熊猫融化从宽到长

>>> df
   ID  Year  Jan_salary  Feb_salary  Mar_salary
0   1  2016        4500        4200        4700
1   2  2016        3800        3600        4400
2   3  2016        5500        5200        5300

>>> melted_df = pd.melt(df,id_vars=['ID','Year'],
                        value_vars=['Jan_salary','Feb_salary','Mar_salary'],
                        var_name='month',value_name='salary')

>>> melted_df
   ID  Year       month  salary
0   1  2016  Jan_salary    4500
1   2  2016  Jan_salary    3800
2   3  2016  Jan_salary    5500
3   1  2016  Feb_salary    4200
4   2  2016  Feb_salary    3600
5   3  2016  Feb_salary    5200
6   1  2016  Mar_salary    4700
7   2  2016  Mar_salary    4400
8   3  2016  Mar_salary    5300

>>> melted_['month'] = melted_['month'].str.replace('_salary','')

>>> import calendar
>>> def mapper(month_abbr):
...     # from http://stackoverflow.com/a/3418092/42346
...     d = {v: str(k).zfill(2) for k,v in enumerate(calendar.month_abbr)}
...     return d[month_abbr]

>>> melted_df['month'] = melted_df['month'].apply(mapper)
>>> melted_df
   ID  Year month  salary
0   1  2016    01    4500
1   2  2016    01    3800
2   3  2016    01    5500
3   1  2016    02    4200
4   2  2016    02    3600
5   3  2016    02    5200
6   1  2016    03    4700
7   2  2016    03    4400
8   3  2016    03    5300