isin() for value matching in Pandas - Mini Project: Build & Apply

Using isin() for Value Matching in pandas

📖 Scenario: You work in a store and have a list of products with their categories. You want to find which products belong to certain categories you are interested in.

🎯 Goal: Build a pandas DataFrame with product data, create a list of categories to filter, use isin() to find matching products, and display the filtered results.

📋 What You'll Learn

Create a pandas DataFrame called products with columns 'Product' and 'Category' using exact data.

Create a list called selected_categories with exact category names.

Use isin() on the 'Category' column of products to filter rows.

Print the filtered DataFrame.

💡 Why This Matters

🌍 Real World

Stores and businesses often need to filter product lists by categories to analyze or display specific groups.

💼 Career

Data analysts and scientists use <code>isin()</code> to quickly filter data based on lists of values, which is common in data cleaning and exploration.

1

Create the products DataFrame

Create a pandas DataFrame called products with two columns: 'Product' and 'Category'. Use these exact entries: 'Apple' in 'Fruit', 'Carrot' in 'Vegetable', 'Banana' in 'Fruit', 'Broccoli' in 'Vegetable', and 'Chicken' in 'Meat'.

Pandas

import pandas as pd
# Create the products DataFrame with the exact data
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary where keys are column names and values are lists of entries.

2

Create the list of selected categories

Create a list called selected_categories with these exact values: 'Fruit' and 'Meat'.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Carrot', 'Banana', 'Broccoli', 'Chicken'],
    'Category': ['Fruit', 'Vegetable', 'Fruit', 'Vegetable', 'Meat']
})
# Create the list selected_categories with 'Fruit' and 'Meat'
# Your code here

Need a hint?

Use square brackets to create a list with the exact category names.

3

Filter products using isin()

Create a new DataFrame called filtered_products by selecting rows from products where the 'Category' column values are in the list selected_categories. Use the isin() method on the 'Category' column.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Carrot', 'Banana', 'Broccoli', 'Chicken'],
    'Category': ['Fruit', 'Vegetable', 'Fruit', 'Vegetable', 'Meat']
})
selected_categories = ['Fruit', 'Meat']
# Use isin() on 'Category' to filter products into filtered_products
# Your code here

Need a hint?

Use products['Category'].isin(selected_categories) inside the square brackets to filter rows.

4

Print the filtered products

Print the DataFrame filtered_products to display the products that belong to the selected categories.

Pandas

import pandas as pd
products = pd.DataFrame({
    'Product': ['Apple', 'Carrot', 'Banana', 'Broccoli', 'Chicken'],
    'Category': ['Fruit', 'Vegetable', 'Fruit', 'Vegetable', 'Meat']
})
selected_categories = ['Fruit', 'Meat']
filtered_products = products[products['Category'].isin(selected_categories)]
# Print the filtered_products DataFrame
# Your code here

Need a hint?

Use print(filtered_products) to show the filtered rows.