聚类-31省市居民家庭消费水平-city

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===分三类的=====

======分四类的========

直接写文件名，那么你的那个txt文件应该是和py文件在同一个路径的

============code===========

import numpy as np
from sklearn.cluster import KMeans
def loadData(filePath):
    fr = open(filePath,‘r+‘)
    lines = fr.readlines()
    retData = []
    retCityName = []
    for line in lines:
        items = line.strip().split(",")
        retCityName.append(items[0])
        retData.append([float(items[i]) for i in range(1,len(items))])
    for i in range(1,len(items)):
        return retData,retCityName
if __name__ == ‘__main__‘:
    data,cityName=loadData(‘city.txt‘)
    km = KMeans(n_clusters=3)
    label = km.fit_predict(data)
    expenses = np.sum(km.cluster_centers_,axis=1)
    #print(expense)
    CityCluster =[[],[],[]]
    for i in range(len(cityName)):
        CityCluster[label[i]].append(cityName[i])
    for i in range(len(CityCluster)):
        print("Expenses:%.2f"%expenses[i])
        print(CityCluster[i])
   

聚类-31省市居民家庭消费水平-city

标签：style   http   mic   readlines   float   center   文件名   ===   learn   

原文地址：https://www.cnblogs.com/wanghui626/p/10361631.html