Seaborn Is Not Plotting Within Defined Subplots

seaborn is not plotting within defined subplots

• seaborn.distplot has been DEPRECATED in seaborn 0.11 and 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, so it will not work with matplotlib.pyplot.subplots.
  • histplot(), an axes-level function for plotting histograms, including with kernel density smoothing. This does have the ax parameter, so it will work with matplotlib.pyplot.subplots.
• 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.
  • See Figure-level vs. axes-level functions
• 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
• Also review seaborn histplot and displot output doesn't match
• 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})

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Multiple DataFrames

• If there are multiple dataframes, they can be combined with pd.concat, and use .assign to create an identifying 'source' column, which can be used for row=, col=, or hue=

# list of dataframe
lod = [df1, df2, df3]

# create one dataframe with a new 'source' column to use for row, col, or hue
df = pd.concat((d.assign(source=f'df{i}') for i, d in enumerate(lod, 1)), ignore_index=True)

• See Import multiple csv files into pandas and concatenate into one DataFrame to read multiple files into a single dataframe with an identifying column.

Why is the first subplot skipped?

The reason you are seeing the displot outside is because it is a figure-level function and you cannot use ax in it. You can change it to histplot and should see it working...

fig, axes = plt.subplots(2,1,figsize=(5,5))
sns.histplot(wine['fixed acidity'], ax=axes[0])
sns.boxplot(wine['fixed acidity'], ax=axes[1])

Plot

Seaborn displot - plot multiple plots in a a single figure

Displot doesn't accept the ax= parameter, try instead to use histplot as follows:

fig, ax =plt.subplots(1,3,figsize=(20,10))
sns.histplot(profile["age"], ax=ax[0])
sns.histplot(profile["income"], ax=ax[1])
sns.histplot(profile["memberdays"], ax=ax[2])
fig.show()

It gives the following output:

Seaborn plots not showing up

Plots created using seaborn need to be displayed like ordinary matplotlib plots.
This can be done using the

plt.show()

function from matplotlib.

Originally I posted the solution to use the already imported matplotlib object from seaborn (sns.plt.show()) however this is considered to be a bad practice. Therefore, simply directly import the _matplotlib.pyplot_ module and show your plots with

import matplotlib.pyplot as plt
plt.show()

If the IPython notebook is used the inline backend can be invoked to remove the necessity of calling show after each plot. The respective magic is

%matplotlib inline

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