Date arithmetic with timedelta in Pandas - Mini Project: Build & Apply

Date Arithmetic with timedelta in pandas

📖 Scenario: You work in a small delivery company. You have a list of package shipment dates. You want to find out the expected delivery dates by adding a fixed number of days to each shipment date.

🎯 Goal: Build a pandas DataFrame with shipment dates, add a timedelta to calculate expected delivery dates, and display the results.

📋 What You'll Learn

Create a pandas DataFrame with shipment dates

Create a timedelta variable representing the delivery time

Add the timedelta to each shipment date to get expected delivery dates

Print the DataFrame showing shipment and expected delivery dates

💡 Why This Matters

🌍 Real World

Delivery companies often need to calculate expected delivery dates by adding fixed transit times to shipment dates.

💼 Career

Data analysts and scientists use date arithmetic to analyze timelines, schedules, and deadlines in many industries.

1

Create a pandas DataFrame with shipment dates

Import pandas as pd and create a DataFrame called shipments with a column 'shipment_date' containing these exact dates as strings: '2024-06-01', '2024-06-05', '2024-06-10'.

Pandas

import pandas as pd
# Create the DataFrame called shipments with shipment_date column
# Your code here

Hint

Use pd.DataFrame with a dictionary where the key is 'shipment_date' and the value is the list of date strings.

2

Convert shipment_date to datetime and create timedelta

Convert the 'shipment_date' column in shipments to datetime type using pd.to_datetime(). Then create a variable called delivery_time that is a pd.Timedelta of 7 days.

Pandas

import pandas as pd

shipments = pd.DataFrame({
    'shipment_date': ['2024-06-01', '2024-06-05', '2024-06-10']
})

# Convert shipment_date to datetime
# Create delivery_time as 7 days timedelta
# Your code here

Hint

Use pd.to_datetime() to convert the column. Use pd.Timedelta(days=7) to create the timedelta.

3

Calculate expected delivery dates by adding timedelta

Create a new column in shipments called 'expected_delivery' by adding the delivery_time timedelta to the 'shipment_date' column.

Pandas

import pandas as pd

shipments = pd.DataFrame({
    'shipment_date': ['2024-06-01', '2024-06-05', '2024-06-10']
})

shipments['shipment_date'] = pd.to_datetime(shipments['shipment_date'])
delivery_time = pd.Timedelta(days=7)

# Add delivery_time to shipment_date to create expected_delivery
# Your code here

Hint

Use simple addition of the timedelta to the datetime column to create the new column.

4

Print the DataFrame with shipment and expected delivery dates

Print the shipments DataFrame to show the 'shipment_date' and 'expected_delivery' columns.

Pandas

import pandas as pd

shipments = pd.DataFrame({
    'shipment_date': ['2024-06-01', '2024-06-05', '2024-06-10']
})

shipments['shipment_date'] = pd.to_datetime(shipments['shipment_date'])
delivery_time = pd.Timedelta(days=7)

shipments['expected_delivery'] = shipments['shipment_date'] + delivery_time

# Print the shipments DataFrame
# Your code here

Hint

Use print(shipments) to display the DataFrame.

Practice

1. What does pd.Timedelta(days=3) represent in pandas?

easy

A. A string describing 3 days

B. A specific date 3 days from now

C. A time difference of 3 days

D. A timestamp at 3 AM

Solution

1. Step 1: Understand Timedelta purpose

   pd.Timedelta is used to represent a duration or difference in time, not a fixed date or time.

2. Step 2: Interpret the argument

   The argument days=3 means the duration is 3 days long.

3. Final Answer:

   A time difference of 3 days -> Option C

4. Quick Check:

   Timedelta(days=3) = 3 days [OK]

Hint: Timedelta means duration, not a fixed date [OK]

Common Mistakes:

• Thinking Timedelta is a fixed date
• Confusing Timedelta with Timestamp
• Assuming it returns a string

2. Which of the following is the correct way to add 5 days to a pandas Timestamp ts?

easy

A. ts.add(pd.Timedelta(5))

B. ts + pd.Timedelta('5')

C. ts + pd.Timedelta(5 days)

D. ts + pd.Timedelta(days=5)

Solution

1. Step 1: Check correct Timedelta syntax

   The correct way to specify 5 days is pd.Timedelta(days=5). The argument must be named or a valid string.

2. Step 2: Verify addition syntax

   Adding a Timedelta to a Timestamp uses the + operator, so ts + pd.Timedelta(days=5) is correct.

3. Final Answer:

   ts + pd.Timedelta(days=5) -> Option D

4. Quick Check:

   Correct syntax uses days=5 inside Timedelta [OK]

Hint: Use named argument days=5 inside Timedelta [OK]

Common Mistakes:

• Missing quotes or wrong argument format
• Using add() method incorrectly
• Passing string without units

3. What is the output of this code?

import pandas as pd
start = pd.Timestamp('2024-01-01')
new_date = start + pd.Timedelta(days=10) - pd.Timedelta(days=3)
print(new_date.strftime('%Y-%m-%d'))

medium

A. 2024-01-08

B. 2024-01-13

C. 2024-01-04

D. 2024-01-10

Solution

1. Step 1: Calculate addition of 10 days

   Starting from 2024-01-01, adding 10 days gives 2024-01-11.

2. Step 2: Subtract 3 days from the result

   Subtracting 3 days from 2024-01-11 results in 2024-01-08.

3. Final Answer:

   2024-01-08 -> Option A

4. Quick Check:

   2024-01-01 + 10 - 3 days = 2024-01-08 [OK]

Hint: Add then subtract days stepwise to find final date [OK]

Common Mistakes:

• Adding and subtracting days in wrong order
• Miscounting days
• Confusing string formatting output

4. The following code throws an error. What is the problem?

import pandas as pd
start = pd.Timestamp('2024-05-01')
new_date = start + pd.Timedelta(5)
print(new_date)

medium

A. Timedelta needs a unit like days=5

B. Timestamp cannot be added to Timedelta

C. pd.Timedelta requires string input only

D. Missing import for Timedelta

Solution

1. Step 1: Check Timedelta argument

   pd.Timedelta(5) is missing the unit. It needs a keyword like days=5 or a string like '5 days'.

2. Step 2: Understand error cause

   Without specifying units, pandas cannot interpret the number 5 alone, causing an error.

3. Final Answer:

   Timedelta needs a unit like days=5 -> Option A

4. Quick Check:

   Timedelta(5) missing units causes error [OK]

Hint: Always specify units when creating Timedelta [OK]

Common Mistakes:

• Passing integer without units
• Assuming default unit is days
• Confusing Timestamp and Timedelta usage

5. You have a pandas DataFrame df with a column 'date' of type datetime. You want to create a new column 'date_plus_7' that adds 7 days to each date. Which code correctly does this?

hard

A. df['date_plus_7'] = df['date'] + pd.Timedelta('7 days')

B. df['date_plus_7'] = df['date'] + pd.Timedelta(days=7)

C. df['date_plus_7'] = df['date'] + pd.Timedelta(7)

D. df['date_plus_7'] = df['date'] + pd.Timedelta(days=7) * len(df)

Solution

1. Step 1: Understand Timedelta broadcasting

   Adding a Timedelta to a pandas Series of dates works if the Timedelta is a scalar (single duration).

2. Step 2: Check each option

   df['date_plus_7'] = df['date'] + pd.Timedelta('7 days') uses a string '7 days' which works but is less common in vectorized operations. df['date_plus_7'] = df['date'] + pd.Timedelta(days=7) uses pd.Timedelta(days=7) which is the standard and recommended way. df['date_plus_7'] = df['date'] + pd.Timedelta(7) misses units and causes error. df['date_plus_7'] = df['date'] + pd.Timedelta(days=7) * len(df) multiplies timedelta by length, which incorrectly scales the timedelta.

3. Step 3: Choose the best practice

   df['date_plus_7'] = df['date'] + pd.Timedelta(days=7) is the correct and recommended way to add 7 days to each date in a column.

4. Final Answer:

   df['date_plus_7'] = df['date'] + pd.Timedelta(days=7) -> Option B

5. Quick Check:

   Use pd.Timedelta(days=7) for vectorized addition with Series [OK]

Hint: Use pd.Timedelta(days=7) for vectorized addition with Series [OK]

Common Mistakes:

• Passing integer without units
• Multiplying Timedelta by length of DataFrame
• Not using vectorized Timedelta correctly