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.
- 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.
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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
Teacher
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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