groupby Sum on columns of multiple dataframes in Pandas

Question

I have 2 dataframes (df1 and df2) below. Based on the values of df1.col1 and df2.col1 , I want the values in df1.col2 and df2.col2 to be added. This sum total should then go against each row in df1 as a 3rd column. For example: wherever we have A01 in col1, the values in col2 should be summed. So 1+7+5=13. Same for all other col1 values.

To give further clarity, I have given a snapshot of how df1 should look at the end (End Result)

**df1
|col1  |  col2**   |   
|------| --------  |
| A01  |    1      |
| A02  |    0      |
| A03  |    0      |
| A01  |    7      |
| A02  |    1      |

**df2
|col1  |  col2   |    col3**
|------| --------|----------
| A01  |    5    |      x
| A02  |    0    |      y
| A06  |    0    |      asa
| A07  |    1    |      asa
| A02  |    4    |      st

END Result:
**df1**
**col1 |   col2  |    col3**
|------| --------|----------
 A01   |   1     |    13
 A02   |   0     |    5
 A03   |   0     |    0
 A01   |   7     |    13
 A02   |   1     |    5

Answer 1

found a solution based on manipulating merge and groupby operations.
First I grouped by 'col1' df1 and 'df2', then calculated the sum, and finally merged with df1 the 'sum'

dic_df1={'col1':['A01', 'A02', 'A03', 'A01', 'A02'], 'col2':[1, 0, 0, 7, 1]}
df1=pd.DataFrame(dic_df1)

dic_df2={'col1':['A01', 'A02', 'A06', 'A07', 'A02'], 'col2':[5, 0, 0, 1, 4] ,'col3**':['x', 'y', 'asa', 'asa', 'st']}
df2=pd.DataFrame(dic_df2)

print(df1), print(df2)

then perform a groupby on 'col1' so we can calculate the first part of the sum, and then when merging df1 and df2, we will have total sum in both datasets in column 'sum'

df2=df2.groupby(['col1'], as_index=False)['col2'].sum()
merged=(df1.groupby(['col1'], as_index=False)['col2'].sum()).merge(df2, left_on='col1', right_on='col1', how='left')
merged['sum']=merged['col2_x']+merged['col2_y']

finally a merge on df1 with merged

df1=df1.merge(merged[['col1', 'sum']], left_on='col1', right_on='col1', how='left')

final output if df1:

There are many ways to fill the Nan value in final output df1.