Parquet to CSV Converter — Free, In-Browser
Universal Format Converter
Convert between CSV, TSV, JSON, and Excel. Supports multiple files, primary data, and batch operations.
Select a data source to begin conversion
No data loaded
Upload files or use primary data to start converting
How to convert a Parquet file to CSV
- Open the .parquet file. Drop a Parquet file from your data lake, Spark job or pandas export onto the converter. It is read locally — no upload, no cluster.
- Preview the columns. The tool reads the row groups and schema and shows the data as a table. Nested structs and lists are kept as JSON in the cell.
- Download CSV (or go back to Parquet). Export a plain CSV for a spreadsheet or a non-technical teammate — or convert cleaned CSV back into a typed Parquet file for your pipeline.
About Parquet to CSV
Convert Apache Parquet columnar files into CSV rows, and CSV back into Parquet — the standard format for data engineering, Spark, and pandas pipelines.
Parquet is the de-facto columnar storage format across data engineering, analytics warehouses, and ML pipelines (Spark, pandas, DuckDB), chosen precisely because it's compact and fast for machines — not something you can casually open and eyeball.
This tool reads a Parquet file's row groups and columns directly in your browser and flattens them into ordinary CSV rows, handling the full range of Parquet types and compression codecs.
It also writes CSV data back into a real Parquet file, inferring column types automatically, useful when you've cleaned or filtered data in a spreadsheet and need it back in columnar form for a pipeline that expects Parquet input.
The Parquet library only loads when you actually open this tool, so it never slows down the rest of the site for people who aren't converting Parquet files.
Category: Conversion & ExportCommon Use Cases
- Previewing a Parquet file from a data lake without spinning up Spark
- Converting a pandas DataFrame export to CSV for a non-technical teammate
- Turning cleaned CSV data back into Parquet for a pipeline
Key Features
- Reads Parquet row groups and columns directly in the browser, including compressed codecs
- Writes CSV back into real Parquet with automatic column type inference
- Loads the Parquet library only when this tool is opened, keeping it off the rest of the site
The Parquet to CSV tool is compatible with: Apache Spark, pandas, DuckDB, Data Lakes.
Preview or convert a data lake Parquet export here, then use Avro to CSV when the same pipeline also produces Kafka Avro files, or Multi-Format Converter for other targets.
Frequently Asked Questions
It reads row groups and columns directly, so typical analytical Parquet files work well — very large multi-gigabyte files may be slow since everything runs in your browser tab rather than a distributed engine.
Standard primitive types (strings, numbers, booleans, dates) convert cleanly to CSV columns; deeply nested struct or list columns are preserved as their JSON representation in the cell rather than being split into new columns.
No — column types are inferred automatically from your data, which keeps the process one-click but means you should double-check inferred types (e.g. numeric-looking IDs) before feeding the file into a strict schema pipeline.
Built for data engineers and analysts who need to look inside a Spark or data lake Parquet file without spinning up a cluster.
Read the related guide →