explore: Explore a dataset or variable

In explore: Simplifies Exploratory Data Analysis

Explore a dataset or variable

Description

Explore a dataset or variable

Usage

explore(
  data,
  var,
  var2,
  n,
  target,
  targetpct,
  split,
  min_val = NA,
  max_val = NA,
  auto_scale = TRUE,
  na = NA,
  ...
)

Arguments

data	A dataset
var	A variable
var2	A variable for checking correlation
n	A Variable for number of observations (count data)
target	Target variable (0/1 or FALSE/TRUE)
targetpct	Plot variable as target% (FALSE/TRUE)
split	Alternative to targetpct (split = !targetpct)
min_val	All values < min_val are converted to min_val
max_val	All values > max_val are converted to max_val
auto_scale	Use 0.2 and 0.98 quantile for min_val and max_val (if min_val and max_val are not defined)
na	Value to replace NA
...	Further arguments (like flip = TRUE/FALSE)

Value

Plot object

Examples

## Launch Shiny app (in interactive R sessions)
if (interactive())  {
   explore(iris)
}

## Explore grafically

# Load library
library(magrittr)

# Explore a variable
iris %>% explore(Species)
iris %>% explore(Sepal.Length)
iris %>% explore(Sepal.Length, min_val = 4, max_val = 7)

# Explore a variable with a target
iris$is_virginica <- ifelse(iris$Species == "virginica", 1, 0)
iris %>% explore(Species, target = is_virginica)
iris %>% explore(Sepal.Length, target = is_virginica)

# Explore correlation between two variables
iris %>% explore(Species, Petal.Length)
iris %>% explore(Sepal.Length, Petal.Length)

# Explore correlation between two variables and split by target
iris %>% explore(Sepal.Length, Petal.Length, target = is_virginica)

explore documentation built on Oct. 11, 2023, 9:07 a.m.