global-gender-predictor 0.0.3

Predict gender using first name using data from World Gender Name Dictionary 2.0.

Global Gender Predictor

Predict gender using first name using data from World Gender Name Dictionary 2.0. The dataset contains 4,148,966 unique names. The predictor is case-insensitive and predicts Male, Female, or Unknown (i.e. unisex or not found in data)

Install using pip:

pip install global_gender_predictor

Usage

from global_gender_predictor import GlobalGenderPredictor

predictor = GlobalGenderPredictor()

predictor.predict_gender('John')
'Male'
predictor.predict_gender('Jane')
'Female'
predictor.predict_gender('attract.ai')
'Unknown'

The dataset contains probabilities for each name: {'name': 'taylor', 'gender_prob': {'F': 0.699, 'M': 0.301}}. Change the probability threshold for unisex names:

predictor.predict_gender('taylor',threshold=0.5)
'Female'
predictor.predict_gender('taylor',threshold=0.8)
'Unknown'

Citation

World Gender Name Dictionary (WGND 2.0)

@data{DVN/MSEGSJ_2021,
author = {Raffo, Julio},
publisher = {Harvard Dataverse},
title = {{WGND 2.0}},
UNF = {UNF:6:5rI3h1mXzd6zkVhHurelLw==},
year = {2021},
version = {DRAFT VERSION},
doi = {10.7910/DVN/MSEGSJ},
url = {https://doi.org/10.7910/DVN/MSEGSJ}
}