README.Rmd

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

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
comma <- function(x) {
  paste0(paste(x[-length(x)], collapse = ", "), ", and ", x[length(x)])
}
```

# tidyverse

[![Travis-CI Build Status](https://travis-ci.org/hadley/tidyverse.svg?branch=master)](https://travis-ci.org/hadley/tidyverse)

The tidyverse is a set of packages that work in harmony because they share common data representations and API design. The __tidyverse__ package is designed to make it easy to install and load core packages from the tidyverse in a single command.

If you'd like to learn how to use the tidyverse effectively, the best place to start is [R for data science](http://r4ds.had.co.nz).

## Installation

You can install tidyverse from github with:

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

This will install the __core__ tidyverse packages that you are likely to use in almost every analysis:

* ggplot2, for data visualisation.
* dplyr, for data manipulation.
* tidyr, for data tidying.
* readr, for data import.
* purrr, for functional programming.
* tibble, for tibbles, a modern re-imagining of data frames.

It also installs a selection of other tidyverse packages that you're likely to use frequently, but probably not in every analysis. This includes packages for:

*   Working with specific types of vectors:

    * stringr, for strings.
    * lubridate, for date/times.
    * forcats, for factors.

*   Importing other types of data:

    * DBI, for databases.
    * haven, for SPSS, SAS and Stata files.
    * [jsonlite](https://github.com/jeroenooms/jsonlite) for JSON.
    * readxl, for `.xls` and `.xlsx` files.
    * xml2, for XML.

*   Modelling

    * modelr, for modelling within a pipeline
    * [broom](https://github.com/dgrtwo/broom), for turning models into 
      tidy data

These packages will be installed along with tidyverse, but you'll load them explicitly with `library()`.

## Usage

`library(tidyverse)` will load the core tidyverse packages: `r comma(tidyverse:::load)`. You also get a condensed summary of conflicts with other packages you have loaded:

```{r example}
library(tidyverse)
```

You can see conflicts created later with `tidyverse_conflicts()`:

```{r conflicts}
library(MASS)
tidyverse_conflicts()
```

And you can check that all tidyverse packages are up-to-date with `tidyverse_update()`:

```{r update, eval = FALSE}
tidyverse_update()
#> The following packages are out of date:
#>  * broom (0.4.0 -> 0.4.1)
#>  * DBI   (0.4.1 -> 0.5)
#>  * Rcpp  (0.12.6 -> 0.12.7)
#> Update now?
#> 
#> 1: Yes
#> 2: No
```