Workshop: Dealing with Data in R

An introduction to R for data management and manipulation

Instructor: Steffi LaZerte (sel@steffilazerte.ca)
Location: Online
Date/time: Tues/Wed February 27-28th 2024, 8:30am-4:30pm Pacific

This workshop is being run for staff in BC Government. Contact Julie-Ann Ishikawa to register.

⚠️Important!⚠️

Make sure you’re ready for the workshop by following the Before the workshop instructions below. Please email Steffi if you run into any problems.

Take care to update both R and RStudio, in particular.

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Welcome!

Running statistics in R, while difficult, is made even more so by the challenge of using R to manipulate data. This workshop therefore focuses on teaching the use of RStudio and the tidyverse suite of packages (e.g., ggplot2, dplyr, tidyr, etc.) to create figures and data visualizations, load, clean and summarize data, and generally troubleshoot R. This workshop is geared towards raw beginners, those with a basic familiarity with R, and towards intermediate R users unfamiliar with the tidyverse suite of packages or those wanting to up their game.

Each day includes an hour for you to work on your own data, with support from the instructor to work through your own R problems and learn how to do analyses specific to your work. Please bring your work if you would like to take advantage of this.

This GitHub repository holds all the information relating to our workshop.

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Slides

These are the slides used throughout the workshop. Answers to the activities are be posted after the workshop.

I recommend using the html version of these slides as they will be the most accurate with respect to formatting and will allow you to easily copy/paste code and navigate

1. Intro to R (html | pdf | html-answers | pdf-answers)

2. Visualizing data in R (html | pdf | html-answers | pdf-answers)

3. Loading & Cleaning Data in R (html | pdf | html-answers | pdf-answers)

4. Summarizing & Transforming Data in R (html | pdf | html-answers | pdf-answers)

5. Getting help with R (html | pdf | No answer slides)

Answer slides will be posted after the workshop

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Before the workshop - In brief

(see below for details)

• Install/Update R

• Install/Update RStudio

• Install R packages for following along

  • tidyverse
  • patchwork
  • palmerpenguins
  • skimr
  • janitor
  • readxl

  To install via R commands:

  install.packages(c("tidyverse", "palmerpenguins", "skimr", "patchwork", "janitor", "readxl"))
  

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Before the workshop - In detail

1. Install/Update R

Even if you already have R installed, please update it, so we’re all working with the same version.

Depending on your operating system, you can install R in one of the following ways:

Windows

• Go to the Windows download page: https://muug.ca/mirror/cran/bin/windows/base/
• Download and install R for windows (the link at the top)

Mac

• Go to the Mac OS X download page: https://muug.ca/mirror/cran/bin/macosx/
• Download and install the version that matches your Mac OS X

Linux: Debian/Ubuntu

• Specific details:
  • Ubuntu https://muug.ca/mirror/cran/bin/linux/ubuntu/
  • Debian https://muug.ca/mirror/cran/bin/linux/debian/
• Add one of the CRAN repositories to you apt (otherwise your R will be out of date)

2. Install/Update RStudio

Even if you already have RStudio installed, please update it, so we’re all working with the same version.

For all Operating systems (i.e., Windows, Mac Os, Linux, etc.) follow step 2 from RStudio’s download page: https://www.rstudio.com/products/rstudio/download/#download

Open RStudio not R . RStudio automatically opens R for you in the ‘Console’ pane

Verify your version of R by looking at the first line of the console (left or lower left pane), you should see something like this:

R version 4.3.2 (2023-10-31) -- Eye Holes
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

The important line is the first one: R version 4.3.2 (2023-10-31) – Eye Holes

3. Install/Update Packages

Packages are extensions or add-ons for R. You will use many different ones over the course of your work with R. tidyverse is name of a collection of newer packages for data management.

We will use the following packages:

• tidyverse
• patchwork
• palmerpenguins
• skimr
• janitor
• readxl

Installing/Updating these packages may take a while (you will see lots of download text in red in your console). When it’s finished, you should see a message similar this one to in the console (lower left hand pane)

* DONE (tidyverse)

The downloaded source packages are in
    ‘/tmp/RtmpACWq9S/downloaded_packages’
> 

To install/update via R commands, type the following in the R Console

install.packages(c("tidyverse", "palmerpenguins", "skimr", "patchwork", "janitor", "readxl"))

Alternatively you can use the RStudio package manager.

• Click on the ‘Packages’ tab in the lower right hand corner
• Click on the ‘Install’ button right below the tab
• Type the name of the package (e.g., ‘tidyverse’) into the ‘Packages’ box, and click on ‘Install’
• Repeat for the other packages

• Test that your installation had no problems by typing library("tidyverse") into the console and hitting enter. You should see something like this (Note: These are messages, not errors!):

library("tidyverse")

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Problems?

• If you already had R/RStudio installed, try removing them both and installing everything from scratch
• If you get an error about a problem installing a specific package or with the tidyverse, try installing packages invidiually
  • dplyr, tidyr, readr, ggplot2, lubridate
  • e.g., install.packages("dplyr") or in the Install Packages Menu
• Email Steffi sel@steffilazerte.ca

4. A bit of background (optional)

If you have time, consider reading the first couple of sections of R for cats (“Using the R console” to “lists”).

This is a quick introduction to R coding which is will be a great way to get up to speed on the basics before we jump in.

Congratulations! Now you’re ready to get into the fun stuff :)