Free · No signup · Browser-based

Convert CSV to Parquet.

Drop a CSV, get a typed Apache Parquet file — columnar and compact, ready for pandas, polars, DuckDB, Spark and your data lake. Runs entirely in your browser.

To convert CSV to Parquet, drop or paste a CSV file — csvtodashboard parses it into rows and columns in your browser, then emits a typed, compressed Apache Parquet file. Data is stored by column with compression and a real type per column, so it's far smaller than CSV and reads back without a schema guess. Nothing is uploaded; the whole conversion runs on your device.

01 · How it works

Three steps, then done.

Parquet is the columnar on-disk format every modern data tool reads — pandas, polars, DuckDB, Spark, Athena, BigQuery. This converter infers a type per column and writes a real Parquet file locally, so you get a compact, typed file instead of a bulky CSV. The Parquet engine loads on demand the first time you convert, and your data never leaves the browser.

i. drop

Drop your file

Drag from Finder, click to choose, or paste data directly into the input pane.

ii. detect

We read the shape

Column types are inferred from the data so the output is correctly typed — not strings everywhere.

iii. use it

Copy, download, or dashboard

Copy the Parquet, download it as a file, or hit 'Build dashboard' to chart what's in your data.

02 · Why ours

Smart Parquet conversion by default.

Most free Parquet converters output a string for every value and bury your file in an upload form. Ours infers types from your data and runs entirely in your browser, so the Parquet looks like what you'd write by hand.

  • 01

    Correct types

    Numbers stay numbers, dates stay dates, booleans stay booleans — no quoted-string Parquet output.

  • 02

    Local-first

    Your file is parsed and converted in your browser. Nothing is uploaded; verify in DevTools → Network.

  • 03

    Fails loudly

    Malformed input gives a clear, specific error instead of silently wrong Parquet — so you can trust the result.

  • 04

    One click to a dashboard

    Every conversion keeps a tabular copy, so you can send the data straight to our visualization tool to chart it.

"Needed a quick Parquet conversion and ended up making a dashboard. Didn't expect that."
— the typical csvtodashboard arc
Good to know

csv to parquet notes.

Format-specific details worth knowing before you convert CSV to Parquet.

  • Columnar and compressed

    Parquet stores data by column with compression, so the file is typically far smaller than the equivalent CSV and faster to scan by column.

  • Types are preserved

    Each column is written with a real Parquet type, so pandas, DuckDB, Spark and Athena read it back without guessing a schema.

  • Binary, for data tools

    It's a binary on-disk format, not a text file — the de-facto data-lake format for DuckDB, Spark, Athena and BigQuery external tables.

03 · FAQ

csv to parquet questions.

Will pandas and DuckDB read the file?
Yes — `pandas.read_parquet(path)`, `polars.read_parquet(path)`, and DuckDB's `read_parquet(...)` all open it. It's a standard Parquet file.
From the site-wide type inference: numeric columns are written as numbers, true/false as booleans, and everything else as strings. Empty cells become nulls.
It's written as a standard Parquet file with column chunks. For very large datasets you may still get smaller files from a dedicated ETL tool, but for everyday CSVs it's far more compact and faster to query than CSV.
No. The Parquet writer is downloaded to your browser on first use and runs locally — nothing is sent to a server. Verify in DevTools → Network.
Related tools
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CSV to JSON
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CSV Validator
Check types before the Parquet export.
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CSV Pipeline
Clean and reshape before converting.
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Dashboard Builder
Visualize the data instead of exporting it.
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