to_datetime() for parsing dates in Pandas - Mini Project: Build & Apply

Parsing Dates with pandas to_datetime()

📖 Scenario: You work in a small business that tracks customer orders. The order dates are stored as text, but you want to analyze them as real dates to find trends.

🎯 Goal: You will convert a list of order date strings into proper date objects using pandas to_datetime(). This will help you work with dates easily.

📋 What You'll Learn

Create a pandas DataFrame with order IDs and order date strings

Create a variable for the date column name

Use pandas to_datetime() to convert the date strings to datetime objects

Print the DataFrame to see the converted dates

💡 Why This Matters

🌍 Real World

Businesses often receive dates as text from forms or files. Converting them to datetime lets you analyze sales trends, delays, or seasonal patterns.

💼 Career

Data analysts and scientists frequently clean and prepare date data before analysis. Knowing how to parse dates is a key skill in data cleaning.

1

Create the orders DataFrame

Create a pandas DataFrame called orders with two columns: 'order_id' containing [101, 102, 103] and 'order_date' containing ['2024-01-15', '2024-02-20', '2024-03-10'].

Pandas

# Create the orders DataFrame with order_id and order_date columns
# Your code here

Need a hint?

Use pd.DataFrame with a dictionary containing the two columns and their values.

2

Set the date column name

Create a variable called date_column and set it to the string 'order_date'.

Pandas

import pandas as pd

orders = pd.DataFrame({
    'order_id': [101, 102, 103],
    'order_date': ['2024-01-15', '2024-02-20', '2024-03-10']
})

# Create the variable date_column with value 'order_date'
# Your code here

Need a hint?

Just assign the string 'order_date' to the variable date_column.

3

Convert the order_date strings to datetime

Use pandas to_datetime() to convert the orders[date_column] column to datetime objects. Assign the result back to orders[date_column].

Pandas

import pandas as pd

orders = pd.DataFrame({
    'order_id': [101, 102, 103],
    'order_date': ['2024-01-15', '2024-02-20', '2024-03-10']
})

date_column = 'order_date'

# Convert orders[date_column] to datetime using pd.to_datetime()
# Your code here

Need a hint?

Use pd.to_datetime() on the column and assign it back to the same column.

4

Print the DataFrame with parsed dates

Print the orders DataFrame to see the order_date column as datetime objects.

Pandas

import pandas as pd

orders = pd.DataFrame({
    'order_id': [101, 102, 103],
    'order_date': ['2024-01-15', '2024-02-20', '2024-03-10']
})

date_column = 'order_date'

orders[date_column] = pd.to_datetime(orders[date_column])

# Print the orders DataFrame
# Your code here

Need a hint?

Use print(orders) to display the DataFrame.