df.pivotCounts { city }

Input DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15	London	54	true
Bob	Dylan	45	Dubai	87	true
Charlie	Daniels	20	Moscow	null	false
Charlie	Chaplin	40	Milan	null	true
Bob	Marley	30	Tokyo	68	true
Alice	Wolf	20	null	55	false
Charlie	Byrd	30	Moscow	90	true

Output DataFrame: rowsCount = 7, columnsCount = 5

name		age	weight	isHappy	city
firstName	lastName				London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	15	54	true	1	0	0	0	0	0
Bob	Dylan	45	87	true	0	1	0	0	0	0
Charlie	Daniels	20	null	false	0	0	1	0	0	0
Charlie	Chaplin	40	null	true	0	0	0	1	0	0
Bob	Marley	30	68	true	0	0	0	0	1	0
Alice	Wolf	20	55	false	0	0	0	0	0	1
Charlie	Byrd	30	90	true	0	0	1	0	0	0

df.pivot { city }.groupByOther().count()

Input DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15	London	54	true
Bob	Dylan	45	Dubai	87	true
Charlie	Daniels	20	Moscow	null	false
Charlie	Chaplin	40	Milan	null	true
Bob	Marley	30	Tokyo	68	true
Alice	Wolf	20	null	55	false
Charlie	Byrd	30	Moscow	90	true

Step 1: Pivot

London	Dubai	Moscow	Milan	Tokyo	null
DataFrame 1 x 5	DataFrame 1 x 5	DataFrame 2 x 5	DataFrame 1 x 5	DataFrame 1 x 5	DataFrame 1 x 5

Step 2: PivotGroupBy

name		age	weight	isHappy	city
firstName	lastName				London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	15	54	true	DataFrame 1 x 5
Bob	Dylan	45	87	true		DataFrame 1 x 5
Charlie	Daniels	20	null	false			DataFrame 1 x 5
Charlie	Chaplin	40	null	true				DataFrame 1 x 5
Bob	Marley	30	68	true					DataFrame 1 x 5
Alice	Wolf	20	55	false						DataFrame 1 x 5
Charlie	Byrd	30	90	true			DataFrame 1 x 5

Output DataFrame: rowsCount = 7, columnsCount = 5

name		age	weight	isHappy	city
firstName	lastName				London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	15	54	true	1	0	0	0	0	0
Bob	Dylan	45	87	true	0	1	0	0	0	0
Charlie	Daniels	20	null	false	0	0	1	0	0	0
Charlie	Chaplin	40	null	true	0	0	0	1	0	0
Bob	Marley	30	68	true	0	0	0	0	1	0
Alice	Wolf	20	55	false	0	0	0	0	0	1
Charlie	Byrd	30	90	true	0	0	1	0	0	0

df.groupBy { name }.pivotCounts { city }

Input DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15	London	54	true
Bob	Dylan	45	Dubai	87	true
Charlie	Daniels	20	Moscow	null	false
Charlie	Chaplin	40	Milan	null	true
Bob	Marley	30	Tokyo	68	true
Alice	Wolf	20	null	55	false
Charlie	Byrd	30	Moscow	90	true

Step 1: GroupBy

name		group
firstName	lastName
Alice	Cooper	DataFrame 1 x 5
Bob	Dylan	DataFrame 1 x 5
Charlie	Daniels	DataFrame 1 x 5
Charlie	Chaplin	DataFrame 1 x 5
Bob	Marley	DataFrame 1 x 5
Alice	Wolf	DataFrame 1 x 5
Charlie	Byrd	DataFrame 1 x 5

Output DataFrame: rowsCount = 7, columnsCount = 2

name		city
firstName	lastName	London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	1	0	0	0	0	0
Bob	Dylan	0	1	0	0	0	0
Charlie	Daniels	0	0	1	0	0	0
Charlie	Chaplin	0	0	0	1	0	0
Bob	Marley	0	0	0	0	1	0
Alice	Wolf	0	0	0	0	0	1
Charlie	Byrd	0	0	1	0	0	0

df.groupBy { name }.pivot { city }.count()

Input DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15	London	54	true
Bob	Dylan	45	Dubai	87	true
Charlie	Daniels	20	Moscow	null	false
Charlie	Chaplin	40	Milan	null	true
Bob	Marley	30	Tokyo	68	true
Alice	Wolf	20	null	55	false
Charlie	Byrd	30	Moscow	90	true

Step 1: GroupBy

name		group
firstName	lastName
Alice	Cooper	DataFrame 1 x 5
Bob	Dylan	DataFrame 1 x 5
Charlie	Daniels	DataFrame 1 x 5
Charlie	Chaplin	DataFrame 1 x 5
Bob	Marley	DataFrame 1 x 5
Alice	Wolf	DataFrame 1 x 5
Charlie	Byrd	DataFrame 1 x 5

Step 2: PivotGroupBy

name		city
firstName	lastName	London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	DataFrame 1 x 5
Bob	Dylan		DataFrame 1 x 5
Charlie	Daniels			DataFrame 1 x 5
Charlie	Chaplin				DataFrame 1 x 5
Bob	Marley					DataFrame 1 x 5
Alice	Wolf						DataFrame 1 x 5
Charlie	Byrd			DataFrame 1 x 5

Output DataFrame: rowsCount = 7, columnsCount = 2

name		city
firstName	lastName	London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	1	0	0	0	0	0
Bob	Dylan	0	1	0	0	0	0
Charlie	Daniels	0	0	1	0	0	0
Charlie	Chaplin	0	0	0	1	0	0
Bob	Marley	0	0	0	0	1	0
Alice	Wolf	0	0	0	0	0	1
Charlie	Byrd	0	0	1	0	0	0

df.groupBy { name }.aggregate { pivotCounts { city } }

Input DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15	London	54	true
Bob	Dylan	45	Dubai	87	true
Charlie	Daniels	20	Moscow	null	false
Charlie	Chaplin	40	Milan	null	true
Bob	Marley	30	Tokyo	68	true
Alice	Wolf	20	null	55	false
Charlie	Byrd	30	Moscow	90	true

Step 1: GroupBy

name		group
firstName	lastName
Alice	Cooper	DataFrame 1 x 5
Bob	Dylan	DataFrame 1 x 5
Charlie	Daniels	DataFrame 1 x 5
Charlie	Chaplin	DataFrame 1 x 5
Bob	Marley	DataFrame 1 x 5
Alice	Wolf	DataFrame 1 x 5
Charlie	Byrd	DataFrame 1 x 5

Output DataFrame: rowsCount = 7, columnsCount = 2

name		city
firstName	lastName	London	Dubai	Moscow	Milan	Tokyo	null
Alice	Cooper	true	false	false	false	false	false
Bob	Dylan	false	true	false	false	false	false
Charlie	Daniels	false	false	true	false	false	false
Charlie	Chaplin	false	false	false	true	false	false
Bob	Marley	false	false	false	false	true	false
Alice	Wolf	false	false	false	false	false	true
Charlie	Byrd	false	false	true	false	false	false