Python & Excel Data Automation

Many small teams build weekly reports by copy-pasting from several exports. In this demo, three regional sales files each use different column names, date formats, “$” price strings, inconsistent casing, duplicate rows, missing sales reps and negative-quantity typos.

Ingest: reads any number of .xlsx / .csv files

Normalize: maps every source to one schema, parses 3 date formats, cleans prices and text

Validate: removes duplicates, fixes negative quantities, fills missing owners, logs every fix

Aggregate: revenue by month, region, product and sales rep

Report: formatted Excel workbook with summary, chart, quality log and clean data

3 sources → 1 report; 612 raw rows → 600 clean rows

25 data issues fixed and logged automatically

Full run in under 1 second, one command

Self-directed demo built with synthetic data. I can adapt it to your files and report layout. Source code: https://github.com/cricket20052022/excel-report-automation