Using mappers to clean up your data
Intermediate Functional Programming with purrr
Colin Fay
Data Scientist & R Hacker at ThinkR
Setting the name of your objects
set_names(): sets the names of an unnamed list
names(visits2016)length(visits2016)month.abb
NULL12"Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
visits2016 <- set_names(visits2016, month.abb)
names(visits2016)
"Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
Setting names with map():
all_visits <- list(visits2015, visits2016, visits2017)
named_all_visits <- map(all_visits, ~ set_names(.x, month.abb))
names(named_all_visits[[1]])
"Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
names(named_all_visits[[2]])
"Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
names(named_all_visits[[3]])
"Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" "Nov" "Dec"
keep()
keep(): extract elements that satisfy a condition
# Which month has received more than 30000 visits?
over_30000 <- keep(visits2016, ~ sum(.x) > 30000)
names(over_30000)
"Jan" "Mar" "Apr" "May" "Jul" "Aug" "Oct" "Nov"
limit <- as_mapper(~ sum(.x) > 30000)
# Which month has received more than 30000 visits?
over_mapper <- keep(visits2016, limit)
names(over_mapper)
"Jan" "Mar" "Apr" "May" "Jul" "Aug" "Oct" "Nov"
discard()
discard(): remove elements that satisfy a condition
# Which month has received less than 30000 visits?
under_30000 <- discard(visits2016, ~ sum(.x) > 30000)
names(under_30000)
"Feb" "Jun" "Sep" "Dec"
limit <- as_mapper(~ sum(.x) > 30000)
# Which month has received less than 30000 visits?
under_mapper <- discard(visits2016, limit)
names(under_mapper)
"Feb" "Jun" "Sep" "Dec"
keep(), discard(), and map()
Using map() & keep() :
df_list <- list(iris, airquality) %>% map(head)
map(df_list, ~ keep(.x, is.factor))
[[1]]
Species
1 setosa
2 setosa
3 setosa
4 setosa
5 setosa
6 setosa
[[2]]
data frame with 0 columns and 6 rows
Let's practice!
Intermediate Functional Programming with purrr
