revdep/library/silicate/magrittr/doc/magrittr.R

In mdsumner/gibble: Geometry Decomposition

## ----, echo = FALSE, message = FALSE-------------------------------------
library(magrittr)
options(scipen = 3)
knitr::opts_chunk$set(
  comment = NA,
  error   = FALSE,
  tidy    = FALSE)

## ------------------------------------------------------------------------
library(magrittr)

car_data <- 
  mtcars %>%
  subset(hp > 100) %>%
  aggregate(. ~ cyl, data = ., FUN = . %>% mean %>% round(2)) %>%
  transform(kpl = mpg %>% multiply_by(0.4251)) %>%
  print

## ------------------------------------------------------------------------
car_data <- 
  transform(aggregate(. ~ cyl, 
                      data = subset(mtcars, hp > 100), 
                      FUN = function(x) round(mean(x, 2))), 
            kpl = mpg*0.4251)

## ----, eval = FALSE------------------------------------------------------
#  car_data %>%
#  (function(x) {
#    if (nrow(x) > 2)
#      rbind(head(x, 1), tail(x, 1))
#    else x
#  })

## ------------------------------------------------------------------------
car_data %>%
{ 
  if (nrow(.) > 0)
    rbind(head(., 1), tail(., 1))
  else .
}

## ------------------------------------------------------------------------
1:10 %>% (substitute(f(), list(f = sum)))

## ----, fig.keep='none'---------------------------------------------------
rnorm(200) %>%
matrix(ncol = 2) %T>%
plot %>% # plot usually does not return anything. 
colSums

## ----, eval = FALSE------------------------------------------------------
#  iris %>%
#    subset(Sepal.Length > mean(Sepal.Length)) %$%
#    cor(Sepal.Length, Sepal.Width)
#  
#  data.frame(z = rnorm(100)) %$%
#    ts.plot(z)

## ----, eval = FALSE------------------------------------------------------
#  iris$Sepal.Length %<>% sqrt

## ------------------------------------------------------------------------
rnorm(1000)    %>%
multiply_by(5) %>%
add(5)         %>%
{ 
   cat("Mean:", mean(.), 
       "Variance:", var(.), "\n")
   head(.)
}

## ----, results = 'hide'--------------------------------------------------
rnorm(100) %>% `*`(5) %>% `+`(5) %>% 
{
  cat("Mean:", mean(.), "Variance:", var(.),  "\n")
  head(.)
}