If you would try to find a complete list of languages with its stats, you will face with a problem - there are no public datasets. Moreover, there are no robust data sources that explain methodology of data collection, so eventually you will waste a hours to find a randomized data.

This package is for you then.

The langstats package is provides a data about languages, including

language codes
total speakers count
countries summary with list of used languages and population count

Methodology

This package is free you of data collection, all data is included in package and will be updated automatically in a new package versions.

We use different sources of data, but in general you can't rely on this data as a robust source of truth, since data may be partially incomplete because data collection is a difficult thing.

But you may be sure the data is reflect a state of the world and even when numbers is approximated, the relations between numbers are correct in general, that is enough for application purposes.

Currently we use a Wikidata as a data source.

Data source may be changed in future (and probably will), and README will reflect this changes.

Usage

Languages stats

To get languages list, call getLanguagesList

import { getLanguagesList } from 'langstats';

const languages = await getLanguagesList();

console.log(languages);

It will return over 1600 languages sorted by total speakers in descending order.

Output sample:

[
  {
    "codes": {
      "iso639_1": "zh",
      "iso639_3": "zho"
    },
    "speakers": {
      "total": 1299877520
    }
  },
  {
    "codes": {
      "iso639_1": "en",
      "iso639_3": "eng"
    },
    "speakers": {
      "total": 1132366680
    }
  },
  {
    "codes": {
      "iso639_3": "cmn"
    },
    "speakers": {
      "total": 897071810
    }
  },
  {
    "codes": {
      "iso639_1": "es",
      "iso639_3": "spa"
    },
    "speakers": {
      "total": 485000000
    }
  },
  {
    "codes": {
      "iso639_1": "ar",
      "iso639_3": "ara"
    },
    "speakers": {
      "total": 422000000
    }
  },
  {
    "codes": {
      "iso639_1": "bn",
      "iso639_3": "ben"
    },
    "speakers": {
      "total": 300000000
    }
  },
  {
    "codes": {
      "iso639_1": "pt",
      "iso639_3": "por"
    },
    "speakers": {
      "total": 254300000
    }
  },
  {
    "codes": {
      "iso639_1": "fr",
      "iso639_3": "fra"
    },
    "speakers": {
      "total": 208157220
    }
  },
  {
    "codes": {
      "iso639_1": "id",
      "iso639_3": "ind"
    },
    "speakers": {
      "total": 198996550
    }
  },
  {
    "codes": {
      "iso639_1": "ru",
      "iso639_3": "rus"
    },
    "speakers": {
      "total": 171428900
    }
  },
  ...
]

Countries stats

To get countries list, call getCountriesList

import { getCountriesList } from 'langstats';

const countries = await getCountriesList();

console.log(countries);

It returns a list of countries with summary that includes a country code, population and used languages.

Output sample:

[
  {
    "code": "CN",
    "population": 1442965000,
    "languages": []
  },
  {
    "code": "IN",
    "population": 1326093247,
    "languages": [
      "hi",
      "en"
    ]
  },
  {
    "code": "US",
    "population": 340110988,
    "languages": [
      "en"
    ]
  },
  {
    "code": "ID",
    "population": 275439000,
    "languages": [
      "id"
    ]
  },
  {
    "code": "PK",
    "population": 223773700,
    "languages": [
      "ur",
      "en"
    ]
  },
  {
    "code": "NG",
    "population": 211400708,
    "languages": [
      "en"
    ]
  },
  {
    "code": "BR",
    "population": 203062512,
    "languages": [
      "pt"
    ]
  },
  {
    "code": "BD",
    "population": 171466990,
    "languages": [
      "bn"
    ]
  },
  {
    "code": "RU",
    "population": 146119928,
    "languages": [
      "ru"
    ]
  },
  {
    "code": "ET",
    "population": 128691692,
    "languages": [
      "am"
    ]
  },
  ...
]

Example of usage

You may combine data depends on your use case.

As example, let's create demo that will draw top 20 languages by number of speakers, and join to every language a list of countries where people speak this language sorted in country population order.

import { getCountriesList, getLanguagesList } from 'langstats';

Promise.all([getLanguagesList(), getCountriesList()])
	.then(([languages, countries]) => {
		const languageNames = new Intl.DisplayNames(['en'], { type: 'language' });
		const countryNames = new Intl.DisplayNames(['en'], { type: 'region' });

		console.log(`Top languages:`);

		let order = 0;
		for (const language of languages.slice(0, 20)) {
			const { codes, speakers } = language;
			const code = codes.iso639_1 ?? codes.iso639_3;
			if (!code) continue;

			const displayName = languageNames.of(code);
			if (displayName === code) continue;

			const { iso639_1: shortLangCode } = codes;
			const countriesList = shortLangCode
				? countries
						.filter(({ languages }) => languages.includes(shortLangCode))
						.sort((a, b) => b.population - a.population)
						.map(({ code }) => countryNames.of(code))
						.slice(0, 10)
						.join(', ')
				: '';

			console.log(
				[
					`#${++order} ${languageNames.of(code)} (${[codes.iso639_1, codes.iso639_3].filter(Boolean).join(',')})`,
					`- Total speakers: ${speakers.total}`,
					countriesList && `- Top 10 countries where used: ${countriesList}`,
				]
					.filter(Boolean)
					.join('\n'),
			);
		}
	});

Will print top 20 languages

Top languages:
#1 Chinese (zh,zho)
- Total speakers: 1299877520
#2 English (en,eng)
- Total speakers: 1132366680
- Top 10 countries where used: India, United States, Pakistan, Nigeria, Philippines, United Kingdom, South Africa, Tanzania, Kenya, Uganda
#3 Chinese (cmn)
- Total speakers: 897071810
#4 Spanish (es,spa)
- Total speakers: 485000000
- Top 10 countries where used: Mexico, Colombia, Spain, Argentina, Venezuela, Chile, Guatemala, Ecuador, Bolivia, Honduras
#5 Arabic (ar,ara)
- Total speakers: 422000000
- Top 10 countries where used: Egypt, Algeria, Afghanistan, Sudan, Iraq, Morocco, Morocco, Saudi Arabia, Yemen, Syria
#6 Bangla (bn,ben)
- Total speakers: 300000000
- Top 10 countries where used: Bangladesh
#7 Portuguese (pt,por)
- Total speakers: 254300000
- Top 10 countries where used: Brazil, Angola, Portugal, Timor-Leste, Cape Verde, São Tomé & Príncipe
#8 French (fr,fra)
- Total speakers: 208157220
- Top 10 countries where used: Congo - Kinshasa, France, Canada, Côte d’Ivoire, Cameroon, Chad, Senegal, Rwanda, Benin, Burundi
#9 Indonesian (id,ind)
- Total speakers: 198996550
- Top 10 countries where used: Indonesia
#10 Russian (ru,rus)
- Total speakers: 171428900
- Top 10 countries where used: Russia, Kazakhstan, Tajikistan, Belarus
#11 Japanese (ja,jpn)
- Total speakers: 128000000
- Top 10 countries where used: Japan, Palau
#12 Punjabi (pa,pan)
- Total speakers: 125000000
#13 German (de,deu)
- Total speakers: 105000000
- Top 10 countries where used: Germany, Belgium, Austria, Switzerland, Luxembourg, Liechtenstein
#14 Egyptian Arabic (arz)
- Total speakers: 100542400
#15 Javanese (jv,jav)
- Total speakers: 84308740
#16 Marathi (mr,mar)
- Total speakers: 83100000
#17 Swahili (swh)
- Total speakers: 82300000
#18 Turkish (tr,tur)
- Total speakers: 82231620
- Top 10 countries where used: Türkiye, Cyprus
#19 Telugu (te,tel)
- Total speakers: 82000000
#20 Wu Chinese (wuu)
- Total speakers: 81400000

Some details may be missed, it will be improved when data source will be updated.

Roadmap

Find more data sources and enrich the data
- Find data source with information about methodology of data collection
- Find data source about language usage in regions
Implement query function to select languages by countries and regions lists, by territory size and by borders with another countries

Keywords

FAQs

What is langstats?

Is langstats well maintained?

Package last updated on 14 Jul 2025

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