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(This article was first published on <strong><a href="https://blog.rstudio.org/2016/09/15/tidyverse-1-0-0/"> RStudio Blog</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>The tidyverse is a set of packages that work in harmony because they share common data representations and API design. The <strong>tidyverse</strong> package is designed to make it easy to install and load core packages from the tidyverse in a single command.</p>
<p>The best place to learn about all the packages in the tidyverse and how they fit together is <a target="_blank" href="http://r4ds.had.co.nz/">R for Data Science</a>. Expect to hear more about the tidyverse in the coming months as I work on improved package websites, making <a target="_blank" href="http://joss.theoj.org/">citation easier</a>, and providing a common home for discussions about data analysis with the tidyverse.</p>
<div>
<h2>Installation</h2>
<p>You can install tidyverse with</p>
<pre><code><span>install.packages</span><span>(</span><span>&quot;tidyverse&quot;</span><span>)</span></code></pre>
<p>This will install the core tidyverse packages that you are likely to use in almost every analysis:</p>
<ul>
<li><a target="_blank" href="http://ggplot2.org/">ggplot2</a>, for data visualisation.</li>
<li><a target="_blank" href="https://github.com/hadley/dplyr">dplyr</a>, for data manipulation.</li>
<li><a target="_blank" href="https://github.com/hadley/tidyr">tidyr</a>, for data tidying.</li>
<li><a target="_blank" href="https://github.com/hadley/readr">readr</a>, for data import.</li>
<li><a target="_blank" href="https://github.com/hadley/purrr">purrr</a>, for functional programming.</li>
<li><a target="_blank" href="https://github.com/hadley/tibble">tibble</a>, for tibbles, a modern re-imagining of data frames.</li>
</ul>
<p>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 data manipulation:</p>
<ul>
<li><a target="_blank" href="https://github.com/krlmlr/hms">hms</a>, for times.</li>
<li><a target="_blank" href="https://github.com/hadley/stringr">stringr</a>, for strings.</li>
<li><a target="_blank" href="https://github.com/hadley/lubridate">lubridate</a>, for date/times.</li>
<li><a target="_blank" href="https://hadley.github.io/forcats/">forcats</a>, for factors.</li>
</ul>
<p>Data import:</p>
<ul>
<li><a target="_blank" href="https://github.com/rstats-db/DBI">DBI</a>, for databases.</li>
<li><a target="_blank" href="https://github.com/hadley/haven/">haven</a>, for SPSS, SAS and Stata files.</li>
<li><a target="_blank" href="https://github.com/hadley/httr/">httr</a>, for web apis.</li>
<li><a target="_blank" href="https://github.com/jeroenooms/jsonlite">jsonlite</a> for JSON.</li>
<li><a target="_blank" href="https://github.com/hadley/readxl">readxl</a>, for <code>.xls</code> and <code>.xlsx</code> files.</li>
<li><a target="_blank" href="https://github.com/hadley/rvest">rvest</a>, for web scraping.</li>
<li><a target="_blank" href="https://github.com/hadley/xml2">xml2</a>, for XML.</li>
</ul>
<p>And modelling:</p>
<ul>
<li><a target="_blank" href="https://github.com/hadley/modelr">modelr</a>, for simple modelling within a pipeline</li>
<li><a target="_blank" href="https://github.com/dgrtwo/broom">broom</a>, for turning models into tidy data</li>
</ul>
<p>These packages will be installed along with tidyverse, but you’ll load them explicitly with <code>library()</code>.</p>
</div>
<div>
<h2>Usage</h2>
<p><code>library(tidyverse)</code> will load the core tidyverse packages: ggplot2, tibble, tidyr, readr, purrr, and dplyr. You also get a condensed summary of conflicts with other packages you have loaded:</p>
<pre><code><span>library</span><span>(</span><span>tidyverse</span><span>)</span>
<span>#> Loading tidyverse: ggplot2</span>
<span>#> Loading tidyverse: tibble</span>
<span>#> Loading tidyverse: tidyr</span>
<span>#> Loading tidyverse: readr</span>
<span>#> Loading tidyverse: purrr</span>
<span>#> Loading tidyverse: dplyr</span>
<span>#> Conflicts with tidy packages ---------------------------------------</span>
<span>#> filter(): dplyr, stats</span>
<span>#> lag(): dplyr, stats</span></code></pre>
<p>You can see conflicts created later with <code>tidyverse_conflicts()</code>:</p>
<pre><code><span>library</span><span>(</span><span>MASS</span><span>)</span>
<span>#> </span>
<span>#> Attaching package: 'MASS'</span>
<span>#> The following object is masked from 'package:dplyr':</span>
<span>#> </span>
<span>#> select</span>
<span>tidyverse_conflicts</span><span>(</span><span>)</span>
<span>#> Conflicts with tidy packages --------------------------------------</span>
<span>#> filter(): dplyr, stats</span>
<span>#> lag(): dplyr, stats</span>
<span>#> select(): dplyr, MASS</span></code></pre>
<p>And you can check that all tidyverse packages are up-to-date with <code>tidyverse_update()</code>:</p>
<pre><code><span>tidyverse_update</span><span>(</span><span>)</span>
<span>#> The following packages are out of date:</span>
<span>#> * broom (0.4.0 -> 0.4.1)</span>
<span>#> * DBI (0.4.1 -> 0.5)</span>
<span>#> * Rcpp (0.12.6 -> 0.12.7)</span>
<span>#> Update now?</span>
<span>#> </span>
<span>#> 1: Yes</span>
<span>#> 2: No</span></code></pre>
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