Gefeliciteerd!

Gevorderd functioneel programmeren met purrr

Colin Fay

Data-Scientist & R-Hacker @ ThinkR

Lambda-functies:

map(1:5, ~ .x*10)

[[1]]
[1] 10

[[2]]
[1] 20

[[3]]
[1] 30

[[4]]
[1] 40

[[5]]
[1] 50

Herbruikbare mappers:

ten_times <- as_mapper(~ .x * 10)
map(1:5, ten_times)

[[1]]
[1] 10

[[2]]
[1] 20

[[3]]
[1] 30

[[4]]
[1] 40

[[5]]
[1] 50

Functies manipuleren

Functionals:

map() & co.
keep() & discard()
some() & every()

Functie-operatoren:

safely() & possibly()
partial()
compose()
negate()

Schonere code

library(purrr)
rounded_mean <- compose(
  partial(round, digits = 1),
  partial(mean, trim = 2, na.rm = TRUE))
map(list(airquality, mtcars), 
  ~ map_dbl(.x, rounded_mean))

[[1]]
Ozone Solar.R    Wind    Temp   Month     Day 
 31.5   205.0     9.7    79.0     7.0    16.0 

[[2]]
 mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb 
19.2   6.0 196.3 123.0   3.7   3.3  17.7   0.0   0.0   4.0   2.0

Wat nu?

Ga purrr in het echt proberen ;)
DataCamp-cursussen over het tidyverse
Advanced R
Blijf purrr verkennen

Tot snel!

Gevorderd functioneel programmeren met purrr