Spreadsheet Cleaning & Rule Engine Architecture

Manual Excel processing wastes hundreds of hours per month. A custom rule engine standardizes data ingest automatically.

Pipeline Breakdown

1. Header Normalization: Trim whitespace, strip special accents, and map aliases to canonical schemas.
2. Type Enforcement: Coerce numeric, date, and text columns with explicit fallback defaults.
3. Validation & Logging: Track modified rows and export clean CSV/Parquet outputs.

import pandas as pd

def clean_spreadsheet(file_path):
    df = pd.read_excel(file_path)
    df.columns = [c.strip().lower().replace(" ", "_") for c in df.columns]
    # Apply business validation rules
    return df

Written by Jaime Escoto · Data Automation Specialist.