Evaluates a Function Groupwise
Split the vector x into partitions and apply the function to each partition separately. Computation restarts for each partition.
The logic is the same as the OLAP functions in SQL, e.g. SUM(x) OVER (PARTITION BY group).
DoBy(x, ...)
## S3 method for class 'formula'
DoBy(formula, data = parent.frame(), subset, na.action,
vnames = NULL, ...)
## Default S3 method:
DoBy(x, by, FUN, vnames = NULL, collapse = FALSE, ...)x |
a vector that should be operated. |
by |
list of one or more factors, each of same length as |
FUN |
Function to apply for each factor level combination. |
formula |
a formula of the form |
data |
an optional matrix or data frame (or similar: see |
subset |
an optional vector specifying a subset of observations to be used. |
na.action |
a function which indicates what should happen when the data contain |
vnames |
name for the new variables. |
collapse |
logical, determining if the results should be collapsed to groups. Default is |
... |
optional arguments to |
This is more or less the same as the function ave, with the arguments organized a bit different and offering more flexibility.
a data.frame with the same number of rows as length as x containing the groupwise results of FUN and the used group factors.
The attribute response denotes the name of the response variable in case the formula interface was used.
Optional arguments to FUN supplied by the ... argument are not divided into cells. It is therefore inappropriate for FUN to expect additional arguments with the same length as x.
Andri Signorell <andri@signorell.net>
d.frm <- data.frame(x=rep(1:4,3), v=sample(x=1:3, size=12, replace=TRUE),
g=gl(4,3,labels=letters[1:4]), m=gl(3,4,labels=LETTERS[1:3]))
# SQL-OLAP: sum() over (partition by g)
DoBy(d.frm$x, d.frm$g, FUN=sum)
# DoBy(d.frm$x, FUN=sum)
# more than 1 grouping variables are organized as list as in tapply:
DoBy(d.frm$x, list(d.frm$g, d.frm$m), mean)
# count
d.frm$count <- DoBy(d.frm$x, d.frm$g, length)
# rank
d.frm$rank <- DoBy(d.frm$v, d.frm$g, rank)
d.frm$dense_rank <- DoBy(d.frm$v, d.frm$g, Rank, ties.method="dense")
d.frm$rank_desc <- DoBy(d.frm$x, d.frm$g, function(x) rank(-x))
# row_number
d.frm$row_number <- DoBy(d.frm$v, d.frm$g, function(x) order(x))
d.frmPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.