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?
The seaborn equivalent of
df.boxplot()
is
sns.boxplot(x="variable", y="value", data=pd.melt(df))
Complete example:
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