Pie Chart

A pie chart is a circualr graphic that displays numeric proportions by dividing a circle (or pie) into proportional slices. You are most likely already familiar with pie charts as it is widely used in business and media. We can create pie charts in Matplotlib by passing in the kind=pie keyword.

%%capture
!pip3 install xlrd

import matplotlib.pyplot as plt
import pandas as pd

df_can = pd.read_excel(
    './data/ibm/canada.xlsx',
    sheet_name='Canada by Citizenship',
    skiprows=range(20),
    skipfooter=2
)

df_can.columns = list(map(lambda x: str(x), df_can.columns))

drops = [
    'AREA', 
    'REG', 
    'DEV', 
    'Type', 
    'Coverage'
]
df_can.drop(columns=drops, inplace=True)

columns = {
    'OdName': 'Country',
    'AreaName': 'Continent',
    'RegName': 'Region'
}

df_can.rename(columns=columns, inplace=True)

df_can.set_index('Country', inplace=True)

df_can['Total'] = df_can.sum(axis=1)

df_continents = df_can.groupby('Continent', axis=0).sum()

Remove the text labels on the pie chart by passing in legend and add it as a seperate legend using plt.legend().
Push out the percentages to sit just outside the pie chart by passing in pctdistance parameter.
Pass in a custom set of colors for continents by passing in colors parameter.
Explode the pie chart to emphasize the lowest three continents (Africa, North America, and Latin America and Carribbean) by pasing in explode parameter.

colors_list = [
    'gold', 
    'yellowgreen', 
    'lightcoral', 
    'lightskyblue', 
    'lightgreen', 
    'pink'
]
explode_list = [0.1, 0, 0, 0, 0.1, 0.1]

df_continents['Total'].plot(
    kind='pie',
    figsize=(15, 6),
    autopct='%1.1f%%',
    startangle=90,
    shadow=True,       
    labels=None,   
    pctdistance=1.12, 
    colors=colors_list, 
    explode=explode_list
)

plt.title('Immigration to Canada by Continent [1980 - 2013]', y=1.12) 
plt.axis('equal') 

plt.legend(labels=df_continents.index, loc='upper left') 
plt.show()