README.md

lplyr: dplyr verbs for lists and other verbs for data frames

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Installation

You can install 'lplyr' from GitHub with:

# install.packages("devtools")
devtools::install_github("paulponcet/lplyr")

Verbs for lists and pairlists

The package 'lplyr' extends some dplyr verbs to lists and pairlists:

library(lplyr)

xs <- list(x1 = 1:3, 
           x2 = 2:5, 
           x3 = list("alpha", c("beta", "gamma")))

mutate(xs, x4 = 4)
rename(xs, x0 = x1)

Usual verbs made for standard evaluation work as well:

mutate_(xs, x4 = ~ 4)
rename_(xs, x0 = ~ x1)

New verbs for data frames

The mutate_which and transmute_which functions are made for adding new variables or modifying existing ones on a subset of the data.

df <- mtcars[1:10,]
mutate_which(df, gear==4, carb = 100)
transmute_which(df, gear==4, carb = 100)

There is also a standard evaluation version of these functions, called mutate_which_ and transmute_which_:

mutate_which_(df, ~ gear==4, carb = ~ 100)
transmute_which_(df, ~ gear==4, carb = ~ 100)

The function pull selects a column in a data frame and transforms it into a vector. This is useful to use it in combination with magrittr's pipe operator and dplyr's verbs.

mtcars[["mpg"]]
mtcars %>% pull(mpg)

# more convenient than (mtcars %>% filter(mpg > 20))[[3L]]
mtcars %>%
 filter(mpg > 20) %>%
 pull(3)


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lplyr documentation built on Nov. 17, 2017, 7:34 a.m.