Introducing the R tidyverse - R Tutorial

What is the R Tidyverse? You may have heard of some of the R Tidyverse packages and use them in your previous coding work. The R Tidyverse is a collection of R packages designed to primarily use for data science purposes. This ecosystem of packages is built to optimize functionality for common data science tasks. The main data science tasks these Tidyverse packages work with are data importing, data cleaning and wrangling, data analysis and data visualization. Why would you want to use Tidyverse packages to complete these tasks instead of the base R language? Generally, the Tidyverse packages have functions that make it easier, quicker, and simpler to accomplish tasks in R. Instead of having to programme these tasks from scratch, you can simply call on a function from the package and insert any necessary parameters to accomplish your task. Using functions from Tidyverse packages can also make it easier to collaborate with others on your code. Instead of everyone having a different way to accomplish a certain task with code that needs to be explained and documented, you can simply use standardized functions from these packages to accomplish the same task with the same format each time. Are R Tidyverse packages dependable? Anyone can make a package for R, but this leaves a lot up in the air regarding the usability and maintainability of using a package on a long term basis. Thankfully, the development and maintenance of the core Tidyverse packages are done so by the RStudio team. This also ensures the packages work well with this software, since it tends to be a top choice for many R programmers to use. The Tidyverse is also openly developed on GitHub, making it easy to find documentation and code. The R Tidyverse has a website they maintain that contains a lot of great information and documentation about these different packages. Let's head over to the R Tidyverse website to learn more about this collection of packages. On the R Tidyverse home page, you will see a brief introduction to the packages. You will also see the code you need to run to install all Tidyverse packages in your R code, such as in RStudio, so you can view that here where it's install.packages("Tidyverse"); If you navigate to the packages section, you can learn more about the individual packages in this ecosystem. At the top, you will see brief instructions on how to import the Tidyverse and how to learn more about it. Let's click on this link here to learn more about the Tidyverse. On this page you can learn more about the Tidyverse in a condensed manner. At the top are installation instructions. So here you can see how to install packages for the Tidyverse. Below that is usage where it lists out the core Tidyverse packages and their uses. For example, you have ggplot2, which is used for data visualization. Once you scroll down some more towards the bottom, you can view some less frequently used tidyverse packages. In this course, you will learn about the functioning of all the main Tidyverse packages along with the readxl package. Let's navigate back to the packages page. Here you can see the core Tidyverse packages. So here we have ggplot2, dplyr, tidyr, readr, purrr tibble, stringr, and forcats. Near the bottom, you can view more resources regarding importing, wrangling, programming, and modeling data with the Tidyverse. Let's scroll back up to the tidyr package. If you click on the word tidyr, or the go to docs link, it will take you to the tidyr information page. Each of the main Tidyverse package pages will be formatted similar to this one. At the top you'll see an overview of the package and what type of functionality it has. Below that, you can view some installation instructions on how to install all packages for the Tidyverse along with that particular package. Below that is a link to a cheat sheet for that package, which I will dive into later in this course as I review each package. And below that you'll see some other content regarding the package, for example usage, getting started, some examples, related work and getting help. Let's navigate back to the Tidyverse website. In the navigation you will see a Blog page. So if you click here, this will show you a variety of blog posts including updates regarding the Tidyverse. Next, if you click on the Learn section, you can find some common learning tools for the Tidyverse packages. This includes some books that are listed here, along with some workshops and some teaching materials. If you click on the Help section, you can learn how to make a reprex, also known as a reproducible example to get help with your R Tidyverse code. If you scroll down to the bottom, you will also find some common resources on how to get help with your R Tidyverse code, for example StackOverflow and their community website. In the last section called Contribute, you can view how you can contribute to the R Tidyverse once you get more comfortable with it. This includes helping answer questions, filing issues, contributing to documentation, and contributing to code. I suggest taking a few minutes to familiarize yourself with this website, especially the packages section, since I will often reference it throughout this course. You can also learn more about the R Tidyverse via LinkedIn learning courses such as Charlotte Hadley's course Learning the R Tidyverse. Up next, I will walk you through the main packages that will be discussed in this course.