Genderize.io

How to Use This API

1. Predict Gender for "Peter"

https://api.genderize.io/?name=peter

Returns: {"name":"peter","gender":"male","probability":1.0,"count":120567}. A probability of 1.0 means 100% of records with this name were male.

2. Country-Specific — "Kim"

https://api.genderize.io/?name=kim&country_id=US
https://api.genderize.io/?name=kim&country_id=KR

"Kim" in the US is often female (surname as given name). In Korea it's strongly male. The country filter reveals this difference.

3. Batch Prediction

https://api.genderize.io/?name[]=alex&name[]=jordan&name[]=cameron

Gender-neutral names in batch form. See which way each leans statistically.

4. JavaScript — Name Demographics

async function predictGender(name, country = null) {
  const params = new URLSearchParams({ name });
  if (country) params.set('country_id', country);
  const resp = await fetch('https://api.genderize.io/?' + params);
  return resp.json();
}

async function analyzeNames(names) {
  const params = new URLSearchParams();
  names.forEach(n => params.append('name[]', n));
  const resp = await fetch('https://api.genderize.io/?' + params);
  const results = await resp.json();
  
  results.forEach(r => {
    const confidence = (r.probability * 100).toFixed(0);
    console.log(`${r.name}: ${r.gender || 'unknown'} ` +
      `(${confidence}% confidence, n=${r.count})`);
  });
}

analyzeNames(['alex', 'jordan', 'riley', 'casey']);

5. Python — Probability Heatmap

import requests

def gender_probability(name, country='US'):
    resp = requests.get(
        'https://api.genderize.io/',
        params={'name': name, 'country_id': country}
    )
    data = resp.json()
    return {
        'name': data['name'],
        'gender': data.get('gender'),
        'probability': data.get('probability', 0),
        'samples': data.get('count', 0)
    }

# Check ambiguous names across countries
for name in ['ashley', 'leslie', 'jesse', 'marion']:
    us = gender_probability(name, 'US')
    uk = gender_probability(name, 'GB')
    print(f"{name.title()} in US: {us['gender']} "
          f"({us['probability']:.0%}) — in UK: {uk['gender']} "
          f"({uk['probability']:.0%})")