If you are working with data analysis, then R could be the language for you. R is an open-source language (meaning it is free) developed for statisticians with the purpose of making it easier to do great data analysis. And with with an active community, R is becomming more user friendly. It is especially popular witin fields as statistics, data analysis or analytics, machine learning, and psychometrics!
If you are just getting started, I suggest you have a look at R studio education, where they suggest 6 ways to begin to learn R. As they say “No one starting point will serve all beginners”.
I would suggest getting around R-studio, rmarkdown, tidyverse, ggplot2, and you should be well on your way.
You may be interested in:
R programming for research, an online course book for Colorado State University, by Brooke Anderson, Rachel Severson, and Nicholas Good. It has the chapters: Preliminaries, Basics, Intermediate, Advanced.
“Advanced R“, by Hadley Wickham, for R users who want to improve their programming skills and understanding of the language. It has the chapters: Foundations, Functional programming, Object-oriented programming, Metaprogramming, Techniques.
“R for Data Science” which introduces you to R as a tool for doing data science, focussing on a consistent set of packages known as the tidyverse. It has the chapters: Explore, Wrangle, Program, Model, and Communicate.
“R Packages” which teaches you how to make the most of R’s fantastic package system. It has the chapters: Getting started, Package components, Package metadata, Testing, Documentation, Maintenance and distribution.
Here are some good R forums: https://r-dir.com/community/forums.html