select

Create a new data frame with only the selected columns.

// data-frames can be a  mix of atomic (int, double, boolean, string) and object columns
val birthdays = DataFrame.builder("name", "height", "sex", "birthday")(
        "Tom", 1.89, Sex.MALE, LocalDate.of(1980, 5, 22),
        "Jane", 1.73, Sex.FEMALE, LocalDate.of(1973, 2, 13)
)

// just select/deselect columns of interest with varargs
birthdays.select("name", "height")
birthdays.remove("sex")

// use helper API to match columns of interest
birthdays.select { matches("^na") }
birthdays.select { endsWith("x") }

// do positive and negative selection as needed
birthdays.remove { startsWith("birth") }
birthdays.select { except("birth") }


// or use stdlib-like filter with `selectIf`
birthdays.selectIf { it is IntCol }
birthdays.selectIf { it.name.startsWith("bar") }

Convenience wrapper around to work with varag krangl.DataFrame.select

Keeps only the variables that match any of the given expressions.

E.g. use startsWith("foo") to select for columnSelect staring with 'foo'.

// data-frames can be a  mix of atomic (int, double, boolean, string) and object columns
val birthdays = DataFrame.builder("name", "height", "sex", "birthday")(
        "Tom", 1.89, Sex.MALE, LocalDate.of(1980, 5, 22),
        "Jane", 1.73, Sex.FEMALE, LocalDate.of(1973, 2, 13)
)

// just select/deselect columns of interest with varargs
birthdays.select("name", "height")
birthdays.remove("sex")

// use helper API to match columns of interest
birthdays.select { matches("^na") }
birthdays.select { endsWith("x") }

// do positive and negative selection as needed
birthdays.remove { startsWith("birth") }
birthdays.select { except("birth") }


// or use stdlib-like filter with `selectIf`
birthdays.selectIf { it is IntCol }
birthdays.selectIf { it.name.startsWith("bar") }