first value from selective column with groupby and .first() function

September 28, 2022

Existing Dataframe :

Id       col_1        col_2       col_3         col_4
A         3             6          6              2
A         3             6          6              5
A         3             6          6              4
B         2             4          4              6
B         2             4          4              6

Expected Dataframe :

Id       col_1        col_2       col_3         
A         3             6          6              
B         2             4          4

I am trying to find first Appearance of the value from the selective columns.
I know with new_df= df.groupby('Id')['col_1'].first().reset_index() we can get the first value , but is there a way to get first value for multiple column(Required column) at once

>Solution :

For aggregation add list after groupby:

cols = ['col_1','col_2','col_3']
new_df = df.groupby('Id', as_index=False, sort=False)[cols].first()
print (new_df)
  Id  col_1  col_2  col_3
0  A      3      6      6
1  B      2      4      4

Or solution without groupby with DataFrame.drop_duplicates and select columns by names (added Id column):

cols = ['Id','col_1','col_2','col_3']
new_df = df.drop_duplicates('Id')[cols]
print (new_df)
  Id  col_1  col_2  col_3
0  A      3      6      6
3  B      2      4      4