causallang_screening_animated-plot.R

# Causallang screening process animated plot
# author: Daloha Rodriguez-Molina @darokun

# load packages
library(tidyverse)
library(gganimate)
library(readxl)
library(here)

# data
data_screening <- read_excel(here::here("R", "causallang", "causallang_screening_progress.xlsx")) %>%
  map_if(is.numeric, function(x) x*100) %>% 
  map_if(is.numeric, round, digits = 2) %>%
  as.tibble() %>% 
  pivot_longer(!reviewer_id, names_to = "checkpoint", values_to = "percentage_screened") %>% 
  mutate(checkpoint = as.integer(checkpoint))

# View(data_screening) # NOT RUN

# plot
p <- ggplot(data = data_screening, 
       aes(x = reorder(reviewer_id, percentage_screened), 
           y = percentage_screened, 
           fill = reviewer_id)) +
  geom_bar(stat = "identity") +
  ylab("Percentage screened") +
  scale_y_continuous(limits = c(0, 105)) +
  theme(legend.position = "none", 
        axis.text.y = element_blank(), 
        axis.title.y = element_blank(),
        axis.ticks.y = element_blank(),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank()) +
  geom_text(aes(label = reviewer_id),
            vjust = 1,
            hjust = -0.1,
            color = "black",
            size = 3.5) +
  coord_flip() +
  ## gganimate code
  labs(title = "Causallang project, screening checkpoint: {frame_time}",
       caption = "@darokun") +
  transition_time(checkpoint) +
  ease_aes("linear")

# save plot as a gif
p <- animate(p)
magick::image_write(p, path = here::here("R", "causallang","screening.gif"))