df.distinctBy { age and name }
Input DataFrame: rowsCount = 7, columnsCount = 5
nameagecityweightisHappy
firstNamelastName
AliceCooper15London54true
BobDylan45Dubai87true
CharlieDaniels20Moscownullfalse
CharlieChaplin40Milannulltrue
BobMarley30Tokyo68true
AliceWolf20null55false
CharlieByrd30Moscow90true

Output DataFrame: rowsCount = 7, columnsCount = 5
nameagecityweightisHappy
firstNamelastName
AliceCooper15London54true
BobDylan45Dubai87true
CharlieDaniels20Moscownullfalse
CharlieChaplin40Milannulltrue
BobMarley30Tokyo68true
AliceWolf20null55false
CharlieByrd30Moscow90true


df.groupBy { age and name }.mapToRows { group.first() }
Input DataFrame: rowsCount = 7, columnsCount = 5
nameagecityweightisHappy
firstNamelastName
AliceCooper15London54true
BobDylan45Dubai87true
CharlieDaniels20Moscownullfalse
CharlieChaplin40Milannulltrue
BobMarley30Tokyo68true
AliceWolf20null55false
CharlieByrd30Moscow90true

Step 1: GroupBy
agenamegroup
firstNamelastName
15AliceCooperDataFrame 1 x 5
45BobDylanDataFrame 1 x 5
20CharlieDanielsDataFrame 1 x 5
40CharlieChaplinDataFrame 1 x 5
30BobMarleyDataFrame 1 x 5
20AliceWolfDataFrame 1 x 5
30CharlieByrdDataFrame 1 x 5

Output DataFrame: rowsCount = 7, columnsCount = 5
nameagecityweightisHappy
firstNamelastName
AliceCooper15London54true
BobDylan45Dubai87true
CharlieDaniels20Moscownullfalse
CharlieChaplin40Milannulltrue
BobMarley30Tokyo68true
AliceWolf20null55false
CharlieByrd30Moscow90true