Working with the RStudio IDE (Part 1)

Learn the basics of the important features of the RStudio IDE.
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3 Hours24 Videos69 Exercises26,442 Learners
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Course Description

<p>In the first part of this two-part RStudio tutorial, you will learn how to use RStudio, an IDE for R.</p><p>Chapter 1 will cover:</p><ol><li>how to install R Studio for Mac, Windows, or Linux </li><li>how to run R code</li><li>debugging in R</li></ol><p>Chapter 2 will get into the features of the IDE geared toward making you a more effective R programmer, including code diagnostics and running scripts.</p><p>Finally, Part 1 finishes with a brief chapter on using RStudio projects for organizing and sharing your code with others.</p><p>In <a href="https://www.datacamp.com/courses/working-with-the-rstudio-ide-part-2">Part 2</a>, you will learn how RStudio makes it easy to build your own R packages, integrate with GitHub, and use tools like R Markdown.</p>

  1. 1

    Orientation

    Free
    This chapter shows you around the most important parts of the RStudio IDE. You'll learn about the data viewer, the environment tab, the history tab, how to set and get your working directory, using the plots pane, navigating the help tab when you get stuck, and more.
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  2. 2

    Programming

    This chapter builds on the last by showing you how to take advantage of the IDE for a more efficient and enjoyable R programming experience. For example, you'll see how RStudio's built-in code and style diagnostics can flag things before they go terribly wrong. You'll learn tricks for using multiple cursors at once, collapsing code for better visibility, and using RStudio's handy tools for debugging your code.
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  3. 3

    Projects

    In this brief chapter, you'll see how to use RStudio projects to organize and share your code with others. Projects come with many benefits, including the ability to keep all relevant files in one place and to easily search all of these files with a single command. You'll also be exposed to the Packrat system for package management and reproducibility.
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Collaborators
Nick Carchedi
Prerequisites
Introduction to R
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Team RStudio

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