Horror Movies

library(tidyverse)

horror_movies <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-11-01/horror_movies.csv')
horror_movies%>%head

horror_movies%>%names

horror_movies%>%DataExplorer::profile_missing()

# Library
library(tidyverse)
library(streamgraph)

# set the fonts
library(showtext)
library(sysfonts)
library(extrafont)
showtext::showtext_auto()
showtext::showtext_opts(dpi=320)
font_add_google(name="Creepster",family="Creepster")


horror_movies<-readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-11-01/horror_movies.csv')

horror_movies%>%
  pull(revenue)%>%summary()
horror_movies%>%
filter(revenue==701842551)%>%View

# Create data:
horror_movies%>%
  arrange(release_date) %>%
  filter(str_detect(genre_names,"horror|Horror"),
         status=="Released",
         revenue> 0) %>%
  select(id,title,original_language,
         release_date,
         genre_names,
         popularity,vote_average,
         budget,revenue) %>% 
  mutate(title=trimws(title),
         ymonth=zoo::as.yearmon(release_date),
         year=lubridate::year(release_date)) %>%
  group_by(original_language,year) %>%
  summarize(avg_budget=round(mean(budget),2),
            avg_revenue=round(mean(revenue),2))%>%
  ungroup() %>%
  arrange(-avg_budget,-avg_revenue) %>%
  mutate(name=original_language,
         value=avg_revenue) -> data




# remotes::install_github("davidsjoberg/ggstream")
library(ggstream)

label<-data %>%
  group_by(original_language)%>%
  summarize(year=round(mean(year)),
            value=max(value))%>%
  ungroup()

data %>% #pull(value)%>%summary()
  ggplot(
    aes(
      year, value, 
      color = original_language, 
      fill = original_language
    )
  ) +
  geom_stream(
    geom = "polygon",
    bw = .45,
    size = 0,
    show.legend = F
  ) +
  geom_stream(
    geom = "contour",
    color = "grey20",
    size = 0.05,
    bw = .45, # Controls smoothness
    show.legend = F
  ) +
  scale_y_log10()+
  geom_text(data=label,
            aes(x=year,value,
                label=original_language),
            family="Creepster",
            show.legend = FALSE,
            check_overlap = FALSE)+
  labs(title="Horror Movies",
       subtitle="revenue by original language",
       caption="Your fears are unleashed - IT (2017) reached the highest revenue with $701 842 551\nDataSource: #TidyTuesday 2022 week 44: Horror Movies by The Movie Database\nDataViz: Federica Gazzelloni (@fgazzelloni)",
       x="Year",y="Revenue") +
  theme_minimal()+
  theme(text=element_text(color="white",
                          family="Creepster"),
        plot.title = element_text(size=25),
        axis.text.x = element_text(color="grey80"),
        plot.background = element_rect(color="grey5",fill="grey5"))

# 7.53 x 6.03
ggsave("w44_horror_movies.png",
       dpi=300,
       width = 7.53,
       height = 6.03)
# geom_stream_label(aes(label = original_language),)