A fast, safe, and intuitive DataFrame library.
- Encourages concise, declarative, and composable data pipelines.
- Static typing makes code easier to reason about and catches many bugs at compile time—before your code ever runs.
- Delivers high performance thanks to Haskell’s optimizing compiler and efficient memory model.
- Designed for interactivity: expressive syntax, helpful error messages, and sensible defaults.
- Works seamlessly in both command-line and notebook environments—great for exploration and scripting alike.
- Type-safe column operations with compile-time guarantees
- Familiar, approachable API designed to feel easy coming from other languages.
- Interactive REPL for data exploration and plotting.
Browse through some examples in binder or in our playground.
See the Quick Start guide for setup and installation instructions.
dataframe> df = D.fromNamedColumns [("product_id", D.fromList [1,1,2,2,3,3]), ("sales", D.fromList [100,120,50,20,40,30])]
dataframe> df
------------------
product_id | sales
-----------|------
Int | Int
-----------|------
1 | 100
1 | 120
2 | 50
2 | 20
3 | 40
3 | 30
dataframe> :declareColumns df
"product_id :: Expr Int"
"sales :: Expr Int"
dataframe> df |> D.groupBy [F.name product_id] |> D.aggregate [F.sum sales `as` "total_sales"]
------------------------
product_id | total_sales
-----------|------------
Int | Int
-----------|------------
1 | 220
2 | 70
3 | 70 - 📚 User guide: https://dataframe.readthedocs.io/en/latest/
- 📖 API reference: https://hackage.haskell.org/package/dataframe/docs/DataFrame.html