How to plot multiple seaborn.distplot in a single figure

Question

I want to plot multiple seaborn distplot under a same window, where each plot has the same x and y grid. My attempt is shown below, which does not work.

# function to plot the density curve of the 200 Median Stn. MC-losses
def make_density(stat_list,color, layer_num):

    num_subplots = len(stat_list)
    ncols = 3
    nrows = (num_subplots + ncols - 1) // ncols
    fig, axes = plt.subplots(ncols=ncols, nrows=nrows, figsize=(ncols * 6, nrows * 5))
    
    for i in range(len(stat_list)):
        
        # Plot formatting
        plt.title('Layer ' + layer_num)
        plt.xlabel('Median Stn. MC-Loss')
        plt.ylabel('Density')
        plt.xlim(-0.2,0.05)
        plt.ylim(0, 85)
        min_ylim, max_ylim = plt.ylim()
    
        # Draw the density plot.
        sns.distplot(stat_list, hist = True, kde = True,
                 kde_kws = {'linewidth': 2}, color=color)

# `stat_list` is a list of 6 lists
# I want to draw histogram and density plot of 
# each of these 6 lists contained in `stat_list` in a single window,
# where each row containing the histograms and densities of the 3 plots
# so in my example, there would be 2 rows of 3 columns of plots (2 x 3 =6).
stat_list = [[0.3,0.5,0.7,0.3,0.5],[0.2,0.1,0.9,0.7,0.4],[0.9,0.8,0.7,0.6,0.5]
          [0.2,0.6,0.75,0.87,0.91],[0.2,0.3,0.8,0.9,0.3],[0.2,0.3,0.8,0.87,0.92]]

How can I modify my function to draw multiple distplot under the same window, where the x and y grid for each displayed plot is identical?

Thank you,

PS: Aside, I want the 6 distplots to have identical color, preferably green for all of them.

Answer 1

• The easiest method is to load the data into pandas and then use seaborn.displot.
• .displot replaces .distplot in seaborn version 0.11.0
  • Technically, what you would have wanted before, is a FacetGrid mapped with distplot.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# data
stat_list = [[0.3,0.5,0.7,0.3,0.5], [0.2,0.1,0.9,0.7,0.4], [0.9,0.8,0.7,0.6,0.5], [0.2,0.6,0.75,0.87,0.91], [0.2,0.3,0.8,0.9,0.3], [0.2,0.3,0.8,0.87,0.92]]

# load the data into pandas and then transpose it for the correct column data
df = pd.DataFrame(stat_list).T

# name the columns; specify a layer number
df.columns = ['A', 'B', 'C', 'D', 'E', 'F']

# now stack the data into a long (tidy) format
dfl = df.stack().reset_index(level=1).rename(columns={'level_1': 'Layer', 0: 'Median Stn. MC-Loss'})

# plot a displot
g = sns.displot(data=dfl, x='Median Stn. MC-Loss', col='Layer', col_wrap=3, kde=True, color='green')
g.set_axis_labels(y_var='Density')
g.set(xlim=(0, 1.0), ylim=(0, 3.0))

sns.FacetGrid and sns.distplot

• .distplot is deprecated

p = sns.FacetGrid(data=dfl, col='Layer', col_wrap=3, height=5)
p.map(sns.distplot, 'Median Stn. MC-Loss', bins=5, kde=True, color='green')
p.set(xlim=(0, 1.0))