README.md

gender-identification

Code and pipeline for gender identification based on names. The repo contains a CLI and a package for easily adding a gender column to tabular data.

Usage

Install the package:

pip install gender-identification

If you have some tabular data in csv, tsv or jsonl you can just add a gender and a gender_confidence column to these using the CLI.

python3 -m gender_identification data.csv --name_column "first_name"

Alternatively you can save it to a different file:

python3 -m gender_identification data.csv --name_column "first_name" -o results.csv

You can also just use the package in Python:

from gender_identification import add_gender

df = pd.DataFrame({"name": ["Peter Jørgensen", "Malte Larsen"]})

df = add_gender(df, name_column="name", remove_last_name=True)

Parameters

Parameter	Flag(s)	Description	Default Value
in_file		Input file path.	-
name_column	--name_column, -n	Column where names are contained.	-
out_file	--out_file, -o	Output file path. If not specified, the original file will be overwritten.	None
remove_last_name	--remove_last_name, -r	Indicates whether last names should be removed.	False
drop_confidence	--drop_confidence, -d	Indicates whether to drop the column indicating the model's confidence in its predictions.	False
batch_size	--batch_size, -b	Size of the batches to do inference in.	32