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rdatatable
data.table:Extension of `data.frame`
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Maintained by Tyson Barrett. Last updated 1 days ago.
3.7k stars 23.47 score 230k scripts 4.6k dependents
hope-data-science
tidyfst:Tidy Verbs for Fast Data Manipulation
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.
Maintained by Tian-Yuan Huang. Last updated 7 months ago.
100 stars 10.06 score 118 scripts 4 dependents
gdemin
maditr:Fast Data Aggregation, Modification, and Filtering with Pipes and 'data.table'
Provides pipe-style interface for 'data.table'. Package preserves all 'data.table' features without significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data manipulation tasks. For example, you can write 'take(mtcars, mean(mpg), by = am)' for aggregation or 'let(mtcars, hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional aggregation/modification. Additionally there are some conveniences such as automatic 'data.frame' conversion to 'data.table'.
Maintained by Gregory Demin. Last updated 5 months ago.
61 stars 8.98 score 248 scripts 7 dependents