Plotly library of Python can be very useful for data visualization and understanding the data simply and easily.
plotly.figure_factory.create_dendrogram
A dendrogram is a diagram representing a tree. The figure factory called create_dendrogram performs hierarchical clustering on data and represents the resulting tree. Values on the tree depth axis correspond to distances between clusters.
Syntax: plotly.figure_factory.create_dendrogram(X, orientation=’bottom’, labels=None, colorscale=None, distfun=None, linkagefun=<function <lambda>>, hovertext=None, color_threshold=None)
Parameter:
X ((ndarray)) – it describes the matrix of observations as array of arrays
orientation ((str)) – in this we use ‘top’, ‘right’, ‘bottom’, or ‘left’
labels ((list)) – it describes the list of axis category labels(observation labels)
colorscale ((list)) – it describes the optional colorscale for dendrogram tree
distfun ((function)) – it describes the function to compute the pairwise distance from the observations
linkagefun ((function)) – it describes the function to compute the linkage matrix from the pairwise distances
hovertext ((list[list])) – it describes the list of hovertext for constituent traces of dendrogram clusters
color_threshold ((double)) – it describes the value at which the separation of clusters will be made
Example 1: Simple bottom oriented dendrogram
Python3
from plotly.figure_factory import create_dendrogram import numpy as np X = np.random.rand( 10 , 10 ) fig = create_dendrogram(X) fig.show() |
Output:
Example 2: Dendrogram to put on the left of the heatmap
Python3
from plotly.figure_factory import create_dendrogram import numpy as np X = np.random.rand( 5 , 5 ) names = [ 'Jack' , 'Oxana' , 'John' , 'Chelsea' , 'Mark' ] dendro = create_dendrogram(X, orientation = 'right' , labels = names) dendro.update_layout({ 'width' : 700 , 'height' : 500 }) dendro.show() |
Output: