categorical-distance

1.9 verified Fri May 01 auth: no python

Python library for measuring distances between categorical variables. Supports a variety of distance metrics including Hamming, Jaccard, and Dice coefficients. Version 1.9, stable.

pip install categorical-distance

Common errors

error ValueError: arrays must have same length ↓

cause Input sequences have different lengths.

fix

Ensure both input lists have the same length.

error AttributeError: module 'categorical_distance' has no attribute 'categorical_distance' ↓

cause Importing the module directly instead of the function.

fix

Use 'from categorical_distance import categorical_distance' to import the function.

error ImportError: No module named 'categorical_distance' ↓

cause Library not installed.

fix

Run 'pip install categorical-distance'.

Warnings

gotcha The function `categorical_distance` expects lists or arrays of equal length; if lengths differ, it raises a ValueError. ↓

fix Ensure input lists have the same length.

gotcha The library does not handle missing values (NaN/None). Input must be clean categorical values. ↓

fix Preprocess data to remove or impute missing values before calling the function.

deprecated The `distances` module is deprecated and has been replaced by `metrics`. ↓

fix Use `from categorical_distance import metrics` instead.

Imports

categorical_distance
wrong
```
import categorical_distance
```
correct
```
from categorical_distance import categorical_distance
```
Direct import of module does not expose the function; must import the function explicitly.

metrics

wrong

import categorical_distance.metrics

correct

from categorical_distance import metrics

Import the submodule directly as shown.

Quickstart

Compute the distance matrix between two lists of categorical values.

from categorical_distance import categorical_distance
distance_matrix = categorical_distance(['a','b','c'], ['a','c','b'])
print(distance_matrix)