using mutate_if() and the tidyverse

[joshbaxter]

hi, i am undertaking a project looking tax incomes across local authorities.

I have a dataset, with tax data over the years known as tax_data

I have a column with the names of the local authorities in them, denoted by localauthority.

I want to create and if statement and a dummy column that will use a select bunch of local authorities to match up

eg something that looks like this;

if localauthority == c('Exeter', 'Oxford', 'Cambridge') then return a value of 1
if not return a value of 0

ie an if statement that will create a dummy column, where if the localauthority matches the ones listed it will return a value of 1, and if not return a value of 0.

[nirgrahamuk]

mutate_if, would be relevant if the decision of which variable to transform was to be judged based on properties of the variable. rather, you want to do something like this.

library(tidyverse)
mympg <- mutate(mpg,
                   is_in_my_group = ifelse(manufacturer %in%  c("chevrolet","dodge","ford" ),
                                          1L,
                                           0L)

[hadley]

Whenever you use a logical vector in a numeric context, R automatically converts FALSE to 0 and TRUE to 1, so in this case you don't even need the ifelse():

my_manfacturer <- c("chevrolet", "dodge", "ford")
mympg <- mutate(mpg, is_in_my_group = manufacturer %in% my_manfacturer)