dataframe-0.4.0.8: README.md

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  <a href="https://dataframe.readthedocs.io/en/latest/">User guide</a>
  |
  <a href="https://discord.gg/8u8SCWfrNC">Discord</a>
</p>

# DataFrame

A fast, safe, and intuitive DataFrame library.

## Why use this 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.

## Features
- 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.

## Quick start
Browse through some examples in [binder](https://mybinder.org/v2/gh/mchav/ihaskell-dataframe/HEAD) or in our [playground](https://ulwazi-exh9dbh2exbzgbc9.westus-01.azurewebsites.net/lab).

## Install
See the [Quick Start](https://dataframe.readthedocs.io/en/latest/quick_start.html) guide for setup and installation instructions.

## Example

```haskell
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         
```

## Documentation
* 📚 User guide: https://dataframe.readthedocs.io/en/latest/
* 📖 API reference: https://hackage.haskell.org/package/dataframe/docs/DataFrame.html