Monster Movies by Decade and Title Type

An exploration of ‘monster’ movies from 1960 onwards, categorized by type.

#TidyTuesday
Author

Steven Ponce

Published

October 28, 2024

Figure 1: Bar mosaic chart showing the distribution of ‘monster’ movies by decade and title type (Movie, TV Movie, Video) from 1960 to 2020. Movies dominate in recent decades, while TV Movies and Videos were more prominent in earlier years.

Steps to Create this Graphic

1. Load Packages & Setup

Show code 
## 1. LOAD PACKAGES & SETUP ----
if (!require("pacman")) install.packages("pacman")
pacman::p_load(
    tidyverse,         # Easily Install and Load the 'Tidyverse'
    ggtext,            # Improved Text Rendering Support for 'ggplot2'
    showtext,          # Using Fonts More Easily in R Graphs
    janitor,           # Simple Tools for Examining and Cleaning Dirty Data
    scales,            # Scale Functions for Visualization
    glue,              # Interpreted String Literals
    here,              # A Simpler Way to Find Your Files
    ggmosaic           # Mosaic Plots in the 'ggplot2' Framework # Mosaic Plots in the 'ggplot2' Framework
)   

### |- figure size ----
camcorder::gg_record(
    dir    = here::here("temp_plots"),
    device = "png",
    width  =  10,
    height =  8,
    units  = "in",
    dpi    = 320
)

### |- resolution ----
showtext_opts(dpi = 320, regular.wt = 300, bold.wt = 800)

2. Read in the Data

Show code 
tt <-tidytuesdayR::tt_load(2024, week = 44) 

monster_movie_genres <- tt$monster_movie_genres |> clean_names() 
monster_movies       <- tt$monster_movies|> clean_names() 

tidytuesdayR::readme(tt)
rm(tt)

3. Examine the Data

Show code 
glimpse(monster_movie_genres)
glimpse(monster_movies)

4. Tidy Data

Show code 
### |- tidy data ----
plot_data <- monster_movies |>
    mutate(title_type = str_to_title(title_type)) |> 
    mutate(decade = (year %/% 10) * 10) |> 
    filter(decade >= 1960) |> 
    drop_na(title_type, decade) |>
    count(title_type, decade)

5. Visualization Parameters

Show code 
### |- plot aesthetics ----
bkg_col      <- colorspace::lighten('#f7f5e9', 0.05)    
title_col    <- "gray20"           
subtitle_col <- "gray20"     
caption_col  <- "gray30"   
text_col     <- "gray20"    
col_palette  <- paletteer::paletteer_d("rcartocolor::TealRose")[c(1,3,6)] 
# show_col(col_palette)

### |-  titles and caption ----
# icons
tt <- str_glue("#TidyTuesday: { 2024 } Week { 44 } &bull; Source: IMDb non-commercial datasets<br>")
li <- str_glue("<span style='font-family:fa6-brands'>&#xf08c;</span>")
gh <- str_glue("<span style='font-family:fa6-brands'>&#xf09b;</span>")
mn <- str_glue("<span style='font-family:fa6-brands'>&#xf4f6;</span>")

# text
title_text    <- str_glue("Monster Movies by Decade and Title Type")
subtitle_text <- str_glue("An exploration of 'monster' movies from 1960 onwards, categorized by type.")
caption_text  <- str_glue("{tt} {li} stevenponce &bull; {mn} @sponce1(graphic.social) {gh} poncest &bull; #rstats #ggplot2")

### |-  fonts ----
font_add("fa6-brands", here::here("fonts/6.4.2/Font Awesome 6 Brands-Regular-400.otf"))
font_add_google("Oswald", regular.wt = 400, family = "title")
font_add_google("Merriweather Sans", regular.wt = 400, family = "subtitle")
font_add_google("Merriweather Sans", regular.wt = 400, family = "text")
font_add_google("Noto Sans", regular.wt = 400, family = "caption")
font_add_google("Shadows Into Light", regular.wt = 400, family = "anotation")
showtext_auto(enable = TRUE)

### |-  plot theme ----
theme_set(theme_minimal(base_size = 14, base_family = "text"))                

theme_update(
    plot.title.position   = "plot",
    plot.caption.position = "plot",
    legend.position       = "plot",
    plot.background       = element_rect(fill = bkg_col, color = bkg_col),
    panel.background      = element_rect(fill = bkg_col, color = bkg_col),
    plot.margin           = margin(t = 10, r = 20, b = 10, l = 20),
    axis.title.x          = element_text(margin = margin(10, 0, 0, 0), size = rel(1.1), 
                                         color = text_col, family = "text", face = "bold", hjust = 0.5),
    axis.title.y          = element_text(margin = margin(0, 10, 0, 0), size = rel(1.1), 
                                         color = text_col, family = "text", face = "bold", hjust = 0.5),
    axis.text             = element_text(size = rel(0.8), color = text_col, family = "text"),
    panel.grid.minor      = element_blank(),
    panel.grid.major      = element_blank()
)

6. Plot

Show code 
### |- initial plot ----

# Mekko Chart

p <- plot_data |>
    ggplot() +
    
    # Geoms
    geom_mosaic(aes(weight = n, x = product(decade), fill = title_type)) +
    
    # Scales
    scale_y_continuous() +
    scale_fill_manual(values = col_palette) +
    coord_cartesian(clip = 'off') +
    
    # Labs
    labs(
        x = "Decade", 
        y = "Proportion",
        title = title_text,
        subtitle = subtitle_text,
        caption = caption_text
        ) +
    
    # Theme
    theme(
        plot.title = element_text(
            size = rel(2.2),
            family = "title",
            face = "bold",
            color = title_col,
            lineheight = 1.1,
            margin = margin(t = 5, b = 5)
        ),
        plot.subtitle = element_text(
            size = rel(1),
            family = "subtitle",
            color = subtitle_col,
            lineheight = 1.1,
            margin = margin(t = 5, b = 5)
        ),
        plot.caption = element_markdown(
            size = rel(0.75),
            family = "caption",
            color = caption_col,
            lineheight = 1.1,
            hjust = 0.5,
            halign = 1,
            margin = margin(t = 15, b = 5)
        )
    )

### |- annotated plot ----
p <- p +
    annotate(
        "text",
        x = .55, y = .5, label = "Movie",
        color = "#fafafa", size = 7, vjust = 1, hjust = 0,
        fontface = "bold", family = "text"
    ) +
    annotate(
        "text",
        x = .55, y = .8, label = "TV Movie",
        color = "gray40", size = 7, vjust = 1, hjust = 0,
        fontface = "bold", family = "text"
    ) +
    annotate(
        "text",
        x = .55, y = .95, label = "Video",
        color = "#fafafa", size = 7, vjust = 1, hjust = 0,
        fontface = "bold", family = "text"
    )

7. Save

Show code 
### |-  plot image ----  

# Save the plot as PNG
ggsave(
  filename = here::here("data_visualizations/TidyTuesday/2024/tt_2024_44.png"), 
  plot = p,
  width = 10, height = 8, units = "in", dpi = 320
)

### |-  plot thumbnail----  
magick::image_read(here::here("data_visualizations/TidyTuesday/2024/tt_2024_44.png")) |> 
  magick::image_resize(geometry = "400") |> 
  magick::image_write(here::here("data_visualizations/TidyTuesday/2024/thumbnails/tt_2024_44.png"))

8. Session Info

R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)

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    

time zone: America/New_York
tzcode source: internal

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

other attached packages:
 [1] ggmosaic_0.3.3  here_1.0.1      glue_1.8.0      scales_1.3.0   
 [5] janitor_2.2.0   showtext_0.9-7  showtextdb_3.0  sysfonts_0.8.9 
 [9] ggtext_0.1.2    lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1  
[13] dplyr_1.1.4     purrr_1.0.2     readr_2.1.5     tidyr_1.3.1    
[17] tibble_3.2.1    ggplot2_3.5.1   tidyverse_2.0.0 pacman_0.5.1   

loaded via a namespace (and not attached):
 [1] tidyselect_1.2.1        viridisLite_0.4.2       farver_2.1.2           
 [4] fastmap_1.2.0           lazyeval_0.2.2          gh_1.4.1               
 [7] digest_0.6.37           timechange_0.3.0        lifecycle_1.0.4        
[10] rsvg_2.6.0              magrittr_2.0.3          compiler_4.4.0         
[13] rlang_1.1.4             tools_4.4.0             utf8_1.2.4             
[16] yaml_2.3.10             data.table_1.16.0       knitr_1.48             
[19] labeling_0.4.3          htmlwidgets_1.6.4       bit_4.0.5              
[22] curl_5.2.2              plyr_1.8.9              xml2_1.3.6             
[25] camcorder_0.1.0         tidytuesdayR_1.0.3.9000 withr_3.0.1            
[28] productplots_0.1.1      grid_4.4.0              fansi_1.0.6            
[31] colorspace_2.1-1        paletteer_1.6.0         gitcreds_0.1.2         
[34] cli_3.6.3               rmarkdown_2.28          crayon_1.5.3           
[37] ragg_1.3.2              generics_0.1.3          rstudioapi_0.16.0      
[40] httr_1.4.7              tzdb_0.4.0              commonmark_1.9.1       
[43] parallel_4.4.0          vctrs_0.6.5             jsonlite_1.8.8         
[46] hms_1.1.3               bit64_4.0.5             ggrepel_0.9.6          
[49] systemfonts_1.1.0       magick_2.8.4            plotly_4.10.4          
[52] gifski_1.12.0-2         rematch2_2.1.2          stringi_1.8.4          
[55] gtable_0.3.5            prismatic_1.1.2         munsell_0.5.1          
[58] pillar_1.9.0            rappdirs_0.3.3          htmltools_0.5.8.1      
[61] R6_2.5.1                httr2_1.0.3             textshaping_0.4.0      
[64] rprojroot_2.0.4         vroom_1.6.5             evaluate_0.24.0        
[67] markdown_1.13           gridtext_0.1.5          snakecase_0.11.1       
[70] renv_1.0.3              Rcpp_1.0.13             svglite_2.1.3          
[73] xfun_0.47               fs_1.6.4                usethis_3.0.0          
[76] pkgconfig_2.0.3

9. GitHub Repository

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