dtplyr provides the most impressive speed for packages in R. dplyr is the most frequently used package in the R community for data wrangling. Sometimes, for large datasets, it can be somewhat slow. Scientific researcher and financial engineer Guillaume Coqueret. An Associate Professor of Finance & Data Science at Emlyon business school tested some supposedly fast alternatives:
– firstly, multidplyr: https://lnkd.in/dPhD7s7h
– secondly, tidytable: https://lnkd.in/dAEFejNn
– in addition, collapse: https://lnkd.in/d8PJNWFg
– dtplyr: https://lnkd.in/dp-Aszx7
– lastly, arrow: https://lnkd.in/dDDBzHgv
Moreover, based on a (limited) exercise of pivot-tables (grouping & summarizing) over a dataset of ~4M rows, I find that dtplyr provides the most impressive speed.
http://www.gcoqueret.com/files/misc/benchmark_dplyr.html
dtplyr provides the most impressive speed for packages in R
What is R coding used for?
R is a programming language for statistical computing and graphics that you can use to clean, analyze, and graph your data. Moreover, widely used by researchers from diverse disciplines. To estimate and display results and by teachers of statistics and research methods.
Is R difficult to learn, is R Hard to Learn?
Yes, the difficulty level of learning coding in R is substantial. This is in large part because R is so different to many programming languages. Lastly, the syntax of R, unlike languages like Python, is very difficult to read.
