EVOLUTION-MANAGER
Edit File: magrittr.R
## ----, 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(.) }