pct_change() for percentage change in Pandas - Mini Project: Build & Apply

Calculate Percentage Change Using pct_change()

📖 Scenario: You work in a small shop and track daily sales. You want to see how sales change day to day in percentage to understand growth or decline.

🎯 Goal: Build a small program that creates a sales data table, sets a configuration for percentage change periods, calculates the percentage change using pct_change(), and prints the result.

📋 What You'll Learn

Create a pandas DataFrame with daily sales data

Set a variable for the number of periods to calculate percentage change

Use the pct_change() method with the periods variable

Print the resulting DataFrame with percentage changes

💡 Why This Matters

🌍 Real World

Tracking percentage change in sales helps businesses understand growth trends and make better decisions.

💼 Career

Data analysts and business intelligence professionals often calculate percentage changes to report performance metrics.

1

Create sales data DataFrame

Import pandas as pd and create a DataFrame called sales_data with a column 'Sales' containing these exact values: 100, 120, 90, 150, 130.

Pandas

# Import pandas and create the sales_data DataFrame
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where the key is 'Sales' and the value is the list of sales numbers.

2

Set periods for percentage change

Create a variable called periods and set it to 1 to calculate the percentage change compared to the previous day.

Pandas

import pandas as pd

sales_data = pd.DataFrame({'Sales': [100, 120, 90, 150, 130]})

# Set periods variable to 1
# Your code here

Need a hint?

Just create a variable named periods and assign it the value 1.

3

Calculate percentage change

Create a new column in sales_data called 'Pct_Change' that stores the percentage change of 'Sales' using the pct_change() method with the periods variable.

Pandas

import pandas as pd

sales_data = pd.DataFrame({'Sales': [100, 120, 90, 150, 130]})

periods = 1

# Calculate percentage change and add as 'Pct_Change' column
# Your code here

Need a hint?

Use sales_data['Sales'].pct_change(periods=periods) and assign it to sales_data['Pct_Change'].

4

Print the sales data with percentage change

Print the sales_data DataFrame to display the sales and their percentage changes.

Pandas

import pandas as pd

sales_data = pd.DataFrame({'Sales': [100, 120, 90, 150, 130]})

periods = 1

sales_data['Pct_Change'] = sales_data['Sales'].pct_change(periods=periods)

# Print the sales_data DataFrame
# Your code here

Need a hint?

Use print(sales_data) to show the DataFrame with the new column.