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
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.____)