Package: collapse
Title: Advanced and Fast Data Transformation
Version: 1.1.0
Date: 2020-03-27
Authors@R: c(
           person("Sebastian", "Krantz", role = c("aut", "cre"), 
                  email = "sebastian.krantz@graduateinstitute.ch"),
           person("Matt", "Dowle", role = "ctb"),
           person("Arun", "Srinivasan", role = "ctb"),
           person("Simen", "Gaure", role = "ctb"),
           person("Dirk", "Eddelbuettel", role = "ctb"),
           person("R Core Team and contributors worldwide", role = "ctb"),
           person("Martyn", "Plummer", role = "cph"),
           person("1999-2016 The R Core Team", role = "cph")
           )
BugReports: https://github.com/SebKrantz/collapse/issues
Description: A C/C++ based package for advanced data transformation in R that is 
    extremely fast, flexible and parsimonious to code with and programmer 
    friendly. It is well integrated with 'dplyr', 'plm' and 'data.table'.
    --- Key Features: ---
    (1) Advanced data programming: A full set of fast statistical functions 
        supporting grouped and/or weighted computations on vectors, matrices 
        and data.frames. Fast (ordered) and reusable grouping, quick data 
        conversions, and quick select, replace or add data.frame columns.
    (2) Advanced aggregation: Fast and easy multi-data-type, multi-function, 
        weighted, parallelized and fully customized data aggregation.
    (3) Advanced transformations: Fast (grouped, weighted) replacing and 
        sweeping out of statistics, scaling, centering, higher-dimensional 
        centering, complex linear prediction and partialling-out.
    (4) Advanced time-computations: Fast (sequences of) lags / leads, and 
        (lagged / leaded, iterated) differences and growth rates on (unordered) 
        time-series and panel data. Multivariate auto, partial and cross-
        correlation functions for panel data. Panel data to (ts-)array conversions.
    (5) List Processing: (Recursive) list search / identification, extraction / 
        subsetting, data-apply, and row-binding / unlisting in 2D.
    (6) Advanced data exploration: Fast (grouped, weighted, panel-decomposed) 
        summary statistics for complex multilevel / panel data.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.1), lfe (>= 2.7)
LinkingTo: Rcpp
Suggests: dplyr, plm, data.table, ggplot2, scales, vars, knitr,
        rmarkdown, testthat, microbenchmark
SystemRequirements: C++11
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-03-30 23:48:35 UTC; Sebastian Krantz
Author: Sebastian Krantz [aut, cre],
  Matt Dowle [ctb],
  Arun Srinivasan [ctb],
  Simen Gaure [ctb],
  Dirk Eddelbuettel [ctb],
  R Core Team and contributors worldwide [ctb],
  Martyn Plummer [cph],
  1999-2016 The R Core Team [cph]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>
Repository: CRAN
Date/Publication: 2020-04-01 12:20:03 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 06:21:00 UTC; windows
Archs: i386, x64
