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Advanced and Fast Data Transformation
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Fast Statistical Functions

Fast (grouped and weighted) statistical functions for vector, matrix, data frame and grouped tibble (class ‘grouped_df’, dplyr compatible).

Fast (Grouped, Weighted) Statistical Functions for Matrix-Like Objects
Fast (Grouped, Weighted) Mean for Matrix-Like Objects
fnth() fmedian()
Fast (Grouped, Weighted) N'th Element/Quantile for Matrix-Like Objects
Fast (Grouped, Weighted) Statistical Mode for Matrix-Like Objects
Fast (Grouped, Weighted) Sum for Matrix-Like Objects
Fast (Grouped, Weighted) Product for Matrix-Like Objects
fvar() fsd()
Fast (Grouped, Weighted) Variance and Standard Deviation for Matrix-Like Objects
fmax() fmin()
Fast (Grouped) Maxima and Minima for Matrix-Like Objects
ffirst() flast()
Fast (Grouped) First and Last Value for Matrix-Like Objects
Fast (Grouped) Observation Count for Matrix-Like Objects
Fast (Grouped) Distinct Value Count for Matrix-Like Objects

Fast Grouping and Ordering

Fast (ordered) groupings from vectors, data.frames, lists. Fast ordering, matching, unique values/rows and counts, factor generation and interactions, run-length type grouping and grouping of time-sequences.

Fast Grouping and Ordering
GRP() is_GRP() length(<GRP>) GRPN() GRPid() GRPnames() as_factor_GRP() gsplit() greorder() fgroup_by() fgroup_vars() fungroup() print(<GRP>) plot(<GRP>)
Fast Grouping / collapse Grouping Objects
radixorder() radixorderv()
Fast Radix-Based Ordering
Fast Hash-Based Grouping
fmatch() ckmatch() `%!in%` `%iin%` `%!iin%`
Fast Matching
funique() fnunique() fduplicated() any_duplicated()
Fast Unique Elements / Rows
fcount() fcountv()
Efficiently Count Observations by Group
qF() qG() is_qG() as_factor_qG() finteraction()
Fast Factor Generation, Interactions and Vector Grouping
Fast Removal of Unused Factor Levels
Generate Run-Length Type Group-Id
Generate Group-Id from Integer Sequences
Generate Integer-Id From Time/Date Sequences

Fast Data Manipulation

Fast and flexible select, replace, add, subset, transform, sort/reorder, rename/relabel, bind, join and pivot/reshape data / data frame columns.

Fast Data Manipulation
fselect() `fselect<-`() get_vars() `get_vars<-`() add_vars() `add_vars<-`() num_vars() `num_vars<-`() cat_vars() `cat_vars<-`() char_vars() `char_vars<-`() fact_vars() `fact_vars<-`() logi_vars() `logi_vars<-`() date_vars() `date_vars<-`()
Fast Select, Replace or Add Data Frame Columns
fsubset() ss()
Fast Subsetting Matrix-Like Objects
fsummarise() fsummarize()
Fast Summarise
fmutate() ftransform() ftransformv() settransform() settransformv() `ftransform<-`() fcompute() fcomputev()
Fast Transform and Compute Columns on a Data Frame
Apply Functions Across Multiple Columns
roworder() roworderv()
Fast Reordering of Data Frame Rows
colorder() colorderv()
Fast Reordering of Data Frame Columns
frename() setrename() relabel() setrelabel()
Fast Renaming and Relabelling Objects
Row-Bind Lists / Data Frame-Like Objects
Fast Table Joins
Fast and Easy Data Reshaping

Quick Data Conversion

Quick conversions between data.frame’s, data.table’s, tibbles, matrices, arrays, lists, vectors and factors - fast and flexible, without method dispatch or extensive checks.

qDF() qDT() qTBL() qM() mctl() mrtl() as_numeric_factor() as_character_factor()
Quick Data Conversion
qF() qG() is_qG() as_factor_qG() finteraction()
Fast Factor Generation, Interactions and Vector Grouping

Advanced Data Aggregation

Fast and easy multi-data-type, multi-function, weighted and parallelized data aggregation.

collap() collapv() collapg()
Advanced Data Aggregation

Data Transformations

Fast row/column arithmetic, efficient row/column apply to data objects and Split-Apply-Combine computing. Fast (grouped, weighted) replacing and sweeping out of statistics, scaling/standardizing, (quasi-)centering, higher-dimensional centering, linear prediction/partialling-out.

Data Transformations
`%rr%` `%r+%` `%r-%` `%r*%` `%r/%` `%cr%` `%c+%` `%c-%` `%c*%` `%c/%`
Fast Row/Column Arithmetic for Matrix-Like Objects
Data Apply
Split-Apply-Combine Computing
TRA() setTRA()
Transform Data by (Grouped) Replacing or Sweeping out Statistics
fscale() STD()
Fast (Grouped, Weighted) Scaling and Centering of Matrix-like Objects
fbetween() fwithin() B() W()
Fast Between (Averaging) and (Quasi-)Within (Centering) Transformations
fhdbetween() fhdwithin() HDB() HDW()
Higher-Dimensional Centering and Linear Prediction

Linear Models

Fast (weighted) linear model fitting. A fast F-test for high-dimensional linear models.

Fast (Weighted) Linear Model Fitting
Fast (Weighted) F-test for Linear Models (with Factors)

Time Series and Panel Series

Fast and flexible indexed time series and panel data classes, (sequences of) lags/leads, and (lagged/leaded, iterated, quasi-, log-) differences and (compounded) growth rates on (irregular) time series and panel data. Auto-, partial- and cross-correlation functions for panel data. Panel data to (ts-)array conversion.

Time Series and Panel Series
findex_by() findex() unindex() reindex() is_irregular() to_plm() print(<index_df>)
Fast Indexed Time Series and Panels
Generate Integer-Id From Time/Date Sequences
flag() L()
Fast Lags and Leads for Time Series and Panel Data
fdiff() D() Dlog()
Fast (Quasi-, Log-) Differences for Time Series and Panel Data
fgrowth() G()
Fast Growth Rates for Time Series and Panel Data
Fast (Grouped, Ordered) Cumulative Sum for Matrix-Like Objects
psacf() pspacf() psccf()
Auto- and Cross- Covariance and Correlation Function Estimation for Panel Series
psmat() plot(<psmat>)
Matrix / Array from Panel Series

List Processing

Recursive list search, splitting, extraction/subsetting, apply, and generalized row-binding / unlisting to data frame.

List Processing
Unlistable Lists
Determine the Depth / Level of Nesting of a List
atomic_elem() `atomic_elem<-`() list_elem() `list_elem<-`() reg_elem() irreg_elem() get_elem() has_elem()
Find and Extract / Subset List Elements
Fast (Recursive) Splitting
Efficient List Transpose
Recursively Apply a Function to a List of Data Objects
Recursive Row-Binding / Unlisting in 2D - to Data Frame

Summary Statistics

Fast (grouped, weighted, panel-decomposed) summary statistics and descriptive tools.

Summary Statistics
qsu()<qsu>) print(<qsu>)
Fast (Grouped, Weighted) Summary Statistics for Cross-Sectional and Panel Data
qtab() qtable()
Fast (Weighted) Cross Tabulation
descr()<descr>) print(<descr>)
Detailed Statistical Description of Data Frame
pwcor() pwcov() pwnobs() print(<pwcor>) print(<pwcov>)
(Pairwise, Weighted) Correlations, Covariances and Observation Counts
Fast Check of Variation in Data

Other Statistical

Fast euclidean distance computations, (weighted) sample quantiles, and range of vector.

Fast and Flexible Distance Computations
fquantile() frange()
Fast (Weighted) Sample Quantiles and Range

Recode and Replace Values

Efficiently recode and replace values in matrix-like objects.

recode_num() recode_char() replace_na() replace_inf() replace_outliers()
Recode and Replace Values in Matrix-Like Objects
Pad Matrix-Like Objects with a Value

(Memory) Efficient Programming

Functions to make R programming more efficient.

Small (Helper) Functions

Convenience functions to perform multiple-assignment, nonstandard concatenation, and deal with variable names, labels, other attributes, object checking, and help with metaprogramming.


Groningen Growth and Development Centre 10-Sector Database and World Bank World Development dataset.

Groningen Growth and Development Centre 10-Sector Database
World Development Dataset

Package Options

Global options affecting package operation.

set_collapse() get_collapse()
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