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pythonpandaspie-chart

How to produce a subdivided pie chart using pandas?

I have a pandas dataframe containing qualtitative variables. I would like to find a nice way to show how an independant variable affects a dependant one. I thought that a "subdivided pie-chart" (don't know how to call it) could be a good idea but I do not know if that exists. Given a pandas data frame like the following one:

import pandas as pd
data = {'Gender': ['m','m','m','f','m','f','m','f','f','f','f','m','m'], 'Favorite character':['Jim','Jim','Pam','Jim','Pam','Jim','Jim','Jim','Pam','Pam','Jim','Jim','Pam' ]}

where m stands for male and f for female, I would like to obtain a figure looking like this

Purely descriptive

Anyone who knows how to it? or where to look for?

Thank you very much for your help!

Solution

  • You can use nested pie charts for something like this:

    import pandas as pd 
import matplotlib.pyplot as plt 

import pandas as pd
data = {'Gender': ['m','m','m','f','m','f','m','f','f','f','f','m','m'], 'Favorite character':['Jim','Jim','Pam','Jim','Pam','Jim','Jim','Jim','Pam','Pam','Jim','Jim','Pam' ]}
df = pd.DataFrame(data)

level_one = df.groupby('Gender', as_index=False).count()
level_two = df.groupby(['Gender', 'Favorite character'], as_index=False).value_counts()

fig, ax = plt.subplots()

size = 0.3
vals = np.array([[60., 32.], [37., 40.], [29., 10.]])

cmap = plt.colormaps["tab20c"]
outer_colors = cmap(np.arange(3)*4)
inner_colors = cmap([1, 2, 5, 6, 9, 10])

ax.pie(level_one['Favorite character'], radius=1, colors=outer_colors,
       wedgeprops=dict(width=size, edgecolor='w'), labels=['F', 'M'])

ax.pie(level_two['count'], radius=1-size, colors=inner_colors,
       wedgeprops=dict(width=size, edgecolor='w'), labels=['F-Jim', 'F-Pam', 'M-Jim', 'M-Pam'])

ax.set(aspect="equal", title='Nested Pie Plot')
plt.show()