BinGuru is a Javascript package with an API to several established data binning / data classification methods, often used for visualizing data on choropleth maps. It also includes an implementation of a new, consensus binning method, 'Resiliency'.
npm install binguruBinGuru is a Javascript package with an API to several established data binning / data classification methods, often used for visualizing data on choropleth maps. It also includes an implementation of a new, consensus binning method, 'Resiliency'.
npm install binguru``ts
import { BinGuru } from "binguru";
let rawData = [1, 45, 65, 23, 65, 87, 54, 45, 31, 21, 12, 12, 98, 56, 76, null, null, "nan", undefined, "", "null"]; // Input array of numbers, strings, nulls, nans, undefineds.
let binCount = 5; // Desired number of bins (inconsequential for certain binning methods, e.g., boxPlot).
let binExtent = 10; // Desired bin interval (only applicable for certain binning methods, e.g., definedInterval).
let precision = 2; // Desired rounding off precision.
let binGuruObj = new BinGuru(rawData=rawData, binCount=binCount, binExtent=binExtent, precision=precision); // Initialize an instance of BinGuru
let bins = binGuruObj.fisherJenks(); // Call an endpoint, e.g., fisherJenks() to bin using the FisherJenks / Natural Breaks binning method first.
console.log(bins);
`
- Build the package:
- Set version:
- For stable release:
- For specific prerelease:
- For auto-increment prerelease: (replace alpha with another preid, if any)
- Dry run: npm publish --dry-run
- Publish to the registry:
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BinGuru was created by
Arpit Narechania, Alex Endert, and Clio Andris of the Georgia Tech Visualization Lab. We thank the members of the Georgia Tech Visualization Lab for their support and constructive feedback.
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bibTeX
@InProceedings{narechania2023resiliency,
author = {Narechania, Arpit and Endert, Alex and Andris, Clio},
title = {{Resiliency: A Consensus Data Binning Method}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {55:1--55:7},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
year = {2023},
volume = {277},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
doi = {10.4230/LIPIcs.GIScience.2023.55}
}
``