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Rdatatable/data.table

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R's data.table package extends data.frame:

16 mentions on Hacker News by 12 people: 1 story, 15 comments · first 2014-11-24 · latest 2024-03-15

Mentions per year 16 mentions · busiest year 2014 (4)
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  1. ▲ 1
    Data.table: R's data.table package extends data.frame
    story by tosh · 2024-03-15 · 0 comments
  2. …package may also make a huge difference in performance, and often simplifies the code as well https://github.com/Rdatatable/data.table
    comment by karencarits · 2023-12-21 · in Discovering copy-on-write in R
  3. data.table is basically a highly optimized C library https://github.com/Rdatatable/data.table
    comment by nojito · 2021-03-14 · in I wrote one of the fastest DataFrame libraries
  4. …way in the last decade. The tibble and data.table packages both address this issue. data.table ( https://github.com/Rdatatable/data.table ) is the more strongly-typed of the two, by default it fails loudly when it encounters data that…
    comment by kyllo · 2020-04-24 · in R 4.0
  5. Almost always faster, actually. https://github.com/Rdatatable/data.table/wiki/Benchmarks-:-G...
    comment by creddit · 2019-06-21 · in Another Book on Data Science – Learn R and Python in Parallel
  6. Have you seen the R package data.table ( https://github.com/rdatatable/data.table )? Not sure whether data.table is in the same domain as xsv, and certainly a lot of it is written in C. But for comparison's sake: fread("cities.csv") 1.30 s…
    comment by hugh-avherald · 2018-09-09 · in XSV: A fast CSV command-line toolkit written in Rust
  7. …usually implemented with something else under the hood. Take the data.table library, for example: https://github.com/Rdatatable/data.table It's wicked fast for many kinds of tasks, but its R API is just a thin layer on top of C.
    comment by michaelsbradley · 2018-02-07 · in Python’s Weak Performance Matters
  8. …Arrow can perform, and hopefully we'll see solid bindings to R as well. The data.table package ( https://github.com/Rdatatable/data.table/wiki ) does make progress on some of these - I'd say #1, #3, maybe #7, #8. Dplyr has a query planner…
    comment by huac · 2017-09-26 · in Apache Arrow and the “Things I Hate About Pandas”
  9. …underrated teaching tools. The R package "data.table" does a good job at this. Just scroll through https://github.com/Rdatatable/data.table/blob/master/R/data.... and search for "warning(".
    comment by nerdponx · 2017-07-20 · in Writing code with multiple overlapping side effects with a straight face
  10. …in less than a few years. I think this is the trend given it's faster than basically everything: https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A...
    comment by mikeskim · 2016-07-23 · in Boost Your Data Munging with R
  11. …faster). It's possible to use dplyr and data.table together, as well, to good effect[2]. [1] https://github.com/Rdatatable/data.table/wiki [&] https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A... [2]…
    comment by michaelsbradley · 2016-06-18 · in Data Analysis with Vector Functional Programming [video]
  12. data.table and dplyr take data frames up a notch! https://github.com/Rdatatable/data.table/wiki/Getting-starte... https://cran.rstudio.com/web/packages/dplyr/vignettes/introd... xts is quite useful as well, when you need to do…
    comment by michaelsbradley · 2016-06-09 · in R Passes SAS in Scholarly Use
  13. …a detailed benchmark (only on grouping so far) on 10 million (in MB) to 2 billion rows (100GB): https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A...
    comment by arun_sriniv · 2014-12-30 · in Dataframes – Julia, R, Python
  14. Here's a benchmark Matt recently did comparing data.table, dplyr and pandas on 50GB and 100GB: https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A...
    comment by arun_sriniv · 2014-12-05 · in The R language, for programmers
  15. …the philosophy behind data.table's `i, j, by`. Should make things lot easier for beginners - https://github.com/Rdatatable/data.table/issues/944 data.table is not just fast, but is also more memory efficient - we want to highlight in the…
    comment by arun_sriniv · 2014-12-05 · in The R language, for programmers
  16. I'd start here: https://github.com/Rdatatable/data.table/wiki/Benchmarks-:-G... Performance isn't currently a huge focus for dplyr. In my opinion dplyr is fast enough that the bottleneck becomes mostly cognitive - you spend more time…
    comment by hadley · 2014-11-24 · in Rvest: Easy web scraping with R