Merging the output of one table to another in the column format

Question

I have a data frame which looks like this:

Plant       Date        Item          unitsSold
1          10-oct        A               15        
1          11-Oct        A               20
1          12-Oct        A               10
2          10-Oct        B               19
2          11-Oct        A               20
2          12-Oct        C               10

And another data set which look like this:

Plant       Date         Item        unit Price
1          10-Oct        A,B           10            ---That means both A and B have same unit price
1          11-Oct         A            14
1          12-Oct        A,B,C         10            ----That means both A, B and C have same price
2          10-oct        A,B,C         15
2          11-Oct         A            10
3          12-Oct        A,C           20

Now i want my output to look like this:

Plant       Date         Item        unit Price      A.UnitsSold        B.Unitssold          C.unitssold
1          10-Oct        A,B           10            15                    0                     0    --Since only a was sold on 10-oct
1          11-Oct         A            14            20                    0                     0
1          12-Oct        A,B,C         10            10                    0                     0   
2          10-oct        A,B,C         15            0                     19                    0
2          11-Oct         A            10            20                    0                     0
3          12-Oct        A,C           20            0                     0                     10

Can anyone please tell me how to get the columns for unit sold. Note- there can be any number of style

Answer 1

df1.merge(df2, left_on='lkey', right_on='rkey') YOU CAN get an idea from this merge code or this question:

might helps : stackoverflow.com/questions/37113173/…

Answer 2

Merging with column

df_new =pd.concat([df1, df2], axis=1)