How to plot a stacked bar chart using hvplot?

Currently it is not possible in HoloViews (1.13) to have more than 2 categorical variables for a barchart.

See also this github issue:
https://github.com/holoviz/holoviews/issues/2878

However, you could do a workaround like this:
The trick is to put one categorical as x, one categorical variable in the by keyword, and other categorical variables in the groupby keyword.

import pandas as pd
import hvplot.pandas

# create sample data
df = pd.DataFrame({
    'Type': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],
    'Fiscal Period': ['2019-01', '2019-01', '2019-02', '2019-02', '2019-01', '2019-01', '2019-02', '2019-02'],
    'Request Type': ['S', 'D', 'S', 'D', 'S', 'D', 'S', 'D'],
    'values': range(1, 9),
})

# create a separate barchart per Type
layout = df.hvplot.bar(
    x='Fiscal Period', 
    y='values', 
    by='Request Type', 
    groupby='Type', 
    stacked=True, 
    cmap='Category20', 
    legend='top_left',
    width=400,
    xlabel='',
).layout()

# make plots nicer so they look more like a clustered barchart
plotA = layout['A'].opts(title='Type: A')
plotB = layout['B'].opts(show_legend=False, yaxis=None, ylabel='', title='Type: B')

# add separate plots together again
(plotA + plotB).opts(title='Showing the counts per Fiscal Period, Request Type and Type')

Resulting plot:



As a bonus, this code will give you the same result as above:

def create_subplot(type_selected):
    plot = df[df['Type'] == type_selected].hvplot.bar(
        x='Fiscal Period', 
        y='values', 
        by='Request Type', 
        stacked=True, 
        cmap='Category20', 
        label='Type: ' + type_selected,
        legend='top_left',
        width=400,
        xlabel='',
        ylabel='',
    )
    return plot

plotA = create_subplot('A')
plotB = create_subplot('B').opts(show_legend=False, yaxis=None)

(plotA + plotB).opts(title='Showing the counts per Fiscal Period, Request Type and Type')