Does this convert the entire file or just a preview?

The entire file. Unlike the Parquet Reader and Viewer, which caps its table preview at 500 rows for performance, this converter reads and converts every row in the file.

How are nested or list-type columns handled in the CSV output?

A column whose value is an object or array is JSON-encoded into a single CSV cell, since CSV has no native way to represent nested structure. Simple scalar values (numbers, strings, booleans) are written as plain text.

How is this different from the Parquet to JSON Converter?

CSV output flattens every value to text and loses native types (numbers and booleans all become strings), while the Parquet to JSON Converter preserves each column's actual JSON type. Pick CSV for spreadsheet compatibility, JSON if downstream tooling needs real types.

What happens to Parquet's INT64 columns in the CSV output?

INT64 columns are read back as JavaScript bigint values internally, then converted to plain decimal text in the CSV, so large integers display correctly without any precision loss.

Parquet to CSV Converter - Convert Online

Overview

Introduction

Parquet's columnar binary format is great for analytics engines but useless for a quick look, or for handing data to a tool that only speaks CSV. This converter bridges that gap directly in the browser.

Upload a .parquet file and get back standard CSV text: a header row of column names followed by every row's values, ready to copy, download, or send to another tool on this site.

What Is Parquet to CSV Converter?

A Parquet-to-CSV converter that reads a file's full row set with a Parquet reader, then maps each row's values into a rectangular grid keyed by the file's own schema-defined column order before serializing that grid as RFC 4180 CSV text.

It's the mirror image of this site's CSV to Parquet Converter, taking Parquet's typed, columnar data back down to CSV's plain, flat, text-only shape.

How Parquet to CSV Converter Works

The uploaded file is wrapped as an in-memory buffer, its schema is read to fix a stable column order, and every row is read out as a plain JavaScript object.

Each cell is cast to a string, with objects and arrays JSON-encoded rather than stringified as "[object Object]", then the full grid of header plus data rows is serialized through this site's shared RFC 4180 CSV writer, which quotes any field containing a comma, quote character, or newline.

When To Use Parquet to CSV Converter

Use it whenever a downstream tool, spreadsheet program, or teammate needs CSV but the data you have is a .parquet file.

It's also useful for quickly diffing a Parquet dataset against another CSV source, since CSV is easy to eyeball or paste into a plain-text diff tool.

Often used alongside CSV to Parquet Converter and Parquet Reader and Viewer.

Features

Advantages

Converts the complete dataset, not a capped preview, entirely client-side with no upload.
Schema-driven column ordering keeps headers stable and correctly ordered even with sparse or null values.
Structured (nested/list) column values are JSON-encoded rather than silently corrupted into "[object Object]".

Limitations

CSV has no native types, so every value becomes text; a downstream tool needs to re-parse numbers and booleans itself.
Very large Parquet files may take a noticeable moment to fully decode before the CSV output appears, since the whole file is read into memory.

Examples

Converting a small Parquet file to CSV

Input

(a .parquet file with columns id, name, active and 2 rows)

Output

id,name,active
1,Ada,true
2,Alan,false

Column headers come from the file's schema, and each row's boolean and numeric values are cast to plain text.

Best Practices & Notes

Best Practices

Use the Parquet Schema Reader first if you want to confirm column names and types before converting a large or unfamiliar file.
For data with nested list or map columns, check the CSV output's JSON-encoded cells carefully before treating the conversion as a full type-safe export.
Use Parquet Metadata Reader first on a very large file to see the row count before converting, so a huge CSV output doesn't come as a surprise.

Developer Notes

Column headers are resolved from the file's schema rather than `Object.keys()` of the first row, matching the same reasoning as the sibling Parquet Reader and Viewer: a first row with a null in some column would otherwise silently drop that column's header from the CSV.

Parquet to CSV Converter Use Cases

Converting a Parquet data export into CSV for a spreadsheet program or a CSV-only tool
Quickly diffing a Parquet dataset against a CSV source using a plain-text diff
Handing Parquet data off to a script or system that only understands CSV

Common Mistakes

Expecting numeric or boolean types to survive the round trip; CSV output is plain text, so a consumer needs to re-parse those values.
Not noticing a nested column became a JSON string in the output, rather than being split into multiple CSV columns.

Tips

Round-trip through this site's CSV to Parquet Converter to sanity-check that a conversion preserved every row correctly.
Use the download button to save the output as converted.csv directly, rather than copying and pasting large files.

Parquet to CSV Converter