CSV & Excel support
Load everyday `.csv` and `.xlsx` exports from one focused desktop flow.
Self-initiated portfolio project
Turn messy spreadsheets into clean, usable data.
A Python desktop automation tool for cleaning, analyzing, and reporting Excel and CSV data.
PythonPandasOpenPyXLTkinterExcel automation
Built for teams who need repeatable cleanup without a data specialist.
Excel & CSV automation tool
Clean your source file
messy_sales_data.csv
Rows after cleaning4
Duplicates removed1
Issues found10
Order IDCustomer NameRegionStatus
SO-1001Maya ChenNorthShipped
SO-1002Liam O'ConnorNorthShipped
SO-1003Sofia AlvarezWestPending
DataFlow / 01Python desktop workflowCSV + XLSX
Browser-based CSV demo
Try DataFlow Live
Drop in a messy CSV and see the cleaning workflow in seconds. Nothing leaves this page.
Your file is processed locally in your browser.
Drop a CSV file here
or choose a file from your device
CSV only · 5 MB limitLocal processing
Ready for a source file
DataFlow trims whitespace, removes empty and duplicate rows, and reports missing values while keeping the original file unchanged.
Choose a CSV to begin.
Download DataFlow for Windows
Windows ZIP coming soon · place it in
portfolio-site/assets/.
Before cleaning
Source preview (first 10 rows)
Live demo supports CSV files. The full Windows DataFlow application also supports XLSX reports and creates Cleaned Data, Summary, and Data Quality Issues worksheets.
The problem
The spreadsheet is rarely ready when it arrives.
Exports from CRMs, stores, and internal tools often contain duplicates, missing values, inconsistent formatting, and empty records. Before anyone can use the information, someone has to make it coherent.
Manual cleanup steals time from the work that matters and creates a new risk with every copy, paste, and ad-hoc formula.
01 Duplicate records02 Missing values03 Mixed formatting04 Empty data
The solution
A calm, repeatable path from source file to report.
DataFlow keeps the workflow visible so a non-technical teammate can move from a raw export to a useful workbook in a few clear steps.
01
Select file
Choose a CSV or XLSX without moving the original.
02
Preview
Check the first rows before any changes are made.
03
Clean & analyze
Apply safe rules and surface anything uncertain.
04
Export report
Save a styled workbook with a quality log.
Key features
Practical automation with a visible paper trail.
Every feature is shaped around a real spreadsheet handoff: make the useful changes, keep the source safe, and show what needs a human eye.
Duplicate removal
Find repeated rows, keep the first occurrence, and report the count.
Missing-value detection
See which columns still need attention before a report is shared.
Data normalization
Trim text and safely normalize dates, numbers, labels, and whitespace.
Safe source handling
The original file stays untouched while the working copy is cleaned.
Automated Excel reports
Export a readable workbook with filters, frozen headers, and clear sections.
Quality issue tracking
Capture missing values, skipped conversions, and suspicious values in one log.
Desktop GUI
A simple Tkinter interface gives non-technical users an obvious next step.
No-overwrite exports
Existing reports are preserved with automatic `_1`, `_2` naming.
Measured on the included sample files
Small inputs. Clear outcomes.
The sample project uses two fictional exports and the same processor that powers the Windows app.
12rows processed6 + 6 across both files
1duplicate detectedsales sample
18issues identified10 sales + 8 customer
2reports generatedone per sample file
DFDataFlow reportXLSX
Cleaning summary
Original rows6
Final rows4
Issues10
Cleaned DataSummaryQuality Issues
Output report
One workbook, three useful views.
The exported report is designed to be handed to a teammate or client without another explanation.
01
Cleaned Data
Normalized rows with filters and a frozen header.
02
Summary
Counts, file details, timing, and processing date.
03
Data Quality Issues
A filterable record of missing and uncertain values.
Safety by design
Automation should make the next decision easier.
DataFlow makes safe changes automatically and leaves uncertain data visible for review.
✓
Original files remain untouched
Processing always works on a copy.
✓
No silent deletion
Uncertain values are preserved and reported.
✓
No report overwriting
Existing outputs get a unique filename.
✓
Clear error handling
Corrupt or unsupported files receive a human-readable message.
Testing
A small app with a real verification loop.
The test suite runs against the processor and report generator, including source preservation and duplicate filename behavior.
✓
10 tests passed0 failures · 0 errors
test_dataflow.pyPASS
01CSV and Excel loadingPASS
02Duplicate and blank cleanupPASS
03Safe dates and numbersPASS
04Missing-value reportingPASS
05Report export + filename safetyPASS
06Source remains unchangedPASS
07Invalid file handlingPASS
unittest -v / latest run
Desktop application
A focused workspace for Windows.
Replace the placeholder with a real capture whenever you are ready to show the app in action.
DataFlow
DataFlow running on Windows
Place dataflow-app.png in portfolio-site/assets/ to replace this preview.
Application preview / Windows desktopReplace with dataflow-app.png
Tech stack
Simple tools, carefully connected.
PythonPandasOpenPyXLTkinterHTMLCSSJavaScript
Have a repetitive workflow?
Need spreadsheet work automated?
DataFlow is a portfolio-ready example of how a manual spreadsheet handoff can become a dependable desktop tool.