python 2.7 - Reshaping Pandas data frame (a complex case!) -

i want reshape following data frame:

 index   id     numbers 1111    5      58.99 2222    5      75.65 1000    4      66.54  11      4      60.33 143     4      62.31 145     51     30.2 1       7      61.28

the reshaped data frame should following:

 id   1       2        3  5    58.99   75.65    nan 4    66.54   60.33    62.31 51   30.2    nan      nan 7    61.28   nan      nan

i use following code this.

import pandas pd dtframe = pd.read_csv("data.csv") ids = dtframe['id'].unique() temp = dtframe.groupby(['id']) temp2 = {} in ids:     temp2[i]= temp.get_group(i).reset_index()['numbers']  dtframe = pd.dataframe.from_dict(temp2) dtframe = dtframe.t 

although above code solve problem there more simple way achieve this. tried pivot table not solve problem perhaps requires have same number of element in each group. or may there way not aware of, please share thoughts it.

in [69]: df.groupby(df['id'])['numbers'].apply(lambda x: pd.series(x.values)).unstack() out[69]:          0      1      2 id                      4   66.54  60.33  62.31 5   58.99  75.65    nan 7   61.28    nan    nan 51  30.20    nan    nan 

this quite similar doing except loop replaced apply. pd.series(x.values) has index default ranges on integers starting @ 0. index values become column names (above). doesn't matter various groups may have different lengths. apply method aligns various indices (and fills missing values nan). convenience!

i learned trick here.