# r2spss: Format R Output to Look Like SPSS

Create plots and LaTeX tables that look like SPSS output for use in teaching materials. Rather than copying-and-pasting SPSS output into documents, R code that mocks up SPSS output can be integrated directly into dynamic LaTeX documents with tools such as knitr. Functionality includes methods that are typically covered in introductory statistics classes: descriptive statistics, common hypothesis tests, ANOVA, and linear regression, as well as boxplots, histograms, scatterplots, and line plots (including profile plots).

## Installation

To install the latest (possibly unstable) development version from GitHub, you can pull this repository and install it from the R command line via

install.packages("devtools")
devtools::install_github("aalfons/r2spss")

If you already have package devtools installed, you can skip the first line.

## LaTeX requirements and knitr options

Some of the tables produced by r2spss require the LaTeX package amsmath, hence the following command should be included in the preamble of your LaTeX document.

% somewhere before \begin{document}
\usepackage{amsmath}

When creating LaTeX tables in R code chunks with knitr, the output of the chunk should be written directly into the output document by setting the chunk option results='asis'. For more information on knitr chunk options, in particular various options for figures, please consult the knitr documentation.

## Package vignette

Various examples for using r2spss are given in the package vignette, which can be accessed from the R console with

vignette("r2spss-intro")

## Community guidelines

### Report issues and request features

If you experience any bugs or issues or if you have any suggestions for additional features, please submit an issue via the Issues tab of this repository. Please have a look at existing issues first to see if your problem or feature request has already been discussed.

### Contribute to the package

If you want to contribute to the package, you can fork this repository and create a pull request after implementing the desired functionality.