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tidyfst: Tidy Verbs for Fast Data Manipulation

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ZENODO DOI JOSS DOI

Overview

tidyfst is a toolkit of tidy data manipulation verbs with data.table as the backend . Combining the merits of syntax elegance from dplyr and computing performance from data.table, tidyfst intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of data.table, while enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations. Also, tidyfst would introduce more tidy data verbs from other packages, including but not limited to tidyverse and data.table. If you are a dplyr user but have to use data.table for speedy computation, or data.table user looking for readable coding syntax, tidyfst is designed for you (and me of course). For further details and tutorials, see vignettes. Both Chinese and English tutorials could be found there.

Till now, tidyfst has an API that might even transcend its predecessors (e.g. select_dt could accept nearly anything for super column selection). Enjoy the efficient data operations in tidyfst !

PS: For extreme performance in tidy syntax, try tidyfst’s mirror package tidyft.

Features

Installation

install.packages("tidyfst")

Example

library(tidyfst)

iris %>%
  mutate_dt(group = Species,sl = Sepal.Length,sw = Sepal.Width) %>%
  select_dt(group,sl,sw) %>%
  filter_dt(sl > 5) %>%
  arrange_dt(group,sl) %>%
  distinct_dt(sl,.keep_all = T) %>%
  summarise_dt(sw = max(sw),by = group)
#>         group  sw
#>        <fctr> <num>
#> 1:     setosa 4.4
#> 2: versicolor 3.4
#> 3:  virginica 3.8

iris %>%
  count_dt(Species) %>%
  add_prop()
#>       Species     n      prop prop_label
#>        <fctr> <int>     <num>     <char>
#> 1:     setosa    50 0.3333333      33.3%
#> 2: versicolor    50 0.3333333      33.3%
#> 3:  virginica    50 0.3333333      33.3%

iris[3:8,] %>%
  mutate_when(Petal.Width == .2,
              one = 1,Sepal.Length=2)
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species one
#>          <num>       <num>        <num>       <num>  <fctr> <num>
#> 1:          2.0         3.2          1.3         0.2  setosa   1
#> 2:          2.0         3.1          1.5         0.2  setosa   1
#> 3:          2.0         3.6          1.4         0.2  setosa   1
#> 4:          5.4         3.9          1.7         0.4  setosa  NA
#> 5:          4.6         3.4          1.4         0.3  setosa  NA
#> 6:          2.0         3.4          1.5         0.2  setosa   1

Future plans

tidyfst will keep up with the updates of data.table , in the next step would introduce more new features to improve the performance and flexibility to facilitate fast data manipulation in tidy syntax.

Vignettes

Cheat sheet

Suggested citation

Huang et al., (2020). tidyfst: Tidy Verbs for Fast Data Manipulation. Journal of Open Source Software, 5(52), 2388, https://doi.org/10.21105/joss.02388

Acknowledgement

The author of maditr, Gregory Demin and the author of fst, Marcus Klik have helped me a lot in the development of this work. It is so lucky to have them (and many other selfless contributors) in the same open source community of R.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.