% Generated by roxygen2 (4.0.0): do not edit by hand
\name{chain}
\alias{\%.\%}
\alias{chain}
\alias{chain_q}
\title{Chain together multiple operations.}
\usage{
chain(..., env = parent.frame())

chain_q(calls, env = parent.frame())

x \%.\% y
}
\arguments{
  \item{x,y}{A dataset and function to apply to it}

  \item{...,calls}{A sequence of data transformations,
  starting with a dataset.  The first argument of each call
  should be omitted - the value of the previous step will
  be substituted in automatically.  Use \code{chain} and
  \code{...} when working interactive; use \code{chain_q}
  and \code{calls} when calling from another function.}

  \item{env}{Environment in which to evaluation
  expressions. In ordinary operation you should not need to
  set this parameter.}
}
\description{
The downside of the functional nature of dplyr is that when you combine
multiple data manipulation operations, you have to read from the inside
out and the arguments may be very distant to the function call. These
functions providing an alternative way of calling dplyr (and other data
manipulation) functions that you read can from left to right.
}
\details{
The functions work via simple substitution so that \code{chain(x, f(y))} or
\code{x \%.\% f(y)} is translated into \code{f(x, y)}.
}
\examples{
if (require("hflights")) {
# If you're performing many operations you can either do step by step
a1 <- group_by(hflights, Year, Month, DayofMonth)
a2 <- select(a1, Year:DayofMonth, ArrDelay, DepDelay)
a3 <- summarise(a2,
  arr = mean(ArrDelay, na.rm = TRUE),
  dep = mean(DepDelay, na.rm = TRUE))
a4 <- filter(a3, arr > 30 | dep > 30)

# If you don't want to save the intermediate results, you need to
# wrap the functions:
filter(
  summarise(
    select(
      group_by(hflights, Year, Month, DayofMonth),
      Year:DayofMonth, ArrDelay, DepDelay
    ),
    arr = mean(ArrDelay, na.rm = TRUE),
    dep = mean(DepDelay, na.rm = TRUE)
  ),
  arr > 30 | dep > 30
)

# This is difficult to read because the order of the operations is from
# inside to out, and the arguments are a long way away from the function.
# Alternatively you can use chain or \%.\% to sequence the operations
# linearly:

hflights \%.\%
  group_by(Year, Month, DayofMonth) \%.\%
  select(Year:DayofMonth, ArrDelay, DepDelay) \%.\%
  summarise(
    arr = mean(ArrDelay, na.rm = TRUE),
    dep = mean(DepDelay, na.rm = TRUE)
  ) \%.\%
  filter(arr > 30 | dep > 30)

chain(
  hflights,
  group_by(Year, Month, DayofMonth),
  select(Year:DayofMonth, ArrDelay, DepDelay),
  summarise(
    arr = mean(ArrDelay, na.rm = TRUE),
    dep = mean(DepDelay, na.rm = TRUE)
  ),
  filter(arr > 30 | dep > 30)
)
}
}