[FIXED] How to create stacked bar chart in python, color coded by category

Issue

I'm working on a popular Titanic dataset on Kaggle, and I would like to create a bar chart showing the numbers of survivors vs. deceased by gender. On the x-axis, I want gender (male/female). I want to have the survivors and deceased stacked and color coded.

Here is my current code, which produces four bars for each combination of male/survived, male/deceased, female/survived, female/deceased:

import pandas as pd
import seaborn as sns  # for the data

df = sns.load_dataset('titanic').loc[:, ['sex', 'survived']]
df.groupby('sex').survived.value_counts().plot(kind='bar', color=['C0', 'C1'], stacked=True)

Current output

Solution

• The simplest way is to reshape the DataFrame with pandas.DataFrame.pivot_table, and then plot with pandas.DataFrame.plot specifying kind='bar' and stacked=True.
  • The important thing to remember is to shape the data into the correct format for the plot API.
  • Use .pivot_table if values need to be aggregated, otherwise use .pivot.
• Using pandas v1.2.4 and matplotlib v3.3.4 (matplotlib is imported by pandas as a dependency).

import seaborn as sns  # used for the titanic data
import pandas as pd

# load the two necessary column
df = sns.load_dataset('titanic').loc[:, ['sex', 'survived']]

# create a pivot table
dfp = df.pivot_table(index='sex', columns=['survived'], aggfunc=len)

# display(dfp)
survived    0    1
sex               
female     81  233
male      468  109

# plot the dataframe
dfp.plot(kind='bar', stacked=True, ylabel='Counts', xlabel='Gender',
         title='Survival Status Count by Gender', rot=0)

• I do not recommend stacked bars because it is more difficult to differentiate and compare the values for each category.

dfp.plot(kind='bar', stacked=False, ylabel='Counts', xlabel='Gender',
         title='Survival Status Count by Gender', rot=0)

Answered By - Trenton McKinney