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Hi, Wes here. R data frames have limited to no query planning and are not multithreaded in general, so Problems 10 and 11 are problems in R also.

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Native data.frames don't but data.table does to some extent. It's parallelization is still relatively new/nascent and requires OpenMP which doesn't have good support on MacOS but it is present.

And R’s syntax leaves much to be desired: it’s ugly compared to python’s.

To each their own - I find the grammar of dplyr and the tidyverse is quite elegant.

Agreed! Sadly it is difficult to fully emulate in Python without some form of delayed evaluation in the language.

R is one of the few language that popularize data frame.

Out of SAS, R, and Python or even C++ and Java. Data frame are native.

So personally, the syntax especially for data frame is beautiful compares to python.

Python don't even have missing value built in or subsetting data frame.

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