Ward Clustering

usarrests.csv

"Murder","Assault","UrbanPop","Rape"
Alabama,13.2,236,58,21.2
Alaska,10,263,48,44.5
Arizona,8.1,294,80,31
Arkansas,8.8,190,50,19.5
California,9,276,91,40.6
Colorado,7.9,204,78,38.7
Connecticut,3.3,110,77,11.1
Delaware,5.9,238,72,15.8
Florida,15.4,335,80,31.9
Georgia,17.4,211,60,25.8
Hawaii,5.3,46,83,20.2
Idaho,2.6,120,54,14.2
Illinois,10.4,249,83,24
Indiana,7.2,113,65,21
Iowa,2.2,56,57,11.3
Kansas,6,115,66,18
Kentucky,9.7,109,52,16.3
Louisiana,15.4,249,66,22.2
Maine,2.1,83,51,7.8
Maryland,11.3,300,67,27.8
Massachusetts,4.4,149,85,16.3
Michigan,12.1,255,74,35.1
Minnesota,2.7,72,66,14.9
Mississippi,16.1,259,44,17.1
Missouri,9,178,70,28.2
Montana,6,109,53,16.4
Nebraska,4.3,102,62,16.5
Nevada,12.2,252,81,46
New Hampshire,2.1,57,56,9.5
New Jersey,7.4,159,89,18.8
New Mexico,11.4,285,70,32.1
New York,11.1,254,86,26.1
North Carolina,13,337,45,16.1
North Dakota,0.8,45,44,7.3
Ohio,7.3,120,75,21.4
Oklahoma,6.6,151,68,20
Oregon,4.9,159,67,29.3
Pennsylvania,6.3,106,72,14.9
Rhode Island,3.4,174,87,8.3
South Carolina,14.4,279,48,22.5
South Dakota,3.8,86,45,12.8
Tennessee,13.2,188,59,26.9
Texas,12.7,201,80,25.5
Utah,3.2,120,80,22.9
Vermont,2.2,48,32,11.2
Virginia,8.5,156,63,20.7
Washington,4,145,73,26.2
West Virginia,5.7,81,39,9.3
Wisconsin,2.6,53,66,10.8
Wyoming,6.8,161,60,15.6

usarrests.py

import numpy as np
from sklearn import cluster

def hclust(n_clusters, arrests, states):
    ward = cluster.Ward(n_clusters = n_clusters)
    pred =  ward.fit_predict(arrests)
    for i in range(0, len(arrests)):
        print states[i], pred[i]

arrests = np.genfromtxt(fname = "usarrests.csv",
                        delimiter = ",",
                        skip_header = 1,
                        usecols = (1, 2, 3, 4))

states =  np.genfromtxt(fname = "usarrests.csv",
                        dtype = str,
                        delimiter = ",",
                        skip_header = 1,
                        usecols = (0))

for i in range(2, 5):
    print "----------n_clusters=%d-----------", i
    hclust(i, arrests, states)