normalizer-usps 0.1.0

A library for normalizing US addresses.

normalizer_usps

normalizer_usps is a Python library for normalizing US addresses by abbreviating street types and secondary address designations according to USPS standards.

Features

• Street Type Abbreviation: Converts street types like "Street" to "ST", "Avenue" to "AVE", etc.
• Secondary Address Abbreviation: Abbreviates secondary address units like "Apartment" to "APT", "Suite" to "STE".
• Easy Integration: Designed to work seamlessly with Pandas Series for batch processing.

Installation

Install the package using pip:

pip install normalizer_usps

Usage

import pandas as pd from normalizer_usps.normalizer import abbreviate_address_series, street_type_abbreviations, secondary_address_abbreviations

Sample address data

addresses = pd.Series([ '123 Happy Street', '456 Elm Avenue', '789 Oak Boulevard', '101 Maple Apartment' ])

Normalize street types

normalized_addresses = abbreviate_address_series(addresses, street_type_abbreviations) print(normalized_addresses)

Normalize secondary address units

normalized_addresses = abbreviate_address_series(addresses, secondary_address_abbreviations) print(normalized_addresses)

0     123 Happy ST
1       456 Elm AVE
2    789 Oak BLVD
3    101 Maple Apartment
dtype: object

0     123 Happy Street
1       456 Elm Avenue
2    789 Oak Boulevard
3        101 Maple APT
dtype: object

Data Files

The package includes two JSON files containing abbreviation mappings:

street_type_abbreviations.json secondary_address_abbreviations.json Contributing Contributions are welcome! Please open an issue or submit a pull request on GitHub.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Larissa [e-mail]