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sebkrantz
collapse:Advanced and Fast Data Transformation
A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', 'plm' (panel-series and data frames), and 'xts'/'zoo'.
Maintained by Sebastian Krantz. Last updated 8 days ago.
data-aggregationdata-analysisdata-manipulationdata-processingdata-sciencedata-transformationeconometricshigh-performancepanel-datascientific-computingstatisticstime-seriesweightedweightscppopenmp
672 stars 16.68 score 708 scripts 99 dependentsinsightsengineering
rtables:Reporting Tables
Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Maintained by Joe Zhu. Last updated 3 months ago.
232 stars 13.65 score 238 scripts 17 dependentsfishfollower
stockassessment:State-Space Assessment Model
Fitting SAM...
Maintained by Anders Nielsen. Last updated 27 days ago.
49 stars 7.76 score 324 scripts 2 dependentsluqqe
outliers:Tests for Outliers
A collection of some tests commonly used for identifying outliers.
Maintained by Lukasz Komsta. Last updated 3 years ago.
1 stars 6.56 score 888 scripts 11 dependents