{"id":175266,"date":"2023-12-17T10:05:29","date_gmt":"2023-12-17T09:05:29","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=175266"},"modified":"2023-12-17T10:09:53","modified_gmt":"2023-12-17T09:09:53","slug":"ggplot-everything-you-need-to-know-about-the-r-data-visualization-library","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/ggplot-everything-you-need-to-know-about-the-r-data-visualization-library","title":{"rendered":"ggplot : Everything you need to know about the R data visualization library"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"175266\" class=\"elementor elementor-175266\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4404b46 e-flex e-con-boxed e-con\" data-id=\"4404b46\" 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-248bdc6 elementor-widget elementor-widget-heading\" data-id=\"248bdc6\" 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\">In this article, we will explore the fundamental concepts of ggplot and learn how to create a chart using this library to effectively present your data.<\/h2>\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-137e531 e-flex e-con-boxed e-con\" data-id=\"137e531\" 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-b06f439 elementor-widget elementor-widget-heading\" data-id=\"b06f439\" 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 ggplot?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4329b9b elementor-widget elementor-widget-text-editor\" data-id=\"4329b9b\" 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><strong>ggplot<\/strong> is a<a href=\"https:\/\/datascientest.com\/en\/google-data-studio-introduction-to-googles-dataviz-tool\"> data visualization library<\/a> in R, developed by Hadley Wickham in 2005. This library is based on the grammar of graphics, which allows describing graphs in terms of basic components such as axes, legends, or labels.<\/p><p>With ggplot, you can think of a graph as a series of layers that stack up to produce the final graph. Each graph layer can be added using the + function and can include elements such as points, lines, bars, scatterplots, histograms, boxplots, text, and much more.<\/p><p>To create a graph using the layering system in ggplot, start by specifying the data and the variables to use for the x and y axes, then gradually add additional graph layers.<\/p><p>One of the most commonly used graph layers involves geometric functions using the appropriate geom_ functions.<\/p><p>Here are some examples of geometric function graph layers:<\/p><p>&#8211; geom_point(): adds points to the graph<br \/>&#8211; geom_line(): adds a line to the graph<br \/>&#8211; geom_bar(): adds a bar chart to the graph<br \/>&#8211; geom_histogram(): adds a histogram to the graph<br \/>&#8211; geom_boxplot(): adds a boxplot to the graph<br \/>&#8211; geom_text(): adds text to the graph<\/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-d5c74a4 elementor-widget elementor-widget-text-editor\" data-id=\"d5c74a4\" 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>Please note that each graph layer can be <strong>customized using function-specific options.<\/strong><\/p><p>To understand this principle, let&#8217;s take a step-by-step look at how to create the following chart with the Iris dataset.<\/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-589ded9 elementor-widget elementor-widget-image\" data-id=\"589ded9\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image6.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-c8e11a8 elementor-widget elementor-widget-text-editor\" data-id=\"c8e11a8\" 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>Here is an overview of our data:<\/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-ab7ab47 elementor-widget elementor-widget-image\" data-id=\"ab7ab47\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image4-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-a289ff8 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"a289ff8\" 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-analyst-course\">\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 ggplot<\/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<div class=\"elementor-element elementor-element-3c3a926 elementor-widget elementor-widget-heading\" data-id=\"3c3a926\" 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\">Step 1: Load the ggplot library and read the csv file <\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e9f622e elementor-widget elementor-widget-text-editor\" data-id=\"e9f622e\" 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>library(ggplot2)<\/p><p>iris &lt;- read.csv(&#8220;species.csv&#8221;)<\/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-790d155 elementor-widget elementor-widget-heading\" data-id=\"790d155\" 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\">Step 2: Create the ggplot object<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-192be71 elementor-widget elementor-widget-text-editor\" data-id=\"192be71\" 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<pre>p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width))<\/pre>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c583eb elementor-widget elementor-widget-image\" data-id=\"3c583eb\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image5.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-e592ef8 elementor-widget elementor-widget-text-editor\" data-id=\"e592ef8\" 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 <strong>line creates a ggplot<\/strong> object named p, which represents the iris dataset with the variables Sepal.Length, Petal.Length, Sepal.Width and Petal.Width. The values of Sepal.Length and Petal.Length are added to create the x-axis, while the values of Sepal.Width and Petal.Width are added to create the y-axis.<\/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-4e27812 elementor-widget elementor-widget-heading\" data-id=\"4e27812\" 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\">Step 3: Creating a point cloud<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c01b8ad elementor-widget elementor-widget-text-editor\" data-id=\"c01b8ad\" 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<pre><span style=\"font-weight: 400;\">p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width))\u00a0<\/span><\/pre><p><span style=\"font-weight: 400;\">+ geom_jitter(aes(color = Species), alpha =0.6, width = 1)<\/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-544864f elementor-widget elementor-widget-image\" data-id=\"544864f\" 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\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image3-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-834e368 elementor-widget elementor-widget-text-editor\" data-id=\"834e368\" 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 line adds a point cloud (geom_jitter) to the graph. The points are colored according to the Species variable and have a transparency of 0.6 and a width of 1.<\/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-78e0d35 elementor-widget elementor-widget-heading\" data-id=\"78e0d35\" 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\">Step 4: Create a linear regression<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cce8326 elementor-widget elementor-widget-text-editor\" data-id=\"cce8326\" 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<pre><span style=\"font-weight: 400;\">p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width))\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_jitter(aes(color = Species), alpha =0.6, width = 1)<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_smooth(method='lm', se = FALSE)<\/span><\/pre>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aeb9bc3 elementor-widget elementor-widget-image\" data-id=\"aeb9bc3\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image7.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-b9fcb3b elementor-widget elementor-widget-text-editor\" data-id=\"b9fcb3b\" 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<a href=\"https:\/\/datascientest.com\/en\/classification-algorithms-definition-and-main-models\"> line adds a regression line layer<\/a> (geom_smooth) to the graph. The modeling method used is linear regression (method=&#8217;lm&#8217;). The se = FALSE option is used to avoid displaying confidence intervals.<\/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-1db55a1 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"1db55a1\" 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-analyst-course\">\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 master ggplot with DataScientest<\/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<div class=\"elementor-element elementor-element-9ea4627 elementor-widget elementor-widget-heading\" data-id=\"9ea4627\" 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\">Step 5: Separate the graph into sub-sections<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-51ff81a elementor-widget elementor-widget-text-editor\" data-id=\"51ff81a\" 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<pre><span style=\"font-weight: 400;\">p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width))<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_jitter(aes(color = Species), alpha =0.6, width = 1)<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_smooth(method='lm', se = FALSE)\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ facet_wrap(~Species)<\/span><\/pre>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-19b80fa elementor-widget elementor-widget-image\" data-id=\"19b80fa\" 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\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image2-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-c732931 elementor-widget elementor-widget-text-editor\" data-id=\"c732931\" 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 line divides the graph into panels (facet_wrap) according to the Species variable. This allows you to see the relationship between variables for each species separately.<\/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-8437a2b elementor-widget elementor-widget-heading\" data-id=\"8437a2b\" 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\">Step 6: Add labels<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4e2b0e1 elementor-widget elementor-widget-text-editor\" data-id=\"4e2b0e1\" 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<pre><span style=\"font-weight: 400;\">p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width)) + geom_jitter(aes(color = Species), alpha =0.6, width = 1)<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_smooth(method='lm', se = FALSE)\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ facet_wrap(~Species)\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ labs(title = \"Relation Length\/Width\", x= \"Length\", y= \"Width\")<\/span><\/pre>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1b980ba elementor-widget elementor-widget-image\" data-id=\"1b980ba\" 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\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-99d4ab9 elementor-widget elementor-widget-text-editor\" data-id=\"99d4ab9\" 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 line adds title and axis labels to the graph. The title is &#8220;Relation Length\/Width&#8221;, the x-axis is labelled &#8220;Length&#8221; and the y-axis is labelled &#8220;Width&#8221;.<\/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-a9d3fc5 elementor-widget elementor-widget-heading\" data-id=\"a9d3fc5\" 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\">Step 7: Adding the theme<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0b29507 elementor-widget elementor-widget-text-editor\" data-id=\"0b29507\" 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<pre><span style=\"font-weight: 400;\">p = ggplot(iris, aes(x=Sepal.Length + Petal.Length, y = Sepal.Width + Petal.Width))\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_jitter(aes(color = Species), alpha =0.6, width = 1)<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ geom_smooth(method='lm', se = FALSE)\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ facet_wrap(~Species)\u00a0<\/span><br \/><br \/><span style=\"font-weight: 400;\">+ labs(title = \"Relation Length\/Width\", x= \"Length\", y= \"Width\")<\/span><br \/><br \/><span style=\"font-weight: 400;\">+\u00a0 theme(plot.background = element_rect(fill = '#E8EAF6', color = \"#08104E\", size = 3))<\/span><\/pre>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ae6a021 elementor-widget elementor-widget-image\" data-id=\"ae6a021\" 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\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/image6-1.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\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-3140592 elementor-widget elementor-widget-text-editor\" data-id=\"3140592\" 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 <strong>line defines a custom theme<\/strong> for the graphic using the theme() function. The argument plot.background is used to define the background of the graphic. The element_rect() function is used to create a rectangle with a fill color of &#8216;#E8EAF6&#8217;, a border color of &#8220;#08104E&#8221; and a thickness of 3 pixels.<\/p><p>This code creates a 7-step ggplot graph showing the relationship between sepal and petal length and width for different iris flower species. Points are colored according to species, and a linear regression is fitted for each species.<\/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-be8f595 e-flex e-con-boxed e-con\" data-id=\"be8f595\" 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-dfcc8a2 elementor-widget elementor-widget-heading\" data-id=\"dfcc8a2\" 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 do I need to know about ggplot?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aca806a elementor-widget elementor-widget-text-editor\" data-id=\"aca806a\" 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>ggplot is a library for<a href=\"https:\/\/datascientest.com\/en\/altair-everything-you-need-to-know-about-this-statistical-visualization-library\"> data visualization<\/a> in R. Thanks to its flexible layering system, we can create complex custom graphics by gradually adding additional graphic components.<\/p><p>If you&#8217;re interested in data visualization, don&#8217;t hesitate to join our Data Analyst training 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-b8162f9 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"b8162f9\" 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-analyst-course\">\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\">Register for our Data Analyst 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-bb65414 e-flex e-con-boxed e-con\" data-id=\"bb65414\" 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-1f0be47 elementor-widget elementor-widget-html\" data-id=\"1f0be47\" 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\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"What is ggplot?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Ggplot is a data visualization library in R, developed by Hadley Wickham in 2005. The library is based on graph grammar, which allows graphs to be described in terms of basic components such as axes, legends and labels.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What do I need to know about ggplot?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"ggplot is a library for data visualization in R. Thanks to its flexible layering system, we can create customized, complex graphs by gradually adding additional graphical components.\"\n    }\n  }]\n}\n<\/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\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>In this article, we will explore the fundamental concepts of ggplot and learn how to create a chart using this library to effectively present your data. What is ggplot? ggplot is a data visualization library in R, developed by Hadley Wickham in 2005. This library is based on the grammar of graphics, which allows describing [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":175273,"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>ggplot : Everything you need to know about the R data visualization library<\/title>\n<meta name=\"description\" content=\"Dive into ggplot, the powerful R data visualization library, and learn how to create stunning and informative data visualizations with ease. 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