# Load the packages in ----------------------------------------------------
if(!require(httr)){install.packages("httr"); library(httr)}
if(!require(jsonlite)){install.packages("jsonlite"); library(jsonlite)}
if(!require(withr)){install.packages("withr"); library(withr)}
if(!require(tidyverse)){install.packages("tidyverse"); library(tidyverse)}
if(!require(patchwork)){install.packages("patchwork"); library(patchwork)}
if(!require(gridExtra)){install.packages("gridExtra"); library(gridExtra)}
if(!require(grid)){install.packages("grid"); library(grid)}
if(!require(cowplot)){install.packages("cowplot"); library(cowplot)}
if(!require(showtext)){install.packages("showtext"); library(showtext)}
if(!require(ggpmisc)){install.packages("ggpmisc"); library(ggpmisc)}
if(!require(rlist)){install.packages("rlist"); library(rlist)}
# get the wd
wd <- getwd()
pixar_films <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-03-11/pixar_films.csv')
public_response <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-03-11/public_response.csv')
font_add_google("Noto Sans Mono", "noto_mono")
font <- "noto_mono"
showtext_auto()
# Color palette
color <- palette.colors(palette = "Okabe-Ito")
color <- append(color, "gold")
color[1] <- "#D41159"
Custom_Style <- function() {
ggplot2::theme(
plot.title = ggplot2::element_text(family=font,
size=24,
face="bold",
color="#222222"),
plot.subtitle = ggplot2::element_text(family=font,
size=18,
color="#222222"),
plot.caption = ggplot2::element_text(family=font,
size=10,
color="#222222"),
legend.position = "bottom",
legend.title = ggplot2::element_text(family=font,
size=12,
face="bold",
color="#222222"),
# legend.text.align = 0,
legend.key = ggplot2::element_blank(),
legend.text = ggplot2::element_text(family=font,
size=9,
color="#222222"),
# Axis format
axis.text = ggplot2::element_text(family = font,
size=10,
color="#222222"),
axis.text.x = ggplot2::element_text(margin=ggplot2::margin(5, b = 10), size =8),
axis.line = ggplot2::element_line(colour = alpha('#222222', 0.5), size =0.5),
axis.title = ggplot2::element_text(family=font,
size=12,
face="bold",
color="#222222"),
# Grid lines
panel.grid.minor = ggplot2::element_blank(),
panel.grid.major.y = ggplot2::element_blank(),
panel.grid.major.x = ggplot2::element_blank(),
# Very pale cream/yellow background
panel.background = element_rect(fill = "#FFFBF0",
color = "#FFFBF0",
linewidth = 0.5,
linetype = "solid"),
plot.background = element_rect(fill = "#FFFBF0",
color = "#FFFBF0",
linewidth = 0.5,
linetype = "solid"),
legend.background = element_rect(fill = "#FFFBF0",
color = "#FFFBF0",
linewidth = 0.5,
linetype = "solid"),
)
}
# MAke a Big Dataframe
Combined <- left_join(pixar_films, public_response, by = "film") %>%
filter(!is.na(metacritic)) %>%
mutate(decade = floor(year(as.Date(release_date)) / 10) * 10, .after = release_date) %>%
group_by(decade) %>%
arrange(release_date) %>%
mutate(order_in_decade = row_number(),
decade = as.factor(decade)) %>%
rename(`Rotten Tomatoes` = rotten_tomatoes,
`MetaCritic` = metacritic,
`Critics Choice` = critics_choice)
rating_columns <- c("MetaCritic", "Rotten Tomatoes", "Critics Choice")
list_of_plots <- list()
for (rating in rating_columns) {
heatmap_plot <- ggplot(Combined, aes(x = factor(decade), y = order_in_decade, fill = .data[[rating]])) +
geom_tile() +
scale_x_discrete(limits = sort(unique(Combined$decade))) +
geom_text(aes(label = paste0(str_wrap(film, 14), "\n", round(.data[[rating]], 1))),
color = alpha("Black", 1), size = 6, family = font) +
scale_fill_gradient(low = "yellow", high = "darkgreen") +
labs(
subtitle = paste("Heatmap of ", str_to_title(rating), "Ratings"),
x = "Decade",
y = "Order in Decade \n First film in each decade is at the bottom",
fill = paste(str_to_title(rating), "Rating")
) +
Custom_Style() +
theme(legend.position = "right")
list_of_plots <- list.append(list_of_plots, heatmap_plot)
}
final_patchwork <- wrap_plots(list_of_plots) &
theme(legend.position = "bottom") &
plot_annotation(
title = str_wrap('Comparison of Public and Critic Rating Systems for different Pixar films', 80),
subtitle = "TidyTuesday: Week 10, 2025",
theme = Custom_Style()
) &
theme(
plot.subtitle = element_text(size = 16)
)
print(final_patchwork)
