Agencies: does a messy client export keep delaying your reporting or handoff?
I offer Excel/CSV cleanup with written rules agreed before processing. You receive the cleaned file, a change log, unresolved exceptions and a separate validation summary. Identifiers are preserved; ambiguous values are flagged for your decision.
The $99 package covers one flat table up to 5,000 rows and 20 columns, with delivery in three business days after rule approval and funding.
Send me the column names, approximate row count and desired changes through Contra first. Please keep sensitive files out of public posts.
DataFlow is a self-initiated Python automation tool designed to clean, analyze, and transform messy Excel and CSV files into structured, usable reports.
It detects duplicates, missing values, empty rows and columns, and common formatting issues while preserving the original source file. The project includes a Windows desktop application, automated Excel report generation, and an interactive browser-based CSV cleaning demo.
I created a clean Excel sheet with Product Name, SKU, Price, Category, Stock and Status. Applied conditional formatting for Low Stock and removed all duplicates.
Finance teams waste 20+ hours every month doing manual data entry:
Export budget numbers -> hunt down department leads for explanations -> copy-paste everything into a slide deck.
The spreadsheet tells leadership what happened. But explaining why is what burns time.
I automated the entire cycle:
• Pairs numbers with context: Instantly connects budget overruns to actual operational causes (cloud migrations, commission accelerators, onboarding delays).
• Cuts the noise: Filters out small immaterial variances so leadership only sees what impacts EBITDA.
• Zero slide building: Auto-generates a branded, 3-slide executive deck in Google Slides and drops the summary into Slack. From raw accounting files to an executive-ready deck in under 2 minutes.
Watch the full flow in the video below.