README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# effex

[![Travis-CI Build Status](https://travis-ci.org/sflippl/effex.svg?branch=master)](https://travis-ci.org/sflippl/effex)
[![Coverage Status](https://img.shields.io/codecov/c/github/sflippl/effex/master.svg)](https://codecov.io/github/sflippl/effex?branch=master)

R provides powerful opportunities to outsource everyday thought processes in data analysis. However, adapting these mechanisms for application-specific thought processes is expensive and difficult. Whenever a statistician builds a plot he needs to specify the variable name, scale transformations etc. `effex` supports automation of these parameters. In particular, it supports automated visualization of complex datasets.

You can install effex from github with:

```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("sflippl/effex")
```

For now, an introduction to `effex` can be found in my [Bachelor's Thesis](https://github.com/sflippl/bachelor-thesis/blob/master/_book/bachelor-thesis.pdf) (please note that the package has since been renamed and had been called `tectr` at that stage).

The package [`fxVdem`](https://github.com/sflippl/fx-vdem) applies `effex` to the [V-Dem database](v-dem.net).