Extracting datetime components

There are several columns in the volunteer dataset comprised of datetimes. Let's take a look at the start_date_date column and extract just the month to use as a feature for modeling.

This exercise is part of the course

Preprocessing for Machine Learning in Python

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Exercise instructions

Convert the start_date_date column into a pandas datetime column and store it in a new column called start_date_converted.
Retrieve the month component of start_date_converted and store it in a new column called start_date_month.
Print the .head() of just the start_date_converted and start_date_month columns.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# First, convert string column to date column
volunteer["start_date_converted"] = pd.____(____)

# Extract just the month from the converted column
volunteer["start_date_month"] = volunteer[____].____

# Take a look at the converted and new month columns
print(volunteer[[____, ____]].____)

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