{"id":8320,"date":"2018-12-31T01:36:00","date_gmt":"2018-12-30T23:36:00","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?post_type=dt_lessons&#038;p=8320"},"modified":"2019-11-17T23:14:32","modified_gmt":"2019-11-17T21:14:32","slug":"ggplot-line-plot","status":"publish","type":"dt_lessons","link":"https:\/\/www.datanovia.com\/en\/lessons\/ggplot-line-plot\/","title":{"rendered":"GGPlot Line Plot"},"content":{"rendered":"<div id=\"rdoc\">\n<p>In a <strong>line plot<\/strong>, observations are ordered by x value and connected by a line.<\/p>\n<p>x value (for x axis) can be :<\/p>\n<ul>\n<li>date : for a time series data<\/li>\n<li>texts<\/li>\n<li>discrete numeric values<\/li>\n<li>continuous numeric values<\/li>\n<\/ul>\n<p>This article describes how to create a line plot using the ggplot2 R package<\/p>\n<p>You will learn how to:<\/p>\n<ul>\n<li>Create basic and grouped line plots<\/li>\n<li>Add points to a line plot<\/li>\n<li>Change the line types and colors by group<\/li>\n<\/ul>\n<p>Contents:<\/p>\n<div id=\"TOC\">\n<ul>\n<li><a href=\"#key-r-functions\">Key R functions<\/a><\/li>\n<li><a href=\"#data-preparation\">Data preparation<\/a><\/li>\n<li><a href=\"#loading-required-r-package\">Loading required R package<\/a><\/li>\n<li><a href=\"#basic-line-plots\">Basic line plots<\/a><\/li>\n<li><a href=\"#line-plot-with-multiple-groups\">Line plot with multiple groups<\/a><\/li>\n<li><a href=\"#line-plot-with-a-numeric-x-axis\">Line plot with a numeric x-axis<\/a><\/li>\n<li><a href=\"#line-plot-with-dates-on-x-axis-time-series\">Line plot with dates on x-axis: Time series<\/a><\/li>\n<li><a href=\"#conclusion\">Conclusion<\/a><\/li>\n<\/ul>\n<\/div>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div class='dt-sc-ico-content type1'><div class='custom-icon' ><a href='https:\/\/www.datanovia.com\/en\/product\/ggplot2-essentials-for-great-data-visualization-in-r\/' target='_blank'><span class='fa fa-book'><\/span><\/a><\/div><h4><a href='https:\/\/www.datanovia.com\/en\/product\/ggplot2-essentials-for-great-data-visualization-in-r\/' target='_blank'> Related Book <\/a><\/h4>GGPlot2 Essentials for Great Data Visualization in R<\/div>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div id=\"key-r-functions\" class=\"section level2\">\n<h2>Key R functions<\/h2>\n<ul>\n<li>Key functions:\n<ul>\n<li><code>geom_path()<\/code> connects the observations in the order in which they appear in the data.<\/li>\n<li><code>geom_line()<\/code> connects them in order of the variable on the x axis.<\/li>\n<li><code>geom_step()<\/code> creates a stairstep plot, highlighting exactly when changes occur.<\/li>\n<\/ul>\n<\/li>\n<li>Key arguments to customize the plot: alpha, color, linetype and size<\/li>\n<\/ul>\n<\/div>\n<div id=\"data-preparation\" class=\"section level2\">\n<h2>Data preparation<\/h2>\n<p>We\u2019ll create two data frames derived from the <code>ToothGrowth<\/code> datasets.<\/p>\n<pre class=\"r\"><code>df &lt;- data.frame(dose=c(\"D0.5\", \"D1\", \"D2\"),\r\n                len=c(4.2, 10, 29.5))\r\n\r\nhead(df, 4)<\/code><\/pre>\n<pre><code>##   dose  len\r\n## 1 D0.5  4.2\r\n## 2   D1 10.0\r\n## 3   D2 29.5<\/code><\/pre>\n<pre class=\"r\"><code>df2 &lt;- data.frame(supp=rep(c(\"VC\", \"OJ\"), each=3),\r\n                dose=rep(c(\"D0.5\", \"D1\", \"D2\"),2),\r\n                len=c(6.8, 15, 33, 4.2, 10, 29.5))\r\n\r\nhead(df2, 4)<\/code><\/pre>\n<pre><code>##   supp dose  len\r\n## 1   VC D0.5  6.8\r\n## 2   VC   D1 15.0\r\n## 3   VC   D2 33.0\r\n## 4   OJ D0.5  4.2<\/code><\/pre>\n<ul>\n<li><code>len<\/code>: Tooth length<\/li>\n<li><code>dose<\/code>: Dose in milligrams (0.5, 1, 2)<\/li>\n<li><code>supp<\/code>: Supplement type (VC or OJ)<\/li>\n<\/ul>\n<\/div>\n<div id=\"loading-required-r-package\" class=\"section level2\">\n<h2>Loading required R package<\/h2>\n<p>Load the ggplot2 package and set the default theme to <code>theme_classic()<\/code> with the legend at the top of the plot:<\/p>\n<pre class=\"r\"><code>library(ggplot2)\r\ntheme_set(\r\n  theme_classic() +\r\n    theme(legend.position = \"top\")\r\n  )<\/code><\/pre>\n<\/div>\n<div id=\"basic-line-plots\" class=\"section level2\">\n<h2>Basic line plots<\/h2>\n<pre class=\"r\"><code>p &lt;- ggplot(data = df, aes(x = dose, y = len, group = 1)) \r\n# Basic line plot with points\r\n p + geom_line() + geom_point()\r\n\r\n# Change line type and color\r\np + geom_line(linetype = \"dashed\", color = \"steelblue\")+\r\n  geom_point(color = \"steelblue\")\r\n\r\n# Use geom_step()\r\np + geom_step() + geom_point()<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-basic-data-visualization-1.png\" width=\"192\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-basic-data-visualization-2.png\" width=\"192\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-basic-data-visualization-3.png\" width=\"192\" \/><\/p>\n<p>Note that, the group aesthetic determines which cases are connected together.<\/p>\n<\/div>\n<div id=\"line-plot-with-multiple-groups\" class=\"section level2\">\n<h2>Line plot with multiple groups<\/h2>\n<p>In the graphs below, line types and point shapes are controlled automatically by the levels of the variable <code>supp<\/code>:<\/p>\n<pre class=\"r\"><code>p &lt;- ggplot(df2, aes(x = dose, y = len, group = supp))\r\n# Change line types and point shapes by groups\r\np + geom_line(aes(linetype = supp)) +\r\n    geom_point(aes(shape = supp))\r\n\r\n# Change line types, point shapes and colors\r\n# Change color manually: custom color\r\np + geom_line(aes(linetype = supp, color = supp))+\r\n    geom_point(aes(shape = supp, color = supp)) +\r\n    scale_color_manual(values=c(\"#999999\", \"#E69F00\"))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-multiple-groups-change-line-type-data-visualization-1.png\" width=\"307.2\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-multiple-groups-change-line-type-data-visualization-2.png\" width=\"307.2\" \/><\/p>\n<\/div>\n<div id=\"line-plot-with-a-numeric-x-axis\" class=\"section level2\">\n<h2>Line plot with a numeric x-axis<\/h2>\n<p>If the variable on x-axis is numeric, it can be useful to treat it as a continuous or a factor variable depending on what you want to do:<\/p>\n<pre class=\"r\"><code># Create some data\r\ndf3 &lt;- data.frame(supp=rep(c(\"VC\", \"OJ\"), each=3),\r\n                dose=rep(c(\"0.5\", \"1\", \"2\"),2),\r\n                len=c(6.8, 15, 33, 4.2, 10, 29.5))\r\nhead(df3)<\/code><\/pre>\n<pre><code>##   supp dose  len\r\n## 1   VC  0.5  6.8\r\n## 2   VC    1 15.0\r\n## 3   VC    2 33.0\r\n## 4   OJ  0.5  4.2\r\n## 5   OJ    1 10.0\r\n## 6   OJ    2 29.5<\/code><\/pre>\n<pre class=\"r\"><code># x axis treated as continuous variable\r\ndf3$dose &lt;- as.numeric(as.vector(df3$dose))\r\nggplot(data = df3, aes(x = dose, y = len, group = supp, color = supp)) +\r\n  geom_line() + geom_point()\r\n\r\n# Axis treated as discrete variable\r\ndf3$dose&lt;-as.factor(df3$dose)\r\nggplot(data=df3, aes(x = dose, y = len, group = supp, color = supp)) +\r\n  geom_line() + geom_point()<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-numeric-x-axis-data-visualization-1.png\" width=\"307.2\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-numeric-x-axis-data-visualization-2.png\" width=\"307.2\" \/><\/p>\n<\/div>\n<div id=\"line-plot-with-dates-on-x-axis-time-series\" class=\"section level2\">\n<h2>Line plot with dates on x-axis: Time series<\/h2>\n<p><code>economics<\/code> time series data sets are used :<\/p>\n<pre class=\"r\"><code>head(economics)<\/code><\/pre>\n<pre><code>## # A tibble: 6 x 6\r\n##   date         pce    pop psavert uempmed unemploy\r\n##   &lt;date&gt;     &lt;dbl&gt;  &lt;int&gt;   &lt;dbl&gt;   &lt;dbl&gt;    &lt;int&gt;\r\n## 1 1967-07-01  507. 198712    12.5     4.5     2944\r\n## 2 1967-08-01  510. 198911    12.5     4.7     2945\r\n## 3 1967-09-01  516. 199113    11.7     4.6     2958\r\n## 4 1967-10-01  513. 199311    12.5     4.9     3143\r\n## 5 1967-11-01  518. 199498    12.5     4.7     3066\r\n## 6 1967-12-01  526. 199657    12.1     4.8     3018<\/code><\/pre>\n<p>Plots :<\/p>\n<pre class=\"r\"><code># Basic line plot\r\nggplot(data=economics, aes(x = date, y = pop))+\r\n  geom_line()\r\n\r\n# Plot a subset of the data\r\nss &lt;- subset(economics, date &gt; as.Date(\"2006-1-1\"))\r\nggplot(data = ss, aes(x = date, y = pop)) + geom_line()<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-time-serie-data-data-visualization-1.png\" width=\"307.2\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-time-serie-data-data-visualization-2.png\" width=\"307.2\" \/><\/p>\n<p>Change line size :<\/p>\n<pre class=\"r\"><code>ggplot(data = economics, aes(x = date, y = pop)) +\r\n  geom_line(aes(size = unemploy\/pop))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-line-plot-time-serie-data-line-size-data-visualization-1.png\" width=\"480\" \/><\/p>\n<p>Plot multiple time series data:<\/p>\n<pre class=\"r\"><code>ggplot(economics, aes(x=date)) + \r\n  geom_line(aes(y = psavert), color = \"darkred\") + \r\n  geom_line(aes(y = uempmed), color=\"steelblue\", linetype=\"twodash\") <\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-multiple-time-series-1.png\" width=\"576\" \/><\/p>\n<pre class=\"r\"><code># Area plot\r\nggplot(economics, aes(x=date)) + \r\n  geom_area(aes(y = psavert), fill = \"#999999\", \r\n            color = \"#999999\", alpha=0.5) + \r\n  geom_area(aes(y = uempmed), fill = \"#E69F00\",\r\n            color = \"#E69F00\",  alpha=0.5) <\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggplot2\/figures\/009-ggplot-line-plot-multiple-time-series-2.png\" width=\"576\" \/><\/p>\n<\/div>\n<div id=\"conclusion\" class=\"section level2\">\n<h2>Conclusion<\/h2>\n<p>This article shows how to create line plots using the ggplot2 package.<\/p>\n<\/div>\n<\/div>\n<p><!--end rdoc--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In a line plot, observations are ordered by x value and connected by a line. This article describes how to create a line plot using the ggplot2 R package. You will learn how to: 1) Create basic and grouped line plots; 2) Add points to a line plot; 3) Change the line types and colors by group.<\/p>\n","protected":false},"author":1,"featured_media":7849,"parent":0,"menu_order":12,"comment_status":"open","ping_status":"closed","template":"","class_list":["post-8320","dt_lessons","type-dt_lessons","status-publish","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>GGPlot Line Plot Best Reference - Datanovia<\/title>\n<meta name=\"description\" content=\"This article describes how to create a line plot using the ggplot2 R package. 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