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r_intro_bc_stats

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An Introduction to R and RStudio with the tidyverse delivered at BC Stats

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This is the repo for an introduction to R using the `tidyverse`
developed for [BC
Stats](https://www2.gov.bc.ca/gov/content/data/about-data-management/bc-stats).

The repo currently reflects a 1 day version to be delivered Oct 2019. If
you are looking for an older version, try:

- [Jul 2018: A 1.5 day
    version](https://github.com/cwickham/r_intro_bc_stats/tree/v2.0)
  - [Dec 2017: A 2.5 day
    version](https://github.com/cwickham/r_intro_bc_stats/tree/v1.0)

**Solutions** to “Your Turns” available at
[r\_intro\_bc\_stats\_solutions](https://github.com/cwickham/r_intro_bc_stats_solutions).

## License

<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /><span xmlns:dct="http://purl.org/dc/terms/" data-property="dct:title">Introduction
to data science with the tidyverse</span> by
<a xmlns:cc="http://creativecommons.org/ns#" href="https://github.com/cwickham/r_intro_bc_stats" property="cc:attributionName" rel="cc:attributionURL">Charlotte
Wickham</a> is licensed under a
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Creative
Commons Attribution 4.0 International License</a>. Based on a work at
<a xmlns:dct="http://purl.org/dc/terms/" href="https://github.com/rstudio/master-the-tidyverse" rel="dct:source">https://github.com/rstudio/master-the-tidyverse</a>.

<h2>

Overview

</h2>

<p>

This course will give you a feel for the complete data analysis process
in R - from importing and manipulating data through visualization.
You'll see how using code to capture the analysis pipeline leads to
deliverables that are documented, easily reproduced and easily
automated.

</p>

<p>

We'll focus on tools in the
<a href="https://www.tidyverse.org/"><code>tidyverse</code></a> a core
set of R packages that are designed to be easy to learn, easy to use,
and solve the most frequent data analysis problems.

</p>

<p>

During the course, we'll alternate between me introducing a new concept
with some examples, and you applying that concept on your own. You
should expect to spend at least 50% of your time writing code in RStudio
on your own laptop.

</p>

<p>

The first half day is specifically for those who are new to R. Take a
look at the <a href="#prerequisites">prerequisites</a> to see if you
might be able to skip it.

</p>

<h2>

Schedule

</h2>

<table>

</colgroup>

<thead>

<th>

Session

</th>

<th>

Date/Time

</th>

<th>

Topic

</th>

</tr>

</thead>

<tbody>

<td>

Day 1: afternoon

</td>

<td>

Tue Jul 24th 1pm-4:30pm

</td>

<td>

Getting Started with R and RStudio

</td>

</tr>

<td>

Day 2: morning

</td>

<td>

Wed Jul 25th 8:30am-12pm

</td>

<td>

Data Visualization with <code>ggplot2</code>

</td>

</tr>

<td>

Day 2: afternoon

</td>

<td>

Wed Jul 25th 1pm-4:30pm

</td>

<td>

Data Manipulation with <code>dplyr</code> and <code>tidyr</code>

</td>

</tr>

</tbody>

</table>

<h3>

Day 1 - Getting Started with R and RStudio

</h3>

<p>

On your first afternoon you'll focus on getting comfortable writing code
and executing it in RStudio. We'll take things slow as you learn to
navigate RStudio, learn some syntax rules, and how to get help when you
get stuck. Along the way you'll meet R's most ubiquitous objects for
holding data and learn to import data whether it is a CSV, SPSS or Excel
data file.

</p>

<p>

By the end of the day you will be able to:

</p>

<ul>

<li>

Open a notebook in RStudio and execute the code chunks in it

</li>

<li>

Install and load an R package

</li>

<li>

Open the help page for a function or built-in dataset

</li>

<li>

Identify the components of an R function: the function name and
arguments

</li>

<li>

Assign the results of a function to a new variable

</li>

<li>

Get an overview of a dataset that is in a data frame or tibble

</li>

<li>

Import CSV, SPSS and SAS data files

</li>

</ul>

<h3>

Day 2 - Visualization and Manipulation of Data

</h3>

<p>

We'll start the day with visualization of data in R using the package
<code>ggplot2</code>. You'll see how <code>ggplot2</code> provides a
framework for thinking about plots, which means you only need to learn
one template to make almost any plot you can imagine. To practice,
you'll make some of the most common kinds of data visualizations:
histograms, scatterplots and time series plots, and continue building
your skills as we continue through data manipulation.

</p>

<p>

In the afternoon we'll focus of the most common types of data
manipulation: extracting subsets from data, adding new variables and
creating grouped summaries. You'll find that doing this is quite
intuitive using the <code>dplyr</code> package which boils down
manipulation into a set of verbs like: <code>filter()</code>,
<code>mutate()</code> and <code>summarise()</code>. Occasionally, data
won't come in quite the right shape for manipulation or visualization
you want to do, so we'll also talk about the key parts of the
<code>tidyr</code> package that help to reshape not not-so-tidy data.

</p>

<p>

By the end of the day you will be able to:

</p>

<ul>

<li>

Create plots in <code>ggplot2</code> to explore data

</li>

<li>

Select variables and filter observations to subset data

</li>

<li>

Add new variables, and transform variables

</li>

<li>

Create grouped summaries of data

</li>

<li>

Reshape data for use with tidy tools

</li>

</ul>

<h2>

Prerequisites

</h2>

<p>

The first half-day is specifically for people that are new to R. You can
safely join us starting on day 2 if you already:

</p>

<ul>

<li>

know how to define variables in R

</li>

<li>

have called a few basic functions (e.g. <code>mean()</code>), and

</li>

<li>

know how to open .R script files, and run code in the console

</li>

</ul>

<p>

Although I'll assume on the first half-day you haven't used R, you might
like to get a little experience before we meet. Some options are:

</p>

<ul>

<li>

Work through the non-interactive
<a href="https://www.safaribooksonline.com/library/view/hands-on-programming-with/9781449359089/ch01.html">Chapter
1 of Hands on Programming with R</a>, which introduces RStudio as well
as basic R syntax.

</li>

<li>

Work through the interactive chapters at
<a href="http://tryr.codeschool.com/">Try R</a>

</li>

<li>

Try the free
<a href="https://www.datacamp.com/courses/free-introduction-to-r">“Introduction
to R” course at DataCamp</a>

</li>

</ul>

<h2>

Software Requirements

</h2>

<p>

You'll need to bring a laptop with R and RStudio installed. In addition,
you'll want to install the following
packages:

</p>

<pre><code>install.packages(c(&quot;tidyverse&quot;, &quot;rmarkdown&quot;, &quot;gapminder&quot;, &quot;usethis&quot;))
</code></pre>

<p>

If you've installed the tidyverse before, re-installing it may not
update all the component packages, in which case run,

</p>

<pre><code>tidyverse::tidyverse_update()
</code></pre>

<p>

to identify any out-of-date packages, and follow the instructions to
update them.

</p>

<p>

Don't forget to bring your power cable\!

</p>

<p>

I'll also be providing some additional materials (slides, code and data)
prior to our meeting, keep your eyes out for an email about soon.

</p>

<h2>

Getting the materials

</h2>

<p>

To download the materials, open RStudio and on the Console run:

</p>

<pre><code>usethis::use_course(&quot;bit.ly/rintro-bc&quot;)
</code></pre>

<p>

After a pause, you'll be asked a few questions about the download
process. The materials will be downloaded, unzipped to your Desktop, and
a new RStudio session will open.

</p>

<p>

You only need to do this once. If you close RStudio, and want to pick it
up again later (i.e. on the day of the training):

</p>

<ol>

<li>

Navigate to where the folder was downloaded (this should be a folder
called <code>r\_intro\_bc\_stats-master</code> on your
<strong>Desktop</strong>)

</li>

<li>

Double-click the file <code>r\_intro\_bc\_stats.Rproj</code> to open up
RStudio

</li>

</ol>

<h2>

rstudio.cloud

</h2>

<p>

If you have a good internet connection, an alternative to installing the
pacakges, and getting the materials, locally is to use
<a href="https://rstudio.cloud/project/49127">https://rstudio.cloud/project/49127</a>

</p>

<p>

You may need to sign up for an account (free) first.

</p>

<h2>

Instructor Info

</h2>

<p>

Charlotte Wickham

</p>

<ul>

<li>

<a href="cwickham@gmail.com">cwickham@gmail.com</a>

</li>

<li>

<a href="http://www.cwick.co.nz">cwick.co.nz</a>

</li>

<li>

@<a href="http://www.twitter.com/cvwickham">cvwickham</a>

</li>

</ul>

r_intro_bc_stats

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