library(forcats)
issue_data3 <- issue_data2 %>%
filter(!is.na(event)) %>%
select(event, owner, package, num = issue, type, status) %>%
mutate(
date = as.Date(event),
event = NULL,
n = if_else(status %in% c("closed", "merged"), -1, 1)
)
daily <- issue_data3 %>%
group_by(date, type, status, ) %>%
summarise(n = sum(n))
daily %>%
mutate(status = fct_relevel(status, "opened", "merged")) %>%
ggplot(aes(date, n, fill = type)) +
geom_col() +
facet_grid(status ~ ., scales = "free_y", space = "free") +
labs(
title = "Daily changes in issues and PRs",
x = NULL,
y = NULL
) +
scale_y_continuous(breaks = scales::breaks_width(20), expand = c(0, 5)) +
scale_fill_brewer(palette = "Set1", guide = NULL) +
scale_x_date(date_breaks = "1 week", date_labels = "%b %d", date_minor_breaks = "1 day")
