熊猫-列标题到行值

Question

I'm trying to achieve the following transformation to a pandas DataFrame:

Source DataFrame:

    Food    Type       Eaten 2018-01    Eaten 2018-02   Eaten 2018-03
0   Apple   Fruit      3                4               0
1   Pizza   Fast Food  2                1               3
2   Cake    Desert     3                6               7

Target DataFrame:

        Food    Type        Month      Eaten
0       Apple   Fruit       2018-01    3
1       Apple   Fruit       2018-02    4
2       Apple   Fruit       2018-03    0
3       Pizza   Fast Food   2018-01    2
4       Pizza   Fast Food   2018-02    1
5       Pizza   Fast Food   2018-03    3
6       Cake    Desert      2018-01    3
7       Cake    Desert      2018-02    6
8       Cake    Desert      2018-03    7

The ordering of the target DataFrame is not important.

The Date headers are essenssially beign expanded to multiple rows and we get an entry per month instead of one column per month

Answer 1

This is a typical wide_to_long question

pd.wide_to_long(df,'Eaten ',i=['Food','Type'],j='Month').reset_index()
Out[38]: 
    Food       Type    Month  Eaten 
0  Apple      Fruit  2018-01       3
1  Apple      Fruit  2018-02       4
2  Apple      Fruit  2018-03       0
3  Pizza  Fast Food  2018-01       2
4  Pizza  Fast Food  2018-02       1
5  Pizza  Fast Food  2018-03       3
6   Cake     Desert  2018-01       3
7   Cake     Desert  2018-02       6
8   Cake     Desert  2018-03       7

Answer 2

I believe the melt function also satisfies this. Pandas doc says wide_to_long is more user friendly but the melt function allows more flexibility. With melt:

df.melt(id_vars=['Food','Type'],var_name = 'Month', value_name = 'Eaten')

The id_vars value represents which columns you want to stay put. The remaining columns will be rotated down.