R vs. Python: Which Should You Learn First?

Yesi Days
3 min readSep 3, 2023

So you’re just setting foot into the thrilling world of data science, and you’ve probably heard the names R and Python tossed around as the languages of the data gods. But which should you learn first?

Learning a programming language isn’t like choosing a life partner; you’re not stuck with your first choice forever. Both R and Python are excellent tools with their pros and cons.

Before diving into the R vs. Python debate, let’s briefly discuss data science. Data science is the field where statistics, programming, and domain knowledge combine to extract insights from data. Whether it’s predicting election outcomes, recommending Netflix shows, or analyzing medical data, data science is everywhere.

The R Programming Language

Origin and Philosophy

R was created in 1993 and was primarily developed for statisticians and data miners. It’s a language that focuses on making data analysis and statistical work as smooth as possible.

Syntax

R’s syntax is highly user-friendly. This is especially helpful for those who need to gain prior programming experience.

Pros

  • Excellent for Statistical Analysis and Data Visualization
  • Comprehensive library for data analysis
  • Active community and a plethora of free learning resources

Cons

  • Slower computational speed
  • Not as versatile as Python for non-data science tasks

The Python Programming Language

Origin and Philosophy

Python was conceived in the late 1980s but has seen a massive upsurge in popularity in the last decade. Unlike R, Python wasn’t built solely for data analysis; it’s a general-purpose language.

Syntax

Python’s syntax is clean and easy to understand, making it great for beginners.

Pros

  • Extremely Versatile: Can be used for web development, automation, and more
  • Libraries like Pandas, NumPy, and…

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Yesi Days

GDE Machine Learning | Data Scientist | PhD in Artificial Intelligence | Content creator | Ex-backend