hclust.js  Agglomerative hierarchical clustering for Node JS
Description
Agglomerative hierarchical clustering for Node JS (no dependencies).
Parameters
Method can be called by hclust(arrays, distanceType = 'euclidean', linkageType = 'average', na = 'pairwise', arrayMin, arrayMax)
, where

arrays
 list of arrays to calculate clusters 
distanceType
 distance measures euclidean (default)  Eucledian distance, usual distance between the two vectors
 maximum  maximum distance between two components of x and y
 canberra  sum(x_i  y_i / x_i + y_i)
 manhattan  absolute distance between the two vectors
 percent  percent of similarity between vectors, based on possible maximum difference between vectors
 cosine  cosine similarity
 angular  angular similarity
 pearson  Pearson correlation based distance
 spearman  Spearman correlation based distance

linkageType
 linkage method single  Method of single linkage or nearest neighbour. Proximity between two clusters is the proximity between their two closest objects.
 complete  Method of complete linkage or farthest neighbour. Proximity between two clusters is the proximity between their two most distant objects.
 average (default)  Simple average, or method of equilibrious betweengroup average linkage (WPGMA) is the modified previous. Proximity between two clusters is the arithmetic mean of all the proximities between the objects of one, on one side, and the objects of the other, on the other side; while the subclusters of which each of these two clusters were merged recently have equalized influence on that proximity – even if the subclusters differed in the number of objects.

na
 handling missing data (they must be null) pairwise (default)  pairwise deletion of missing values

arrayMin
,arrayMax
 range or your variable for calculation of percent difference, otherwise their values will be found in data
Installation
npm install hclust save
Usage
const hclust = let arrays = 5214162 1535561 6277567 1234667let clusters = console
Expected outcome:
[ { "elements": [ [ [ 0 ], [ 1 ] ], [ [ 2 ], [ 3 ] ] ], "distance": 8.509116724833937 }, { "elements": [ [ 2 ], [ 3 ] ], "distance": 7.14142842854285 }, { "elements": [ [ 0 ], [ 1 ] ], "distance": 6.855654600401044 } ]
Alternatives
hcluster.js  Agglomerative Hierarchical Clustering in JavaScript. (that plays nice with d3.js).
mlhclust  Hierarchical clustering algorithms in JavaScript (includes divisive analysis).
License
MIT