iloc for position-based selection in Pandas - Mini Project: Build & Apply

Using iloc for Position-Based Selection in pandas

📖 Scenario: You work in a small bookstore. You have a list of books with their prices and stock counts. You want to select specific rows and columns by their position to analyze the data.

🎯 Goal: Learn how to use iloc in pandas to select rows and columns by their integer position.

📋 What You'll Learn

Create a pandas DataFrame with book data

Create a variable for row and column positions

Use iloc to select data by position

Print the selected data

💡 Why This Matters

🌍 Real World

Selecting data by position is useful when you do not know the exact labels or want to quickly access data by order, such as recent sales or top products.

💼 Career

Data analysts and scientists often use iloc to slice and dice data efficiently when working with large datasets.

1

Create the book DataFrame

Import pandas as pd and create a DataFrame called books with these exact data: columns 'Title', 'Price', 'Stock' and rows: 'Python Basics' priced 25 with 10 in stock, 'Data Science' priced 40 with 5 in stock, and 'Machine Learning' priced 50 with 2 in stock.

Pandas

# Import pandas and create the DataFrame books with the given data
# Your code here

Need a hint?

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

2

Set row and column positions

Create two variables: row_pos and col_pos. Set row_pos to 1 to select the second row, and col_pos to 2 to select the third column.

Pandas

import pandas as pd

books = pd.DataFrame({
    'Title': ['Python Basics', 'Data Science', 'Machine Learning'],
    'Price': [25, 40, 50],
    'Stock': [10, 5, 2]
})

# Create variables row_pos and col_pos with values 1 and 2
# Your code here

Need a hint?

Remember, Python counting starts at 0, so 1 means the second row.

3

Select data using iloc

Use iloc on the books DataFrame with row_pos and col_pos to select the value at that row and column position. Store the result in a variable called selected_value.

Pandas

import pandas as pd

books = pd.DataFrame({
    'Title': ['Python Basics', 'Data Science', 'Machine Learning'],
    'Price': [25, 40, 50],
    'Stock': [10, 5, 2]
})

row_pos = 1
col_pos = 2

# Use iloc with row_pos and col_pos to get the value
# Your code here

Need a hint?

Use books.iloc[row_pos, col_pos] to select by position.

4

Print the selected value

Print the variable selected_value to display the stock count of the second book.

Pandas

import pandas as pd

books = pd.DataFrame({
    'Title': ['Python Basics', 'Data Science', 'Machine Learning'],
    'Price': [25, 40, 50],
    'Stock': [10, 5, 2]
})

row_pos = 1
col_pos = 2

selected_value = books.iloc[row_pos, col_pos]

# Print the selected_value
# Your code here

Need a hint?

Use print(selected_value) to show the result.