Boxplot of Multiple Columns of a Pandas Dataframe on the Same Figure (seaborn)

Question

I feel I am probably not thinking of something obvious. I want to put in the same figure, the box plot of every column of a dataframe, where on the x-axis I have the columns' names. In the seaborn.boxplot() this would be equal to groupby by every column.

In pandas I would do

df = pd.DataFrame(data = np.random.random(size=(4,4)), columns = ['A','B','C','D']) df.boxplot() 

which yields

Now I would like to get the same thing in seaborn. But when I try sns.boxplot(df), I get only one grouped boxplot. How do I reproduce the same figure in seaborn?

Answer 1

The seaborn equivalent of

df.boxplot() 

is

sns.boxplot(x="variable", y="value", data=pd.melt(df)) 

or just

sns.boxplot(data=df) 

which will plot any column of numeric values, without converting the DataFrame from a wide to long format, using seaborn v0.11.1. This will create a single figure, with a separate boxplot for each column.

Complete example with melt:

import numpy as np; np.random.seed(42) import pandas as pd import matplotlib.pyplot as plt import seaborn as sns  df = pd.DataFrame(data = np.random.random(size=(4,4)), columns = ['A','B','C','D'])  sns.boxplot(x="variable", y="value", data=pd.melt(df))  plt.show() 

This works because pd.melt converts a wide-form dataframe

          A         B         C         D 0  0.374540  0.950714  0.731994  0.598658 1  0.156019  0.155995  0.058084  0.866176 2  0.601115  0.708073  0.020584  0.969910 3  0.832443  0.212339  0.181825  0.183405 

to long-form

   variable     value 0         A  0.374540 1         A  0.156019 2         A  0.601115 3         A  0.832443 4         B  0.950714 5         B  0.155995 6         B  0.708073 7         B  0.212339 8         C  0.731994 9         C  0.058084 10        C  0.020584 11        C  0.181825 12        D  0.598658 13        D  0.866176 14        D  0.969910 15        D  0.183405