Date arithmetic (Timedelta) in Data Analysis Python - Mini Project: Build & Apply

Date Arithmetic with Timedelta in Python

📖 Scenario: Imagine you work in a library. You have a list of books with their borrow dates. You want to find out when each book should be returned by adding a fixed borrowing period.

🎯 Goal: You will create a dictionary of books with their borrow dates, set a borrowing period, calculate the return dates by adding the borrowing period to each borrow date, and finally display the return dates.

📋 What You'll Learn

Create a dictionary with book titles as keys and borrow dates as datetime objects as values

Create a variable for the borrowing period using timedelta

Calculate return dates by adding the borrowing period to each borrow date using a dictionary comprehension

Print the dictionary of return dates

💡 Why This Matters

🌍 Real World

Libraries, rental services, and any system that tracks borrowed items use date arithmetic to calculate due dates.

💼 Career

Understanding date arithmetic is important for data analysts and scientists working with time series data, scheduling, and event tracking.

1

Create the dictionary of borrow dates

Create a dictionary called borrow_dates with these exact entries: 'Book A': datetime(2024, 6, 1), 'Book B': datetime(2024, 6, 3), 'Book C': datetime(2024, 6, 5). Import datetime from the datetime module.

Data Analysis Python

from datetime import datetime
# Create the borrow_dates dictionary with exact entries
# Your code here

Hint

Use datetime(2024, 6, 1) to create the date for June 1, 2024.

2

Set the borrowing period

Import timedelta from the datetime module and create a variable called borrow_period that represents 14 days.

Data Analysis Python

from datetime import datetime, timedelta
borrow_dates = {
    'Book A': datetime(2024, 6, 1),
    'Book B': datetime(2024, 6, 3),
    'Book C': datetime(2024, 6, 5)
}
# Create borrow_period as timedelta of 14 days
# Your code here

Hint

Use timedelta(days=14) to represent 14 days.

3

Calculate return dates using dictionary comprehension

Create a new dictionary called return_dates using a dictionary comprehension. For each book and borrow_date in borrow_dates.items(), add borrow_period to borrow_date.

Data Analysis Python

from datetime import datetime, timedelta
borrow_dates = {
    'Book A': datetime(2024, 6, 1),
    'Book B': datetime(2024, 6, 3),
    'Book C': datetime(2024, 6, 5)
}
borrow_period = timedelta(days=14)
# Create return_dates dictionary by adding borrow_period to each borrow_date
# Your code here

Hint

Use {book: borrow_date + borrow_period for book, borrow_date in borrow_dates.items()} to create the new dictionary.

4

Print the return dates

Print the return_dates dictionary to see the calculated return dates.

Data Analysis Python

from datetime import datetime, timedelta
borrow_dates = {
    'Book A': datetime(2024, 6, 1),
    'Book B': datetime(2024, 6, 3),
    'Book C': datetime(2024, 6, 5)
}
borrow_period = timedelta(days=14)
return_dates = {book: borrow_date + borrow_period for book, borrow_date in borrow_dates.items()}
# Print the return_dates dictionary
# Your code here

Hint

Use print(return_dates) to display the dictionary.