Fill values from one dataframe to another with matching IDs

Question

I have two pandas data frames, I want to get the sum of items_bought for each ID in DF1. Then add a column to DF2 containing the sum of items_bought calculated from DF1 with matching ID else fill it with 0. How can I do this in an elegant and efficient manner?

DF1

ID | items_bought
1        5
3        8
2        2
3        5
4        6
2        2

DF2

ID
1
2
8
3
2

Desired Result: DF2 Becomes

ID | items_bought
1        5
2        4
8        0
3        13
2        4

Answer 1

df1.groupby('ID').sum().loc[df2.ID].fillna(0).astype(int)
Out[104]: 
    items_bought
ID              
1              5
2              4
8              0
3             13
2              4

1. Work on df1 to calculate the sum for each ID .
2. The resulting dataframe is now indexed by ID , so you can select with df2 IDs by calling loc .
3. Fill the gaps with fillna .
4. NA are handled by float type. Now that they are removed, convert the column back to integer.

Answer 2

Solution with groupby and sum , then reindex with fill_value=0 and last reset_index :

df2 = df1.groupby('ID').items_bought.sum().reindex(df2.ID, fill_value=0).reset_index()
print (df2)
   ID  items_bought
0   1             5
1   2             4
2   8             0
3   3            13
4   2             4