In eamutaigwe/statsummary: Compute summary statistics, produce a list object with two items: a tibble or data frame and a ggplot object- boxplot

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statsummary

The goal of statsummary is to compute summary statistics (mean, median, minimum, maximum, count) on a numeric variable grouped by a categorical variable.

Installation

statsummary is not yet on CRAN. You can install the development version of statsummary like so:

devtools::install_github("eamutaigwe/statsummary")

Example

Summarize_data() is a function that helps to carry out a fairly common task on a dataset which quickly computes summary statistics (mean, median, minimum, maximum, and count) on a numeric variable grouped by a categorical variable.

It produces a list object with two items- a tibble or data frame containing summary statistics on a numeric variable grouped by a categorical variable, and a ggplot object- a boxplot which visually presents some of the summary statistics found in the summary table generated such as median, minimum, maximum, and count.

Below is a basic example which shows you how to use the function:

library(statsummary)
summarize_data(gapminder::gapminder, continent, lifeExp)

summarize_data() is designed to always group by a categorical variable. So, if you decide to group by a numeric variable, it would throw an error. An error message is also returned if your y variable is categorical.

summarize_data(gapminder::gapminder, gdpPercap, lifeExp)

eamutaigwe/statsummary documentation built on Dec. 20, 2021, 2:22 a.m.