# Kurtosis

Source code

## Description

Compute the kurtosis (Fisher or Pearson) of a dataset.

## Usage

``````<Expr>\$kurtosis(fisher = TRUE, bias = TRUE)
``````

## Arguments

 `fisher` If `TRUE` (default), Fisher’s definition is used (normal, centered at 0). Otherwise, Pearson’s definition is used (normal, centered at 3). `bias` If `FALSE`, the calculations are corrected for statistical bias.

## Details

Kurtosis is the fourth central moment divided by the square of the variance. If Fisher’s definition is used, then 3 is subtracted from the result to give 0 for a normal distribution.

If bias is `FALSE`, then the kurtosis is calculated using `k` statistics to eliminate bias coming from biased moment estimators.

Expr

## Examples

``````library(polars)

pl\$DataFrame(a = c(1:3, 2:1))\$
with_columns(kurt = pl\$col("a")\$kurtosis())
``````
``````#> shape: (5, 2)
#> ┌─────┬───────────┐
#> │ a   ┆ kurt      │
#> │ --- ┆ ---       │
#> │ i32 ┆ f64       │
#> ╞═════╪═══════════╡
#> │ 1   ┆ -1.153061 │
#> │ 2   ┆ -1.153061 │
#> │ 3   ┆ -1.153061 │
#> │ 2   ┆ -1.153061 │
#> │ 1   ┆ -1.153061 │
#> └─────┴───────────┘
``````