What question did this study set out to answer?

This paper aims to compare R and Python as tools for data science, addressing aspects of usability and performance.

February 21, 2026

R (and Dialects) versus Python for Data Science

Key Points

This paper aims to compare R and Python as tools for data science, addressing aspects of usability and performance.
Comparative analysis of R and Python based on various criteria.
Examination of base-R and tidyverse as different dialects of R.
Assessment of learning curves and coding philosophies of both languages.
Python shows a steeper learning curve compared to R.
Base-R and tidyverse have distinct advantages in terms of clarity and expressiveness.
High-performance computing capabilities are evaluated for both languages.

Abstract

ABSTRACT R and Python are the two dominant language tools for data science today. Which one is better, and in what senses? This paper explores such questions, in terms of aspects such as learning curve, clarity of expression, coding philosophy, high‐performance computing capability and so on. Also, the article treats base‐ R and the tidyverse as two separate ‘dialects’ of R , so that the above comparisons are in many cases tripartite in nature.

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