我在熊猫数据框中有两列。 一列具有相同的值（id），另一列中具有对应的值的票证数

Question

   id         n_tickets
0  1586391          2
1   640             2
2   640             1
3  1181593          2
4   964842          1
5    780            1
6    780            1  

I have the above data frame. As you can see that in id column 640 and 780 have occurred two times. I want that just a single occurrence remains but there corresponding values in column n_tickets gets added up. My final dataframe should look like this:

     id         n_tickets
0  1586391          2
1   640             3
2  1181593          2
3   964842          1
4    780            2 

I am using the code: df_tickets.groupby(['id','n_tickets']).sum() but I am gettting the error:

Empty DataFrame
Columns: []
Index: []

when i use the below code:

df_tickets.groupby('id',sort=False).sum().reset_index()

print(df_tickets.loc[df_tickets['id'] == 780])

I get this:

        id     n_tickets
425166  780          1
985855  780          1

Instead I should get:

           id    n_tickets
   425166  780      2

Answer 1

Try using:

df_tickets = df_tickets.groupby(df_tickets['id']).sum()

This should work.

Answer 2

You only need to group by 'id':

df.groupby('id',sort=False).sum().reset_index()
Out[60]: 
        id  n_tickets
0  1586391          2
1      640          3
2  1181593          2
3   964842          1
4      780          2

when i use the above code:

df_tickets.groupby('id',sort=False).sum().reset_index()

    print(df_tickets.loc[df_tickets['id'] == 780])

I get this:

         id     n_tickets
425166  780          1
985855  780          1

Instead I should get:

    id    n_tickets
 425166  780      2