Tax Data Import and Processing System

This repository contains a Python-based system for importing and processing tax-related data files. The system handles various fixed-width text files containing tax information, account details, and property data.

Features

• Imports multiple fixed-width text files with different encodings support
• Processes tax bills, account information, and property data
• Handles various data types and formats
• Merges related data into comprehensive datasets

File Processing

The system processes the following files:

1. CITYBILL.txt

• Contains billing information
• Fields include: Bill Account, Bill Type, Real Value, Personal Value, etc.
• Fixed-width format with specific column specifications

2. ACCOUNT.txt

• Contains account holder information
• Fields include: Account Number, Account Type, Names, SSN, Business Details, etc.
• Fixed-width format with address and contact information

3. PARCEL.txt

• Contains property parcel information
• Fields include: Parcel ID, Legal Description
• Fixed-width format for property details

4. NASH.txt

• Contains comprehensive property and tax information
• Includes jurisdiction details, property IDs, values, and location data
• Extended property and owner information

Technical Details

Dependencies

• pandas
• Python 3.x

Data Types

The system handles various data types including:

• Strings (for IDs, names, addresses)
• Integers (for values, counts)
• Floats (for measurements)

Encoding Support

Multiple encodings are supported:

• cp1252
• windows-1252
• latin1
• iso-8859-1

Usage

1. Place your data files in the specified data directory
2. Run the script to process the files
3. Access the merged data through the resulting DataFrames

Data Directory Structure

data/
├── CITYBILL.txt
├── ACCOUNT.txt
├── PARCEL.TXT
└── NASH.txt

Output

The system produces merged datasets that combine information from multiple sources:

• merged_df: Combines CITYBILL and ACCOUNT data
• edge_df: Adds PARCEL data to the merged dataset
• nash_df: Processes NASH data separately

Contributing

Feel free to submit issues and enhancement requests!