Clean 10M-row files right in your browser.
Mungr runs DuckDB, a real analytical database compiled to WebAssembly, inside your browser. Clean millions of rows of CSV without uploading a byte, installing anything, or waiting on IT.
No sign-up to try · Guest files up to 50MB · Free account up to 5GB · Your data never leaves your browser
If you work with regulated data, none of the usual tools actually work for you.
Every option fails a different way. In healthcare, finance, or legal, that failure can be a compliance violation.
| Option | Breaks around | What happens |
|---|---|---|
| Excel / Google Sheets | Heavy formulas & large files | It slows to a crawl long before you reach the row limit, especially with real formatting and formulas. |
| OpenRefine / local scripts | >1M rows | It needs installing and IT sign-off before anyone can touch it. Then it runs out of memory the first time someone hands it a real export. |
| Cloud data platforms | No row limit | They handle the scale, but at real cost. And you still have to upload raw data off your device to get there. |
| Healthcare, finance & legal teams | Every file | Uploading data anywhere, cloud tool or not, risks a HIPAA, GDPR, or client-confidentiality violation before you've cleaned a single row. |
What if cleaning your data never required uploading it in the first place?
A real query engine that runs in your browser and never uploads your file.
Under the hood it is DuckDB, the same engine analysts run on a server.
Handle 10M+ rows without the spinning wheel
DuckDB compiled to WebAssembly runs a full analytical engine inside the page, so parsing and querying happen at database speed instead of JavaScript CSV speed.
Your data never leaves your device, PII included
Processing happens entirely client-side. Smart Scan flags PII against known categories like HIPAA Safe Harbor so you can mask, redact, or hash it before it is shared.
Zero install, zero setup
It's a web app. Open a tab, drop a file, and start cleaning. No pip installs, no Docker, no IT ticket.
What's the difference between data munging, data wrangling, and data cleansing?
They all describe the same job: getting raw, messy data ready for analysis. The terms overlap, but each leans a little differently, and Mungr covers all three.
Munge it into shape
Data munging means transforming raw data into a usable format: fixing date formats, mapping aliases, combining fields, and resolving inconsistencies. It's the "get this mess into a shape I can work with" step of data preparation.
Wrangle it into order
Data wrangling covers the whole loop: discovering problems, cleaning them, restructuring, and validating the result. Many analytics teams use "data wrangling" as the umbrella term for all of data preparation.
Clean out the errors
Data cleansing is the cleaning part specifically: removing or fixing incorrect, duplicate, incomplete, or wrongly formatted records. Think null handling, deduplication, and standardizing values before analysis.
Whether you call it data munging, data wrangling, or data cleansing, Mungr does all three in your browser with zero uploads. It's the data cleaning tool for analysts who refuse to send sensitive files to a server. Read the data cleaning 101 guide, see how Mungr stacks up against other data cleaning tools, or read the docs.
Mungr finds the PII. You decide what happens to it.
Nothing leaves your browser, so HIPAA and GDPR stop being a separate cleanup step. The exposure never happens in the first place.
Phone number (HIPAA Safe Harbor #5). Mask or redact before sharing externally.
25 of 25 rows (100%) match phone pattern. Consider masking before sharing. 25 rows
17 of 25 values are missing. Consider filling with a default or filtering these rows. 17 rows
Turn your cleaning steps into a recipe your whole team can reuse.
Build the sequence of steps once, save it as a recipe, and export it as JSON. Next time the same kind of export lands on your desk, a clean file is one click away.
{
"recipe": "facilities_cleanup",
"steps": [
{ "op": "trim", "cols": "*" },
{ "op": "case_standardize", "col": "email" },
{ "op": "date_standardize", "col": "admitted_date" },
{ "op": "pii_mask", "col": "phone", "rule": "hipaa_safe_harbor" },
{ "op": "fill_null", "col": "bed_count", "value": 0 }
]
}
Share the JSON in Slack, Notion, or your team's recipe library. Anyone on the team can load it and apply the same clean-up to their own file, and nothing about the underlying data has to be shared for the recipe to work.
Try it free. No sign-up to start.
Clean files up to 50MB right away. A free account adds 5GB of processing, saved recipes, and larger files.
| Guest | Free | Propopular | Team | |
|---|---|---|---|---|
| Price | $0 | $0 | $29/mo $23/mo | $49/mo per seat $39/mo per seat |
| Sign-up | None, start cleaning | Free account | Account + subscription | Account + subscription |
| Max file size | 50 MB | 100 MB | 1 GB | Unlimited |
| Processing | Session only, nothing stored | Up to 5 GB total | Unlimited | Unlimited, pooled across seats |
| Transforms | 15 core steps | All 19 steps | All 19 steps | All 19 steps |
| Saved recipes | None (session only) | 3 recipes | Unlimited | Unlimited + shared library |
| Recipe history | None | Last 3 recipes | Version history | Version history |
| Data location | Never leaves your device | Never leaves your device | Never leaves your device | Never leaves your device |
| Collaboration | None | None | Saved pipelines | Shared recipe library & admin roles |
| Open workspace | Register Free | Get Pro | Get Team |
Need more room without a subscription? Buy a one-time top-up of 5GB for $5 ▸ , no expiry rush, usable whenever you need it.
Student, academic, or nonprofit? Apply for a discount ▸
Need a fairer price where you live? Ask about Purchasing Power Parity (PPP) pricing at hello@getmungr.com
Built for real-world messy data.
Every feature exists because a real file broke a real tool first.
Native CSV & Parquet
Read columnar Parquet files directly at columnar speed, with no conversion step needed.
19 data cleaning operations
Standardize dates and casing, trim whitespace, handle nulls, deduplicate, and extract fields with presets or your own regex.
Automatic PII detection & redaction
Flags identifiers against known compliance categories like HIPAA Safe Harbor, then masks, redacts, or hashes them in one click.
Smart Scan
One click surfaces compliance and data-integrity issues across every column, with a recommended fix for each.
Streaming architecture
Processes data in chunks instead of all at once, so a 10M-row file doesn't need 10M rows of RAM.
Recipes you can share
Save your cleaning steps, export them as JSON, and let your team apply the exact same clean-up to the next file in one click.
Works offline
Once it loads, no connection is required to keep cleaning. Your data was never going anywhere anyway.
The questions every data analyst and data engineer asks us
We'd rather answer these now than have you wonder later.
Stop fighting your file size.
Start cleaning.
No sign-up to try. Free account up to 5GB. No install. No upload. No credit card.
Try it now, no sign-up →Set up in under 60 seconds · Your data stays on your device, always
Clean 10M rows, privately.
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