Turn Pandas Multi-Index into column

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)  

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:

                         valueTrial        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:

                           valueTrial    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.

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.