Nationalize.io

How to Use This API

1. Predict Nationality for "Smith"

https://api.nationalize.io/?name=smith

Returns: {"name":"smith","country":[{"country_id":"US","probability":0.43},{"country_id":"GB","probability":0.31},{"country_id":"AU","probability":0.08}]}

2. Check a Culturally Specific Name

https://api.nationalize.io/?name=hiroshi

"Hiroshi" should return Japan (JP) as the top result with high probability.

3. Batch Multiple Names

https://api.nationalize.io/?name[]=mohammed&name[]=vladimir

Compare the geographic distributions for culturally distinct names.

4. JavaScript — Nationality Breakdown

async function predictNationality(name) {
  const resp = await fetch(
    `https://api.nationalize.io/?name=${encodeURIComponent(name)}`
  );
  const data = await resp.json();
  return data.country.map(c => ({
    country: c.country_id,
    probability: c.probability
  }));
}

predictNationality('mohammed').then(countries => {
  console.log('Top likely countries:');
  countries.slice(0, 3).forEach(c => {
    const pct = (c.probability * 100).toFixed(1);
    console.log(`  ${c.country}: ${pct}%`);
  });
});

5. Python — Combined Demographic Profile

import requests

def name_profile(first_name):
    """Get age, gender, and nationality from a single name."""
    # Fire all three APIs in parallel
    import asyncio
    
    agify = requests.get(
        'https://api.agify.io/',
        params={'name': first_name}
    ).json()
    genderize = requests.get(
        'https://api.genderize.io/',
        params={'name': first_name}
    ).json()
    nationalize = requests.get(
        'https://api.nationalize.io/',
        params={'name': first_name}
    ).json()
    
    profile = {
        'name': first_name,
        'estimated_age': agify.get('age'),
        'gender': genderize.get('gender'),
        'gender_probability': genderize.get('probability'),
        'top_countries': [
            f"{c['country_id']} ({c['probability']:.0%})"
            for c in nationalize.get('country', [])[:3]
        ]
    }
    return profile

# Profile a few names
for name in ['sarah', 'mohammed', 'wei']:
    p = name_profile(name)
    print(f"{p['name']}: ~{p['estimated_age']}yo, "
          f"{p['gender']} ({p['top_countries']})")