loc vs iloc mental model in Pandas - Hands-On Comparison

Understanding loc vs iloc in pandas

📖 Scenario: You work in a small shop and keep track of daily sales in a table. You want to learn how to pick data from this table using two different methods: loc and iloc.

🎯 Goal: Learn how to select rows and columns from a pandas DataFrame using loc (label-based) and iloc (position-based) to understand their differences.

📋 What You'll Learn

Create a pandas DataFrame with specific sales data

Create a variable to select a specific row label

Use loc to select data by label

Use iloc to select data by position

Print the selected data to compare results

💡 Why This Matters

🌍 Real World

In real life, data tables often have labels like dates or names. Knowing how to pick data by label or by position helps you get exactly what you want.

💼 Career

Data scientists and analysts frequently use <code>loc</code> and <code>iloc</code> to filter and select data efficiently for analysis and reporting.

1

Create the sales DataFrame

Create a pandas DataFrame called sales with these exact data: rows labeled "Mon", "Tue", "Wed", columns "apples" and "oranges", and values: Mon: 3, 2; Tue: 5, 1; Wed: 2, 4.

Pandas

import pandas as pd
# Create the DataFrame 'sales' with the given data and labels
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary for columns and index for row labels.

2

Set the row label to select

Create a variable called day_label and set it to the string "Tue" to select Tuesday's sales by label.

Pandas

import pandas as pd
sales = pd.DataFrame({"apples": [3, 5, 2], "oranges": [2, 1, 4]}, index=["Mon", "Tue", "Wed"])
# Create variable 'day_label' with value 'Tue'
# Your code here

Need a hint?

Just assign the string "Tue" to day_label.

3

Select Tuesday's sales using loc and iloc

Use loc with day_label to select Tuesday's sales by label and save it in sales_loc. Use iloc with the integer 1 to select Tuesday's sales by position and save it in sales_iloc.

Pandas

import pandas as pd
sales = pd.DataFrame({"apples": [3, 5, 2], "oranges": [2, 1, 4]}, index=["Mon", "Tue", "Wed"])
day_label = "Tue"
# Use loc with day_label to get sales_loc
# Use iloc with 1 to get sales_iloc
# Your code here

Need a hint?

Use sales.loc[day_label] and sales.iloc[1] to select the row.

4

Print the selected sales data

Print sales_loc and sales_iloc to see the sales for Tuesday selected by label and by position.

Pandas

import pandas as pd
sales = pd.DataFrame({"apples": [3, 5, 2], "oranges": [2, 1, 4]}, index=["Mon", "Tue", "Wed"])
day_label = "Tue"
sales_loc = sales.loc[day_label]
sales_iloc = sales.iloc[1]
# Print sales_loc and sales_iloc
# Your code here

Need a hint?

Use two print() statements, one for each variable.