# Announcing another slopegraph plotting function – June 14, 2018

June 13, 2018
By

(This article was first published on Chuck Powell, and kindly contributed to R-bloggers)

A couple of weeks ago I wrote a blog post about
slopegraphs
. There was some
polite interest and it was a good chance to practice my functional
programming skills
so
I decided to see if I could make a decent R function from what I had
learned. It’s in pretty good shape so I just pushed an update to
CRAN (it will take awhile to process). You can also get the latest version from GitHub.

The documentation for it is here. Longer
term I hope to move it here.

## Overview

The package also includes other functions that I find useful for teaching
statistics as well as actually practicing the art. They typically are
not “new” methods but rather wrappers around either base R or other
packages and concepts I’m trying to master.

• `Plot2WayANOVA` which as the name implies conducts a 2 way ANOVA and
plots the results using `ggplot2`
• `PlotXTabs` which as the name implies plots cross tabulated
variables using `ggplot2`
• `neweta` which is a helper function that appends the results of a
Type II eta squared calculation onto a classic ANOVA table
• `Mode` which finds the modal value in a vector of data
• `SeeDist` which wraps around ggplot2 to provide visualizations of
univariate data.
• `OurConf` is a simulation function that helps you learn about
confidence intervals

## Installation

``````# Install from CRAN
install.packages("CGPfunctions")

# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("ibecav/CGPfunctions")
``````

## Credits

Many thanks to Dani Navarro and the book > (Learning Statistics with
R
)
whose etaSquared function was the genesis of `neweta`.

“He who gives up safety for speed deserves neither.”
(via)

#### A shoutout to some other packages I find essential.

• stringr, for strings.
• lubridate, for date/times.
• forcats, for factors.
• haven, for SPSS, SAS and Stata
files.
• readxl, for `.xls` and `.xlsx`
files.
• modelr, for modelling within a
pipeline
• broom, for turning models into
tidy data
• ggplot2, for data visualisation.
• dplyr, for data manipulation.
• tidyr, for data tidying.
• purrr, for functional programming.
• tibble, for tibbles, a modern
re-imagining of data frames.

## Leaving Feedback

If you like CGPfunctions, please consider leaving feedback
here
.

## Contributing

Contributions in the form of feedback, comments, code, and bug reports
are most welcome. How to contribute:

• Issues, bug reports, and wish lists: File a GitHub
issue
.
• Contact the maintainer ibecav at gmail.com by email.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...