Extracting with str.extract (regex) in Data Analysis Python - Mini Project: Build & Apply

Extracting with str.extract (regex)

📖 Scenario: You work in a store and have a list of product codes mixed with letters and numbers. You want to pull out just the numbers from each code to analyze sales data.

🎯 Goal: Build a small program that extracts the numeric part from each product code using str.extract with a regular expression.

📋 What You'll Learn

Create a pandas Series called product_codes with the exact values: 'A123', 'B456', 'C789', 'D012'

Create a regex pattern string called pattern that matches one or more digits

Use str.extract on product_codes with pattern to get the numbers

Print the extracted numbers as a pandas Series

💡 Why This Matters

🌍 Real World

Stores and businesses often have product codes mixing letters and numbers. Extracting parts of these codes helps analyze sales or inventory.

💼 Career

Data analysts and scientists use regex extraction to clean and prepare text data for analysis in many industries.

1

Create the product codes data

Create a pandas Series called product_codes with these exact values: 'A123', 'B456', 'C789', 'D012'.

Data Analysis Python

import pandas as pd
# Create the product_codes Series with the exact values
# Your code here

Hint

Use pd.Series and pass a list of the exact strings.

2

Create the regex pattern

Create a string variable called pattern that matches one or more digits using the regex '(\d+)'.

Data Analysis Python

import pandas as pd
product_codes = pd.Series(['A123', 'B456', 'C789', 'D012'])
# Create the regex pattern string to match digits
# Your code here

Hint

The regex '(\d+)' matches one or more digits and captures them.

3

Extract numbers using str.extract

Use str.extract on product_codes with the pattern to extract the numbers. Save the result in a variable called numbers.

Data Analysis Python

import pandas as pd
product_codes = pd.Series(['A123', 'B456', 'C789', 'D012'])
pattern = '(\d+)'
# Extract numbers from product_codes using str.extract and pattern
# Your code here

Hint

Use product_codes.str.extract(pattern) and select the first column with [0] to get a Series.

4

Print the extracted numbers

Print the numbers Series to display the extracted numeric parts.

Data Analysis Python

import pandas as pd
product_codes = pd.Series(['A123', 'B456', 'C789', 'D012'])
pattern = '(\d+)'
numbers = product_codes.str.extract(pattern)[0]
# Print the numbers Series
# Your code here

Hint

Use print(numbers) to show the extracted numbers.