October 2017
Intermediate to advanced
532 pages
16h 10m
English
Content preview from Pandas Cookbook
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How to do it...
- Let's recreate the result from the final step of the Selecting the smallest from the largest recipe:
>>> movie = pd.read_csv('data/movie.csv')>>> movie2 = movie[['movie_title', 'imdb_score', 'budget']]>>> movie_smallest_largest = movie2.nlargest(100, 'imdb_score') \ .nsmallest(5, 'budget')>>> movie_smallest_largest
- Use sort_values to replicate the first part of the expression and grab the first 100 rows with the head method:
>>> movie2.sort_values('imdb_score', ascending=False).head(100)
- Now that we have the top 100 scoring movies, we can use sort_values with head again to grab the lowest five by budget:
>>> movie2.sort_values('imdb_score', ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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