jmclawson.net - Coloring Kansas

Getting Wizard of Oz

library(tidyverse)
library(tmtyro)

oz <- 
  # get_gutenberg_corpus(55, meta_fields = NULL) |> 
  parse_html("gutenberg/55.htm") |> 
  filter(str_detect(part, "Chapter")) |>
  identify_by(part) |> 
  load_texts(keep_original = TRUE) |> 
  mutate(
    chap_num = str_extract(part, "Chapter [IXV]+") |> 
      str_remove_all("Chapter ") |> 
      as.roman() |> 
      as.integer(),
    chap_title = str_remove_all(part, "Chapter [IXV]+") |> trimws(),
    .before = original) |> 
  select(-part) |> 
  identify_by(chap_num)

oz

# A tibble: 39,225 × 6
   doc_id title                      chap_num chap_title  original  word    
   <fct>  <chr>                         <int> <chr>       <chr>     <chr>   
 1 1      The Wonderful Wizard of Oz        1 The Cyclone Dorothy   dorothy 
 2 1      The Wonderful Wizard of Oz        1 The Cyclone lived     lived   
 3 1      The Wonderful Wizard of Oz        1 The Cyclone in        in      
 4 1      The Wonderful Wizard of Oz        1 The Cyclone the       the     
 5 1      The Wonderful Wizard of Oz        1 The Cyclone midst     midst   
 6 1      The Wonderful Wizard of Oz        1 The Cyclone of        of      
 7 1      The Wonderful Wizard of Oz        1 The Cyclone the       the     
 8 1      The Wonderful Wizard of Oz        1 The Cyclone great     great   
 9 1      The Wonderful Wizard of Oz        1 The Cyclone Kansas    kansas  
10 1      The Wonderful Wizard of Oz        1 The Cyclone prairies, prairies
# ℹ 39,215 more rows

oz |> 
  contextualize("yellow", limit = 1:10)

is paved with yellow brick,” said the

one paved with yellow bricks. Within a

on the hard, yellow road-bed. The

the road of yellow brick. When she

the path of yellow brick for the

stumbled over the yellow bricks, which were

the road of yellow brick. It was

the road of yellow brick, she was

was paved with yellow brick. The Tin

still paved with yellow brick, but these

Adding a dictionary

all_colors <- read_csv("~/GitHub/chromatome/all_colors.csv")

Rows: 3841 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (4): term, color, group, listing
dbl (6): red, green, blue, hue, saturation, brightness

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

avg_colors <- read_csv("~/GitHub/chromatome/average_colors.csv")

Rows: 478 Columns: 11
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): term, color, group
dbl (8): sources, red, green, blue, red_diff, hue, saturation, brightness

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

colors <- avg_colors |> 
  select(term, color, hue, saturation, brightness) |> 
  make_dictionary()

oz_c <- oz |> 
  add_dictionary(colors)

Joining with `by = join_by(ngram)`

oz_c |> 
  drop_na(color)

# A tibble: 372 × 11
   doc_id title    chap_num chap_title original word  color color_term color_hue
   <fct>  <chr>       <int> <chr>      <chr>    <chr> <chr> <chr>          <dbl>
 1 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
 2 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
 3 1      The Won…        1 The Cyclo… green,   green #04B… green          0.334
 4 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
 5 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
 6 1      The Won…        1 The Cyclo… gray;    gray  #A29… gray           0    
 7 1      The Won…        1 The Cyclo… red      red   #F80… red            0    
 8 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
 9 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
10 1      The Won…        1 The Cyclo… gray     gray  #A29… gray           0    
# ℹ 362 more rows
# ℹ 2 more variables: color_saturation <dbl>, color_brightness <dbl>

oz_c_plot <- 
  oz_c |> 
  drop_na(color) |> 
  mutate(count = n(),
         .by = c(chap_num, color)) |> 
  ggplot(aes(x = chap_num,
             fill = color,
             text = glue::glue("<b>{color_term}</b><br><br>{color}<br>{count} mentions<br>chapter {chap_num}")
             )) +
  geom_bar(show.legend = FALSE) +
  scale_fill_identity() +
  scale_y_continuous(expand = expansion(mult=c(0,.05))) +
  scale_x_continuous(limits = c(0, 24),
                     expand = expansion(add=c(0.01,1.01)),
                     breaks = c(1:12 * 2),
                     labels = c(1:12 * 2)) +
  theme_gray() +
  theme(panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.line.x = element_line(color = "black")) +
  labs(x = "chapter")

oz_c_plot |> 
  plotly::ggplotly(tooltip = c("text")) |> 
  plotly::config(displayModeBar = FALSE) |> 
  plotly::layout(showlegend = FALSE)

oz_c |> 
  contextualize("rose")

three times and rose slowly through the

round hats that rose to a small

swelled out and rose into the air,

and the balloon rose into the air

and the Monkeys rose into the air

dropping noncolor words

oz_c_plot2 <- 
  oz_c |> 
  drop_na(color) |> 
  filter(!color_term %in% c("rose", "straw", "rust", "desert")) |> 
  mutate(count = n(),
         .by = c(chap_num, color)) |> 
  ggplot(aes(x = chap_num,
             fill = color,
             text = glue::glue("<b>{color_term}</b><br><br>{color}<br>{count} mentions<br>chapter {chap_num}")
             )) +
  geom_bar(show.legend = FALSE) +
  scale_fill_identity() +
  scale_y_continuous(expand = expansion(mult=c(0,.05))) +
  scale_x_continuous(limits = c(0, 24),
                     expand = expansion(add=c(0.01,1.01)),
                     breaks = c(1:12 * 2),
                     labels = c(1:12 * 2)) +
  theme_gray() +
  theme(panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.line.x = element_line(color = "black")) +
  labs(x = "chapter")

oz_c_plot2 |> 
  plotly::ggplotly(tooltip = c("text")) |> 
  plotly::config(displayModeBar = FALSE) |> 
  plotly::layout(showlegend = FALSE) |> 
  plotly::ggplotly(tooltip = c("text")) |> 
  plotly::config(displayModeBar = FALSE) |> 
  plotly::layout(showlegend = FALSE)

show saturation

oz_c |> 
  drop_na(color_saturation) |> 
  summarize(saturation = median(color_saturation),
           .by = doc_id) |>
  ggplot(aes(doc_id, saturation)) +
  geom_point()

References

BBC Three. GIF of RuPaul saying "The library is officially open". https://i.giphy.com/media/v1.Y2lkPTc5MGI3NjExbnNpNzc2Zm83MXg5anJ4ZTllbWl1N2g5d3Z4MjcyZGp6d2oweXFneiZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/DGw7yzbpkiBtFvpQ4w/giphy.gif.

Johnston, Myfanwy, and David Robinson. gutenbergr: Download and Process Public Domain Works from Project Gutenberg. 2023, https://CRAN.R-project.org/package=gutenbergr.

Pinterest user Jeri P. GIF of Dolly Parton saying "I need the money. It’s amazing how much it costs a person to make a person look so cheap!". https://www.pinterest.com/pin/private-gif--403635185340416625/.

Project Gutenberg. www.gutenberg.org.

Reddit user kemmes7. GIF of Thorgy Thor saying "Love Pink!" after initially calling her a bad seed. https://i.redd.it/ehda7xsro0ab1.gif.

Tenor user BryanWilliam1. GIF of Law Roach saying "You did what needed to be done!". https://tenor.com/view/youdidwhatneededtobedone-you-did-what-legendary-gif-22038131.

Wickham, Hadley. rvest: Easily Harvest (Scrape) Web Pages. 2024, https://CRAN.R-project.org/package=rvest.

Wilde, Oscar. The Picture of Dorian Gray. Project Gutenberg, 1890, https://gutenberg.org/ebooks/4078.

Citation

BibTeX citation:

@misc{clawson2024,
  author = {Clawson, James},
  title = {Coloring {Kansas}},
  date = {2024-07-11},
  url = {https://jmclawson.net/posts/coloring-kansas},
  langid = {en}
}

For attribution, please cite this work as:

Clawson, James. “Coloring Kansas.” jmclawson.net, 11 July 2024, https://jmclawson.net/posts/coloring-kansas.