query() for fast filtering in Pandas - Mini Project: Build & Apply

Filter Sales Data Using pandas query()

📖 Scenario: You work in a store and have a table of sales data. You want to quickly find sales that meet certain conditions, like sales above a certain amount or sales from a specific product.

🎯 Goal: Build a small program that uses pandas query() to filter sales data based on a condition.

📋 What You'll Learn

Create a pandas DataFrame with sales data

Create a variable for the sales amount threshold

Use query() to filter rows where sales are above the threshold

Print the filtered DataFrame

💡 Why This Matters

🌍 Real World

Filtering data quickly helps businesses analyze sales trends and make decisions fast.

💼 Career

Data analysts and scientists often use pandas <code>query()</code> to filter large datasets efficiently.

1

Create the sales DataFrame

Import pandas as pd and create a DataFrame called sales with these exact columns and rows:
Product: 'Apple', 'Banana', 'Carrot', 'Date', 'Eggplant'
Amount: 50, 30, 20, 40, 10

Pandas

import pandas as pd
# Create the sales DataFrame with Product and Amount columns
# Your code here

Need a hint?

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

2

Set the sales amount threshold

Create a variable called threshold and set it to 25 to filter sales above this amount.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Date', 'Eggplant'],
    'Amount': [50, 30, 20, 40, 10]
})
# Create threshold variable and set to 25
# Your code here

Need a hint?

Just assign the number 25 to a variable named threshold.

3

Filter sales using query()

Use query() on the sales DataFrame to create a new DataFrame called filtered_sales that only has rows where Amount is greater than threshold.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Date', 'Eggplant'],
    'Amount': [50, 30, 20, 40, 10]
})
threshold = 25
# Use query() to filter sales where Amount > threshold
# Your code here

Need a hint?

Use sales.query('Amount > @threshold') to filter rows where Amount is greater than threshold. The @ symbol lets you use the variable threshold inside the query string.

4

Print the filtered sales

Print the filtered_sales DataFrame to see the rows where sales amount is greater than 25.

Pandas

import pandas as pd
sales = pd.DataFrame({
    'Product': ['Apple', 'Banana', 'Carrot', 'Date', 'Eggplant'],
    'Amount': [50, 30, 20, 40, 10]
})
threshold = 25
filtered_sales = sales.query('Amount > @threshold')
# Print filtered_sales
# Your code here

Need a hint?

Use print(filtered_sales) to show the filtered rows.