## GGPlot Stripchart

* * 10 mins

* *Data Visualization using GGPlot2

444334534839482734

**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.

- Continuous variable:

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"))`

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")`

## 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"))`

## Conclusion

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

## Recommended for you

This section contains best data science and self-development resources to help you on your path.

### Coursera - Online Courses and Specialization

#### Data science

- Course: Machine Learning: Master the Fundamentals by Stanford
- Specialization: Data Science by Johns Hopkins University
- Specialization: Python for Everybody by University of Michigan
- Courses: Build Skills for a Top Job in any Industry by Coursera
- Specialization: Master Machine Learning Fundamentals by University of Washington
- Specialization: Statistics with R by Duke University
- Specialization: Software Development in R by Johns Hopkins University
- Specialization: Genomic Data Science by Johns Hopkins University

#### Popular Courses Launched in 2020

- Google IT Automation with Python by Google
- AI for Medicine by deeplearning.ai
- Epidemiology in Public Health Practice by Johns Hopkins University
- AWS Fundamentals by Amazon Web Services

#### Trending Courses

- The Science of Well-Being by Yale University
- Google IT Support Professional by Google
- Python for Everybody by University of Michigan
- IBM Data Science Professional Certificate by IBM
- Business Foundations by University of Pennsylvania
- Introduction to Psychology by Yale University
- Excel Skills for Business by Macquarie University
- Psychological First Aid by Johns Hopkins University
- Graphic Design by Cal Arts

### Amazon FBA

#### Amazing Selling Machine

- Free Training - How to Build a 7-Figure Amazon FBA Business You Can Run 100% From Home and Build Your Dream Life! by ASM

### Books - Data Science

#### Our Books

- Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
- Network Analysis and Visualization in R by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)

#### Others

- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet

Version: Français

GGPlot Dot Plot (Prev Lesson)

(Next Lesson) GGPlot Line Plot

### No Comments

### Give a comment

#### Course Curriculum

- Introduction to GGPlot2
- GGPlot Scatter Plot
- GGPlot Boxplot
- GGPlot Violin Plot
- GGPlot Dot Plot
- GGPlot Stripchart
- GGPlot Line Plot
- GGPlot Barplot
- GGPlot Error Bars
- GGPlot Density Plot
- GGPlot Histogram
- GGPLOT QQ Plot
- GGPlot ECDF
- Combine Multiple GGPlots into a Figure

##### Teacher

##### Alboukadel Kassambara

###### Role : Founder of Datanovia

- Website : https://www.datanovia.com/en
- Experience : >10 years
- Specialist in : Bioinformatics and Cancer Biology

Read More