Similar to base::rank but much faster. And it accepts vectors, lists, data.frames or data.tables as input. In addition to the ties.method possibilities provided by base::rank, it also provides ties.method="dense".
bit64::integer64 type is also supported.
frank(x, ..., na.last=TRUE, ties.method=c("average",
"first", "random", "max", "min", "dense"))frankv(x, cols=seq_along(x), order=1L, na.last=TRUE,
ties.method=c("average", "first", "random",
"max", "min", "dense"))
A vector, or list with all its elements identical in length or data.frame or data.table.
Only for lists, data.frames and data.tables. The columns to calculate ranks based on. Do not quote column names. If ... is missing, all columns are considered by default. To sort by a column in descending order prefix "-", e.g., frank(x, a, -b, c). -b works when b is of type character as well.
A character vector of column names (or numbers) of x, for which to obtain ranks.
An integer vector with only possible values of 1 and -1, corresponding to ascending and descending order. The length of order must be either 1 or equal to that of cols. If length(order) == 1, it is recycled to length(cols).
Control treatment of NAs. If TRUE, missing values in the data are put last; if FALSE, they are put first; if NA, they are removed; if "keep" they are kept with rank NA.
A character string specifying how ties are treated, see Details.
A numeric vector of length equal to NROW(x) (unless na.last = NA, when missing values are removed). The vector is of integer type unless ties.method = "average" when it is of double type (irrespective of ties).
To be consistent with other data.table operations, NAs are considered identical to other NAs (and NaNs to other NaNs), unlike base::rank. Therefore, for na.last=TRUE and na.last=FALSE, NAs (and NaNs) are given identical ranks, unlike rank.
frank is not limited to vectors. It accepts data.tables (and lists and data.frames) as well. It accepts unquoted column names (with names preceded with a - sign for descending order, even on character vectors), for e.g., frank(DT, a, -b, c, ties.method="first") where a,b,c are columns in DT. The equivalent in frankv is the order argument.
In addition to the ties.method values possible using base's rank, it also provides another additional argument "dense" which returns the ranks without any gaps in the ranking. See examples.
# NOT RUN {
# on vectors
x = c(4, 1, 4, NA, 1, NA, 4)
# NAs are considered identical (unlike base R)
# default is average
frankv(x) # na.last=TRUE
frankv(x, na.last=FALSE)
# ties.method = min
frankv(x, ties.method="min")
# ties.method = dense
frankv(x, ties.method="dense")
# on data.table
DT = data.table(x, y=c(1, 1, 1, 0, NA, 0, 2))
frankv(DT, cols="x") # same as frankv(x) from before
frankv(DT, cols="x", na.last="keep")
frankv(DT, cols="x", ties.method="dense", na.last=NA)
frank(DT, x, ties.method="dense", na.last=NA) # equivalent of above using frank
# on both columns
frankv(DT, ties.method="first", na.last="keep")
frank(DT, ties.method="first", na.last="keep") # equivalent of above using frank
# order argument
frank(DT, x, -y, ties.method="first")
# equivalent of above using frankv
frankv(DT, order=c(1L, -1L), ties.method="first")
# }
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