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Multiple correspondence analysis with pandas

Project Description

mca is a Multiple Correspondence Analysis (MCA) package for python, intended to be used with pandas. MCA is a feature extraction method; essentially PCA for categorical variables. You can use it, for example, to address multicollinearity or the curse of dimensionality with big categorical variables.

Installation

pip install --user mca

Usage

Please refer to the usage notes and this illustrated ipython notebook.

Reference

Michael Greenacre, Jörg Blasius (2006). Multiple Correspondence Analysis and Related Methods, CRC Press. ISBN 1584886285.

History

  • 1.0 (2014-06-24)
    First release. I’m sure it’s an auspicious date somewhere in the world.
  • 1.01 (2015-03-23)
    More documentation, in the form of an ipython notebook. Fixed bug #2 affecting python 2.x
  • 1.02 (2017-07-29)
    Fixed division-by-zero bug (issue #14)
  • 1.03 (2018-01-10)
    Added sparse matrix support

Release History

This version
History Node

1.0.3

History Node

1.0.2

History Node

1.0

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Filename, Size & Hash SHA256 Hash Help File Type Python Version Upload Date
mca-1.0.3.tar.gz
(17.7 kB) Copy SHA256 Hash SHA256
Source None Jan 11, 2018

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