Python vs R – Which is better for data science?

  • Why are where?
  • Which is better in Data Science, ML and LLM?
  • Disadvantages
  • Conclusion – Which is better for you?

Python vs R – Which is better for data science?

Python

  • Python is widely being used as a programming language across multiple sectors.
  • Python is widely used in software development, web development and game development.
  • Python is also used in the field of data science, model development, LLM development, Artificial intelligence and also for visualization developments.
  • Python has very vast and active user community and you will get lots of articles and help on almost all topics of Python.
  • Python has c.3L+ packages available.
  • Python is also known for its ecosystem and integration, Jupyter notebook is very famous for python.

R Language

  • R is a language built for math and statistics. R is also know as statistic language, if you are some one who is from math/stat background and looking for the career in stat or math then R is the language for you.
  • R is very popular in academic areas and research, finance, visualization and data science. R is majorly used in the domains like Healthcare, pharma, BPO etc.
  • R is also known for its data visualization capabilities, R shiny is very popular and power to create dashboards or tools. R has many visualization libraries and they are highly customizable and powerful.
  • R has c.20k packages available in the Comprehensive R Archive Network (CRAN).
  • R’s most popular IDE is R Studio, it is very powerful and you can see your charts parallelly while writing code in the R studio window itself. Also R studio is very useful in creating R shiny dashboards.

R and Python in Machine Learning and LLM

Disadvantages of Python and R

Conclusion – Python vs R – Which is better?

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