# `lingtypology`: Glottolog functions

#### George Moroz

#### 2025-09-27

This package is based on the Glottolog database, so `lingtypology` has several functions for accessing data from that database.

### 1. Command name’s syntax

Most of the functions in `lingtypology` have the same syntax: what you need.what you have. Most of them are based on language name.

- aff.lang() — get affiliation by language
- area.lang() — get macro area by language
- country.lang() — get country by language
- iso.lang() — get ISO 639-3 code by language
- gltc.lang() — get glottocode (identifier for a language in the Glottolog database) code by language
- lat.lang() — get latitude by language
- long.lang() — get longitude by language
- level.lang() — get level by language
- subc.lang() — get subclassification in the Newick tree format by language

Some of them help to define a vector of languages.

- lang.aff() — get language by affiliation
- lang.iso() — get language by ISO 639-3 code
- lang.gltc() — get language by glottocode

Additionally there are some functions to convert glottocodes to ISO 639-3 codes and vice versa:

- gltc.iso() — get glottocode by ISO 639-3 code
- iso.gltc() — get ISO 639-3 code by glottocode

The most important functionality of `lingtypology` is the ability to create interactive maps based on features and sets of languages (see the third section):

- map.feature()

Glottolog database (v. 5.2) provides `lingtypology` with language names, ISO codes, glottocodes, affiliation, macro area, coordinates, and much information. This set of functions doesn’t have a goal to cover all possible combinations of functions. Check out additional information that is preserved in the version of the Glottolog database used in `lingtypology`:

    names(glottolog)

    ##  [1] "glottocode"        "language"          "iso"
    ##  [4] "level"             "area"              "latitude"
    ##  [7] "longitude"         "countries"         "affiliation"
    ## [10] "subclassification"

Using R functions for data manipulation you can create your own database for your purpose.

### 2. Using base functions

All functions introduced in the previous section are regular functions, so they can take the following objects as input:

- a regular string

    iso.lang("West Circassian")

    ## West Circassian
    ##           "ady"

    lang.iso("ady")

    ##               ady
    ## "West Circassian"

    lang.aff("Abkhaz-Adyge")

    ## [1] "Ubykh"           "West Circassian" "Kabardian"       "Abkhaz"
    ## [5] "Abaza"

I would like to point out that you can create strings in R using single or double quotes. Since inserting single quotes in a string created with single quotes causes an error in R, I use double quotes in my tutorial. You can use single quotes, but be careful and remember that `'Ma'ya'` is an incorrect string in R.

- a vector of strings

    area.lang(c("Kabardian", "Aduge"))

    ## Kabardian     Aduge
    ## "Eurasia"  "Africa"

    lang <- c("Kabardian", "Russian")
    aff.lang(lang)

    ##                                                                   Kabardian
    ##                                                  "Abkhaz-Adyge, Circassian"
    ##                                                                     Russian
    ## "Indo-European, Classical Indo-European, Balto-Slavic, Slavic, East Slavic"

- other functions. For example, let’s try to get a vector of ISO codes for the Circassian languages

    iso.lang(lang.aff("Abkhaz-Adyge"))

    ##           Ubykh West Circassian       Kabardian          Abkhaz           Abaza
    ##           "uby"           "ady"           "kbd"           "abk"           "abq"

If you are new to R, it is important to mention that you can create a table with languages, features and other parametres with any spreadsheet software you used to work. Then you can import the created file to R using standard tools.

### 3. Spell Checker: look carefully at warnings!

All functions which take a vector of languages are enriched with a kind of a spell checker. If a language from a query is absent in the database, functions return a warning message containing a set of candidates with the minimal Levenshtein distance to the language from the query.

    aff.lang("Kabardian")

    ##                  Kabardian
    ## "Abkhaz-Adyge, Circassian"

### 4. `subc.lang()` function

The `subc.lang()` function returns language subclassification in the Newick tree format.

    subc.lang("Lechitic")

    ##                                                                                                                                             Lechitic
    ## "((Kashubian_Proper:1,Slovincian:1)kash1274:1,Polabian:1,((Great_Poland:1,Little_Poland:1,Old_Polish:1)poli1260:1,Silesian:1)poli1262:1)lech1241:1;"

This format is hard to interpret by itself, but there are some tools in R that make it possible to visualise those subclassifications:

    library(ape)
    plot(read.tree(text = subc.lang("Lechitic")))

It is possible to specify colors of tips in case you want to emphasize some nodes:

    plot(read.tree(text = subc.lang("Lechitic")),
         tip.color = c("red", "black", "black", "black"))

As you can see nodes are counted from bottom to top.

For more sophisticated tree visualization you can look into `ggtree` package. There are several linguistic packages that provide some functionality for creating glottolog trees:

- `glottoTrees` package by Erich Round
- `lingtypr` package by Laura Becker