Why learn R?

R is a statistical programming language that is used for all steps of the data science process: processing data, analyzing data, building models, and visualizing data. It can even be used to create full reports!

I wrote a post with more details about R and RStudio last week, and I made a video about it over on the Schilling Data Studio YouTube channel.

Today, I want to answer the question: why learn R?

First, R and the software I like to use to write R code (RStudio) are completely free. This means you do not have to pay anything to use them. The R programming language is also open source, which means that people can add on to it and make it better.

This leads me to reason number two: R is flexible and powerful. There are many add-ons to the base R language, called packages. People write packages to make R do more advanced things.

For example, there’s a package called ggwordcloud, which allows you to easily make word cloud visualizations. And that’s not even the only word cloud package, there’s another one simply called wordcloud that’s not quite as advanced, but still accomplishes a basic word cloud.

There are packages to do text analysis, create advanced data visualization, develop reports and presentations, process data, make machine learning models, and so much more (including make art)!

R can do a lot! I love that I can always learn new functions and methods, and I’ve always been able to find a package to do the analysis, visualization, or model that I want.

The third reason to learn R is that R allows you to reproduce, repeat, and share your work easily. When you create an analysis or visualization in a software like Excel, Google Sheets, or Tableau, you have to click on all the options and write formulas inside cells or variables. This can make it challenging for someone else to reproduce or replicate your results. It can also make it challenging for you to easily repeat the process with different data.

With R, you don’t have these challenges. The code to complete a data analysis or create a visualization can be shared with another person who simply has to run the code to reproduce the results. Plus, every step of the process is written out in the code, making it easy for someone else to check the steps and see exactly what you did.

Plus, you can run the same code with updated or different data over again, and the process of analyzing and visualizing data in R is a sequence of steps that is similar each time you do it, so once you learn the sequence and the tweaks you can make based on the type of data you have, it’s easy to repeat analyses with different data.

Finally, the R community is extensive and supportive. There are amazing groups of people learning and working in R together, and there are extensive tutorials, documentation, and answers to questions online that you can find.

So, why learn R? Because R is an amazing tool for working with data, creating visualizations,  developing machine learning models, and even writing reports and articles (plus many more data related tasks). And, I love it!

You may be wondering, do I need to know how to code before I can learn R?

No! R is very user friendly. It’s closer to the way our brains think through processes than the way computers process information. R is a great language to learn as your first coding experience, especially if you want to work with data. The RStudio software also has a lot built into it that can support you as you begin coding.

So, you don’t need to learn to code before you learn R.

Hopefully I’ve convinced you that R is awesome, and now you’d like to learn R!!

If that’s the case, join Learn R With Me to get started! October 3-7, 2022 I’ll be holding a daily hour-long live session to go through an introduction to R, including creating a plot, loading your own data, and doing some data processing and analysis. 

I also have another blog post you might like: 5 Tips for Learning R.