pandas pivot table to data frame [duplicate]

After pivoting, convert the dataframe to records and then back to dataframe:

flattened = pd.DataFrame(pivoted.to_records())#   subject        date  ('pills', 250)  ('pills', 500)  ('pills', 1000)#0        1  10/10/2012             4.0             NaN              NaN#1        1  10/11/2012             4.0             NaN              NaN#2        1  10/12/2012             NaN             2.0              NaN#3        2    1/6/2014             NaN             NaN              1.0#4        2    1/7/2014             1.0             1.0              NaN#5        2    1/8/2014             3.0             NaN              NaN

You can now "repair" the column names, if you want:

flattened.columns = [hdr.replace("('pills', ", "strength.").replace(")", "") \                     for hdr in flattened.columns]flattened#   subject        date  strength.250  strength.500  strength.1000#0        1  10/10/2012           4.0           NaN            NaN#1        1  10/11/2012           4.0           NaN            NaN#2        1  10/12/2012           NaN           2.0            NaN#3        2    1/6/2014           NaN           NaN            1.0#4        2    1/7/2014           1.0           1.0            NaN#5        2    1/8/2014           3.0           NaN            NaN

It's awkward, but it works.