Free · No signup · Browser-based

Convert CSV to Arrow.

Drop a CSV, get a typed Apache Arrow IPC file — columnar and ready for pandas, polars, DuckDB and the rest of the Arrow ecosystem. Runs entirely in your browser.

To convert CSV to Arrow, drop or paste a CSV file — csvtodashboard parses it into rows and columns in your browser, then emits a typed Apache Arrow IPC file. Each column is written with a real Arrow type, so pandas, polars and DuckDB read it back typed without re-parsing. Nothing is uploaded; the whole conversion runs on your device.

01 · How it works

Three steps, then done.

Apache Arrow is the columnar, in-memory standard that pandas, polars, DuckDB and Spark all speak. This converter infers a type for each column up front and writes a proper Arrow IPC **file** (the `ARROW1` framed format) — so `pyarrow.ipc.open_file`, `polars.read_ipc` and friends read it back with the right types, no re-parsing. The Arrow engine loads on demand the first time you convert, and nothing ever leaves your 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 Arrow, download it as a file, or hit 'Build dashboard' to chart what's in your data.

02 · Why ours

Smart Arrow conversion by default.

Most free Arrow 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 Arrow looks like what you'd write by hand.

  • 01

    Correct types

    Numbers stay numbers, dates stay dates, booleans stay booleans — no quoted-string Arrow 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 Arrow — 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 Arrow conversion and ended up making a dashboard. Didn't expect that."
— the typical csvtodashboard arc
Good to know

csv to arrow notes.

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

  • Real columnar types

    Each column gets an inferred Arrow type (int64, float64, utf8, bool, timestamp), so pyarrow, polars and DuckDB read it back typed — no re-parsing.

  • IPC file, not stream

    The output is the ARROW1-framed file format — read it with pyarrow.ipc.open_file or polars.read_ipc, not the streaming reader.

  • Binary, not text

    Arrow is a binary buffer meant for data tools; open it in pandas or DuckDB, not a text editor. For a readable export use CSV or JSON.

03 · FAQ

csv to arrow questions.

Is this the Arrow IPC 'file' or 'stream' format?
The file format — it begins with the `ARROW1` magic and ends with a footer, so random-access readers like `pyarrow.ipc.open_file` and `polars.read_ipc` work directly.
From the same type inference used across the site: numeric columns become 64-bit floats, true/false columns become booleans, and everything else becomes UTF-8 strings. Empty cells become nulls.
Yes — `pyarrow.ipc.open_file(path).read_all().to_pandas()` or `polars.read_ipc(path)` both load it. DuckDB can query the file directly too.
No. The Arrow library is downloaded to your browser the first time you convert, and the conversion runs locally — verify in DevTools → Network.
Related tools
CSV to Parquet
On-disk columnar format for data lakes.
Open →
CSV to JSON
Human-readable alternative for smaller data.
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CSV Validator
Check types before the Arrow 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.
Open →