Resetting index in Pandas - Mini Project: Build & Apply

Resetting index in pandas DataFrame

📖 Scenario: You are working with sales data in a pandas DataFrame. The DataFrame has a custom index representing product IDs, but you want to reset the index to the default integer index for easier processing and display.

🎯 Goal: Build a pandas DataFrame with product sales data, then reset its index to the default integer index.

📋 What You'll Learn

Create a pandas DataFrame named sales with columns 'Product' and 'Sales' and a custom index.

Create a variable named reset_sales that contains the sales DataFrame with its index reset to default.

Use the reset_index() method without dropping the old index in Step 3.

In Step 4, reset the index again but drop the old index so it does not appear as a column.

💡 Why This Matters

🌍 Real World

Resetting the index is common when you want to convert a DataFrame with a meaningful index back to a simple numbered index for exporting or further processing.

💼 Career

Data analysts and scientists often reset indexes to clean data before visualization or machine learning tasks.

1

Create the initial DataFrame with a custom index

Create a pandas DataFrame called sales with columns 'Product' and 'Sales'. Use the data: products ['A', 'B', 'C'] and sales [100, 150, 200]. Set the index to [101, 102, 103] representing product IDs.

Pandas

# Create the sales DataFrame with custom index
# Your code here

Need a hint?

Use pd.DataFrame() with the index parameter to set custom index values.

2

Prepare for resetting the index

Create a variable called reset_sales and assign it the sales DataFrame. This will be used to store the DataFrame after resetting the index.

Pandas

import pandas as pd
sales = pd.DataFrame({'Product': ['A', 'B', 'C'], 'Sales': [100, 150, 200]}, index=[101, 102, 103])
# Assign sales DataFrame to reset_sales
# Your code here

Need a hint?

Simply assign the existing DataFrame sales to a new variable reset_sales.

3

Reset the index keeping the old index as a column

Use the reset_index() method on reset_sales to reset its index to the default integer index. Do not drop the old index; keep it as a column. Assign the result back to reset_sales.

Pandas

import pandas as pd
sales = pd.DataFrame({'Product': ['A', 'B', 'C'], 'Sales': [100, 150, 200]}, index=[101, 102, 103])
reset_sales = sales
# Reset the index of reset_sales without dropping the old index
# Your code here

Need a hint?

Call reset_index() on reset_sales and assign it back to reset_sales.

4

Reset the index dropping the old index column

Reset the index of reset_sales again, but this time use the drop=True parameter to remove the old index column. Assign the result back to reset_sales.

Pandas

import pandas as pd
sales = pd.DataFrame({'Product': ['A', 'B', 'C'], 'Sales': [100, 150, 200]}, index=[101, 102, 103])
reset_sales = sales
reset_sales = reset_sales.reset_index()
# Reset the index of reset_sales again dropping the old index column
# Your code here

Need a hint?

Use reset_index(drop=True) to reset the index and remove the old index column.