Fuzzy Match Python Script

Overview

The fuzzy_match.py script provides comprehensive functionality for fuzzy matching of company names across datasets, utilizing advanced text processing, TF-IDF vectorization, and nearest neighbor search.

Features

• Text Preprocessing: Cleans and normalizes text, handles non-ASCII characters, abbreviations, and removes specific stopwords.
• Vectorization and N-Gram Analysis: Uses TF-IDF vectorization and custom n-gram analysis to prepare text data for matching.
• Fuzzy Matching: Implements efficient fuzzy matching using the nmslib library, ideal for comparing textual data across different datasets.
• Yearly and Quarterly Matching: Facilitates temporal segmentation in data matching, essential for tasks that require historical data alignment.

Usage

This script is suitable for data merging tasks such as aligning customer databases or linking financial records where company names may have discrepancies.

Requirements

• Python 3.x
• Libraries: pandas, sklearn, nmslib, ftfy

Installation

Ensure you have Python installed and then install required packages using:

pip install pandas sklearn nmslib ftfy

Example

Ideal for financial institutions aiming to consolidate customer or transaction data across multiple databases. See the create_dealscan_with_compustat_callreport_tfidf_meausres.py for example use.