Python vs R: some performance comparisons | R Programming

YouTube Excerpt: Calling Python from R is easy and is useful to access Python libraries. In this RStats tutorial, we show you how to set up a Python session within R and some tips for translating your code. We will also run similar algorithms in Python and R to see how they compare for speed! Subscribe to learn more about R and how you can make your code faster. 🐍 00:00 Introduction and dataset 01:45 1st approach: Growing a vector with for loops 02:55 Translating R code to Python code 07:48 1st approach: Benchmarking 08:47 2nd approach: Dataframe pre-allocation 10:41 3rd approach: Lists - vectorization 13:17 4th approach: Linear algebra - matrices: Numpy 14:52 5th approach: Dataframe manipulation: Pandas 16:36 Fastest algorithms comparison 🦕 Get the code here: https://github.com/MaximeRivest/dds/blob/master/README.md 🏎️ R performance playlist https://www.youtube.com/playlist?list=PLyogaPCPr32UaTp-9Fsj4tb_aIcAQ3jKb 🧮 dplyr playlist https://www.youtube.com/playlist?list=PLyogaPCPr32W9wbszOANRJiAvUbbymcCS #R #Rprogramming #Python #Rtutorial #RStats #performance #RStudio #datascience #DDS #DDSR #datatable #dplyr

Calling Python from R is easy and is useful to access Python libraries. In this RStats tutorial, we show you how to set up a Python session within...

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