| Name | global-gender-predictor JSON |
| Version |
0.0.4
JSON |
| download |
| home_page | https://github.com/attract-ai/global-gender-predictor |
| Summary | Predict gender using first name using data from World Gender Name Dictionary 2.0. |
| upload_time | 2024-08-02 00:35:02 |
| maintainer | None |
| docs_url | None |
| author | Rianne Klaver |
| requires_python | >=3.7 |
| license | MIT License Copyright (c) 2024 attract.ai Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# 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:
```bash
pip install global_gender_predictor
```
## Usage
```python
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:
```python
predictor.predict_gender('taylor',threshold=0.5)
'Female'
predictor.predict_gender('taylor',threshold=0.8)
'Unknown'
```
## Citation
World Gender Name Dictionary (WGND 2.0)
```bibtex
@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}
}
```
## deployment
```
rm dist/*
python3 -m build
twine upload dist/*
```
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