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title generalR

generalR

<p>These are instructional materials to help people learn to use R. You can download the files that go with these materials from the <a href="https://github.com/riffomonas/generalR_data/releases/latest">generalR data repository</a> on GitHub. If you would like to contribute to the project or flag any issues that you think need to be addressed, please feel free to file a pull request or start an issue on the <a href="https://github.com/riffomonas/generalR">generalR GitHub repository</a>. The overall philosophy is to give learners the minimum that they need to get going and to teach them the material in a way that most R users learned the material (i.e. not from a book but by hacking their way to success).</p>
  1. Introduction
    • Philosophy behind these instructional materials
    • Why R?
    • Introduction to R
    • Installing R, RStudio, and tidyverse
    • Getting settled in RStudio
    <li><a href="01_session.html">Lyme disease: Session 1</a></li>
    <ul>
    	<li>Learning to analyze data is empowering</li>
    	<li>R is expressive</li>
    	<li>R isn't just for statistics</li>
    	<li>Figuring things out</li>
    </ul>
    
    <li><a href="02_session.html">Lyme disease: Session 2</a></li>
    <ul>
    	<li>Plotting continuous data vs continuous data</li>
    	<li>Manipulating aesthetics</li>
    	<li>Mapping data to aesthetics</li>
    </ul>
    
    <li><a href="03_session.html">Lyme disease: Session 3</a></li>
    <ul>
    	<li>The `+` operator</li>
    	<li>Tracking down the source of errors</li>
    </ul>
    
    <li><a href="04_session.html">Lyme disease: Session 4</a></li>
    <ul>
    	<li>What is a (tidy) data frame?</li>
    	<li>Understanding the structure of our data frame</li>
    	<li>Data types</li>
    	<li>Counting data</li>
    	<li>Summarizing data frames</li>
    </ul>
    
    <li><a href="05_session.html">Lyme disease: Session 5</a></li>
    <ul>
    	<li>Raw data should stay raw</li>
    	<li>Heat maps</li>
    	<li>Simplifying our data frame with `filter`</li>
    	<li>Map maps</li>
    	<li>Taking stock</li>
    </ul>
    
    <li><a href="06_session.html">Weather data: Session 6</a></li>
    <ul>
    	<li>Finding inspiration</li>
    	<li>Specifying variable types with `read_csv`</li>
    	<li>`selecting`-ing columns from a data frame</li>
    	<li>Renaming columns in a data frame</li>
    </ul>
    
    <li><a href="07_session.html">Weather data: Session 7</a></li>
    <ul>
    	<li>Detecting problems in data</li>
    	<li>Fixing data problems</li>
    	<li>Rinse, repeat</li>
    </ul>
    
    <li><a href="08_session.html">Weather data: Session 8</a></li>
    <ul>
    	<li>Creating columns</li>
    	<li>Keeping our code DRY</li>
    	<li>Writing our own functions</li>
    </ul>
    
    <li><a href="09_session.html">Weather data: Session 9</a></li>
    <ul>
    	<li>Grouping and summarizing data</li>
    	<li>Working with dates</li>
    	<li>Thinking about and visualizing our data</li>
    	<li>DRY revisited</li>
    	<li>Rinse, repeat</li>
    </ul>
    
    <li><a href="10_session.html">Weather data: Session 10</a></li>
    <ul>
    	<li>Critiquing visualizations</li>
    	<li>Highlighting data: factors revisited</li>
    	<li>Setting labels in a visualization</li>
    	<li>Themes</li>
    </ul>
    
    <li><a href="11_session.html">IPEDS: Session 11</a></li>
    <ul>
    	<li>Developing questions and finding data</li>
    	<li>Getting familiar with and focusing on data</li>
    	<li>Working with spreadsheets</li>
    	<li>Joining data frames together</li>
    </ul>
    
    <li><a href="12_session.html">IPEDS: Session 12</a></li>
    <ul>
    	<li>Rinse, repeat to answer new questions</li>
    	<li>Plotting continuous data against categorical data</li>
    	<li>Using `factor` to order categorical variables</li>
    	<li>Thinking of our data as paired and redefining tidy</li>
    </ul>
    
    <li><a href="13_session.html">IPEDS: Session 13</a></li>
    <ul>
    	<li>Generalizing an analysis</li>
    	<li>Making a data frame tidy</li>
    	<li>Plotting groups of data</li>
    	<li>Faceting data visualizations</li>
    </ul>
    
    <li><a href="14_session.html">IPEDS: Session 14</a></li>
    <ul>
    	<li>Thinking through questions</li>
    	<li>Finding text with R</li>
    	<li>Adjusting the shape of a data frame</li>
    	<li>More sophisticated text searches</li>
    	<li>Modifying text based on patterns</li>
    </ul>
    
    <li><a href="15_session.html">IPEDS: Session 15</a></li>
    <ul>
    	<li>Thinking through problems</li>
    	<li>Combining data frames</li>
    	<li>DRYing code with functions</li>
    	<li>File operations in R</li>
    	<li>DRYing code with maps</li>
    </ul>