How to pivot multilabel table in pandas

Question

I am trying to import my data regarding the changes of price of different items. The data is kept in MySQL. I have imported the input dataframe df in a stacked format similar to the following:

 ID    Type      Date      Price1   Price2
0001    A     2001-09-20    30       301
0002    A     2001-09-21    31       278
0003    A     2001-09-22    28       299
0004    B     2001-09-18    18       159
0005    B     2001-09-20    21       157
0006    B     2001-09-21    21       162
0007    C     2001-09-19    58       326
0008    C     2001-09-20    61       410
0009    C     2001-09-21    67       383

And, in order to perform time series analysis, I want to convert to another format similar to:

               A               B              C
             Price1  Price2  Price1  Price2  Price1  Price2
Date   
2001-09-18   NULL     NULL    18       159    NULL    NULL
2001-09-19   NULL     NULL   NULL     NULL     58     326
2001-09-20   30       301    21        157     61     410
2001-09-21   31       278    21        168     67     383
2001-09-22   28       299    NULL     NULL    NULL    NULL

I have looked at this question . Both of the suggested ways were not what I want to achieve. The pandas documentation regarding pivot doesn't seems to mention anything about this either.

Answer 1

You can reshape by pivot or set_index with unstack , but then need swaplevel with sort_index for expected Multiindex in columns:

df1 = (df.drop('ID', axis=1)
         .pivot('Date','Type')
         .swaplevel(0,1, axis=1)
         .sort_index(axis=1))

---

df1 = (df.drop('ID', axis=1)
         .set_index(['Date','Type'])
         .unstack()
         .swaplevel(0,1, axis=1)
         .sort_index(axis=1))

---

df1 = (df.set_index(['Date','Type'])[['Price1','Price2']]
         .unstack()
         .swaplevel(0,1, axis=1)
         .sort_index(axis=1))

---

print (df1)
Type            A             B             C       
           Price1 Price2 Price1 Price2 Price1 Price2
Date                                                
2001-09-18    NaN    NaN   18.0  159.0    NaN    NaN
2001-09-19    NaN    NaN    NaN    NaN   58.0  326.0
2001-09-20   30.0  301.0   21.0  157.0   61.0  410.0
2001-09-21   31.0  278.0   21.0  162.0   67.0  383.0
2001-09-22   28.0  299.0    NaN    NaN    NaN    NaN