I need to plot two graphs side by side. Here the column in my dataset which I am interested in.
X
1
53
12
513
135
125
21
54
1231
I did
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
mean = df['X'].mean()
fig, ax =plt.subplots(1,2)
sns.displot(df, x="X", kind="kde", ax=ax[0]) # 1st plot
plt.axvline(mean, color='r', linestyle='--') # this add just a line on the previous plot, corresponding to the mean of X data
sns.boxplot(y="X", data=df, ax=ax[2]) # 2nd plot
but I have this error: IndexError: index 2 is out of bounds for axis 0 with size 2
, so the use of subplots is wrong.
sns.boxplot(..., ax=ax[2])
should use ax=ax[1]
as there doesn't exist an ax[2]
.
sns.displot
is a figure-level function, which creates its own figure, and doesn't accept an ax=
parameter. If only one subplot is needed, it can be replaced by sns.histplot
or sns.kdeplot
.
plt.axvline()
draws on the "current" ax
. You can use ax[0].axvline()
to draw on a specific subplot. See What is the difference between drawing plots using plot, axes or figure in matplotlib?
The following code has been tested with Seaborn 0.11.1:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
sns.set()
df = pd.DataFrame({'X': [1, 53, 12, 513, 135, 125, 21, 54, 1231]})
mean = df['X'].mean()
fig, ax = plt.subplots(1, 2)
sns.kdeplot(data=df, x="X", ax=ax[0])
ax[0].axvline(mean, color='r', linestyle='--')
sns.boxplot(y="X", data=df, ax=ax[1])
plt.show()