Make It Rain with Raincloud Plots in Python¶

What is raincloud plot ?¶

A raincloud plot is a visualization that combines elements of a boxplot, violin plot, and a scatterplot to display the distribution of continuous data and compare distributions between groups. It was introduced by Allen et al. in 2018 as a modification to the traditional boxplot that provides more detailed information about the data and is easier to interpret.

Here's how a raincloud plot works:¶

  1. The "cloud" part of the plot is a combination of a violin plot and a scatterplot. The violin plot shows the kernel density estimation of the data, and the scatterplot shows the individual data points.

  2. The "rain" part of the plot is a box-and-whisker plot that shows the median, quartiles, and outliers of the data.

  3. The two parts are combined in a way that the cloud appears to rain onto the box-and-whisker plot.

Installation¶

To create a raincloud plot, you can use Python libraries such as seaborn or ptitprince. Simply provide your data and specify the variables you want to plot, along with any additional options such as colors, labels, and titles.

pip install ptitprince

Import Libraries¶

In [10]:
import seaborn as sns
import matplotlib.pyplot as plt
import ptitprince as pt

Load Data¶

In [11]:
# Load the example tips dataset
tips = sns.load_dataset("tips")

Create Raincloud Plot¶

In [12]:
# Create a raincloud plot
fig, ax = plt.subplots()
ax = pt.RainCloud(x="day", y="total_bill", data=tips, ax=ax)

# Add labels and title
ax.set(xlabel='Day', ylabel='Total Bill', title='Raincloud Plot of Total Bill by Day')

# Show the plot
plt.show()

This code creates a raincloud plot of the total_bill variable from the tips dataset, grouped by the day variable. The RainCloud function from the ptitprince library is used to create the plot.

The benefits of using a raincloud plot include:¶

  1. It provides more information about the data compared to a traditional boxplot.
  2. It allows for the comparison of multiple distributions within the same plot.
  3. It is easier to interpret than a traditional boxplot.

Conclusion¶

You can use a raincloud plot to:

  • Compare the distribution of a continuous variable across different groups or categories.
  • Visualize the spread, shape, and central tendency of the data.
  • Identify potential outliers in the data.