Horror Movies

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Last updated: 2022-11-02

Checks: 7 0

Knit directory: myTidyTuesday/

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tweetrmd::tweet_embed('https://twitter.com/thomas_mock/status/1587245920604897284')

The @R4DScommunity welcomes you to week 44 of #TidyTuesday! We're exploring @tanya_shapiro 's Horror Movies!!

📂 https://t.co/sElb4fcv3u
📰 https://t.co/7J0OnYJMCj#r4ds #tidyverse #rstats #dataviz pic.twitter.com/NPqSaw5Bdo

— Tom Mock ❤️ @posit_pbc (@thomas_mock) November 1, 2022

Let’s give this color pallette a try, along with the Google Creepster font.

suppressPackageStartupMessages({
library(tidyverse)
library(rtweet)
library(lubridate)
library(ggdist)
library(ggimage)
})

source(here::here("code","_common.R"))

sysfonts::font_add_google("Creepster", "creepster")
showtext::showtext_auto()

scales::show_col(paletteer::palettes_d$DresdenColor$foolmoon)

base_url <- "https://www.themoviedb.org/t/p/w1280/"

movies_raw <- tidytuesdayR::tt_load("2022-11-01")$horror_movies |> 
  mutate(poster = paste0(base_url, poster_path))

--- Compiling #TidyTuesday Information for 2022-11-01 ----

--- There is 1 file available ---

--- Starting Download ---

    Downloading file 1 of 1: `horror_movies.csv`

--- Download complete ---

# skimr::skim(movies_raw)

There’s a lot of good material in this dataset. Let’s plot some time series

movies_raw |>
  mutate(original_language = fct_lump(original_language,
    5,
    other_level = "Other"
  )) |>
  group_by(
    release_date = floor_date(release_date,
      unit = "year",
    ),
    original_language
  ) |>
  summarise(
    sum = sum(revenue, na.rm = TRUE),
    .groups = "keep"
  ) |>
  mutate(original_language = fct_reorder(
    original_language,
    sum, max
  )) |>
  ggplot(aes(x = release_date, sum, fill = original_language)) +
  geom_col(show.legend = FALSE) +
  scale_y_continuous(labels = scales::dollar) +
  paletteer::scale_fill_paletteer_d("DresdenColor::foolmoon") +
  labs(
    title = "Global Annual Horror Movie Box Office Revenue",
    subtitle = "A growing genre, in <span style='color:#532026'>English,</span> <span style='color:#BA141E'>German,</span> <span style='color:#E2E3E7'>Spanish,</span> <span style='color:#61829C'>Japanese,</span> <span style='color:#354C6A'>Portuguese,</span> <span style='color:#050505'>and Other</span> languages<br><br>",
    x = NULL, y = NULL, fill = "Language",
    caption = "Plot: @jim_gruman Data: The Movie Database via github.com/tashapiro/horror-movies"
  ) +
  theme(
    panel.background = element_rect(fill = "gray10"),
    legend.text = element_text(color = "gray80"),
    plot.title = element_text(
      color = "gray80",
      size = 40,
      family = "creepster"
    ),
    plot.subtitle = ggtext::element_markdown(
      color = "gray80",
      size = 25
    ),
    plot.caption = element_text(color = "gray80"),
    axis.text = element_text(color = "gray80"),
    panel.grid = element_line(color = "gray5"),
    plot.background = element_rect(fill = "gray10")
  )

movies_raw |>
  filter(budget > 1e6) |>
  mutate(
    image = case_when(
      budget > 100000000 ~ poster,
      release_date < as.Date("1960-01-01") &
        budget > 10000000 ~ poster,
      TRUE ~ NA_character_
    ),
    profitable = if_else(
      revenue > budget,
      TRUE, FALSE
    )
  ) |>
  ggplot(aes(release_date, budget / 1e6)) +
  geom_point(aes(color = profitable),
    show.legend = FALSE,
    size = 2,
    shape = 21
  ) +
  geom_image(aes(
    x = release_date + years(3),
    image = image
  )) +
  geom_text(
    data = count(movies_raw, release_date = floor_date(release_date, unit = "year")),
    aes(y = if_else(year(release_date) %% 2 == 0,
      -2, -7
    ), label = n),
    color = "gray80"
  ) +
  scale_y_continuous(
    labels = scales::dollar,
    position = "right"
  ) +
  scale_x_date(expand = expansion(mult = c(0, 0))) +
  scale_color_manual(values = c(
    paletteer::palettes_d$DresdenColor$foolmoon[[5]],
    paletteer::palettes_d$DresdenColor$foolmoon[[2]]
  )) +
  labs(
    title = "Horror Movie Budgets",
    subtitle = "Several massive productions since the 1980s.  <span style='color:#354C6A'>Revenue > Budget</span> and <span style='color:#BA141E'>Revenue < Budget</span>",
    x = NULL, y = NULL, fill = "Language",
    caption = "Numbers are the annual counts of releases with budgets over $1M by year. Budgets in Millions $US. Plot: @jim_gruman Data: The Movie Database via github.com/tashapiro/horror-movies"
  ) +
  theme(
    panel.background = element_rect(fill = "gray7"),
    plot.title = element_text(
      color = "#532026",
      size = 80,
      vjust = -50,
      hjust = 0.1,
      family = "creepster"
    ),
    plot.subtitle = ggtext::element_markdown(
      color = "gray80",
      size = 20
    ),
    plot.title.position = "panel",
    plot.caption = element_text(color = "gray80"),
    axis.ticks = element_blank(),
    axis.ticks.length = unit(c(0, 0, 0, 0), "cm"),
    axis.text = element_text(
      color = "gray80",
      size = 20
    ),
    axis.line = element_blank(),
    panel.grid = element_line(color = "gray5"),
    plot.background = element_rect(
      fill = "gray7",
      color = "gray7"
    ),
    plot.margin = unit(c(0, 0.2, 0.1, 0), "cm"),
  )

ggsave(here::here("data", "2022_11_01.png"),
  width = 6, height = 5, dpi = 300, bg = "black",
  device = "png"
)

post_tweet(
  status = "#TidyTuesday #DataViz this week on Horror Movie Budgets. Credit to @tanya_shapiro for the dataset. #rstats #r4ds",
  media = here::here("data", "2022_11_01.png"),
  token = NULL,
  in_reply_to_status_id = NULL,
  destroy_id = NULL,
  retweet_id = NULL,
  auto_populate_reply_metadata = FALSE,
  media_alt_text = "The Horror Movie Budgets by Year in points, with movie posters for the largest",
  lat = NULL,
  long = NULL,
  display_coordinates = FALSE
)

tweetrmd::tweet_embed("https://twitter.com/jim_gruman/status/1587942905951420422")

#TidyTuesday #DataViz this week on Horror Movie Budgets. Credit to @tanya_shapiro for the dataset. #rstats #r4ds pic.twitter.com/E5yllcDwU5

— 🧢📚🚵‍♂️⚙📈☕ (@jim_gruman) November 2, 2022

Session information

sessionInfo()

R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggimage_0.3.1   ggdist_3.2.0    lubridate_1.8.0 rtweet_1.0.2   
 [5] forcats_0.5.2   stringr_1.4.1   dplyr_1.0.10    purrr_0.3.5    
 [9] readr_2.1.3     tidyr_1.2.1     tibble_3.1.8    ggplot2_3.3.6  
[13] tidyverse_1.3.2 workflowr_1.7.0

loaded via a namespace (and not attached):
  [1] readxl_1.4.1         backports_1.4.1      systemfonts_1.0.4   
  [4] workflows_1.1.0      selectr_0.4-2        tidytuesdayR_1.0.2  
  [7] splines_4.2.2        listenv_0.8.0        usethis_2.1.6       
 [10] digest_0.6.29        foreach_1.5.2        yulab.utils_0.0.5   
 [13] htmltools_0.5.3      yardstick_1.1.0      viridis_0.6.2       
 [16] magick_2.7.3         parsnip_1.0.2.9001   fansi_1.0.3         
 [19] magrittr_2.0.3       memoise_2.0.1        tune_1.0.1          
 [22] paletteer_1.5.0      googlesheets4_1.0.1  tzdb_0.3.0          
 [25] recipes_1.0.2        globals_0.16.1       modelr_0.1.9        
 [28] gower_1.0.0          R.utils_2.12.0       vroom_1.6.0         
 [31] sysfonts_0.8.8       hardhat_1.2.0        rsample_1.1.0       
 [34] dials_1.0.0          colorspace_2.0-3     rvest_1.0.3         
 [37] textshaping_0.3.6    haven_2.5.1          xfun_0.33           
 [40] prismatic_1.1.1      callr_3.7.2          crayon_1.5.2        
 [43] jsonlite_1.8.3       survival_3.4-0       iterators_1.0.14    
 [46] glue_1.6.2           gtable_0.3.1         gargle_1.2.1        
 [49] ipred_0.9-13         distributional_0.3.1 R.cache_0.16.0      
 [52] tweetrmd_0.0.9       future.apply_1.9.1   scales_1.2.1        
 [55] infer_1.0.3          DBI_1.1.3            Rcpp_1.0.9          
 [58] showtextdb_3.0       gridtext_0.1.5       viridisLite_0.4.1   
 [61] gridGraphics_0.5-1   bit_4.0.4            GPfit_1.0-8         
 [64] lava_1.7.0           prodlim_2019.11.13   httr_1.4.4          
 [67] ellipsis_0.3.2       R.methodsS3_1.8.2    pkgconfig_2.0.3     
 [70] farver_2.1.1         nnet_7.3-18          sass_0.4.2          
 [73] dbplyr_2.2.1         utf8_1.2.2           here_1.0.1          
 [76] labeling_0.4.2       ggplotify_0.1.0      tidyselect_1.2.0    
 [79] rlang_1.0.6          DiceDesign_1.9       later_1.3.0         
 [82] munsell_0.5.0        cellranger_1.1.0     tools_4.2.2         
 [85] cachem_1.0.6         cli_3.4.0            generics_0.1.3      
 [88] broom_1.0.1          evaluate_0.17        fastmap_1.1.0       
 [91] ragg_1.2.4           yaml_2.3.5           rematch2_2.1.2      
 [94] bit64_4.0.5          processx_3.7.0       knitr_1.40          
 [97] fs_1.5.2             workflowsets_1.0.0   showtext_0.9-5      
[100] future_1.28.0        whisker_0.4          R.oo_1.25.0         
[103] xml2_1.3.3           compiler_4.2.2       rstudioapi_0.14     
[106] curl_4.3.3           reprex_2.0.2         lhs_1.1.5           
[109] bslib_0.4.1          stringi_1.7.8        highr_0.9           
[112] ps_1.7.1             lattice_0.20-45      Matrix_1.5-1        
[115] markdown_1.2         styler_1.8.0         conflicted_1.1.0    
[118] vctrs_0.5.0          tidymodels_1.0.0     pillar_1.8.1        
[121] lifecycle_1.0.3      furrr_0.3.1          jquerylib_0.1.4     
[124] httpuv_1.6.6         R6_2.5.1             promises_1.2.0.1    
[127] gridExtra_2.3        parallelly_1.32.1    codetools_0.2-18    
[130] MASS_7.3-58.1        assertthat_0.2.1     rprojroot_2.0.3     
[133] withr_2.5.0          ggtext_0.1.2         parallel_4.2.2      
[136] hms_1.1.2            grid_4.2.2           rpart_4.1.19        
[139] ggfun_0.0.7          timeDate_4021.106    class_7.3-20        
[142] rmarkdown_2.17       googledrive_2.0.0    git2r_0.30.1        
[145] getPass_0.2-2