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Hexbins

Source: vignettes/articles/hexbins.Rmd
hexbins.Rmd

This document demonstrates how to create hexbin choropleth maps of Mexican states using the mxmaps package. The examples show how to visualize data on a hexbin grid, customize the appearance of state labels with different colors and shadows, and use an automatic contrast feature to ensure text readability against varying background colors.

library("mxmaps")

data("df_mxstate_2020")
df_mxstate_2020$value <- df_mxstate_2020$afromexican / df_mxstate_2020$pop * 100
mxhexbin_choropleth(df_mxstate_2020,
  num_colors = 1,
  title = "Percentage of the population that identifies as Afro-Mexican",
  legend = "%",
  auto_contrast = TRUE
)

Text Shadow

You can use label_color if you want the state abbreviations in a different color than the default black, and you can also add a shadow_color if you want to the state abbreviation labels to have a shadow to better distinguish them from the background colors.

library("viridis")
library("scales")

df_mxstate_2020$value <- df_mxstate_2020$afromexican / df_mxstate_2020$pop
# Will show a warning, look at the municipio examples to see how to remove it
mxhexbin_choropleth(df_mxstate_2020,
  num_colors = 1,
  label_color = "white",
  shadow_color = "black",
  title = "Percentage of the population that identifies as Afro-Mexican",
  legend = "%",
  label_size = 3.8
) +
  scale_fill_viridis("percentage", labels = percent)

Auto Contrast

In your maps, you may encounter situations where the background color changes dynamically, making it difficult to read text in a single color. In such cases, you can use the automatic text color adjustment feature auto_constrast to improve readability. This feature automatically adjusts the text color based on the background color, ensuring optimal readability.

library("viridis")
library("scales")

df_mxstate_2020$value <- df_mxstate_2020$afromexican / df_mxstate_2020$pop
mxhexbin_choropleth(df_mxstate_2020,
  num_colors = 1,
  title = "Percentage of the population that identifies as Afro-Mexican",
  legend = "%",
  shadow_color = "#111111",
  auto_contrast = TRUE
) +
  scale_fill_viridis()

Note how the label colors for GRO and OAX are black with a white outline

Title and Background Colors 

df_mxstate_2020$value <- df_mxstate_2020$afromexican / df_mxstate_2020$pop * 100
mxhexbin_choropleth(df_mxstate_2020,
  num_colors = 1,
  title = "Percentage of the population that identifies as Afro-Mexican",
  legend = "%",
  auto_contrast = TRUE,
  background_color = "#e3dac9",
  state_border_size = 2,
  state_border_color = "#AA7E44"
)