- From the documentation for
seaborn.distplot, which has been DEPRECATED in seaborn 0.11.
.distplot is replaced with the following:
displot(), a figure-level function with a similar flexibility over the kind of plot to draw. This is a FacetGrid, and does not have the ax parameter.histplot(), an axes-level function for plotting histograms, including with kernel density smoothing. This does have the ax parameter.
- It is applicable to any of the
seaborn FacetGrid plots that there is no ax parameter. Use the equivalent axes-level plot.
- Look at the documentation for the figure-level plot to find the appropriate axes-level plot function for your needs.
- Because the histogram of two different columns is desired, it’s easier to use
histplot.
- See How to plot in multiple subplots for a number of different ways to plot into
maplotlib.pyplot.subplots
- Tested in
seaborn 0.11.1 & matplotlib 3.4.2
fig,(ax1,ax2) = plt.subplots(1,2)
sns.histplot(x=X_train['Age'], hue=y_train, ax=ax1)
sns.histplot(x=X_train['Fare'], hue=y_train, ax=ax2)
Imports and DataFrame Sample
import seaborn as sns
import matplotlib.pyplot as plt
# load data
penguins = sns.load_dataset("penguins", cache=False)
# display(penguins.head())
species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g sex
0 Adelie Torgersen 39.1 18.7 181.0 3750.0 MALE
1 Adelie Torgersen 39.5 17.4 186.0 3800.0 FEMALE
2 Adelie Torgersen 40.3 18.0 195.0 3250.0 FEMALE
3 Adelie Torgersen NaN NaN NaN NaN NaN
4 Adelie Torgersen 36.7 19.3 193.0 3450.0 FEMALE
Axes Level Plot
- With the data in a wide format, use
sns.histplot
# select the columns to be plotted
cols = ['bill_length_mm', 'bill_depth_mm']
# create the figure and axes
fig, axes = plt.subplots(1, 2)
axes = axes.ravel() # flattening the array makes indexing easier
for col, ax in zip(cols, axes):
sns.histplot(data=penguins[col], kde=True, stat="density", ax=ax)
fig.tight_layout()
plt.show()
Figure Level Plot
- With the dataframe in a long format, use
displot
# create a long dataframe
dfl = penguins.melt(id_vars="species", value_vars=['bill_length_mm', 'bill_depth_mm'], var_name="bill_size", value_name="vals")
# display(dfl.head())
species bill_size vals
0 Adelie bill_length_mm 39.1
1 Adelie bill_depth_mm 18.7
2 Adelie bill_length_mm 39.5
3 Adelie bill_depth_mm 17.4
4 Adelie bill_length_mm 40.3
# plot
sns.displot(data=dfl, x='vals', col="bill_size", kde=True, stat="density", common_bins=False, common_norm=False, height=4, facet_kws={'sharey': False, 'sharex': False})
