Python: Sum values in DataFrame if other values match between DataFrames

Question

I have two dataframes of different length like those:

DataFrame A:

FirstName    LastName
Adam         Smith
John         Johnson

Da

Answer 1

Use boolean indexing with Series.isin for filtering and then aggregate sum:

df = (df_b[df_b['Last'].isin(df_a['LastName'])]
           .groupby(['First','Last'], as_index=False)['Value']
           .sum())

If want match both, first and last name:

df = (df_b.merge(df_a, left_on=['First','Last'], right_on=['FirstName','LastName'])
           .groupby(['First','Last'], as_index=False)['Value']
           .sum())

Answer 2

Use DataFrame.merge + DataFrame.groupby:

new_df=( dfa.merge(dfb.groupby(['First','Last'],as_index=False).Value.sum() ,
                   left_on='LastName',right_on='Last',how='left')
            .drop('Last',axis=1) )
print(new_df)

---

to join for both columns:

new_df=( dfa.merge(dfb.groupby(['First','Last'],as_index=False).Value.sum() ,
              left_on=['FirstName','LastName'],right_on=['First','Last'],how='left')
            .drop(['First','Last'],axis=1) )
print(new_df)

---

Output:

  FirstName LastName  Value
0      Adam    Smith    5.7
1      John  Johnson    2.5

Answer 3

df_b_a = (pd.merge(df_b, df_a, left_on=['FirstName', 'LastName'], right_on=['First', 'Last'], how='left')
                .groupby(by=['First', 'Last'], as_index=False)['Value'].sum())

print(df_b_a)

    First   Last    Value
0   Adam    Smith   5.7
1   John    Johnson     2.5