Summary and Schedule

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IRIM R Workshops

Presented by Kathryn Napier, with material adapted from from several Carpentries resources, including:

• Data Analysis and Visualization in R for Ecologists
• R for Social Scientists

The English version of the IRIM R Workshop website is located here.

A Mongolian version of the IRIM R Workshop website is located here.

The Mongolian text is automatically translated from the original English text using Google Translate.

The Carpentries aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This is an introduction to R designed for participants with no programming experience. The workshop includes:

The workshop starts with information about the R programming language and the RStudio interface.

1. Introduction to R and R Studio

2. Introduction to R Packages, R Markdown and R Notebooks

3. Starting with data in R

4. Manipulating Data with dplyr and tidyr

This lesson assumes no prior knowledge of R or RStudio and no programming experience.

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. Introduction to R and RStudio	Why should you use R and RStudio? How do you get started working in R and RStudio? :::
Duration: 00h 45m	2. Introduction to R Packages, Markdown and Notebooks	What is an R package? How to install R packages? What is R Markdown and R Notebooks? How can I integrate my R code with text and plots? How can I convert .Rmd files to .html? :::
Duration: 01h 45m	3. Starting with Data	How does R store data? What is a data.frame? How can I read a complete .csv file into R? How can I get basic summary information about my dataset? How can I change the way R treats strings in my dataset? Why would I want strings to be treated differently? How are dates represented in R and how can I change the format? :::
Duration: 02h 57m	4. Manipulating Data with dplyr and tidyr	How can I select specific rows and/or columns from a dataframe? How can I combine multiple commands into a single command? How can I create new columns or remove existing columns from a dataframe? How can I reformat a data frame to meet my needs? :::
Duration: 04h 27m	5. Quantitative Data Analysis in R	What statistical tests should I use? How can I run multiple tests at once? :::
Duration: 05h 57m	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

Preparations

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This series of workshops are designed to be hands-on, so learners must have R and RStudio installed on their computers. You also need to be able to install a number of R packages, create directories, and download files.

Install R and RStudio

R and RStudio are two separate pieces of software:

• R is a programming language and software used to run code written in R.
• RStudio is an integrated development environment (IDE) that makes using R easier. In these workshops, we use RStudio to interact with R.

If you don’t already have R and RStudio installed, follow the instructions for your operating system below. You have to install R before you install RStudio.

For Windows

• Download R from the CRAN website.
• Run the .exe file that was just downloaded
• Go to the RStudio download page
• Click INSTALL RSTUDIO DESKTOP FOR WINDOWS
• Run the .exe file that was just downloaded
• Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.

For MacOS

• Download R from the CRAN website.
• Select the .pkg file for the latest R version
• Double click on the downloaded file to install R
• It is also a good idea to install XQuartz (needed by some packages)
• Go to the RStudio download page
• Under Installers select Mac OS 13+ - RSTUDIO-xxxx.yy.z-zzz.dmg (where x = year, y = month, and z represent version numbers)
• Double click the file to install RStudio
• Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.

For Linux

• Click on your distribution in the Linux folder of the CRAN website. Linux Mint users should follow instructions for Ubuntu.
• Go through the instructions for your distribution to install R.
• Go to the RStudio download page
• Select the relevant installer for your Linux system (Ubuntu/Debian or Fedora)
• Double click the file to install RStudio
• Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.

Update R and RStudio

If you already have R and RStudio installed, first check if your R version is up to date:

• When you open RStudio your R version will be printed in the console on the bottom left. Alternatively, you can type sessionInfo() into the console. If your R version is 4.0.0 or later, you don’t need to update R for this workshop. If your version of R is older than that, download and install the latest version of R from the R project website for Windows, for MacOS, or for Linux
• It is not necessary to remove old versions of R from your system, but if you wish to do so you can check How do I uninstall R?
• After installing a new version of R, you will have to reinstall all your packages with the new version. For Windows, there is a package called installr that can help you with upgrading your R version and migrate your package library. A similar package called pacman can help with updating R packages across To update RStudio to the latest version, open RStudio and click on Help > Check for Updates. If a new version is available follow the instruction on screen. By default, RStudio will also automatically notify you of new versions every once in a while.

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The changes introduced by new R versions are usually backwards-compatible. That is, your old code should still work after updating your R version. However, if breaking changes happen, it is useful to know that you can have multiple versions of R installed in parallel and that you can switch between them in RStudio by going to Tools > Global Options > General > Basic.

While this may sound scary, it is far more common to run into issues due to using out-of-date versions of R or R packages. Keeping up with the latest versions of R, RStudio, and any packages you regularly use is a good practice.

Install required R packages

During the workshops we will need a number of R packages. Packages contain useful R code written by other people. We will use the tidyverse package.

To try to install these packages, open RStudio and copy and paste the following command into the console window (look for a blinking cursor on the bottom left), then press Enter (Windows and Linux) or Return (MacOS) to execute the command.

R

install.packages("tidyverse")
install.packages("help")

Alternatively, you can install the packages usingRStudio's graphical user interface by going to Tools > Install Packages and typing the names of the packages separated by a comma.

R tries to download and install the packages on your machine.

When the installation has finished, you can try to load the packages by pasting the following code into the console:

R

library(tidyverse)
library(here)

If you do not see an error like there is no package called ‘...’ you are good to go!

Updating R packages

Generally, it is recommended to keep your R version and all packages up to date, because new versions bring improvements and important bugfixes. To update the packages that you have installed, click Update in the Packages tab in the bottom right panel of RStudio, or go to Tools > Check for Package Updates...

Sometimes, package updates introduce changes that break your old code, which can be very frustrating. To avoid this problem, you can use a package called renv. It locks the package versions you have used for a given project and makes it straightforward to reinstall those exact package version in a new environment, for example after updating your R version or on another computer. We will introduce the renv package at a future workshop.