python - groupby 1 column and sum of other columns as new dataframe pandas -

i have pandas dataframe:

id    won    lost  match v1     1       0     1 v1     2       1     3 v1     0       5     8 v2     3       1     7 v2     5       5     12 

i want groupby id , sum other columns such df

id    total_won    total_lost    total_match v1      3              6             12 v2      8              6             19 

how can use pandas groupby , sum operation sum multiple columns. tried using this:

pd.groupby('id')['won'].sum() pd.groupby('id')['lost'].sum() pd.groupby('id')['match'].sum() 

is there better way this?

use groupby without define column - aggregate numeric columns sum, add_prefix , last reset_index:

df1 = df.groupby('id').sum().add_prefix('total_').reset_index() print (df1)    id  total_won  total_lost  total_match 0  v1          3           6           12 1  v2          8           6           19 

if need specify multiple columns, add list of columns:

cols = ['won','lost'] df1 = df.groupby('id')[cols].sum().add_prefix('total_').reset_index() print (df1)    id  total_won  total_lost 0  v1          3           6 1  v2          8           6