difference between two dataframes in Pandas

Question

I am trying to find difference between two dataframe and the resulting df should return the rows matching the first dataframe. Since id's 6,7 was not there in df2 so the count value is as it is.

My Two Dataframes

Resulting Dataframe:

Answer 1

Use sub with set_index for align DataFrame s by id columns, add reindex for id only by df1.id :

df = (df1.set_index('id')
        .sub(df2.set_index('id'), fill_value=0)
        .reindex(df1['id'])
        .astype(int)
        .reset_index())
print (df)
   id  count
0   1      0
1   2      0
2   3      0
3   4      0
4   5      0
5   6      9
6   7      4

Another solution with merge and left join, then subtract by sub with extracting count_ column by pop :

df = df1.merge(df2, on='id', how='left', suffixes=('','_'))
df['count'] = df['count'].sub(df.pop('count_'), fill_value=0).astype(int)
print (df)
   id  count
0   1      0
1   2      0
2   3      0
3   4      0
4   5      0
5   6      9
6   7      4

Setup :

df1 = pd.DataFrame({'id':[1,2,3,4,5,6,7],
                    'count':[3,5,6,7,2,9,4]})

print (df1)
   id  count
0   1      3
1   2      5
2   3      6
3   4      7
4   5      2
5   6      9
6   7      4

df2 = pd.DataFrame({'id':[1,2,3,4,5,8,9],
                    'count':[3,5,6,7,2,4,2]})

print (df2)
   id  count
0   1      3
1   2      5
2   3      6
3   4      7
4   5      2
5   8      4
6   9      2

Answer 2

Use:

temp = pd.merge(df1, df2, how='left', on='id').fillna(0)
temp['count'] = temp['count_x'] - temp['count_y']
temp[['id', 'count']]

   id  count
0   1    0.0
1   2    0.0
2   3    0.0
3   4    0.0
4   5    0.0
5   6    9.0
6   7    4.0