collapse provides the following functions to efficiently group and order data:
radixorder, provides fast radix-ordering through direct access to the method
order(..., method = "radix"), as well as the possibility to return some attributes very useful for grouping data and finding unique elements.
radixorderv exists as a programmers alternative. The function
roworder(v) efficiently reorders a data frame based on an ordering computed by
group provides fast grouping in first-appearance order of rows, based on a hashing algorithm in C. Objects have class 'qG', see below.
GRP creates collapse grouping objects of class 'GRP' based on
group. 'GRP' objects form the central building block for grouped operations and programming in collapse and are very efficient inputs to all collapse functions supporting grouped operations.
fgroup_by provides a fast replacement for
dplyr::group_by, creating a grouped data frame (or data.table / tibble etc.) with a 'GRP' object attached. This grouped frame can be used for grouped operations using collapse's fast functions.
funique is a faster version of
unique. The data frame method also allows selecting unique rows according to a subset of the columns.
fnunique efficiently calculates the number of unique values/rows.
fduplicated is a fast alternative to
qF, shorthand for 'quick-factor' implements very fast factor generation from atomic vectors using either radix ordering
method = "radix" or hashing
method = "hash". Factors can also be used for efficient grouped programming with collapse functions, especially if they are generated using
qF(x, na.exclude = FALSE) which assigns a level to missing values and attaches a class 'na.included' ensuring that no additional missing value checks are executed by collapse functions.
qG, shorthand for 'quick-group', generates a kind of factor-light without the levels attribute but instead an attribute providing the number of levels. Optionally the levels / groups can be attached, but without converting them to character. Objects have a class 'qG', which is also recognized in the collapse ecosystem.
finteraction is a fast alternative to
interaction implemented as a wrapper around
as_factor_GRP(GRP(...)). It can be used to generate a factor from multiple vectors, factors or a list of vectors / factors. Unused factor levels are always dropped.
groupid is a generalization of
data.table::rleid providing a run-length type group-id from atomic vectors. It is generalization as it also supports passing an ordering vector and skipping missing values. For example
method = "radix" are essentially implemented using
seqid is a specialized function which creates a group-id from sequences of integer values. For any regular panel dataset
groupid(id, order(id, time)) and
seqid(time, order(id, time)) provide the same id variable.
seqid is especially useful for identifying discontinuities in time-sequences.
timeid is a specialized function to convert integer or double vectors representing time (such as 'Date', 'POSIXct' etc.) to factor or 'qG' object based on the greatest common divisor of elements (thus preserving gaps in time intervals).
|Function / S3 Generic||Methods||Description|
|No methods, for data frames and vectors||Radix-based ordering + grouping information|
|No methods, for data frames incl. pdata.frame||Row sorting/reordering|
|No methods, for data frames and vectors||Hash-based grouping + grouping information|
|Fast grouping and a flexible grouping object|
|No methods, for data frames||Fast grouped data frame|
|Fast (number of) unique values/rows|
|Internal generic, supports vectors, matrices, data.frames, lists, grouped_df and pdata.frame||Fast group counts|
|No methods, for vectors||Quick factor generation|
|No methods, for vectors||Quick grouping of vectors and a 'factor-light' class|
|Fast removal of unused factor levels|
|No methods, for data frames and vectors||Fast interactions|
|No methods, for vectors||Run-length type group-id|
|No methods, for integer vectors||Run-length type integer sequence-id|
|No methods, for integer or double vectors||Integer-id from time/date sequences|