collapse 2.0, released in Mid-October 2023, introduces fast table joins and data reshaping capabilities alongside other convenience functions, and enhances the packages global configurability, including interactive namespace control. Potentially breaking changes In a grouped setting, if .data is used inside fsummarise() and fmutate(), and .cols = NULL, .data will contain all columns except for grouping columns (in-line with the .SD syntax of data.table). Before, .data contained all columns. The selection in .cols still refers to all columns, thus it is still possible to select all columns using e.g. grouped_data %>% fsummarise(some_expression_involving(.data), .cols = seq_col(.)). Other changes In qsu(), argument vlabels was renamed to labels. But vlabels will continue to work. Bug Fixes Fixed a bug in the integer methods of fsum(), fmean() and fprod() that returned NA if and only if there was a single integer followed by NA's e.g fsum(c(1L, NA, NA)) erroneously gave NA. This was caused by a C-level shortcut that returned NA when the first element of the vector had been reached (moving from back to front) without encountering any non-NA-values. The bug consisted in the content of the first element not being evaluated in this case. Note that this bug did not occur with real numbers, and also not in grouped execution. Thanks @blset for reporting (#432). Additions Added join(): class-agnostic, vectorized, and (default) verbose joins for R, modeled after the polars API. Two different join algorithms are implemented: a hash-join (default, if sort = FALSE) and a sort-merge-join (if sort = TRUE). Added pivot(): fast and easy data reshaping! It supports longer, wider and recast pivoting, including handling of variable labels, through a uniform and parsimonious API. It does not perform data aggregation, and by default does not check if the data is uniquely identified by the supplied ids. Underidentification for 'wide' and 'recast' pivots results in the last value being taken within each group. Users can toggle a duplicates check by setting check.dups = TRUE. Added rowbind(): a fast class-agnostic alternative to rbind.data.frame() and data.table::rbindlist(). Added fmatch(): a fast match() function for vectors and data frames/lists. It is the workhorse function of join(), and also benefits ckmatch(), %!in%, and new operators %iin% and %!iin% (see below). It is also possible to set_collapse(mask = "%in%") to replace base::"%in%" using fmatch(). Thanks to fmatch(), these operators also all support data frames/lists of vectors, which are compared row-wise. Added operators %iin% and %!iin%: these directly return indices, i.e. %[!]iin% is equivalent to which(x %[!]in% table). This is useful especially for subsetting where directly supplying indices is more efficient e.g. x[x %[!]iin% table] is faster than x[x %[!]in% table]. Similarly fsubset(wlddev, iso3c %iin% c("DEU", "ITA", "FRA")) is very fast. Added vec(): efficiently turn matrices or data frames / lists into a single atomic vector. I am aware of multiple implementations in other packages, which are mostly inefficient. With atomic objects, vec() simply removes the attributes without copying the object, and with lists it directly calls C_pivot_longer. Improvements set_collapse() now supports options 'mask' and 'remove', giving collapse a flexible namespace in the broadest sense that can be changed at any point within the active session: 'mask' supports base R or dplyr functions that can be masked into the faster collapse versions. E.g. library(collapse); set_collapse(mask = "unique") (or, equivalently, set_collapse(mask = "funique")) will create unique <- funique in the collapse namespace, export unique() from the namespace, and detach and attach the namespace again so R can find it. The re-attaching also ensures that collapse comes right after the global environment, implying that all it's functions will take priority over other libraries. Users can use fastverse::fastverse_conflicts() to check which functions are masked after using set_collapse(mask = ...). The option can be changed at any time. Using set_collapse(mask = NULL) removes all masked functions from the namespace, and can also be called simply to ensure collapse is at the top of the search path. 'remove' allows removing arbitrary functions from the collapse namespace. E.g. set_collapse(remove = "D") will remove the difference operator D(), which also exists in stats to calculate symbolic and algorithmic derivatives (this is a convenient example but not necessary since collapse::D is S3 generic and will call stats::D() on R calls, expressions or names). This is safe to do as it only modifies which objects are exported from the namespace (it does not truly remove objects from the namespace). This option can also be changed at any time. set_collapse(remove = NULL) will restore the exported namespace. For both options there exist a number of convenient keywords to bulk-mask / remove functions. For example set_collapse(mask = "manip", remove = "shorthand") will mask all data manipulation functions such as mutate <- fmutate and remove all function shorthands such as mtt (i.e. abbreviations for frequently used functions that collapse supplies for faster coding / prototyping). <!-- This can also be done before loading the package through `options(collapse_remove = ...)` e.g. via an `.Rprofile` or `.fastverse` configuration file, but this possibility is *dangerous* because you can also remove essential *collapse* functions such as `GRP()` which will cause *collapse* to stop working. **Note** that this option set using `options()` is **non-reversible**, you need to unload *collapse* using `detach("package:collapse", unload = TRUE)` and load it again. --> set_collapse() also supports options 'digits', 'verbose' and 'stable.algo', enhancing the global configurability of collapse. qM() now also has a row.names.col argument in the second position allowing generation of rownames when converting data frame-like objects to matrix e.g. qM(iris, "Species") or qM(GGDC10S, 1:5) (interaction of id's). as_factor_GRP() and finteraction() now have an argument sep = "." denoting the separator used for compound factor labels. alloc() now has an additional argument simplify = TRUE. FALSE always returns list output. frename() supports both new = old (pandas, used to far) and old = new (dplyr) style renaming conventions. across() supports negative indices, also in grouped settings: these will select all variables apart from grouping variables. TRA() allows shorthands "NA" for "replace_NA" and "fill" for "replace_fill". group() experienced a minor speedup with >= 2 vectors as the first two vectors are now hashed jointly. fquantile() with names = TRUE adds up to 1 digit after the comma in the percent-names, e.g. fquantile(airmiles, probs = 0.001) generates appropriate names (not 0% as in the previous version).