README.md

In wu-2018/corrplot: Plot a Scatter Plot with Correlation Coefficient

corrplot

The purpose of corrplot is to provide a easy way for exploring the relationship between two variables. It will plot a scatter plot and show the correlation coefficients.

Installation

You can install the released version of corrplot from github with:

install.packages("devtools")
devtools::install_github("wu-2018/corrplot")

Example

library(corrplot)

Use the iris dataset for example:

correlation_scatter(datasets::iris, x='Sepal.Length', y='Sepal.Width', group='Species', cor_method = "pearson")
#> function started!
#> Successfully calculated the correlation!

It creates a scatter plot showing the relationship between Sepal.Length and Sepal.Length, grouped by the factor Species. Note the correlation coefficients are annotated.

Implementation

How I made each part of this R package: - Using use_r() to create the R scripts contains main functions. - Using use_mit_license() to add the license. - Using document() to generate the documentation files in man. - Using use_testthat() and use_test() for unit testing. - Using use_package() to modify the DESCRIPTION file, which specifies the dependencies. - Using use_readme_rmd() and build_readme() to generate the README.md. - Using use_vignette() to generate the vignettes.

wu-2018/corrplot documentation built on Jan. 1, 2021, 12:52 p.m.