Finding the missing values

While having a summary of how much of your data is missing can be useful, often you will need to find the exact locations of these missing values. Using the same subset of the StackOverflow data from the last exercise (sub_df), you will show how a value can be flagged as missing.

This exercise is part of the course

Feature Engineering for Machine Learning in Python

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Hands-on interactive exercise

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

# Print the top 10 entries of the DataFrame
print(sub_df.____)