[FIXED] Pandas groupby two columns and plot

Issue

I have a dataframe like this:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

df = pd.DataFrame({'category': list('XYZXY'), 'B': range(5,10),'sex': list('mfmff')})

I want to plot count of sex male or female based on category from column 'category'.

I tried:
df.groupby(['category','sex'])['category','sex'].count().plot.bar()

But this gives:

How to get the count of sex per category?

Solution

Various Methods of Groupby Plots

Data

import numpy as np
import pandas as pd
df = pd.DataFrame({'category': list('XYZXY'),
                   'sex': list('mfmff'),
                   'ThisColumnIsNotUsed': range(5,10)})
df

category sex ThisColumnIsNotUsed
0   X   m   5
1   Y   f   6
2   Z   m   7
3   X   f   8
4   Y   f   9

Using crosstab

pd.crosstab(df['category'],df['sex']).plot.bar()

Using groupby+unstack:

(df.groupby(['sex','category'])
   .count().unstack('sex').plot.bar())

Using pivot_table:

pd.pivot_table(df,index = 'category',
               columns = 'sex',aggfunc ='count').plot.bar()

Using seaborn:

import seaborn as sns
sns.countplot(data=df,x='category',hue='sex')

or,
sns.catplot(data=df,kind='count',x='category',hue='sex')

output

Answered By - BhishanPoudel