Bar Charts

Bar charts are a helpful way to visualize categorical summaries such as mean and counts, in a side-by-side comparison. They can often help understand the cross-distribution of the dataset. This example looks at the Electric Vehicle population in the State of Washington.

import pygal
import numpy as np
import pandas as pd 


cars = pd.read_csv('dataset/Electric_Vehicle_Population_Data.csv')
electric_cars = cars.groupby(['Make'])['VIN (1-10)'].count() #.agg({ 'VIN (1-10)': 'count' })
electric_cars.head()

Make AUDI 2332 AZURE DYNAMICS 7 BENTLEY 3 BMW 4680 CADILLAC 108 Name: VIN (1-10), dtype: int64

bar = pygal.Bar( x_label_rotation= -40 )

bar.title = 'Electric Vehicle Population in WA'
for x in electric_cars.items():
    bar.add(x[0], x[1])

bar.render_in_browser()