How to create a FacetGrid stacked barplot using Seaborn?

Question

I am trying to plot a facet_grid with stacked bar charts inside.

I would like to use Seaborn. Its barplot function does not include a stacked argument.

I tried to use FacetGrid.map with a custom callable function.

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

def custom_stacked_barplot(col_day, col_time, col_total_bill, **kwargs):
    dict_df={}
    dict_df['day']=col_day
    dict_df['time']=col_time
    dict_df['total_bill']=col_total_bill
    df_data_graph=pd.DataFrame(dict_df)
    df = pd.crosstab(index=df_data_graph['time'], columns=tips['day'], values=tips['total_bill'], aggfunc=sum)
    df.plot.bar(stacked=True)

tips=sns.load_dataset("tips")
g = sns.FacetGrid(tips, col='size',  row='smoker')
g = g.map(custom_stacked_barplot, "day", 'time', 'total_bill')

However I get an empty canvas and stacked bar charts separately.

Empty canvas:

Graph1 apart:

Graph2:.

How can I fix this issue? Thanks for the help!

Answer 1

The simplest code to achive that result is this:

import seaborn as sns
import matplotlib.pyplot as plt
sns.set()

tips=sns.load_dataset("tips")
g = sns.FacetGrid(tips, col = 'size',  row = 'smoker', hue = 'day')
g = (g.map(sns.barplot, 'time', 'total_bill', ci = None).add_legend())

plt.show()

which gives this result:

Answer 2

Your different mixes of APIs ( pandas.DataFrame.plot ) appears not to integrate with ( seaborn.FacetGrid ). Since stacked bar plots are not supported in seaborn plotting, consider developing your own version with matplotlib subplots by iterating across groupby levels:

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

def custom_stacked_barplot(t, sub_df, ax):
    plot_df = pd.crosstab(index=sub_df["time"], columns=sub_df['day'], 
                           values=sub_df['total_bill'], aggfunc=sum)

    p = plot_df.plot(kind="bar", stacked=True, ax = ax, 
                     title = " | ".join([str(i) for i in t]))   
    return p

tips = sns.load_dataset("tips")
g_dfs = tips.groupby(["smoker", "size"])

# INITIALIZE PLOT
# sns.set()
fig, axes = plt.subplots(nrows=2, ncols=int(len(g_dfs)/2)+1, figsize=(15,6))

# BUILD PLOTS ACROSS LEVELS
for ax, (i,g) in zip(axes.ravel(), sorted(g_dfs)):
    custom_stacked_barplot(i, g, ax)

plt.tight_layout()
plt.show()
plt.clf()
plt.close()

And use seaborn.set to adjust theme and pallette: