install.packages("RCaucTile")RCaucTile: Tile Grid Maps for East Caucasian Languages
1 Introduction
RCaucTile provides an R implementation of the East Caucasian Languages template, designed for generating tile maps for East Caucasian Languages in ggplot2 (see PyCaucTile for the Python version). It draws inspiration from the Typological Atlas of the Languages of Daghestan (TALD). The TALD project initially features three distinct map visualizations. This package extends this by introducing a new tile map visualization, which displays a rectangle for each language and allows for color-coding based on specific linguistic features.
2 Installation
Since RCaucTile is an R package, you should install R on your PC if you haven’t already done so. To install the RCaucTile package, run the following command at your R IDE so you get the stable version from CRAN:
You can also get the development version from GitHub:
install.packages("remotes")
remotes::install_github("LingConLab/RCaucTile")Load the package:
library(RCaucTile)It is important to cite R and R packages when you use them. If you want to cite RCaucTile, use the citation function:
citation("RCaucTile")To cite RCaucTile in publications, please use
Moroz, George (2025). RCaucTile: Tile Grid Maps for East Caucasian
Languages. R package.
A BibTeX entry for LaTeX users is
@Manual{,
title = {{RCaucTile}: {T}ile {G}rid {M}aps for {E}ast {C}aucasian {L}anguages},
author = {George Moroz},
year = {2025},
}3 How to use RCaucTile
The main utility of the RCaucTile package for researchers is a template of East Caucasian languages and their corresponding colors, which is taken directly from the Typological Atlas of the Languages of Daghestan. To see the template, you can call the ec_tile_map() function without any arguments:
ec_tile_map()
As you can see, all languages are color-coded according to their language branch: Nakh languages are brown, Andic languages are blue, Lezgic branch is green, and so on. This template sets the default distribution of languages.
The core of the package is a built-in dataset ec_languages that contains information about 56 languages. Most variables are self-descriptive, except for x and y, which define the location of each language on a grid (you can save it and modify it if you want).
ec_languagesThere are also two features from the Typological Atlas of the Languages of Daghestan:
morning_greetingscontains values from the “Morning Greetings” chapter (Naccarato, Verhees 2021) from the Typological Atlas of the Languages of Daghestan. The languages of Daghestan can be classified into three groups according to whether they feature morning greetings including questions about the night’s rest (valueDid you wake up?), based on the combination of concepts like “morning” and “good” (valueGood morning), and both strategies (valueBoth).consonant_inventory_sizecontains consonant inventory sizes based on “Phonology” chapter (Moroz 2021) from the Typological Atlas of the Languages of Daghestan.
I expect that the user will load a table with columns language and feature and use it within the ec_tile_map() function. We will create the table on the fly, but it is more convenient to use read.csv(), read_csv(), read_tsv(), or read_xlsx() functions to load any table created in Excel or Calc.
df <- data.frame(language = c("Avar", "Chechen", "Mehweb"),
feature = c("value a", "value b", "value b"))
ec_tile_map(df)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
Sometimes the name of the variable in the loaded table is not feature, so there is an argument feature_column in the ec_tile_map() function, where the name can be provided:
ec_tile_map(ec_languages,
feature_column = "morning_greetings")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
It is possible to add title to the plot, using title argument:
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
To change the title position (it appears left by default), one can use the title_position argument:
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)",
title_position = "center")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
ec_tile_map(title = "This is a Tile map of East Caucasian languages",
title_position = "right")
It is really hard to understand the real value for each language when a numeric feature is used. So there is an additional argument annotate_feature that makes it possible to add values near the language names:
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)",
annotate_feature = TRUE)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
It is possible to use this with categorical features, however, one needs to keep track of the short values, because it looks messy:
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)",
annotate_feature = TRUE)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
4 Changing the default colors
It is possible that the default colors provided by ggplot2 are not suitable for your plots. So ggplot2 provides several tools for changing them. The function scale_fill_distiller() will help to change the colors of numeric variables to one of the predefined palettes (Blues, BuGn, BuPu, GnBu, Greens, Grey, Oranges, OrRd, PuBu, PuBuGn, PuRd, Purples, RdPus, Reds, YlGn, YlGnBu, YlOrBr, YlOrRd). There is a direction argument that makes it possible to reverse the order of the colors in the palette.
library(ggplot2)
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)",
annotate_feature = TRUE) +
scale_fill_distiller(palette = "Greens")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)",
annotate_feature = TRUE) +
scale_fill_distiller(palette = "Greens", direction = 1)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color == : Ignoring unknown parameters: `text`
Ignoring unknown parameters: `text`
To define your own palette for a numeric variable, you can use the scale_fill_gradient() function.
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)",
annotate_feature = TRUE) +
scale_fill_gradient(low = "navy", high = "tomato")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
When the color scheme is clear and the annotate_feature argument draws the exact values of the feature, it makes sense to get rid of the legend:
ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)",
annotate_feature = TRUE) +
scale_fill_gradient(low = "navy", high = "tomato")+
theme(legend.position = "none")Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
The function scale_fill_brewer() will help to change the colors of categorical variables to one of the predefined palettes (Accent, Dark2, Paired, Pastel1, Pastel2, Set1, Set2, Set3).
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)")+
scale_fill_brewer(palette = "Pastel1", na.translate = FALSE)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Scale for fill is already present.
Adding another scale for fill, which will replace the existing scale.
To define your own palette for a categorical variable, you can use the scale_fill_manual() function.
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)")+
scale_fill_manual(values = c("#D81E05", "#0070A1", "#00923F"), na.translate = FALSE)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Scale for fill is already present.
Adding another scale for fill, which will replace the existing scale.
5 Changing values’ order
The default order of values in R is alphabetical. To impose a different order, you can use the factor() function. This function doesn’t change the values themselves, but it instructs R to treat an input vector as ordered. This can be important for features with a natural order. For example, the following demonstrates how to override the default alphabetical order using factor().
df <- data.frame(language = c("Avar", "Chechen", "Mehweb"),
feature = c("value a", "value b", "value b"))
df$feature <- factor(df$feature, levels = c("value b", "value a"))
ec_tile_map(df)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
6 Changing the language template
The East Caucasian language family exhibits significant dialectal differentiation. A unified genealogical classification of all idioms spoken in Daghestan does not exist. The default language inventory in RCaucTile is based on the genealogical classification from the Typological Atlas of the Languages of Daghestan (see the languages page). Therefore, it is highly probable that some researchers may wish to modify the default inventory by removing or altering the names of existing units.
To remove specific languages from the template, list the desired languages in the hide_languages argument.
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)",
hide_languages = c("Gigatli", "Shari"))Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
In order to change the names of existing languages in the template, you need to provide the rename_languages argument with an object that maps old language names to their corresponding new names. This can be represented as either:
- A named vector, where the names are the old language names and the values are the corresponding new language names.
new_language_names <- c("Upper Andi" = "Andi",
"Northern Akhvakh" = "Akhvakh")
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)",
hide_languages = c("Lower Andi", "Southern Akhvakh"),
rename_languages = new_language_names)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
- A data frame with two columns:
language(the old language names) andnew_language_name(the corresponding new language names).
new_language_names <- data.frame(language = c("Upper Andi", "Northern Akhvakh"),
new_language_name = c("Andi", "Akhvakh"))
ec_tile_map(ec_languages,
feature_column = "morning_greetings",
title = "Morning greetings (Naccarato, Verhees 2021)",
hide_languages = c("Lower Andi", "Southern Akhvakh"),
rename_languages = new_language_names)Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`Warning in ggplot2::annotate(geom = "text", x = for_plot[for_plot$text_color ==
: Ignoring unknown parameters: `text`
As shown in the example above, we merged:
- Upper and Lower Andi into the joint “Andi” variable;
- Southern and Northern Akhvakh into the joint “Akhvakh” variable.
library(plotly)
p1 <- ec_tile_map(ec_languages,
feature_column = "consonant_inventory_size",
title = "Consonant inventory size (Moroz 2021)")
ggplotly(p1, tooltip = c("text"))