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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 2 days ago.

3.7k stars 23.51 score 230k scripts 4.6k dependents

crunch-io

crunch:Crunch.io Data Tools

The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.

Maintained by Greg Freedman Ellis. Last updated 8 days ago.

9 stars 10.47 score 200 scripts 2 dependents

kurthornik

slam:Sparse Lightweight Arrays and Matrices

Data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.

Maintained by Kurt Hornik. Last updated 5 months ago.

openblas

2 stars 9.45 score 1.3k scripts 308 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.

data-tablemagrittrpipes

61 stars 8.98 score 248 scripts 7 dependents

jsjuni

rollupTree:Perform Recursive Computations

Mass rollup for a Bill of Materials is an example of a class of computations in which elements are arranged in a tree structure and some property of each element is a computed function of the corresponding values of its child elements. Leaf elements, i.e., those with no children, have values assigned. In many cases, the combining function is simple arithmetic sum; in other cases (e.g., mass properties), the combiner may involve other information such as the geometric relationship between parent and child, or statistical relations such as root-sum-of-squares (RSS). This package implements a general function for such problems. It is adapted to specific recursive computations by functional programming techniques; the caller passes a function as the update parameter to rollup() (or, at a lower level, passes functions as the get, set, combine, and override parameters to update_prop()) at runtime to specify the desired operations. The implementation relies on graph-theoretic algorithms from the 'igraph' package of Csárdi, et al. (2006 <doi:10.5281/zenodo.7682609>).

Maintained by James Steven Jenkins. Last updated 23 days ago.

2 stars 5.32 score 1 dependents

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