gganimate: handling of missing values - r

Question

I'm trying the gganimate package for the first time and run into a problem with the handling of missing values (NA). I apologize if my question is trivial but I couldn't find any solution.
Here is a reproducible example of what I'm trying to do:
# Load libraries:
library(ggplot2)
library(gganimate)
library(dplyr)
library(tidyr)
# Create some data
## Monthly sales are in 100:1000
## Expected sales are 400/month, increasing by 5% every year
set.seed(123)
df <- data_frame(Year = rep(2015:2018, each=12),
Month = rep(1:12, 4),
Sales = unlist(lapply(1:4,
function(x){cumsum(sample(100:1000, 12))})),
Expected = unlist(lapply(1:4,
function(x){cumsum(rep(400*1.05^(x-1),12))})))
# gganimate works fine here:
df %>%
tidyr::gather("Type", "value", Sales:Expected) %>%
ggplot(aes(Month, value, col=Type)) +
geom_point() +
geom_line() +
gganimate::transition_time(Year)
# Now data for the end of Year 2018 are missing:
df[df$Year==2018 & df$Month %in% 9:12,"Sales"] = NA
# Plotting with ggplot2 works (and gives a warning about missing values):
df %>%
tidyr::gather("Type", "value", Sales:Expected) %>%
dplyr::filter(Year == "2018") %>%
ggplot(aes(Month, value, col=Type)) +
geom_point() +
geom_line()
# But gganimate fails
df %>%
tidyr::gather("Type", "value", Sales:Expected) %>%
ggplot(aes(Month, value, col=Type)) +
geom_point() +
geom_line() +
gganimate::transition_time(Year)
# I get the following error:
## Error in rep(seq_len(nrow(polygon)), splits + 1) : incorrect 'times' argument
I tried to play with the enter_() / exit_() functions of gganimate but without success.
Thank you for your help.
EDIT: (using the suggestion of MattL)
This works:
df %>%
# filter(!is.na(Sales)) %>% ##Proposed by Matt L but removes Expected values too
gather("Type", "value",Sales:Expected) %>%
filter(!is.na(value)) %>% ## Remove NA values
ggplot(aes(Month, value, col=Type)) +
geom_point() +
geom_line() +
labs(title = "Year: {frame_time}") + ## Add title
gganimate::transition_time(Year) +
gganimate::exit_disappear(early=TRUE) ## Removes 2017 points appearing in Year 2018
I still have the feeling that gganimate should be able to handle these NA values like ggplot does though.
Thanks!

Answer 1

Filter out the missing values before "piping" to the ggplot function:
df %>%
filter(!is.na(Sales)) %>%
tidyr::gather("Type", "value", Sales:Expected) %>%
ggplot(aes(Month, value, col=Type)) +
geom_point() +
geom_line() +
gganimate::transition_time(Year)