Pandas plot of a stacked and grouped bar chart

Question

I have a CSV-file with a couple of data:

# Comment header
# 
MainCategory,SubCategory,DurationM,DurationH,Number
MainCat1,Sub1.1,598,9.97,105
MainCat1,Sub1.2,11,0.18,4
MainCat1,Sub1.3,17,0.28,5
MainCat1,Sub1.4,16,0.27,2
MainCat2,Sub2.1,14161,236.02,102
MainCat2,Sub2.2,834,13.90,17
MainCat3,Sub3.1,4325,72.08,472
MainCat3,Sub3.2,7,0.12,2
MainCat4,Sub4.1,614,10.23,60
MainCat5,Sub5.1,6362,106.03,142
MainCat5,Sub5.2,141,2.35,6
Misc,Misc.1,3033,50.55,53
MainCat4,Sub4.2,339,5.65,4
MainCat4,Sub4.3,925,15.42,11
Misc,Misc.2,2641,44.02,28
MainCat6,Sub6.1,370,6.17,4
MainCat7,Sub7.1,9601,160.02,10
MainCat4,Sub4.4,75,1.25,2
MainCat8,Sub8.1,148,2.47,4
MainCat8,Sub8.2,680,11.35,7
MainCat9,Sub9.1,3997,66.62,1
MainCat8,Sub8.3,105,1.75,2
MainCat4,Sub4.5,997,16.62,1
MainCat10,Sub10.1,12,0.20,3
MainCat4,Sub4.6,10,0.17,1
MainCat10,Sub10.2,13,0.22,1
MainCat4,Sub4.7,561,9.35,4
MainCat10,Sub10.3,1043,17.38,47

What I would like to achieve is a stacked bar plot where

the X-axis values/labels are given by the values/groups given by MainCategory
on the left Y-axis, the DurationH is used
on the right Y-axis the Number is used
DurationH and Number are plotted as bars per MainCategory side-by-side
In each of the bars, the SubCategory is used for stacking

Something like this:

The following code produces stacked plots, but a sequence of them:

import pandas as pd
from pandas import DataFrame
from matplotlib import pyplot as plt
import seaborn as sns

data = pd.read_csv('failureEventStatistic_total_Top10.csv', sep=',', header=2) 
data = data.rename(columns={'DurationM':'Duration [min]', 'DurationH':'Duration [h]'})
data.groupby('MainCategorie')[['Duration [h]', 'Number']].plot.bar()

I tried to use unstack(), but this produces an error

Stef · Accepted Answer · 2022-07-15T12:52:19.227

You can get the plot data from a crosstab and then make a right aligned and a left aligned bar plot on the same axes:

ax = pd.crosstab(df.MainCategory, df.SubCategory.str.partition('.')[2], df.DurationH, aggfunc=sum).plot.bar(
    stacked=True, width=-0.4, align='edge', ylabel='DurationH', ec='w', color=[(0,1,0,x) for x in np.linspace(1, 0.1, 7)], legend=False)
h_durationh, _ = ax.get_legend_handles_labels()

ax = pd.crosstab(df.MainCategory, df.SubCategory.str.partition('.')[2], df.Number, aggfunc=sum).plot.bar(
    stacked=True, width=0.4, align='edge', secondary_y=True, ec='w', color=[(0,0,1,x) for x in np.linspace(1, 0.1, 7)], legend=False, ax=ax)
h_number, _ = ax.get_legend_handles_labels()

ax.set_ylabel('Number')
ax.set_xlim(left=ax.get_xlim()[0] - 0.5)
ax.legend([h_durationh[0], h_number[0]], ['DurationH', 'Number'])

Pandas plot of a stacked and grouped bar chart

1 Answers1