dataframe

A practical DataFrame library for Haskell, focused on type-safe data wrangling and analysis.

dataframe lets you load tabular data and transform it with a functional, composable API. It leans on Haskell’s type system to help you catch common mistakes early (like mixing types or referencing missing columns), while still aiming to stay pleasant to use for everyday 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.

Designed for Productivity

• Interactive-first design: Expressive syntax, helpful error messages, and sensible defaults make safe 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
• Tutorial: Your first analysis with dataframe (Iris)
• Using dataframe in a standalone script
• A primer on Exploratory Data Analysis
• Introduction to probability and data

How-to Guides

Practical guides for accomplishing specific tasks.

• Cookbook
• Coming from Other DataFrame Implementations
• Working with Nullable Columns

Explanation

Understand the concepts and design decisions.

• Design document - Dataframes in Haskell
• Haskell for Data Analysis

Reference

The API is documented in Hackage.