Data frames for Common Lisp

Upstream URL


Tamas Papp <>


Steve Nunez <>



Contributors Forks Stargazers Issues MS-PL License LinkedIn


Data Frame

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
Explore the docs »

Report Bug · Request Feature · Reference Manual

Table of Contents

  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Resources
  6. Contributing
  7. License
  8. Contact

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

Getting Started

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


An ANSI Common Lisp implementation. Developed and tested with SBCL and CCL.

Quicklisp Installation

(ql:quickload :data-frame)

Manual Installation

  1. Clone the repository
    cd ~/quicklisp/local-projects &&
    git clone
  2. Reset the ASDF source-registry to find the new system (from the REPL)
  3. Load the system
    (ql:quickload :data-frame)


Create a data frame:

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

For more examples, please refer to the Documentation.


See the open issues for a list of proposed features (and known issues).


This system is part of the Lisp-Stat project; that should be your first stop for information. Also see the community page for more information.


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 for details on the code of conduct, and the process for submitting pull requests.


Distributed under the MS-PL License. See LICENSE for more information.


Project Link:

Dependencies (7)

  • alexandria
  • anaphora
  • array-operations
  • clunit2
  • let-plus
  • numerical-utilities
  • select

Dependents (2)

  • GitHub
  • Quicklisp
  • Sponsor