Cutting Dendrogram/clustering Tree From Scipy At Distance Height

I'm trying to learn how to use dendrograms in Python using SciPy . I want to get clusters and be able to visualize them; I heard hierarchical clustering and dendrograms are the bes

Solution 1:

color_threshold is the method I was looking for. It doesn't really help when the color_palette is too small for the amount of clusters being generated. Migrated the next step to Bigger color-palette in matplotlib for SciPy's dendrogram (Python) if anyone can help.

Solution 2:

For a bigger color palette this should work:

from scipy.cluster import hierarchy as hc
import matplotlib.cm as cm
import matplotlib.colors as col

#get a color spectrum "gist_ncar" from matplotlib cm. #When you have a spectrum it begins with 0 and ends with 1. #make tinier steps if you need more than 10 colors

colors = cm.gist_ncar(np.arange(0, 1, 0.1)) 

colorlst=[]# empty list where you will put your colorsfor i inrange(len(colors)): #get for your color hex instead of rgb
    colorlst.append(col.to_hex(colors[i]))

hc.set_link_color_palette(colorlst) #sets the color to use.

Put all of that infront of your code and it should work