All Events

library(gdqdonations)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyr)
library(ggplot2)
library(kableExtra)
#> 
#> Attaching package: 'kableExtra'
#> The following object is masked from 'package:dplyr':
#> 
#>     group_rows

donations <- gdqdonations::gdq_donations %>% 
  augment_donations()
runs <- gdqdonations::gdq_runs

gdq_donation_totals <-
  donations %>%
  group_by(event) %>%
  summarize(
    total = sum(amount),
    avg = mean(amount),
    gdq = unique(gdq),
    year = unique(year)
  ) %>%
  arrange(as.numeric(year)) %>%
  mutate(cumtot = cumsum(total))

gdq_donation_totals %>%
  ggplot(aes(x = year, y = total, fill = gdq)) +
  geom_col(position = position_dodge2(preserve = "single"), alpha = .75) +
  scale_x_year_discrete() +
  scale_y_currency(
    breaks = seq(0, 10e6, 5e5),
    minor_breaks = seq(0, 10e6, 2.5e5)
  ) +
  scale_colorfill_gdq(guide = "none") +
  labs(
    title = "Games Done Quick: Donation Totals",
    subtitle = glue::glue("Donation totals for <span style='color:{gdq_pal[['AGDQ']]}'>AGDQ</span> and <span style='color:{gdq_pal[['SGDQ']]}'>SGDQ</span> as per the official tracker page")
  ) +
  theme_gdq()

Relative Progress

Unfortunately finding the proper “end time” is not that easy, since the end time of the last run (or finale section) typically comes way before the last of the donations have trickled in.
Also, the last “run” listed on the runs page is sometimes the finale, sometimes the last game, sometimes an explicit total:?

full_join(
  runs %>%
    group_by(event) %>%
    slice_tail(n = 1) %>% 
    select(event, run, run_end),
  donations %>% 
    group_by(event) %>% 
    slice_tail(n = 1) %>% 
    select(event, amount, donation_time = time),
  by = "event"
) %>% 
  arrange(donation_time) %>% 
  mutate(hours_since_end = (run_end %--% donation_time) / lubridate::dhours(1)) %>% 
  select(
    event,
    last_run = run, last_run_end = run_end,
    last_donation = donation_time, amount,
    hours_since_end
  ) %>% 
  kable() %>% 
  kable_styling()

event	last_run	last_run_end	last_donation	amount	hours_since_end
AGDQ2011	NA	NA	2011-01-17 20:27:17	0.80	NA
SGDQ2011	kingdom hearts 2	NA	2011-08-14 05:18:36	5.00	NA
AGDQ2012	final fantasy vii part 2	NA	2012-01-16 21:35:17	363.99	NA
SGDQ2012	bonus games	NA	2012-05-30 04:40:46	1.00	NA
AGDQ2013	Bonus Games	NA	2013-01-23 14:28:05	2000.00	NA
SGDQ2013	total:	NA	2013-08-14 14:33:29	1500.00	NA
AGDQ2014	bonus stream	NA	2014-03-24 19:46:02	5.00	NA
SGDQ2014	Bonus Stream	NA	2014-07-25 06:26:44	15.00	NA
AGDQ2015	Finale!	NA	2015-01-15 21:14:47	50.00	NA
SGDQ2015	Finale!	NA	2015-08-05 00:37:21	10.00	NA
AGDQ2016	Final Fantasy IV Any% no 64 floor glitch	NA	2016-05-10 05:16:19	5.00	NA
SGDQ2016	Super Mario 64 70 Star Encore 70 star	NA	2016-07-18 21:45:31	35.00	NA
AGDQ2017	Undertale True Pacifist Ending	NA	2017-02-03 02:30:16	6.00	NA
SGDQ2017	Earthbound Any% Glitchless	NA	2017-07-22 20:12:35	50.00	NA
AGDQ2018	The Legend of Zelda: Breath of the Wild All Main Quests (No Amiibo)	NA	2018-03-26 18:53:24	10.00	NA
SGDQ2018	FINALE post-GDQ blues	NA	2018-10-28 02:41:36	25.00	NA
AGDQ2019	Finale! 100%	NA	2019-02-16 22:47:40	11.50	NA
SGDQ2019	Finale The End	NA	2019-08-27 03:21:43	25.00	NA
AGDQ2020	Finale The End	NA	2020-01-17 18:21:56	25.00	NA
SGDQ2020	Finale The End	NA	2020-10-15 16:41:04	10825.00	NA
AGDQ2021	Finale The End	NA	2021-05-13 21:35:11	5.00	NA
SGDQ2021	Finale The End	NA	2021-07-11 11:45:15	300.00	NA
AGDQ2022	Finale The End	NA	2022-01-26 00:02:42	10.00	NA
SGDQ2022	Finale The End	NA	2022-08-02 19:52:12	77.00	NA
AGDQ2023	Finale The End	NA	2023-03-03 04:29:07	5.00	NA
SGDQ2023	Finale! The End%	NA	2023-06-05 14:37:12	10.00	NA

How about we compare first/last donation and first/last run times per event.

bind_rows(
  runs %>%
    group_by(event) %>% 
    summarize(
      type = "run",
      first = min(run_start, na.rm = TRUE),
      last = max(run_end, na.rm = TRUE)
    ),
  donations %>%
    group_by(event) %>% 
    summarize(
      type = "donation",
      first = min(time, na.rm = TRUE),
      last = max(time, na.rm = TRUE)
    )
) %>% 
  arrange(first) %>% 
  mutate(
    event = factor(event, levels = event_index$event)
  ) %>% 
  ggplot(aes(y = 0, xmin = first, xmax = last, fill = type, color = type)) +
  facet_wrap(facets = vars(event), scales = "free", nrow = 4) +
  geom_errorbarh(height = .5, size = 1.5, alpha = 2/3) +
  scale_x_datetime(breaks = scales::pretty_breaks(n = 3)) +
  scale_y_continuous(limits = c(-1, 1)) +
  scale_color_brewer(palette = "Dark2", guide = "none") +
  labs(
    title = "First and Last <span style='color:#1B9E77'>Donation</span> and <span style='color:#D95F02'>Run</span>  per Event",
    subtitle = "Donations are logged long before and after the main event period",
    x = "Date"
  ) +
  theme_gdq(
    axis.text.x = element_text(size = rel(.8)),
    axis.line.y = element_blank(),
    axis.text.y = element_blank(),
    axis.title.y = element_blank()
  )

Trying to reasonably determine start and end of the main event period to scale donation progress relatively.

donations %>%
  filter(time_rel >= 0 & time_rel <= 1.05) %>%
  group_by(event) %>%
  mutate(amount_total = cumsum(amount)) %>%
  ungroup() %>%
  mutate(
    highlight = event == latest_event()
  ) %>% 
  ggplot(aes(x = time_rel, y = amount_total, color = highlight, group = event)) +
  geom_step() +
  scale_x_continuous(labels = scales::percent_format()) +
  scale_y_currency(breaks = scales::pretty_breaks()) +
  scale_color_manual(
    values = c("TRUE" = gdq_pal[["GDQ"]], "FALSE" = "gray"), 
    labels = c("TRUE" = latest_event(), "FALSE" = "Previous events"),
    name = "",
    guide = "none"
  ) +
  labs(
    title = "Latest event donation progression",
    subtitle = "Compared to previous events, with time (roughly) relative to start/end of event",
    y = "Cumulative donation total",
    x = "Event Progression"
  ) +
  theme_gdq()