Why were pandas merges in python faster than data.table merges in R in 2012?

Michael Zippo

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I recently came across the pandas library for python, which according to this benchmark performs very fast in-memory merges. It"s even faster than the data.table package in R (my language of choice for analysis).

Why is pandas so much faster than data.table? Is it because of an inherent speed advantage python has over R, or is there some tradeoff I"m not aware of? Is there a way to perform inner and outer joins in data.table without resorting to merge(X, Y, all=FALSE) and merge(X, Y, all=TRUE)?

Here"s the R code and the Python code used to benchmark the various packages.

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Boris Chamberlet

Paris | 2023-03-26

I was preparing for my coding interview, thanks for clarifying this - Why were pandas merges in python faster than data.table merges in R in 2012? in Python is not the simplest one. Will use it in my bachelor thesis

Oliver Williams

Massachussetts | 2023-03-26

Maybe there are another answers? What Why were pandas merges in python faster than data.table merges in R in 2012? exactly means?. I am just not quite sure it is the best method

Jan Richtgofen

Tallinn | 2023-03-26

Thanks for explaining! I was stuck with Why were pandas merges in python faster than data.table merges in R in 2012? for some hours, finally got it done 🤗. Checked yesterday, it works!