Python’s Pandas vs. R’s dplyr – Which Is The Best Data Analysis Library

 By R-bloggers - 2021-02-06

Description

Pandas vs. dplyr It’s difficult to find the ultimate go-to library for data analysis. Both R and Python provide excellent options, so the question quickly becomes “which data analysis library is the m

Summary

  • As mentioned earlier, this article assumes you are equally skilled in both R and Python.
  • Image 12 – Average life expectancy per continent in 2007 (dplyr) As you can see, both libraries use some sort of grouping functions – groupby() with Pandas, and group_by() with dplyr, which results in a similar-looking syntax.
  • Conclusion According to the test made in this article, dplyr is a clear winner.
  • If you’re a big-time Pandas user, solving tasks with dplyr might seem unnatural, resulting in more time spent to solve the task.

 

Topics

  1. Coding (0.25)
  2. Backend (0.08)
  3. Management (0.06)

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