Git Product home page Git Product logo

marios-mamalis / visualisation-of-mca-results-from-factominer-using-plotly Goto Github PK

View Code? Open in Web Editor NEW
2.0 1.0 0.0 26 KB

A script for automatic visualisation of Multiple Correspondence Analysis (MCA) results from FactoMineR in 3 dimensions using Plotly (exported as html)

License: GNU General Public License v3.0

R 100.00%
data-analysis mca factominer plotly visualisation correspondence-analysis multiple-correspondence-analysis html 3d-scatterplots

visualisation-of-mca-results-from-factominer-using-plotly's Introduction

Visualisation of Multiple Correspondence Analysis (MCA) results from FactoMineR using Plotly

Summary

This is a script for automatic visualisation of MCA results from FactoMineR in 3 dimensions using Plotly (exported as html). It contains a function called plotfun() that transforms the results of FactoMineR's MCA function FactoMineR::MCA() to a structure that can be used by Plotly, and then creates and exports in html format six 3d scatterplots, namely:

  • Contributions of Categories
  • Contributions of Individuals
  • Coordinates of Categories
  • Coordinates of Individuals
  • Cosine Squared of Categories
  • Cosine Squared of Individuals

Usage

The function, in order to work, must be supplied with two arguments:

  1. A list that contains the results of an MCA function of FactoMineR
  2. One of three valid plotting methods of Plotly's 3d scatterplot ("lines", "markers" or "linesmarkers").

ex. plotfun(results.MCA, "lines")

Results

The 3d scatterplots' axes are:

  • x-dimension: The dimension
  • y-dimension: Name of Category or Individual
  • z-dimension: The value of each dimension for either Contributions, Coordinates or Cosine Squared

Example output:

Example Result

visualisation-of-mca-results-from-factominer-using-plotly's People

Contributors

marios-mamalis avatar

Stargazers

 avatar  avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.