df.convert { age }.with { it.toDouble() }

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: Convert

class org.jetbrains.kotlinx.dataframe.api.Convert

Output DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
Alice	Cooper	15.0	London	54	true
Bob	Dylan	45.0	Dubai	87	true
Charlie	Daniels	20.0	Moscow	null	false
Charlie	Chaplin	40.0	Milan	null	true
Bob	Marley	30.0	Tokyo	68	true
Alice	Wolf	20.0	null	55	false
Charlie	Byrd	30.0	Moscow	90	true

df.convert { colsAtAnyDepth().colsOf<String>() }.with { it.toCharArray().toList() }

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: Convert

class org.jetbrains.kotlinx.dataframe.api.Convert

Output DataFrame: rowsCount = 7, columnsCount = 5

name		age	city	weight	isHappy
firstName	lastName
[A, l, i, c, e]	[C, o, o, p, e, r]	15	London	54	true
[B, o, b]	[D, y, l, a, n]	45	Dubai	87	true
[C, h, a, r, l, i, e]	[D, a, n, i, e, l, s]	20	Moscow	null	false
[C, h, a, r, l, i, e]	[C, h, a, p, l, i, n]	40	Milan	null	true
[B, o, b]	[M, a, r, l, e, y]	30	Tokyo	68	true
[A, l, i, c, e]	[W, o, l, f]	20	null	55	false
[C, h, a, r, l, i, e]	[B, y, r, d]	30	Moscow	90	true