Turn Pandas Multi-Index into column

Question

I have a dataframe with 2 index levels                            value Trial    measurement     1              0        13                    1         3                    2         4     2              0       NaN                    1        12     3              0        34    Which I want to turn into this   Trial    measurement       value      1              0        13     1              1         3     1              2         4     2              0       NaN     2              1        12     3              0        34    How can I best do this      I need this because I want to aggregate the data as instructed here  but I can t select my columns like that if they are in use as indices

User · Answer

As  cs95 mentioned in a comment  to drop only one level  use    df reset index level         This avoids having to redefine your desired index after reset

User · Answer

I ran into Karl s issue as well  I just found myself renaming the aggregated column then resetting the index  df   pd DataFrame df groupby   arms    success     success   sum    rename columns   success   sum      df   df reset index

User · Answer

This doesn t really apply to your case but could be helpful for others  like myself 5 minutes ago  to know  If one s multindex have the same name like this                            value Trial        Trial     1              0        13                    1         3                    2         4     2              0       NaN                    1        12     3              0        34    df reset index inplace True  will fail  cause the columns that are created cannot have the same names   So then you need to rename the multindex with df index   df index set names   Trial    measurement    to get                              value Trial    measurement             1              0        13     1              1         3     1              2         4     2              0       NaN     2              1        12     3              0        34    And then df reset index inplace True  will work like a charm    I encountered this problem after grouping by year and month on a datetime-column not index  called live date  which meant that both year and month were named live date

User · Answer

The reset index   is a pandas DataFrame method that will transfer index values into the DataFrame as columns   The default setting for the parameter is drop False  which will keep the index values as columns    All you have to do add  reset index inplace True  after the name of the DataFrame   df reset index inplace True

User · Answer

There may be situations when df reset index   cannot be used  e g   when you need the index  too   In this case  use index get level values   to access index values directly  df  Trial     df index get level values 0  df  measurement     df index get level values 1   This will assign index values to individual columns and keep the index  See the docs for further info

[python] Turn Pandas Multi-Index into column

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