Find the gaps before they matter.
Find missing cells, empty rows, duplicates, and inconsistent columns before sharing a report.
Best next stepProfile → Review flags
A practical data workbench
Make messy data
make sense.
Inspect a dataset, fix common issues, explore patterns, and export useful results. Your files stay in the browser.
Runs in your browserNo account or API key
START WITH YOUR DATANO PRELOADED ROWS
Untitled analysis Empty workspace
Chart canvas READY WHEN YOU ARE
＋READY WHEN YOU AREYour first insight
Import data to reveal patterns.
No data loaded✓Find the gapsMissing values, duplicates
↗See the shapeProfiles and charts
THE WORKFLOWOne file. A clearer next step.
01ImportCSV · TSV · JSON
02InspectQuality + shape
03PreparePreview + undo
04VisualizePatterns + groups
05ExportYour next artifact
Where Data Lab helps
The messy middle
between file and answer.
Inspect and prepare files before you share, report, or act on them.
Make small, reversible fixes.
Trim values, replace missing data, change column types, derive fields, and remove duplicates—with undo.
Best next stepPrepare → Preview → Apply
Turn categories into a readable view.
Compare groups with bars, trends with lines, numeric relationships with scatter plots, and shares with a donut chart.
Best next stepVisualize → Inspect plotted values
Leave with something you can explain.
Export the cleaned dataset, a workspace backup, a chart, or a profile report.
Best next stepReview → Export explicitly
A good fit for
- First-pass inspection of a file you received
- Small-to-medium local data cleaning jobs
- Quick profiling and exploratory charts
- Reviewing data before sending it elsewhere
Not a replacement for
- SQL joins or a database workflow
- Scheduled refreshes or live dashboards
- Multi-user shared workspaces
- Large-scale processing beyond the published local limits
Illustrations only; no sample data is loaded.
One flow, not five tools
From raw rows to
reliable direction.
Inspect, prepare, chart, and profile your imported data in one workspace.
Get your bearings.
Understand the size, shape, columns, missing values, and duplicates before changing a thing.
Rows—Columns—Completeness—
Metrics appear after importClean with intent.
Trim values, fix types, replace missing data, remove duplicates, rename or derive columns—with undo.
TrimReplaceDerive
Find the pattern.
Build bar, line, donut, and scatter views from a category and a value. Export the chart or its data.
Know what's trustworthy.
Review numeric ranges, common values, uniqueness, completeness, and column-level quality signals.
CompleteColumn profile
LOCAL
Export only what you need.
Review your results, then export a dataset, workspace backup, chart, or profile report.
How the session works →A connected workflow
Stay close to
the data.
Inspect your data, preview cleaning steps, and keep the imported version as a baseline. Export the result you need.
Open Data Lab ↗Bring it in
Import CSV, TSV, JSON, or JSONL; paste a table or try a sample file.
Understand the data
Review values, data types, missing values, duplicates, and outliers.
Clean and review
Apply a cleaning step, preview the result, and undo if needed.
Export your results
Download a cleaned dataset, workspace backup, or SVG chart.
DATA & PRIVACY
Private by default.
Honest about limits.
Data stays in this tab and is not uploaded. Closing or reloading clears the workspace, so export your dataset or a backup to keep your work.
✓No account neededOpen the app and work locally.
✓In-tab processingSource files are read only after you select them.
✓You choose what to exportDownloads are the way to keep your work.