# NOT RUN {
dat <- structure(list(month1 = c("Jan", "Nov", "Mar", "Jul", "Aug",
"Jan", "Aug", "May", "Dec", "Apr"), month2 = c("March", "May",
"March", "July", "May", "October", "March", "November", "April",
"January"), weekday1 = c("Th", "F", "M", "Su", "Th", "Su", "M",
"Th", "W", "T"), weekday2 = c("We", "Th", "Fr", "Sa", "We", "Su",
"Tu", "Su", "Su", "Th"), weekday3 = c("Sat", "Wed", "Mon", "Wed",
"Wed", "Wed", "Wed", "Sun", "Fri", "Thu"), weekday4 = c("Sunday",
"Sunday", "Thursday", "Saturday", "Monday", "Wednesday", "Friday",
"Thursday", "Sunday", "Saturday")), .Names = c("month1", "month2",
"weekday1", "weekday2", "weekday3", "weekday4"))
## Note that the 'forcats' package imported by the 'tidyverse' package, has an
## `as_factor` function that can compete with numform's version. If in doubt
## prefix with `numform::as_factor`
as_factor(dat$month1)
as_factor(dat$month2)
as_factor(dat$weekday1)
as_factor(dat$weekday2)
as_factor(dat$weekday3)
as_factor(dat$weekday4)
## shift levels
as_factor(dat$weekday4, -1)
as_factor(dat$weekday4, -2)
as_factor(dat$weekday4, 1)
as_factor(dat$weekday4, 2)
# }
# NOT RUN {
library(tidyverse)
data_frame(
revenue = rnorm(10000, 500000, 50000),
date = sample(seq(as.Date('1999/01/01'), as.Date('2000/01/01'), by="day"), 10000, TRUE),
site = sample(paste("Site", 1:5), 10000, TRUE)
) %>%
mutate(
dollar = f_comma(f_dollar(revenue, digits = -3)),
thous = f_thous(revenue),
thous_dollars = f_thous(revenue, prefix = '$'),
abb_month = f_month(date),
abb_week = numform::as_factor(f_weekday(date, distinct = TRUE))
) %T>%
print() %>%
ggplot(aes(abb_week, revenue)) +
geom_jitter(width = .2, height = 0, alpha = .2) +
scale_y_continuous(label = ff_thous(prefix = '$'))+
facet_wrap(~site) +
theme_bw()
# }
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