如何仅汇总数据框的某些列（python pandas）

Question

I want to get new dataframe, in which I need to see sum of certain columns for rows which have same value of 'Index' columns ( campaign_id and group_name in my example) This is sample (example) of my dataframe:

campaign_id  group_name  clicks    conversions   cost    label    city_id 
101          blue        40        15            100     foo      15
102          red         20        5             50      bar      12
102          red         7         3             25      bar      12
102          brown       5         0             18      bar      12

this is what I want to get:

campaign_id  group_name  clicks    conversions   cost    label    city_id 
101          blue        40        15            100     foo      15
102          red         27        8             75      bar      12
102          brown       5         0             18      bar      12

I tried:

df = df.groupby(['campaign_id','group_name'])['clicks','conversions','cost'].sum().reset_index()

but this gives my only mentioned (summarized) columns (and Index), like this:

campaign_id  group_name  clicks    conversions   cost    
101          blue        40        15            100
102          red         27        8             75
102          brown       5         0             18

I can try to add leftover columns after this operation, but I'm not sure if this will be optimal and adequate way to solve the problem

Is there simple way to summarize certain columns and leave other columns untouched (I don't care if they would differ, because in my data all leftover columns have same data for rows with same corresponding values in 'Index' columns (which are campaign_id and group_name )

Answer 1

When I finished my post I saw the answer right away: since all columns except those which I want to summarize - have matching values - I just need to take all those columns as part of multi-index, for this operation. Like this:

df = df.groupby(['campaign_id','group_name','lavel','city_id'])['clicks','conversions','cost'].sum().reset_index()

In this case I got exacty what I wanted.