I need to convert a multi-row two-column data.frame
to a named character vector.
My data.frame
would be something like:
dd = data.
You can also use deframe(x) from the tibble package for this.
tibble::deframe()
It converts the first column to names and second column to values.
There's also a magrittr
solution to this via the exposition pipe (%$%):
library(magrittr)
dd %$% set_names(as.character(name), crit)
Minor advantage over tibble::deframe
is that one doesn't have to have exactly a two-column frame/tibble as argument (i.e., avoid a select(value_col, name_col) %>%
).
Note that the magrittr::set_names
versus base::setNames
is exchangeable. I simply prefer the former since it matches "set_(col|row)?names"
.
For variety, try split
and unlist
:
unlist(split(as.character(dd$name), dd$crit))
# a b c d
# "Alpha" "Beta" "Caesar" "Doris"
Here is a very general, easy way. Presently, it works with the development version of dplyr available via github
# devtools::install_github("tidyverse/dplyr") # dplyr_0.8.99.9003
# .rs.restartR() # Restart R session if dplyr was loaded before
library(dplyr)
iris %>%
pull(Sepal.Length, Species)
(the first argument is the values, the second argument is the names)
Use the names
function:
whatyouwant <- as.character(dd$name)
names(whatyouwant) <- dd$crit
as.character
is necessary, because data.frame
and read.table
turn characters into factors with default settings.
If you want a one-liner:
whatyouwant <- setNames(as.character(dd$name), dd$crit)
You can make a vector from dd$name
, and add names using names()
, but you can do it all in one step with structure()
:
whatiwant <- structure(as.character(dd$name), names = as.character(dd$crit))