knitr::opts_chunk$set(echo = TRUE, fig.dim = c(6, 5), dpi = 200, out.width = '100%')
library("mxmaps") data("df_mxstate_2020") df_mxstate_2020$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 = "%")
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$pop # Will show a warning, look at the municipio examples to see how to remove it mxhexbin_choropleth(df_mxstate_2020, num_colors = 1, label_color = "white", shadow_color = "black", title = "Percentage of the population that identifies as Afro-Mexican", legend = "%", label_size = 3.8) + scale_fill_viridis("percentage", labels = percent)
In your maps, you may encounter situations where the background color changes dynamically, making it difficult to read text in a single color. In such cases, you can use the automatic text color adjustment feature auto_constrast
to improve readability. This feature automatically adjusts the text color based on the background color, ensuring optimal readability.
library("viridis") library("scales") df_mxstate_2020$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
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