Nothing
knitr::opts_chunk$set(collapse = TRUE, comment = "#>") library(dplyr) library(lplyr)
The package 'lplyr' extends some dplyr verbs to lists and pairlists:
xs <- list(x1 = 1:3, x2 = 2:5, x3 = "alpha")
mutate(xs, x4 = 4) %>% str rename(xs, x0 = x1) %>% str
Usual verbs made for standard evaluation work as well:
mutate_(xs, x4 = ~ 4) %>% str rename_(xs, x0 = ~ x1) %>% str
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[1:6,] 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.
df[["mpg"]] df %>% pull(mpg) # more convenient than (mtcars %>% filter(mpg > 20))[[3L]] df %>% filter(mpg > 20) %>% pull(3)
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