How to Open and View Parquet Files in a Spreadsheet

22 September 2026

Excel cannot open a Parquet file at all, because Parquet is a compressed columnar format rather than text. You do not need Python or pandas to read one. BigXL opens Parquet files directly in a spreadsheet grid for free, reading them where they sit without converting or unpacking them first.

A data engineer sends you a file ending in .parquet. You double-click it, and your computer asks which application to use. Excel does not recognize the format, text editors display binary gibberish, and online converters fail on large file sizes.

Here is why Parquet files are replacing CSVs in modern data stacks, and how to view, search, and edit them in a spreadsheet interface without writing Python scripts.

What is Apache Parquet?

Apache Parquet is an open-source, columnar file format optimized for fast data storage and retrieval. Unlike CSV files, which store data row by row as plain text, Parquet stores data column by column with built-in compression and data typing.

Data teams prefer Parquet for three reasons:

Compact size. Parquet files are typically 70% to 90% smaller than equivalent CSV files due to dictionary encoding and Snappy or ZSTD compression.
Fast column filtering. If a table has 200 columns and you only query customer_id and total_amount, Parquet reads only those two columns from disk instead of reading the whole file.
Strict schema preservation. CSV files treat everything as plain text, causing date corruptions and scientific notation errors. Parquet preserves exact data types (integers, decimals, timestamps, booleans) natively.

Why Excel and Google Sheets cannot open Parquet files natively

Standard spreadsheet software was built around row-oriented file formats. Excel expects plain text CSVs or XML-based .xlsx workbooks.

When you attempt to open a .parquet file:

Excel does not support dragging and dropping .parquet files. While Power Query has limited Parquet connector support in newer Windows builds, it requires configuring database connection strings and cannot load rows past the 1,048,576 row limit.
Google Sheets caps uploads at 10 million cells and has no native importer for binary Parquet files.
Text editors like VS Code or Notepad show garbled binary headers because Parquet is not a plain-text format.

Three ways to view Parquet files

1. Using Python (pandas or PyArrow)

If you are a programmer, loading a Parquet file in Python takes two lines:

import pandas as pd
df = pd.read_parquet('data.parquet')
print(df.head())

While Python works well for data science pipelines, it is inefficient for non-programmers who simply need to filter rows, check column distributions, or export a quick summary table.

2. Using DuckDB command line

DuckDB allows querying Parquet files directly using SQL syntax:

SELECT * FROM 'data.parquet' WHERE status = 'ACTIVE' LIMIT 50;

This is fast and efficient, but requires running terminal commands rather than clicking and scrolling through cells.

3. Using BigXL desktop spreadsheet GUI

If you want a native desktop spreadsheet grid that opens Parquet files like regular spreadsheets, BigXL reads Parquet files natively.

Instant GUI grid. Drag and drop any .parquet file to open it in a clean spreadsheet interface.
No row limit. View datasets containing tens of millions of rows with memory to spare.
Plain English queries. Ask questions about your Parquet data in natural language without writing SQL or Python code.
Convert and export. Filter or edit Parquet records and export the results to CSV, Excel XLSX, or JSON.
100% Local & Private. Everything runs on your machine. Your data is never uploaded to cloud servers or third-party APIs.

Parquet is the standard format for modern analytics. With BigXL, you can inspect and work with Parquet files as easily as a traditional spreadsheet.

Common questions

Can Excel open a Parquet file?

Not directly. Excel has no Parquet reader. You would have to convert the file to CSV or XLSX first, which loses the compression and often will not fit inside the 1,048,576 row limit anyway.

How do I view a Parquet file without writing code?

Open it in BigXL, which reads Parquet natively and shows it as a normal grid you can sort and filter. Reading Parquet is part of the free tier.

Why do data teams send Parquet instead of CSV?

It is far smaller and much faster to read, because it stores each column separately and compresses it. A dataset that is 10 GB as CSV is often under 1 GB as Parquet.