DataFramed #70 Beyond the Language Wars: R & Python for the Modern Data Scientist
Sep 6, 2021
Rick Scavetta, a prolific data science educator and founder of Skaveta Academy, teams up with Boyan Angelov, a data strategist and author, to discuss their new book. They dive into the history of Python and R, advocating for a collaborative approach in data science. The duo explains how each language has unique strengths and benefits for different tasks. They emphasize the importance of being bilingual in these languages and share insights on how beginner and experienced data scientists can enhance their skill sets for modern challenges.
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Origins of R and Python
- R originated in academia for statistical analysis, termed "FUBU" (for us, by us).
- Python emerged as a general-purpose language, with data science applications coming later.
Beyond One-to-One Translation
- Direct translation between R and Python is not ideal; aim for bilingualism.
- Focus on understanding each language's approach to problem-solving.
Conceptual Thinking through Bilingualism
- Bilingualism in programming fosters conceptual thinking, not just syntax.
- This allows for faster problem-solving and creative solutions.
