bless your chart - 071: Waffle Minutes

Data

Code

# Build data from kenpom

min_df <- tibble::tribble(
  ~year,~min_pct,~type,~games,
  2024,27.1,"bench",18,
  2024,72.9,"start",18,
  2023,18.3,"bench",33,
  2023,81.7,"start",33,
  2022,19.8,"bench",39,
  2022,80.2,"start",39
)

Waffle Plot

Code

theme_me <- function() {
  # Create a base theme with minimal style
  base_theme <- ggplot2::theme_minimal(base_size = 10, base_family = "RobotoCondensed-Regular")
  
  # Customize the base theme with additional modifications
  custom_theme <- base_theme +
    ggplot2::theme(
      plot.title = ggplot2::element_text(
        hjust = 0.5,
        size = 24,
        face = "bold"
      ),
      plot.subtitle = ggplot2::element_text(
        hjust = 0.5,
        size = 10,
      ),
      plot.caption = ggplot2::element_text(
        hjust = 0.5,
        size = 6,
        lineheight = 0.35,
        margin = ggplot2::margin(t = 0.5)
      ),
      plot.background = ggplot2::element_rect(fill = "floralwhite", color = "floralwhite")
    )
  
  return(custom_theme)
} 

min_df |> 
  dplyr::mutate(min_pct = round(min_pct)) |> 
  ggplot2::ggplot(ggplot2::aes(fill = type, values = min_pct)) +
  waffle::geom_waffle(color = "floralwhite", size = .25, rows = 10, flip = TRUE) +
  ggplot2::facet_wrap(~year, nrow = 1, strip.position = "bottom",
                      labeller = ggplot2::labeller(year = c("2022" = "2021-22 \nDI Avg: 30.7",
                                                            "2023" = "2022-23 \nDI Avg: 30.5",
                                                            "2024" = "2023-24  \nDI Avg: 31.5"))) +
  ggplot2::scale_x_discrete() + 
  ggplot2::scale_y_continuous(labels = function(x) x * 10, 
                              expand = c(0,0)) +
  ggplot2::scale_fill_manual("",
                             values=c("start"="#bdd7e7", "bench"="#3182bd"),
                             labels=c("Bench", "Starters")) +
  ggplot2::coord_equal() +
  ggplot2::labs(
    title = "<span style='color:#56a0d3;'>North Carolina basketball</span>  \nminutes distribution  \nover the last three seasons",
    subtitle = "Compares percentage of minutes from the bench and starters.",
    x = "",
    y = "",
    caption = "Bless your chart | January 20, 2024 | data via kenpom"
  ) +
  theme_me() +
  ggplot2::guides(fill = ggplot2::guide_legend()) +
  ggplot2::theme(panel.grid = ggplot2::element_blank(),
                 axis.ticks.y = ggplot2::element_blank(),
                 axis.text.y = ggplot2::element_blank()) +
  ggplot2::theme(legend.position = "top",  
                 plot.title = ggtext::element_markdown(), 
                 plot.subtitle = ggtext::element_markdown(),
                 plot.caption = ggtext::element_markdown(size = 7),
                 plot.margin = ggplot2::margin(5,0,0,0)) +
  ggplot2::geom_text(data = min_df |> dplyr::filter(type == "bench"),
                     ggplot2::aes(x = 3.3, y = 5, label = paste0("Bench: ", min_pct, "%")),
                     color = "#333333", size = 4, 
                     family = "RobotoCondensed-Regular", 
                     fontface = "bold") +
  ggplot2::geom_text(data = min_df |> dplyr::filter(type == "bench"),
                     ggplot2::aes(x = 2.5, y = 4, label = paste0(games, " games")),
                     color = "#333333", size = 4, 
                     family = "RobotoCondensed-Regular", 
                     fontface = "bold") -> waf_plot

ggplot2::ggsave(
  "waf_plot.png",
  waf_plot,
  w = 7.5,
  h = 5,
  dpi = 600,
  type = 'cairo'
)

waf_plot