"elementor-element elementor-element-080c121 e-flex e-con-boxed e-con\" data-id=\"080c121\" 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-5244a1a elementor-widget elementor-widget-heading\" data-id=\"5244a1a\" 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 benefits of Seaborn?\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f699b55 elementor-widget elementor-widget-text-editor\" data-id=\"f699b55\" 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;\">The Seaborn library offers <strong>several major advantages<\/strong>. It provides different types of <\/span><b>visualizations<\/b><span style=\"font-weight: 400;\">. Its syntax is reduced and it offers very attractive default themes.<\/span><\/p><p><span style=\"font-weight: 400;\">It is an ideal tool for <\/span><b>statistical visualization<\/b><span style=\"font-weight: 400;\">. It is used to summarize data in visualizations and data distribution.<\/span><\/p><p><span style=\"font-weight: 400;\">In addition, <\/span><b>Seaborn<\/b><span style=\"font-weight: 400;\"> is better integrated than Matplotlib for working with Pandas data frames. Finally, it is an extension of Matplotlib to create beautiful graphs using <\/span><b>Python <\/b><span style=\"font-weight: 400;\">through a more direct set of methods.<\/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-b3bc9e2 elementor-widget elementor-widget-spacer\" data-id=\"b3bc9e2\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\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<div class=\"elementor-element elementor-element-7baea55 e-flex e-con-boxed e-con\" data-id=\"7baea55\" 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-f44f2fb elementor-widget elementor-widget-heading\" data-id=\"f44f2fb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Seaborn vs Matplotlib: which one to use?\n<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c5bef9a elementor-widget elementor-widget-text-editor\" data-id=\"c5bef9a\" 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;\">Matplotlib and Seaborn are the <\/span><b>two most popular Python tools<\/b><span style=\"font-weight: 400;\"> for data visualization. Each one has advantages and disadvantages.<\/span><\/p><p><span style=\"font-weight: 400;\">Matplotlib is primarily used for <\/span><b>basic graphing<\/b><span style=\"font-weight: 400;\">, while Seaborn offers many default themes and a wide variety of schemas for statistical visualization.<\/span><\/p><p><span style=\"font-weight: 400;\">In addition, Seaborn <\/span><b>automates<\/b><span style=\"font-weight: 400;\"> the creation of multiple figures. This is an advantage, although it can lead to problems with memory usage. Another advantage of Seaborn is the tight integration with Pandas and its <\/span><b>Data Frames<\/b><span style=\"font-weight: 400;\">, although Matplotlib is also integrated with Pandas and <\/span><b>NumPy<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">On the other hand, Matplotlib offers <\/span><b>increased flexibility<\/b><span style=\"font-weight: 400;\"> in terms of customization and sometimes superior performance. It may therefore be a better option in some situations.<\/span><\/p><p><span style=\"font-weight: 400;\">Overall, Seaborn is the best choice of DataViz tool for statistical data visualizations. On the other hand, Matplotlib is better for customization needs.<\/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-5b2d15f elementor-widget elementor-widget-spacer\" data-id=\"5b2d15f\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\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<div class=\"elementor-element elementor-element-fef14c5 e-flex e-con-boxed e-con\" data-id=\"fef14c5\" 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-29d0c8b elementor-widget elementor-widget-heading\" data-id=\"29d0c8b\" 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\">Why and how to learn to use Seaborn? \n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d2af260 elementor-widget elementor-widget-text-editor\" data-id=\"d2af260\" 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;\">Data visualization is widely used in all business sectors. Therefore, mastering a DataViz tool is a valuable and coveted skill.<\/span><\/p><p><b>DataScientest&#8217;s data visualization training<\/b><span style=\"font-weight: 400;\"> allows you to acquire this mastery. Both Matplotlib and Seaborn are included in the Data Visualization module of our <\/span><a href=\"https:\/\/datascientest.com\/en\/data-analyst-course\"><span style=\"font-weight: 400;\"><span style=\"text-decoration: underline;\"><strong>Data Analyst<\/strong><\/span><\/span><\/a><span style=\"font-weight: 400;\">, <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/data-scientist-course\">Data Scientist<\/a><\/strong><\/span><span style=\"font-weight: 400;\">, and <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/data-management-course\">Data Management<\/a><\/strong><\/span><span style=\"font-weight: 400;\"> courses.<\/span><\/p><p><span style=\"font-weight: 400;\">Through these courses, you can acquire all the skills required to work as an analyst, manager, or data scientist. In addition to DataViz, you will also learn programming, database management, <\/span><b>Machine Learning, <\/b><span style=\"font-weight: 400;\">and <\/span><b>Deep Learning<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Our various training courses adopt an innovative and beneficial <\/span><b>Blended Learning approach<\/b><span style=\"font-weight: 400;\">, combining face-to-face and distance learning. They can be done in Continuing Education, or in BootCamp in just a few weeks.<\/span><\/p><p><span style=\"font-weight: 400;\">At the end of the course, learners receive a degree certified by the <\/span><b>Sorbonne University<\/b><span style=\"font-weight: 400;\">. Among the alumni, 93% found a job immediately after completing the training. Don&#8217;t wait any longer and discover our different training courses to learn how to use <\/span><b>Seaborn<\/b><span style=\"font-weight: 400;\"> and all the <\/span><b>Data Science tools!<\/b><\/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-707a5b0 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"707a5b0\" 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-md\" 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\">Start a Data Science training<\/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<div class=\"elementor-element elementor-element-7ea298c e-flex e-con-boxed e-con\" data-id=\"7ea298c\" 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-f4b5880 elementor-widget elementor-widget-text-editor\" data-id=\"f4b5880\" 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;\">You know everything about Seaborn. Check out our introduction to <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/data-science-definition-issues-and-use-cases\">Data Science<\/a><\/strong><\/span><span style=\"font-weight: 400;\">, and our guide to getting started with <\/span><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\"><span style=\"font-weight: 400;\"><span style=\"text-decoration: underline;\"><strong>Machine Learning<\/strong><\/span><\/span><\/a><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\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-db8270a e-flex e-con-boxed e-con\" data-id=\"db8270a\" 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-7dd9847 elementor-widget elementor-widget-html\" data-id=\"7dd9847\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is Seaborn?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Seaborn is a library for creating statistical graphs in Python. 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Discover all you need to know: presentation, use cases, benefits, training\u2026 Data Visualization is a technique allowing Data Scientists to transform raw data into graphs and charts. Such illustrations facilitate the reading and understanding of data, which is why Dataviz is very useful. There are many [&hellip;]<\/p>\n","protected":false},"author":63,"featured_media":58184,"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>Seaborn : all about the Data Visualization tool in Python<\/title>\n<meta name=\"description\" content=\"Seaborn is a Data Visualization tool in Python language. 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