Profiles Apache Parquet files using pyarrow metadata APIs to extract column statistics, row group distributions, and encoding efficiency metrics without reading full datasets.
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Added June 8, 2026
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---
name: "Parquet Column Statistics Profiler"
slug: "parquet-column-statistics-profiler"
description: "Profiles Apache Parquet files using pyarrow metadata APIs to extract column statistics, row group distributions, and encoding efficiency metrics without reading full datasets."
github_stars: 387
verification: "security_reviewed"
source: "https://github.com/ironSource/parquetjs"
category: "Data Extraction & Transformation"
framework: "ChatGPT Agents"
tool_ecosystem:
github_repo: "ironsource/parquetjs"
github_stars: 387
npm_package: "parquetjs"
npm_weekly_downloads: 170660
---
# Parquet Column Statistics Profiler
Profiles Apache Parquet files using pyarrow metadata APIs to extract column statistics, row group distributions, and encoding efficiency metrics without reading full datasets.
## Installation
Use the upstream install or setup path that matches your environment:
- $ npm install parquetjs
Requirements and caveats from upstream:
- This project requires a major overhaul, as well as handling and sorting through dozens of issues and prs.
- fully asynchronous, pure node.js implementation of the Parquet file format
- To use parquet.js with node.js, install it using npm:
Basic usage or getting-started notes:
- ------------
- --------------------
- Once you have installed the parquet.js library, you can import it as a single
- Source: https://github.com/ironSource/parquetjs
- Extracted from upstream docs: https://raw.githubusercontent.com/ironSource/parquetjs/HEAD/README.md
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/parquet-column-statistics-profiler/)