GGPlot Stripchart Best Reference - Datanovia (2024)

GGPlot Stripchart

10 mins

Data Visualization using GGPlot2

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Stripcharts are also known as one dimensional scatter plots. These plots are suitable compared to box plots when sample sizes are small.

This article describes how to create and customize Stripcharts using the ggplot2 R package.



Contents:

  • Key R functions
  • Data preparation
  • Loading required R package
  • Basic stripcharts
  • Combine with box plots and violin plots
  • Create a stripchart with multiple groups
  • Conclusion

Related Book

GGPlot2 Essentials for Great Data Visualization in R

Key R functions

  • Key function: geom_jitter()
  • key arguments: color, fill, size, shape. Changes points color, fill, size and shape

Data preparation

  • Demo dataset: ToothGrowth
    • Continuous variable: len (tooth length). Used on y-axis
    • Grouping variable: dose (dose levels of vitamin C: 0.5, 1, and 2 mg/day). Used on x-axis.

First, convert the variable dose from a numeric to a discrete factor variable:

data("ToothGrowth")ToothGrowth$dose <- as.factor(ToothGrowth$dose)head(ToothGrowth, 3)
## len supp dose## 1 4.2 VC 0.5## 2 11.5 VC 0.5## 3 7.3 VC 0.5

Loading required R package

Load the ggplot2 package and set the default theme to theme_classic() with the legend at the top of the plot:

library(ggplot2)theme_set( theme_classic() + theme(legend.position = "top") )

Basic stripcharts

We start by initiating a plot named e, then we’ll add layers. The following R code creates stripcharts combined with summary statistics (mean +/- SD), boxplots and violin plots.

  • Change points shape and color by groups
  • Adjust the degree of jittering: position_jitter(0.2)
  • Add summary statistics:
# Initiate a ggplote <- ggplot(ToothGrowth, aes(x = dose, y = len))# Stripcharts with summary statistics# Change color by dose groupse + geom_jitter(aes(shape = dose, color = dose), position = position_jitter(0.2), size = 1.2) + stat_summary(aes(color = dose), size = 0.4, fun.data="mean_sdl", fun.args = list(mult=1))+ scale_color_manual(values = c("#00AFBB", "#E7B800", "#FC4E07"))

GGPlot Stripchart Best Reference - Datanovia (1)

The function mean_sdl is used for adding mean and standard deviation. It computes the mean plus or minus a constant times the standard deviation. In the R code above, the constant is specified using the argument mult (mult = 1). By default mult = 2. The mean +/- SD can be added as a crossbar or a pointrange.

Combine with box plots and violin plots

# Combine with box plote + geom_boxplot() + geom_jitter(position = position_jitter(0.2)) # Strip chart + violin plot + stat summarye + geom_violin(trim = FALSE) + geom_jitter(position = position_jitter(0.2)) + stat_summary(fun.data="mean_sdl", fun.args = list(mult=1), color = "red")

GGPlot Stripchart Best Reference - Datanovia (2)GGPlot Stripchart Best Reference - Datanovia (3)

Create a stripchart with multiple groups

The R code is similar to what we have seen in dot plots section. However, to create dodged jitter points, you should use the function position_jitterdodge() instead of position_dodge().

e + geom_jitter( aes(shape = supp, color = supp), size = 1.2, position = position_jitterdodge(jitter.width = 0.2, dodge.width = 0.8) ) + stat_summary( aes(color = supp), fun.data="mean_sdl", fun.args = list(mult=1), size = 0.4, position = position_dodge(0.8) )+ scale_color_manual(values = c("#00AFBB", "#E7B800"))

GGPlot Stripchart Best Reference - Datanovia (4)

Conclusion

This article describes how to create a stripchart using the ggplot2 package.



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Course Curriculum

  • Introduction to GGPlot2

    20 mins

  • GGPlot Scatter Plot

    15 mins

  • GGPlot Boxplot

    15 mins

  • GGPlot Violin Plot

    10 mins

  • GGPlot Dot Plot

    15 mins

  • GGPlot Stripchart

    10 mins

  • GGPlot Line Plot

    15 mins

  • GGPlot Barplot

    10 mins

  • GGPlot Error Bars

    15 mins

  • GGPlot Density Plot

    10 mins

  • GGPlot Histogram

    10 mins

  • GGPLOT QQ Plot

    10 mins

  • GGPlot ECDF

    10 mins

  • Combine Multiple GGPlots into a Figure

    15 mins

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GGPlot Stripchart Best Reference - Datanovia (6)

Alboukadel Kassambara
Role : Founder of Datanovia
  • Website : https://www.datanovia.com/en
  • Experience : >10 years
  • Specialist in : Bioinformatics and Cancer Biology

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GGPlot Stripchart Best Reference - Datanovia (2024)

FAQs

How do I make my ggplot graph look better? ›

Using Themes

One way to improve your ggplot visualizations is by leveraging themes. Themes provide a consistent and professional appearance to your plots by adjusting elements such as grid lines, axis labels, and backgrounds.

What is the best format to save ggplot? ›

If you are creating plots with ggplot, the best option is to use ggsave() and save the file with an EMF, PDF, or PNG extension, depending on how you would like to use it: Microsoft Word or PowerPoint (EMF), LaTeX editors (PDF), or other uses including sharing with colleagues (PDF or PNG).

What does errorbar mean in ggplot? ›

Error Bars can be applied to graphs such as, Dot Plots, Barplots or Line Graphs, to provide an additional layer of detail on the presented data. Generally, Error bars are used to show either the standard deviation, standard error, confidence intervals or interquartile range.

How to make a barplot in R with ggplot? ›

It follows those steps:
  1. always start by calling the ggplot() function.
  2. then specify the data object. It has to be a data frame. ...
  3. then come thes aesthetics, set in the aes() function: set the categoric variable for the X axis, use the numeric for the Y axis.
  4. finally call geom_bar() .

Why ggplot is better than Matplotlib? ›

One of the key strengths of ggplot2 is its use of a consistent syntax, making it relatively easy to learn and enabling users to create a wide range of graphics with a common set of functions. The package is also highly customizable, allowing detailed adjustments to almost every element of a plot.

Why is ggplot so good? ›

The answer is that ggplot2 is declaratively and efficient in creating data visualization based on The Grammar of Graphics. The layered grammar makes developing charts structural and effusive.

What is the difference between ggplot and ggplot2? ›

ggplot2 is the latest version of the popular open-source data visualization tool ggplot for R, used to create plots using the function ggplot(). It is part of the R tidyverse ecosystem, designed with common APIs, and is used in the statistical programming language.

Is Seaborn better than ggplot? ›

The seaborn corrplot maintains the aspect correlation value on the number scale while the ggplot2 corrplot reads from -1 to +1. There are a lot of similarities as well as differences in these plots made with the different libraries. In general, ggplot2 plot graphics are visually sharper than that of seaborn.

What is the difference between ggplot and R plot? ›

The graph made by ggplot is more clear. The default color is not grey and black and we can see the labels in x direction and we also have legends by default. However, the graph made by normal r packages doesn't have default legends and x labels.

What is jittering in ggplot? ›

Source: R/geom-jitter.R. geom_jitter.Rd. The jitter geom is a convenient shortcut for geom_point(position = "jitter") . It adds a small amount of random variation to the location of each point, and is a useful way of handling overplotting caused by discreteness in smaller datasets.

What is the difference between ggplot geom_text and annotate? ›

geom_text(): adds text directly to the plot. geom_label(): draws a rectangle underneath the text, making it easier to read. annotate(): useful for adding small text annotations at a particular location on the plot.

What is geom_text in ggplot? ›

geom_text() adds only text to the plot. geom_label() draws a rectangle behind the text, making it easier to read.

What is the difference between Geom_col and Geom_bar? ›

There are two types of bar charts: geom_bar() and geom_col() . geom_bar() makes the height of the bar proportional to the number of cases in each group (or if the weight aesthetic is supplied, the sum of the weights). If you want the heights of the bars to represent values in the data, use geom_col() instead.

What does stat identity mean in ggplot? ›

(It plots stat = "identity" , meaning the actual values, instead of stat = "count" . This means that geom_col() and geom_bar(stat = "identity") are equivalent.) The pipe below calculates the mean income by education level.

What is the difference between ggplot histogram and barplot? ›

The x and y axes of bar plots specify the category which is included in specific data set. Histogram is a bar graph which represents the raw data with clear picture of distribution of mentioned data set.

How do you make a graph look pretty? ›

Remove unnecessary elements that clutter the chart and make it harder to understand. For example, eliminate unnecessary axes. Distribute bars evenly by making them wider and reducing the spacing between them.

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