In Pandas How to sort one level of a multi-index based on the values of a column, while maintaining the grouping of the other level
multi-index, pandas, python, sorting
Solution
You're looking for sort:
In [11]: s = pd.Series([3, 1, 2], [[1, 1, 2], [1, 3, 1]])
In [12]: s.sort()
In [13]: s
Out[13]:
1 3 1
2 1 2
1 1 3
dtype: int64
Note; this works inplace (i.e. modifies s), to return a copy use order:
In [14]: s.order()
Out[14]:
1 3 1
2 1 2
1 1 3
dtype: int64
Update: I realised what you were actually asking, and I think this ought to be an option in sortlevels, but for now I think you have to reset_index, groupby and apply:
In [21]: s.reset_index(name='s').groupby('level_0').apply(lambda s: s.sort('s')).set_index(['level_0', 'level_1'])['s']
Out[21]:
level_0 level_1
1 3 1
1 3
2 1 2
Name: 0, dtype: int64
Note: you can set the level names to [None, None] afterwards.
Problem
I'm taking a Data Mining course at university right now, but I'm a wee bit stuck on a multi-index sorting problem. The actual data involves about 1 million reviews of movies, and I'm trying to analyze that based on American zip codes, but to test out how to do what I want, I've been using a much smaller data set of 250 randomly generated ratings for 10 movies and instead of zip codes, I'm using age groups. So this is what I have right now, it's a multiindexed DataFrame in Pandas with two levels, 'group' and 'title' ``` rating group title Alien 4.000000 Argo 2.166667 Adults Ben-Hur 3.666667 Gandhi 3.200000 ... ... Alien 3.000000 Argo 3.750000 Coeds Ben-Hur 3.000000 Gandhi 2.833333 ... ... Alien 2.500000 Argo 2.750000 Kids Ben-Hur 3.000000 Gandhi 3.200000 ... ... ``` What I'm aiming for is to sort the titles based on their rating within the group (and only show the most popular 5 or so titles within each group) So something like this (but I'm only going to show two titles in each group): ``` rating group title Alien 4.000000 Adults Ben-Hur 3.666667 Argo 3.750000 Coeds Alien 3.000000 Gandhi 3.200000 Kids Ben-Hur 3.000000 ``` Anyone know how to do this? I've tried sort_order, sort_index, etc and swapping the levels, but they mix up the groups too. So it then looks like: ``` rating group title Adults Alien 4.000000 Coeds Argo 3.750000 Adults Ben-Hur 3.666667 Kids Gandhi 3.666667 Coeds Alien 3.000000 Kids Ben-Hur 3.000000 ``` I'm kind of looking for something like this: Multi-Index Sorting in Pandas, but instead of sorting based on another level, I want to sort based on the values. Kind of like if that person wanted to sort based on his sales column. Thanks!