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Show HN: Fahmatrix – A Lightweight, Pandas-Like DataFrame Library for Java

(github.com)
45 points mousomashakel | 2 comments | 17 May 25 04:39 UTC | HN request time: 0.436s | source

Hey HN, I’ve built Fahmatrix, a minimal, fast Java library for working with tabular data — inspired by Python’s pandas, but designed for performance and simplicity on the JVM.

After working extensively with Python’s data stack, I often ran into limitations related to speed, especially in larger or long-running data workflows. So I built Fahmatrix from scratch to offer similar APIs for manipulating CSVs, performing summary statistics, slicing rows/columns, and more — but all in Java.

Features:

Lightweight and dependency-free

CSV/TSV import with auto-headers

Series/DataFrame structures (like pandas)

describe(), mean(), stdDev(), percentile() and more

Fast parallel operations on numeric columns

Java 17+ support

Docs: https://moustafa-nasr.github.io/Fahmatrix/ GitHub: https://github.com/moustafa-nasr/fahmatrix

I’d love feedback from the Java and data communities — especially if you’ve ever wanted a simple dataframe utility in Java without needing full-scale ML libraries.

Happy to answer any questions!

1. owlstuffing ◴[17 May 25 13:34 UTC] No.44014221[source]▶
Nice!

I’m currently using manifold-sql with duckdb for this.

replies(1): >>44019084 #
2. mousomashakel ◴[18 May 25 04:52 UTC] No.44019084[source]▶
Thanks! That’s a great combo — manifold-sql + duckdb gives you strong typing with powerful SQL under the hood. Fahmatrix is aiming to complement that approach for cases where you want quick, native Java code without SQL — e.g., when building data flows or custom logic inline. Would love to hear if you’ve hit any pain points that a Java-native approach could help with.