In pandas, how do I get multiple slices of a MultiIndexed-dataframe at a time?

Question

In pandas, I’m familiar with how to slice a Multi-Index with a list to get multiple values, like such:

(Pdb) df = pd.DataFrame({"A": range(0,10), "B": -1, "C": range(20,30), "D": range(30,40), "E":range(40,50)}).set_index(["A", "B", "C"])
(Pdb) df
          D   E
A B  C         
0 -1 20  30  40
1 -1 21  31  41
2 -1 22  32  42
3 -1 23  33  43
4 -1 24  34  44
5 -1 25  35  45
6 -1 26  36  46
7 -1 27  37  47
8 -1 28  38  48
9 -1 29  39  49
(Pdb) df.loc[ [0,1,2]]
          D   E
A B  C         
0 -1 20  30  40
1 -1 21  31  41
2 -1 22  32  42

But how can I do this for multiple levels at a time?

(Pdb) df.loc[ [0,1,2], -1]
*** KeyError: -1

Or ideally:

(Pdb) df.loc[ [0,1,2], [-1]]
*** KeyError: "None of [Int64Index([-1], dtype='int64')] are in the [columns]"

Asked By: YGA

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Source

Answer 1

You have to use tuple to slice your dataframe and you have to specify both index and columns indexes to allow Pandas to slice correctly your dataframes:

#               A       B   v-- all columns
>>> df.loc[([0, 1, 2], -1), :]
          D   E
A B  C         
0 -1 20  30  40
1 -1 21  31  41
2 -1 22  32  42

#               A        all B           C         v-- all columns
>>> df.loc[([0, 1, 2], slice(None), [20, 22, 24]), :]
          D   E
A B  C         
0 -1 20  30  40
2 -1 22  32  42

More information: MultiIndex / advanced indexing

Answered By: Corralien

In pandas, how do I get multiple slices of a MultiIndexed-dataframe at a time?

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