**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:

#### 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 ggplot
e <- ggplot(ToothGrowth, aes(x = dose, y = len))
# Stripcharts with summary statistics
# Change color by dose groups
e + 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 plot
e + geom_boxplot() +
geom_jitter(position = position_jitter(0.2))
# Strip chart + violin plot + stat summary
e + 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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