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lispydata's Introduction

LispyData

Lispydata is an attempt to bring some R like data handling functionality to lisp.

This is the new, shiny October release.

Right now its in pre-alpha and I would not recommend that you use it for the moment. Not that you can easily , as some of the dependencies are not in Quicklisp as yet. I hope to get the package out of Alpha pretty quickly.

In this release, the basic dowloading of files, handling of compression and general infrastructure has been implemented.

There is minimal (ie no) error checking as yet.

LISPYDATA is organized into several packages

FETCH:

The Fetch package provides file downloading capabilities.

(fetch file spec cache)

FIle is a fully specified uri that denotes the protocol and full pathname of the file to download.

Downloaded files are placed in the directory LISPYDATA-HOME using the directory paths found in the URI.

cache (default nil), when t means use the file from cache and don't try to download spec (default nil) is an optional parameter which describes the format of the data in the file

CSV Spec

a CSV spec is currently an plist of the form

'( :skip (colname1 . :type) (Colname2 . :type) ....) where skip means skip existing column headings

 type is one of
  * number  - put into a type t vector, this may be coerced into double-floats
  * date    - a fixnum
  * category - symbol
  * string  - string.

if you don't use a spec for the csv it does its best to guess types. Note: If your file does not have column names, you must use a spec Note: we can't guess categorical variables very well. So we don't try . If a column is categorical you have to use a spec to denote it.

Flat File Spec

a flat file spec is currently a plist of the form similar to a CSV. You MUST use a spec

'( (colname1 . :type) (Colname2 . :type) ....) where skip means skip existing column headings

 type is one of
  * number  - put into a type t vector, this may be coerced into double-floats
  * date    - a fixnum
  * category - symbol
  * string  - string.

.

JSON

a proof of concept for json. We attempt to infer types from the parsed JSON.

Supported protocols

HTTP/HTTPS FTP FILE (local files)

Compression Schemes Supported

  • .gz
  • .zip (partially supported, does not know about members yet)
  • .Z
  • .tar.gz (partially supported, does not know about members yet)
  • .bz2

File types

Currently understands .csv files. Flat fixed record length files supported in the next release NetCDF files in the release after.

EXPLORE:

Descriptive stats & graphics

MUNGE:

(name to be revised, I think) Merging, slicing and dicing

SAVE

dataframe output functions.

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