Learn R Programming

mets (version 1.3.4)

daggregate: aggregating for for data frames

Description

aggregating for for data frames

Usage

daggregate(
  data,
  y = NULL,
  x = NULL,
  subset,
  ...,
  fun = "summary",
  regex = mets.options()$regex,
  missing = FALSE,
  remove.empty = FALSE,
  matrix = FALSE,
  silent = FALSE,
  na.action = na.pass,
  convert = NULL
)

Arguments

data

data.frame

y

name of variable, or formula, or names of variables on data frame.

x

name of variable, or formula, or names of variables on data frame.

subset

subset expression

...

additional arguments to lower level functions

fun

function defining aggregation

regex

interpret x,y as regular expressions

missing

Missing used in groups (x)

remove.empty

remove empty groups from output

matrix

if TRUE a matrix is returned instead of an array

silent

suppress messages

na.action

How model.frame deals with 'NA's

convert

if TRUE try to coerce result into matrix. Can also be a user-defined function

Examples

Run this code
data("sTRACE",package="timereg")
daggregate(iris, "^.e.al", x="Species", fun=cor, regex=TRUE)
daggregate(iris, Sepal.Length+Petal.Length ~Species, fun=summary)
daggregate(iris, log(Sepal.Length)+I(Petal.Length>1.5) ~ Species,
                 fun=summary)
daggregate(iris, "*Length*", x="Species", fun=head)
daggregate(iris, "^.e.al", x="Species", fun=tail, regex=TRUE)
daggregate(sTRACE, status~ diabetes, fun=table)
daggregate(sTRACE, status~ diabetes+sex, fun=table)
daggregate(sTRACE, status + diabetes+sex ~ vf+I(wmi>1.4), fun=table)
daggregate(iris, "^.e.al", x="Species",regex=TRUE)
dlist(iris,Petal.Length+Sepal.Length ~ Species |Petal.Length>1.3 & Sepal.Length>5,
            n=list(1:3,-(3:1)))
daggregate(iris, I(Sepal.Length>7)~Species | I(Petal.Length>1.5))
daggregate(iris, I(Sepal.Length>7)~Species | I(Petal.Length>1.5),
                 fun=table)

dsum(iris, .~Species, matrix=TRUE, missing=TRUE)

par(mfrow=c(1,2))
data(iris)
drename(iris) <- ~.
daggregate(iris,'sepal*'~species|species!="virginica",fun=plot)
daggregate(iris,'sepal*'~I(as.numeric(species))|I(as.numeric(species))!=1,fun=summary)

dnumeric(iris) <- ~species
daggregate(iris,'sepal*'~species.n|species.n!=1,fun=summary)

Run the code above in your browser using DataLab