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Software ==>	Python (34 exercises)
Topic ==>	Overview of Pandas (3 exercises)
Level ==>	Harder than average
Subject ==>	Python training

Rename the columns in a dataframe of the most-viewed Netflix series and filter the rows

This exercise is provided to allow potential course delegates to choose the correct Wise Owl Microsoft training course, and may not be reproduced in whole or in part in any format without the prior written consent of Wise Owl.

Before you can do this exercise, you'll need to download and unzip this file.

Load the most-watched Netflix series of all time at the time of writing (as given by Wikipedia) into a pandas dataframe.

Rename the last two columns as follows:

Old name	New name
Title	Series name
Hours (millions)	Million hours

Print out your dataframe - it should start something like this:

Proving that nothing sells better than violence and horror?

Now sort the series alphabetically by series name, and within each series in descending order of season/part number.

Use iloc to slice this new sorted dataframe, printing out just the first 2 columns:

The series sorted by name and number.

Use the iterrrows() method to loop over the rows of the dataframe, printing out only those whose genre contains the word Horror:

This should be the output from this part of the program.

Still too easy? Try filtering the dataframe to contain only those series whose titles contain the letter u:

Make sure your program picks up on all 3 of these!

The only way Wise Owl could find to do this using filtering was to take the series, convert it to a string, convert this to upper text, convert this to a string again (otherwise you're left with a series object) and then see if this contains the letter u. If you find an easier way - and you probably will - let your trainer know!

Save and close your program.

You can unzip this file to see the answers to this exercise, although please remember this is for your personal use only.

You can find other training resources for the subject of this exercise here:

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