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Japanese Personal Name Dataset

Tests PyPI version Python Versions codecov License: MIT

A comprehensive dataset of Japanese personal names (first names and last names) with hiragana readings, romaji (Hepburn romanization), and kanji variations.

日本語README

Features

  • 5,578 male first names (702 optimized/popular names)
  • 3,294 female first names (241 optimized/popular names)
  • 2,000 last names with estimated population data
  • Multiple kanji variations for each reading
  • Romaji (Hepburn) transliterations
  • Easy-to-use Python API

Installation

pip install japanese-personal-name-dataset

Or install from source:

git clone https://github.com/shuheilocale/japanese-personal-name-dataset.git
cd japanese-personal-name-dataset
pip install -e .

Dataset Structure

The dataset consists of the following CSV files:

  1. first_name_man_org.csv - Male first names (original)
  2. first_name_man_opti.csv - Male first names (optimized/popular)
  3. first_name_woman_org.csv - Female first names (original)
  4. first_name_woman_opti.csv - Female first names (optimized/popular)
  5. last_name_org.csv - Last names

Optimized datasets contain curated popular names only.

CSV Format

First Names

Each row represents one name reading:

  • Column 1: Hiragana reading
  • Column 2: Romaji (Hepburn)
  • Column 3+: Kanji variations (variable number)

Example:

あい,ai,藍,愛,亜衣

Last Names

Each row represents one last name:

  • Column 1: Kanji
  • Column 2: Estimated population
  • Column 3: Hiragana reading
  • Column 4: Romaji (Hepburn)

Example:

佐藤,1887000,さとう,satou

Usage

Basic Usage

from japanese_personal_name_dataset import load_dataset

# Load the dataset (default: full version)
man_names, woman_names = load_dataset()

# Access male names
print(man_names['たろう'])
# Output: {'en': 'tarou', 'kanji': ['多朗', '多郎', '太朗', '太郎', '大郎']}

# Access female names
print(woman_names['はなこ'])
# Output: {'en': 'hanako', 'kanji': ['花子', '華子', ...]}
# Load only popular names
man_names, woman_names = load_dataset(kind='opti')
print(f"Male names: {len(man_names)} types")    # 702 types
print(f"Female names: {len(woman_names)} types")  # 241 types

Include Last Names

# Load with last names
man_names, woman_names, last_names = load_dataset(include_last_names=True)

# Access last name data
print(last_names['佐藤'])
# Output: {'reading': 'さとう', 'en': 'satou', 'count': 1887000}

Using Utility Functions

from japanese_personal_name_dataset import (
    generate_random_name,
    generate_random_full_name,
    search_by_reading,
    search_by_kanji,
    get_last_names,
    is_valid_name,
)

# Generate random name
name = generate_random_name(gender='male')
print(name)  # Example: Taro

# Generate random full name with reading
full_name, reading = generate_random_full_name(gender='female', return_reading=True)
print(f"{full_name} ({reading})")  # Example: Sato Hanako (satou hanako)

# Search by reading (partial match / LIKE search)
results = search_by_reading('kou', partial=True, gender='male')
for r in results[:3]:
    print(f"{r['reading']} ({r['romaji']}): {', '.join(r['kanji'][:3])}")
# Example: kouji (kouji): Koji, Takaji, Yukiharu

# Search by kanji (names containing '子')
results = search_by_kanji('子', partial=True, gender='female')
print(f"Names containing '子': {len(results)} results")

# Get top 10 most common last names
top_10 = get_last_names(limit=10)
for i, name in enumerate(top_10, 1):
    print(f"{i}. {name['kanji']} ({name['reading']}) - {name['count']:,} people")

# Validate name
if is_valid_name('太郎', 'たろう'):
    print("太郎 (tarou) is a valid combination")

Use Cases

  • Test data generation for web applications
  • Name validation and normalization
  • Japanese language learning tools
  • Data science and statistical analysis
  • Game development (character name generation)

Dataset Statistics

Number of Names

Type Count
Male first names (original) 5,578
Male first names (optimized) 702
Female first names (original) 3,294
Female first names (optimized) 241
Last names 1,999

Kanji Variations (per reading)

For original datasets:

  • Male names: avg 10 variations, max 447
  • Female names: avg 11 variations, max 398

For optimized datasets:

  • Male names: avg 45 variations, max 447
  • Female names: avg 51 variations, max 291

Data Format

  • File format: CSV
  • Character encoding: UTF-8
  • Line endings: LF
  • Romaji system: Hepburn romanization

License

MIT License

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

References

Disclaimer

While we strive for accuracy, there may be errors in the romanization or kanji variations. This dataset is provided as-is for informational purposes.

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