std

Computes the standard deviation (std, σ) of values.

null values are ignored.

All primitive numeric types are supported: Byte, Short, Int, Long, Float, and Double.

std also supports the "mixed" Number type, as long as the column consists only of the aforementioned primitive numbers. The numbers are automatically converted to a common type for the operation.

The return type is always Double; Double.NaN for empty columns.

All operations on Double/Float/Number have the skipNaN option, which is set to false by default. This means that if a NaN is present in the input, it will be propagated to the result. When it's set to true, NaN values are ignored.

df.std() // std of values per every numeric column
df.std { age and weight } // std of all values in `age` and `weight`
df.stdFor(skipNaN = true) { age and weight } // std of values per `age` and `weight` separately, skips NA
df.stdOf { (weight ?: 0) / age } // std of expression evaluated for every row

df.std()
df.age.std()
df.groupBy { city }.std()
df.pivot { city }.std()
df.pivot { city }.groupBy { name.lastName }.std()