Learn to create a bar chart race, from data acquisition to dynamic visualization, using the pandas library, Matplotlib, pyplot, NumPy, and imageio for animation.

Become a Data Analyst

In this module, you’ll explore how to create a dynamic bar chart race visualization. We’ll begin by familiarizing ourselves with libraries like pandas, Matplotlib, pyplot, NumPy, and imageio. You’ll learn how to acquire and identify the required data fields, create individual bar charts, and finally, combine these charts into frames to produce a complete bar chart race animation.

Build a Bar Chart Race

import pandas as pd

# Read the dataset
df = pd.read_csv('country_population.csv')

# Display the first few records
print(df)

barchart-copy

colors = {
    'Bangladesh': 'skyblue',
    'Brazil': 'pink',
    'China': 'orange',
    'India': 'blue',
    'Indonesia': 'purple',
    'Nigeria': 'brown',
    'Pakistan': 'green',
    'Russia': 'gray',
    'United States': 'red'
}

See the solution to the bar chart race challenge.




Solution: Create a Bar Chart Race

See the solution to the bar chart race challenge.

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Solution: Create a Bar Chart Race

Task 1: Read and display data

Task 2: Create a color dictionary

Task 3: Function for population conversion