dataframe

A fast, safe, and intuitive DataFrame library for Haskell.

dataframe brings the power of type-safe, functional data manipulation to your analytics workflow. Built on Haskell’s strong type system, it catches errors at compile time while delivering the performance and expressiveness you need for real-world data analysis.

Why use this DataFrame library?

Type Safety Meets Data Analysis

• Catch bugs before runtime: Statically typed expressions makes code easier to reason about and catches many bugs at compile time—before your code ever runs.

• Expressive and composable: Encourages concise, declarative, and composable data pipelines that read like the logic you’re thinking.

• Performance without compromise: Delivers high performance thanks to Haskell’s optimizing compiler and efficient memory model.

Designed for Productivity

• Interactive-first design: Expressive syntax, helpful error messages, and sensible defaults make exploration a joy.

• Works everywhere: Works seamlessly in both command-line and notebook environments—great for exploration and scripting alike.

• Familiar operations: If you’ve used pandas, dplyr, or polars, you’ll feel right at home.

Who is this for?

• Data scientists and analysts who want type safety with minimal cognitive/code overhead.

• Haskell developers building data/machine learning pipelines or analytics applications

Tutorials

Learn by doing—step-by-step lessons to get you started.

• Quick Start
• DataFrame (Haskell) — Comprehensive Tutorial & Cookbook
• A primer on Exploratory Data Analysis
• Introduction to probability and data

How-to Guides

Practical guides for accomplishing specific tasks.

• Cookbook

Explanation

Understand the concepts and design decisions.

• Design document - Dataframes in Haskell
• Haskell for Data Analysis
• Coming from Other DataFrame Implementations

Reference

The API is documented in Hackage.