# univariateSummary: Generate a univariate summary table In dnegrey/miscTools: R package with miscellaneous tools

## Description

`univariateSummary()` produces a univariate summary table, evaluating `x` as the independent variable and `y` as the dependent variable. It uses the S3 generic function `bin` to bin the values of `x`, then per bin, applies `FUN` to `y`. The vector `x` can include missing values but `y` cannot. When `ytype = 1`, `y` must contain only unique (coercable) values of 0 or 1. When `ytype = 2`, `y` must have at least 3 distinct values.

## Usage

 `1` ```univariateSummary(x, y = rep(0, length(x)), ytype = 1, FUN = mean, ...) ```

## Arguments

 `x` character, factor, logical or numeric vector (independent variable) `y` logical, integer or numeric vector (dependent variable) `ytype` integer value of 1 (binary y) or 2 (continuous y) `FUN` function to be applied to `y` `...` further arguments passed to `bin`

## Value

A data frame with class "`mt_univariateSummary`" containing the following columns:

• `xbin`: binned values of x (character)

• `Freq`: frequency of observations (integer)

• `Percent`: relative frequency of observations (numeric)

• `yagg`: aggregated summary statistic of y (numeric)

`bin`
 ```1 2 3 4 5 6 7 8 9``` ```# character x, continuous y z <- univariateSummary(iris\$Species, iris\$Sepal.Length, ytype = 2) print(z) class(z) # numeric x, logical y, additional arguments to bin() z <- univariateSummary(mtcars\$hp, mtcars\$mpg > 15, numBins = 2) print(z) class(z) ```