A data manipulation library for statistical computing

data-frame

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<br />
<p align="center">
  <a href="https://github.com/lisp-stat/data-frame">
    <img src="https://lisp-stat.dev/images/stats-image.svg" alt="Logo" width="80" height="80">
  </a>

  <h3 align="center">Data Frame</h3>

  <p align="center">
  Data frames for Common Lisp. A two-dimensional array-like structure in which each column contains values of one variable and each row contains one set of values from each column
	<br />
    <a href="https://lisp-stat.dev/docs/manuals/data-frame/"><strong>Explore the docs »</strong></a>
    <br />
    <br />
    <a href="https://github.com/lisp-stat/data-frame/issues">Report Bug</a>
    ·
    <a href="https://github.com/lisp-stat/data-frame/issues">Request Feature</a>
    ·
    <a href="https://lisp-stat.github.io/data-frame/">Reference Manual</a>
  </p>
</p>




<details open="open">
  <summary><h2 style="display: inline-block">Table of Contents</h2></summary>
  <ol>
    <li>
      <a href="#about-the-project">About The Project</a>
      <ul>
        <li><a href="#built-with">Built With</a></li>
      </ul>
    </li>
    <li>
      <a href="#getting-started">Getting Started</a>
      <ul>
        <li><a href="#prerequisites">Prerequisites</a></li>
        <li><a href="#installation">Installation</a></li>
      </ul>
    </li>
    <li><a href="#usage">Usage</a></li>
    <li><a href="#roadmap">Roadmap</a></li>
	<li><a href="#resources">Resources</a></li>
    <li><a href="#contributing">Contributing</a></li>
    <li><a href="#license">License</a></li>
    <li><a href="#contact">Contact</a></li>
  </ol>
</details>




## About the Project

  A data frame is a two dimensional data structure structure whose
  columns may be of differing types.  It is similar to, and may be
  manipulated as, a Common Lisp array. Data frames hold tightly
  coupled collections of variables that all belong to one experiment.

### Built With

* [anaphora](https://github.com/tokenrove/anaphora)
* [alexandria](https://gitlab.common-lisp.net/alexandria/alexandria)
* [array-operations](https://github.com/lisp-stat/array-operations)
* [select](https://github.com/lisp-stat/select)
* [let-plus](https://github.com/sharplispers/let-plus)
* [numerical-utilities](https://github.com/lisp-stat/numerical-utilities)



## Getting Started

To get a local copy up and running follow these steps:

### Prerequisites

An ANSI Common Lisp implementation. Developed and tested with [SBCL](https://www.sbcl.org/).

### Installation

Lisp-Stat is composed of several system that are designed to be
independently useful.  So you can, for example, use `data-frame` for
any project needing to manipulate two dimensional data in a machine
learning or statistical setting.

#### Getting the source

To make the system accessible to [ASDF](https://common-lisp.net/project/asdf/) (a build facility, similar to `make` in the C world), clone the repository in a directory ASDF knows about.  By default the `common-lisp` directory in your home directory is known. Create this if it doesn't already exist and then:

1. Clone the repositories
```sh
cd ~/common-lisp && \
git clone https://github.com/Lisp-Stat/data-frame.git && \
git clone https://github.com/Lisp-Stat/dfio.git
```
2. Reset the ASDF source-registry to find the new system (from the REPL)
   ```lisp
   (asdf:clear-source-registry)
   ```
3. Load the system
   ```lisp
   (asdf:load-system :data-frame)
   ```

If you have installed the slime ASDF extensions, you can invoke this
with a comma (',') from the slime REPL in emacs.

#### Getting dependencies

To get the third party systems that Lisp-Stat depends on you can use a dependency manager, such as [Quicklisp](https://www.quicklisp.org/beta/) or [CLPM](https://www.clpm.dev/) Once installed, get the dependencies with either of:

```lisp
(clpm-client:sync :sources "clpi") ;sources may vary
```

```lisp
(ql:quickload :data-frame)
```

You need do this only once. After obtaining the dependencies, you can
load the system with `ASDF` as described above without first syncing
sources.


## Usage

Create a data frame:

```lisp
(make-df '(:a :b) '(#(1 2 3) #(10 20 30)))

```

For more examples, please refer to the [Documentation](https://lisp-stat.dev/docs/manuals/data-frame).



## Roadmap

See the [open issues](https://github.com/lisp-stat/data-frame/issues) for a list of proposed features (and known issues).

## Resources

This system is part of the [Lisp-Stat](https://lisp-stat.dev/)
project; that should be your first stop for information. Also see the
[resources](https://lisp-stat.dev/resources) and
[community](https://lisp-stat.dev/community) page for more
information.


## Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.  Please see [CONTRIBUTING.md](CONTRIBUTING.md) for details on the code of conduct, and the process for submitting pull requests.


## License

Distributed under the MS-PL License. See [LICENSE](LICENSE) for more information.




## Contact

Project Link: [https://github.com/lisp-stat/data-frame](https://github.com/lisp-stat/data-frame)





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[linkedin-url]: https://www.linkedin.com/company/symbolics/

alexandria

alexandria+

anaphora

array-operations

duologue

let-plus

num-utils

sb-cltl2

select

statistics

A data frame is a common way of storing data for statistical analysis.  Under the hood, a data frame is a vector of equal-length vectors.  Each element of the vector can be thought of as a column and the length of each element of the vector is the number of rows.  As a result, data frames can store different classes of objects in each column (i.e. numeric, character, factor).  In essence, the easiest way to think of a data frame is as an Excel worksheet that contains columns of different types of data but are all of equal length rows.

From a design perspective, Lisp-Stat's data frame is conceptually most similar to the 'tibble' from the tidyverse, but using Common Lisp idioms, style and syntax.


clunit2

data-frame/tests

data-frame

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data-frame/tests

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