Skip to content

Latest commit

 

History

History
29 lines (19 loc) · 2.21 KB

README.md

File metadata and controls

29 lines (19 loc) · 2.21 KB
Raw

MultiCat

About

MultiCat is an interactive visualisation technique for analysing multidimensional categorical data. Our prototype has been implemented in Svelte and can handle up to 20 nominal and ordinal variables. The starting point for this project was a template created by Connor Rothschild for his newline course, Better Data Visualizations with Svelte.

Demo

A demo instance of the prototype, featuring the Titanic data, is available at https://dgt12.github.io/multicat/.

The MultiCat interface, including a spreadsheet view on the left and a sidebar on the right

Local Deployment

You can load your own categorical data into MultiCat by following these instructions:

  1. Install the following development tools on your machine: Node.js, Visual Studio Code and Python, including the Pandas library.
  2. Download or clone the entire multicat GitHub repository.
  3. Prepare a CSV file of the data you wish to analyse that contains only nominal and/or ordinal variables (one row per data item, one column per variable). Save this in the multicat/src/data folder.
  4. Open the Python script convert_to_js.py in the same data folder. Update the filename on line 9 to match the name of your CSV file, minus the .csv file extension.
  5. Run convert_to_js.py. This will create a file in the data folder with the same name but with a .js extension. This is the format that MultiCat accepts as input.
  6. Open the entire multicat folder in Visual Studio Code. Update line 11 of App.svelte to reference your new .js file (import data from "$data/<filename>.js";).
  7. Open a terminal within Visual Studio Code and enter the command npm run dev.
  8. Open the localhost link in Google Chrome.
  9. Start exploring the data!

Contact

If you have any questions, feel free to contact David Trye.