CODEWITHSUNDEEP
pythonpandasmulti-index
darXider
darXider

Reputation: 457

Reshaping a multiindex pandas dataframe

I have a multiindex pandas dataframe that looks like this

 ID            I                   II                  III
 METRIC        a    b    c    d    a    b    c    d    a    b    c    d
 2015-08-01    0    1    2    3    20   21   22   23   40   41   42   43
 2015-08-02    4    5    6    7    24   25   26   27   44   45   46   47
 2015-08-03    8    9    10   11   28   29   30   31   48   49   50   51

where it is indexed by the dates (2015-08-01, 2015-08-02, 2015-08-03, etc.), the first-level columns (I, II, III) are IDs and the second-level columns are corresponding METRICs (a, b, c, d). I would like to reshape it to the following

METRIC               a    b    c    d
ID
I      2015-08-01    0    1    2    3
       2015-08-02    4    5    6    7
       2015-08-03    8    9    10   11
II     2015-08-01    20   21   22   23
       2015-08-02    24   25   26   27
       2015-08-03    28   29   30   31
III    2015-08-01    40   41   42   43
       2015-08-02    44   45   46   47
       2015-08-03    48   49   50   51

I have (unsuccessfully) looked into using .pivot, .stack, and .melt, but they don't give me what I am looking for. I currently loop over IDs and build a list of dataframes and concat them together as a new dataframe to get what I want.

Any suggestions would be greatly appreciated.

Upvotes: 8

Views: 4124

Answers (3)

Frank
Frank

Reputation: 515

Using @piRSquared's method, we can skip the transpose, just df.unstack().unstack(1)

Upvotes: 0

piRSquared
piRSquared

Reputation: 294238

You can let transpose or T do some of the work for you.

df.T.stack().unstack(1)

METRIC           a   b   c   d
ID                            
I   2015-08-01   0   1   2   3
    2015-08-02   4   5   6   7
    2015-08-03   8   9  10  11
II  2015-08-01  20  21  22  23
    2015-08-02  24  25  26  27
    2015-08-03  28  29  30  31
III 2015-08-01  40  41  42  43
    2015-08-02  44  45  46  47
    2015-08-03  48  49  50  51

Upvotes: 4

Scott Boston
Scott Boston

Reputation: 153460

Let's use stack, swaplevel and sort_index:

df.stack(0).swaplevel(0,1).sort_index()

Output:

METRIC           a   b   c   d
ID                            
I   2015-08-01   0   1   2   3
    2015-08-02   4   5   6   7
    2015-08-03   8   9  10  11
II  2015-08-01  20  21  22  23
    2015-08-02  24  25  26  27
    2015-08-03  28  29  30  31
III 2015-08-01  40  41  42  43
    2015-08-02  44  45  46  47
    2015-08-03  48  49  50  51

Upvotes: 10

Related Questions