Bite 177. Use Pandas to find most common genres in a movie excel sheet

Another pandas Bite: we took some fake movie data from Mockaroo, an awesome fake data service, and dumped it in an Excel file.

Here is how it looks: sample of the movie data

Complete group_by_genre below doing the following:

  1. Load the data in a pandas DataFrame using read_excel. Check its arguments how to skip rows and cols.
  2. Split the genres, which are now separated by pipe (|) into separate rows. This is not trivial so we provided the explode function mentioned in this article.
  3. Next filter out the 5 rows without a genre = (no genres listed). At this point your DataFrame should have a shape of (rows, columns): (2024, 2)
  4. Lastly group the DataFrame by genre, counting the number of movies for each. Sort the resulting DataFrame on this count descending. This is how it should look: you should see Drama at the top and IMAX at the bottom.

Good luck, have fun and remember: keep calm and code in Python and pandas!

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We use Python 3.7