The following is a pandas multi-level grouping method to implement sorting. It has a good reference value and I hope it will be helpful to everyone. Let’s take a look together
pandas has groupby grouping function and sort_values sorting function, but how to sort the dataframe after grouping?
In [70]: df = pd.DataFrame(((random.randint(2012, 2016), random.choice(['tech', 'art', 'office']), '%dk-%dk'%(random.randint(2,10), random.randint(10, 20)), '') for _ in xrange(10000)), columns=['publish_time', 'classf', 'salary', 'title'])
In [71]: df.head()
Out[71]:
publish_time classf salary title
0 2012 art 2k-19k
1 2014 office 5k-17k
2 2013 office 2k-10k
3 2013 art 5k-14k
4 2013 art 2k-14k
In [72]: df.groupby(['publish_time', 'classf', 'salary']).count()['title'].groupby(level=0, group_keys=False).nlargest(10)
Out[72]:
publish_time classf salary
2012 art 7k-13k 18
4k-13k 16
tech 3k-12k 14
art 6k-16k 13
8k-15k 13
office 5k-18k 13
tech 4k-14k 13Related recommendations:
pandas implements deduplication of duplicate tables and re-converts them into tables
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