Create one boxplot per cluster for each column of information for a dataframe

Question

Let it be the following Python Panda DataFrame:

value	other_value	cluster
1382	2.1	0
10	3.9	1
104	5.9	1
82	-1.1	0
100	0.9	2
1003	0.85	2
232	4.1	0
19	0.6	3
1434	0.3	3
23	1.6	3

Using the seaborn module, I want to display a set of boxplots for each column of values, showing the comparative information per value of the cluster column.

That is, for the above DataFrame, it would show a first graph for the 'value' column with 4 boxplots, one for each cluster value. The second graph would include information for the 'other_value' column also showing 1 boxplot for each cluster.

My idea is to do the same, but instead of in R language, in python: Boxplots of different variables by cluster assigned on one graph in ggplot

My code, It only shows the 1 to 1 graphs, I would like to get a joint graph with all graphs applied, as in the link above:

sns.boxplot(y='value', x='cluster',
                 data=df, 
                 palette="colorblind",
                 hue='cluster')

Thanks for the help offered.

Answer 1

Most seaborn functions work best with the data in "long form".

Here is how the code could look like:

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

df = pd.read_html('https://stackoverflow.com/questions/72301993/')[0]
df_long = df.melt(id_vars='cluster', value_vars=df.columns[:-1], var_name='variable', value_name='values')

sns.catplot(kind='box', data=df_long, 
            col='variable', y='values', x='cluster', hue='cluster', palette="colorblind", sharey=False, colwrap=2)
plt.tight_layout()
plt.show()