Parquet is the go-to columnar storage format in data engineering — used by Spark, Pandas, AWS Athena, BigQuery, and Databricks. But when you need to share data with a business analyst, import it into Excel, or preview it without spinning up a Python environment, CSV is far more practical. This guide shows how to convert Parquet to CSV for free without writing any code.

Why Convert Parquet to CSV?

Parquet is optimised for analytics queries at scale — excellent for storage and compute, terrible for human readability. CSV opens in Excel, Google Sheets, Tableau, Power BI, and any database import wizard.

Reasons to convert Parquet to CSV:

How to Convert Parquet to CSV Free Online

Step 1 — Open the Converter

Go to SolutionGigs Parquet to CSV Converter. No Python, no Spark, no account needed.

Step 2 — Upload Your Parquet File

Click Select File or drag your .parquet file. Supports files up to 500 MB.

Step 3 — Convert and Preview

Click Convert. When complete, you can preview the first 200 rows directly on screen before downloading — useful to verify the data looks correct.

Step 4 — Download Your CSV

Click Download to save the .csv file, ready to open in Excel or any tool.

How to Convert Parquet to CSV in Python (Code Alternative)

If you prefer code, here are the standard approaches:

Using pandas:

import pandas as pd

df = pd.read_parquet("data.parquet")
df.to_csv("data.csv", index=False)

Using PyArrow:

import pyarrow.parquet as pq
import pyarrow.csv as pcsv

table = pq.read_table("data.parquet")
pcsv.write_csv(table, "data.csv")

Using DuckDB (fastest for large files):

COPY (SELECT * FROM read_parquet('data.parquet')) TO 'data.csv' (HEADER, DELIMITER ',');

Parquet vs CSV — Key Differences

Parquet CSV
Format Columnar binary Row-based text
File size 5–10× smaller Larger
Read speed Very fast (columnar) Slower for analytics
Human readable No Yes
Excel/Sheets support No Yes
Schema/types Embedded Inferred
Null handling Native Empty string or "null"
Encoding Binary + compression UTF-8 text

Handling Common Parquet to CSV Issues

Nested columns (structs/arrays): Parquet supports nested structures that CSV cannot represent. The converter flattens or serializes nested values as JSON strings.

Large files: Files over 500 MB are better handled with DuckDB or pandas locally. For smaller partitioned datasets, convert each partition individually.

Date/timestamp columns: Parquet stores timestamps in UTC. The CSV will contain ISO 8601 datetime strings.

Null values: Parquet nulls become empty cells in CSV.

Frequently Asked Questions

Can I open a Parquet file in Excel without converting? Not directly. Excel has no native Parquet support. You need to convert to CSV first, or use Power Query with a third-party connector.

How large a Parquet file can I convert online? Up to 500 MB. For larger files, use DuckDB or pandas locally — both handle multi-GB Parquet files with ease.

Will column names and data types be preserved? Column names are preserved as CSV headers. Data types are converted to text — numbers, dates, and booleans become strings.

Can I convert a partitioned Parquet dataset? The converter handles single Parquet files. For partitioned datasets (folders of .parquet files), combine them first using pandas read_parquet() with a directory path.

Is the conversion free? 100% free. No sign-up, no rate limits, no watermarks.