gower

library0.1.2pypypiunverified

Python implementation of Gower's distance for mixed numerical and categorical data, computing pairwise distances between records in two datasets. Version 0.1.2 is the current and only release, with no active development since 2020. Requires Python >=2.7.

data

pip install gower

github ↗package ↗

INSTALL

IMPORT

SIG · GOWER

gower

datapythonv0.1.2

Install

7.2s avg

Import

—

Disk

230MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 230.7MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 7.2s · import 0.000s · 222MB

230MB installed

● package 230MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

gower_matrix

✓ from gower import gower_matrix

✗ from gower import gower_matrix

Compute pairwise Gower's distance between two dataframes with mixed numeric and categorical columns.

import numpy as np import pandas as pd from gower import gower_matrix # Example data with mixed types X = pd.DataFrame({ 'num': [1.0, 2.0, 3.0], 'cat': ['a', 'b', 'a'] }) Y = pd.DataFrame({ 'num': [2.0, 3.0], 'cat': ['b', 'c'] }) # Compute Gower's distance matrix D = gower_matrix(X, Y) print(D) # Expected: array of shape (len(X), len(Y))

Debug

Known issues

gotchaThe library handles missing values (NaN) by ignoring the feature for that pair (distance contribution set to 0). This may not be expected; no parameter to change this behaviour.

fix

Impute missing values before calling gower_matrix if a different handling is required.

affects: 0.1.2

gotchaThe categorical column handling is based on pandas object dtype. If your categorical columns are encoded as numbers (e.g., int64), they will be treated as numeric, which may produce incorrect distances.

fix

Ensure categorical columns are explicitly of dtype 'object' or 'category' (though category may not be recognized; prefer object dtype).

affects: 0.1.2

Upgrade

Version history

0.1.2latest on PyPI · released Nov 13, 2022

Audit

Dependencies

No dependency data recorded yet.

Agent activity

14 hits · last 30 days

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Resources

githubhttps://github.com/wwwjk366/gower ↗

packagehttps://pypi.org/project/gower/ ↗