Provides 'dplyr' verbs for lists and other useful verbs for manipulation of data frames. In particular, it includes a mutate_which() function that mutates columns for a specific subset of rows defined by a condition, and fuse() which is a more flexible version of 'tidyr' unite() function.
You can install 'lplyr' from GitHub with:
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)
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,
mutate_which_(df, ~ gear==4, carb = ~ 100)transmute_which_(df, ~ gear==4, carb = ~ 100)
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)