15 Tips to Customize lines in ggplot2 with element_line()
If you’ve ever had to plot a date onto a chart, you know that it’s not always easy. The standard way to plot is with a line, but sometimes it’s nice to be able to get fancy if you want to. The ggplot2 line plot function in R allows you to add marks along your line to customize the look of your chart. The plot is very flexible, but it requires a few lines of code.
ggplot2 is a plotting library for R that offers an intuitive and user friendly interface for those who are familiar with the concept of data visualisation. One of the things that make ggplot2 unique is its ability to create a number of options that are not normally available in other plotting libraries. One of the most basic examples is how the series can be generated, which can range from a single point to the entire grid. However, it can be harder to visualize what the line should look like when there are more than one series.
ggplot2 is one of the most popular packages for data visualization nowadays, with a burgeoning community of users. This post introduces you to the function element_line() , which can be used to customize the appearance of the line used in an element, such as a y-axis or a series.
As part of understanding and developing ggplot2’s thematic elements, we will focus on the anatomy of linear elements and explore 15 tips for managing them with ggplot2’s thematic system. With the ggplot2 theme system, we can manage the non-data elements of the graph built with ggplot2. The ggplot2 theme system comes with several element_ functions,
And we learned about element_text() in the previous post. In this tutorial, we will focus on the element_line() topic. We will learn 15 tips for a more subtle use of color, linetype for many line elements in a story.
Anatomy of element_line() in ggplot2
With element_line() we can modify all lines that do not belong to the data. We can do z. For example, customize the color of the x and y axis lines, make the axis lines look like arrows, add a second x axis at the top, etc. For a more specific example of controlling the color of the x-axis line, we will take the axis.line.x element as an argument to theme() and use element_line() to set the color of the x-axis line. Here is the element_line() function with the available arguments and their default selection. In this lesson we will focus on changing the color, size, line type and arrow using the theme() function. element_line( color = NULL, size = NULL, linetype = NULL, lineend = NULL, color = NULL, arrow = NULL, inherit.blank = FALSE ) In general, we can use element_line() to set up three groups of lines in the diagram. The first are the lines of the X and Y axes. The second are the lines connected to the ticks on the X and Y axis. And the third are the major and minor grid lines on the X and Y axes. The figure below shows the anatomy of the line elements and the keyword in ggplot2 that describes the element. Tips for customizing line elements in ggplot2 There are a total of 15 ways (at least?) to control the three main aspects/line items in a graph created with ggplot2. Here is the list of elements we can handle with element_lines().
Thematic elements to control X and Y axis lines.
- axis.line.x: to define the label/name of the x axis
- axis.line.x.top: to define the label/title of the x axis
- axis.line.x.bottom: to define the label/title of the x axis
- axis.line.y : to define the y-axis line
- axis.line.y.left: to position the line of the y-axis to the left
- as.line.y.right : to define the secondary line of the y-axis to the right
Thematic elements for drawing control of X and Y axes
- axis.character: to define the characters on the X and Y axes
- axis.ticks.x : to define the characters of the X axis
- axis.ticks.y : to define the characters on the Y axis
Thematic elements for controlling the principal and secondary grid lines of the X and Y axes
- panel.grid.major: to define the main grid lines on the x and y axes.
- panel.grid.minor: to define the secondary grid lines on the x and y axes
- panel.grid.major.x : to define the outlines of the grid on the x-axis
- panel.grid.major.y : to define the major lines of the grid on the y-axis
- panel.grid.minor.x : to define the secondary lines of the grid on the x-axis
- panel.grid.minor.y : to define the secondary grid lines on the y-axis
Let’s start by creating a scatterplot with ggplot2 with the usual text annotations such as title, subtitle, caption and labels. library(tidyverse) library(palmerpenguins) theme_set(theme_bw(16)) We use the Palmer penguin data to create a scatter diagram. Check labs() to add variations to the diagram. We use the theme_set() option to create the image in a black and white theme with a predefined font size. p <- penguins %>% drop_na() %>% ggplot(aes(x = length_last_mm, y = length_ count_mm, color = view, shape = gender))+ geom_point()+ theme(legend.position = none) p And this is what the scatter diagram looks like. We saved the code to create the story as a variable and use it to customize the 10 different text elements of the ggplot2 theme with element_text(). Simple point cloud with ggplot2
1. Setting the x axis line in ggplot2 with axis.line.x
p + theme(axis.line.x = element_line(linetype = dashed line, color = red, size = 2, arrow = grid::arrow()) ggsave(customize_axis_line_x_element_line_ggplot2.png) Adjust X axis line with element_line()
2. Setting the x axis line in ggplot2 with axis.line.x.bottom
p + theme(axis.line.x.bottom = element_line(linetype = dashed line, color = blue, size = 2, arrow = grid::arrow()) ggsave(customize_axis_line_x_bottom_element_line_ggplot2.png) Adjust X-axis line to x-bottom line
3. ggplot2 Set the top of the x axis with axis.line.x.top
p + theme(axis.line.x.top = element_line(linetype = dashed line, color = blue, size = 2, arrow = grid::arrow()))+ guides(x.sec=axis) ggsave(customize_axis_line_x_top_element_line_ggplot2.png) Adjustment of the top line of the x axis of ggplot2 with axis.line.x.top
4. Define the line of the Y axis with axis.line.y
Subject : axis.line.y p + Subject(axis.line.y = element_line(color = red, size = 0.5, arrow = grid::arrow()) Adjust the y-axis line with axis.line.y
5. Move the line of the Y axis to the left with axis.line.y.left
# Object: axis.line.y.left p + theme(axis.line.y.left = element_line(linetype = dashed line, color = blue, size = 2, arrow = grid::arrow()) ggsave(customize_axis_line_y_left_element_line_ggplot2.png) Adjust the Y axis line on the left side with element_line()
6. Move the secondary line of the Y axis to the right with axis.line.y.right
p + theme(axis.line.y.right = element_line( color = blue))+ guides(y.sec = axis) ggsave(customize_axis_line_y_right_ element_line_ggplot2.png) Secondary Y-axis adjustment on the right side
7. Defining X and Y attributes with axis.ticks
p + theme(axis.ticks = element_line(color = red, size = 2)) ggsave(customize_axis_ticks_element_line_ggplot2.png) Ticks axle adaptation ggplot2
8. Set up X mark with axis.ticks.x
p+ theme(axis.ticks.x = element_line(color = red, size = 4)) ggsave(customize_axis_ticks_x_element_line_ggplot2.png) Modify X-sign with axis.ticks.x
9. Defining Y characters with axis.ticks.y
p+ theme(axis.ticks.y = element_line(color = red, size = 4)) ggsave(customize_axis_ticks_y_element_line_ggplot2.png) Adjusting ticks Y axis with axis.ticks.y
10. Configuring the grid major with Panel.grid.major
p + theme(panel.grid.major = element_line(color = blue, size = 1)) ggsave(customize_panel_grid_major_element_line_ggplot2.png) Adjust gridlines with panel.grid.major
11. Configure the sublines of the grid with panel.grid.major
## panel.grid.minor p+ theme(panel.grid.minor = element_line(color = steelblue4, size = 1, linetype = dotted)) ggsave(customize_panel_grid_minor_element_line_ggplot2.png) Adjustment of secondary grid lines
12. Configure the size of the y-axis grid with panel.grid.major.y
p+ theme(panel.grid.major.y = element_line(color = purple, size = 1, linetype = dotted)) ggsave(customize_panel_grid_major_y_element_line_ggplot2.png) Y-axis adjustment of principal gridlines
13. Configure the small y-axis grid with panel.grid.minor.y
p+ theme(panel.grid.minor.y = element_line(color = purple, size = 1, linetype = dotted)) ggsave(customize_panel_grid_minor_y_element_line_ggplot2.png) Adjust grid side lines to Y axis
14. Set the major grid lines on the x-axis with panel.grid.major.x
p+ theme(panel.grid.major.x = element_line(color = purple, size = 1, linetype = dotted)) ggsave(customize_panel_grid_major_x_element_line_ggplot2.png) Adjusting the headline on the X axis
15. Set small grid lines on the x axis with panel.grid.minor.x
#theme panel.grid.minor.x p+ theme(panel.grid.minor.x = element_line(color = purple, size = 1, linetype = dotted)) ggsave(customize_panel_grid_minor_x_element_line_ggplot2.png) Adjust small panel grid x element_line() The post 15 tips for setting up lines in ggplot2 with element_line() appeared first on .This is the second part of the tutorial series on how to create enhanced output with ggplot2. The first part was about how to create a bar chart using the ggplot2 software. Now, we will learn how to customize the ggplot2 output. The ggplot2 package is built to enable the user to move around the plot and change the look-and-feel of the plots in a way that is similar to previous versions. You can change the look and feel of the plot by adding elements to the ggplot2 object.. Read more about change legend title ggplot2 and let us know what you think.
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