The swift proliferation of data into our lives has resulted in the rise of tools used to analyze and extract valuable insights from this information. Python and R are the two most popular programming languages used to dissect data. If you’re venturing on a new data science project, choosing between them can be challenging.
Both R and Python are state-of-the-art in terms of their orientation toward data science excellence, making it a tough decision to find the better option. If you use the Venn diagram to map the capabilities of the two languages, you will see a lot of convergence around the data-focused fields.
Nevertheless, Python and R have varying strengths and weaknesses. They also take a different approach to developing code and sharing results.
Learning about both Python and R is obviously the ideal solution to choosing the right language. To help you do just that, we wrote this article. Below we’ll discuss: