I am currently following along with Forecasting: Principles and Practice, 3rd Edition, which is graciously available online. To replicate my issue, you will need to install and then load the package fpp3
. You will then need to carry out the following in R (or RStudio):
PBS %>%
filter(ATC2 == "A10") %>%
select(Month, Concession, Type, Cost) %>%
summarise(TotalC = sum(Cost)) %>%
mutate(Cost = TotalC / 1e6) -> a10
After defining a10
, it will then be necessary to plot the tsibble
, like so:
autoplot(a10, Cost) +
labs(y = "$ (millions)",
title = "Australian antidiabetic drug sales")
You should then get a plot like this:
It's fine for the most part, but I would like to have at least twice as many ticks on the x-axis, possibly more if they can be rotated by 45° or so. I tried something that seemed promising which was adding scale_x_date(date_labels = "%m-%Y")
to the plot object but that only works with objects of class Date
and here we are dealing with yearmonth
s. How can I get a more detailed x-axis under these circumstances?
One way could be changing the class of Month
to class date and applying scale_x_date()
:
a10 %>%
mutate(Month = as.Date(Month)) %>%
ggplot(aes(x=Month, y=Cost)) +
geom_line() +
scale_x_date(date_breaks = "1 year")