转置/堆栈/取消堆栈 pandas dataframe 同时将字段名称与现有列连接

Question

I have a dataframe that looks something like:

Component   Date         MTD     YTD    QTD   FC
ABC         Jan 2017     56      nan    nan   nan
DEF         Jan 2017     453     nan    nan   nan
XYZ         Jan 2017     657
PQR         Jan 2017     123
ABC         Feb 2017     56     nan    nan   nan
DEF         Feb 2017     456    nan    nan   nan
XYZ         Feb 2017     6234   57
PQR         Feb 2017     123    346
ABC         Dec 2017     56     nan    nan   nan
DEF         Dec 2017     nan    nan    345   324
XYZ         Dec 2017     6234   57
PQR         Dec 2017     nan    346    54654   546

And i would like to transpose this dataframe in such a way that the component becomes the prefix of the existing MTD,QTD, etc columns

so the output expected would be:

Date         ABC_MTD   DEF_MTD   XYZ_MTD   PQR_MTD  ABC_YTD   DEF_YTD   XYZ_YTD    PQR_YTD   etcetc

Jan 2017     56         453        657       123     nan       nan        nan       nan    
Feb 2017     56         456        6234      123     nan       nan        57        346    
Dec 2017     56         nan        6234       nan                         57        346    

I am not sure whether a pivot or stack/unstack would be efficient out here. Thanks in advance.

Answer 1

You could try this:

newdf=df.pivot(values=df.columns[2:], index='Date', columns='Component' )
newdf.columns = ['%s%s' % (b, '_%s' % a if b else '') for a, b in newdf.columns]   #join the multiindex columns names
print(newdf)

Output:

df
   Component       Date     MTD  YTD    QTD   FC
0        ABC 2017-01-01    56.0  NaN    NaN  NaN
1        DEF 2017-01-01   453.0  NaN    NaN  NaN
2        XYZ 2017-01-01   657.0
3        PQR 2017-01-01   123.0
4        ABC 2017-02-01    56.0  NaN    NaN  NaN
5        DEF 2017-02-01   456.0  NaN    NaN  NaN
6        XYZ 2017-02-01  6234.0   57
7        PQR 2017-02-01   123.0  346
8        ABC 2017-12-01    56.0  NaN    NaN  NaN
9        DEF 2017-12-01     NaN  NaN    345  324
10       XYZ 2017-12-01  6234.0   57
11       PQR 2017-12-01     NaN  346  54654  546



newdf
           ABC_MTD DEF_MTD PQR_MTD XYZ_MTD ABC_YTD DEF_YTD PQR_YTD XYZ_YTD ABC_QTD DEF_QTD PQR_QTD XYZ_QTD ABC_FC DEF_FC PQR_FC XYZ_FC
Date
2017-01-01      56     453     123     657     NaN     NaN                     NaN     NaN                    NaN    NaN
2017-02-01      56     456     123    6234     NaN     NaN     346      57     NaN     NaN                    NaN    NaN
2017-12-01      56     NaN     NaN    6234     NaN     NaN     346      57     NaN     345   54654            NaN    324    546