使用R语言进行聚类分析

一、���本数据描述

城镇居民人均消费支出水平包括食品、衣着、居住、生活用品及服务、通信、文教娱乐、医疗保健和其他用品及服务支出这八项指标来描述。表中列出了2016年我国分地区的城镇居民的人均消费支出的原始数据，数据来源于2017年的《中国统计年鉴》，现要求对下面的数据进行聚类分析。

x1:食品烟酒支出，x2:衣着支出，x3:居住支出，x4:生活用品和服务支出，

x5:交通通信支出，x6:教育文化娱乐支出，x7:医疗保健支出，x8:其他用品和服务支出

City,X1,X2,X3,X4,X5,X6,X7,X8

北京,8070.4,2643,12128,2511,5077.9,4054.7,2629.8,1140.6

天津,8679.6,2114,6187.3,1663.8,3991.9,2643.6,2172.2,892.2

河北,4991.6,1614.4,4483.2,1351.1,2664.1,1991.3,1549.9,460.4

山西,3862.8,1603,3633.8,951.6,2401,2439,1651.6,450.1

内蒙古,6445.8,2543.3,4006.1,1565.1,3045.2,2598.9,1840.2,699.9

辽宁,6901.6,2321.3,4632.8,1558.2,3447,3018.5,2313.6,802.8

吉林,4975.7,1819,3612,1107.1,2691,2367.5,2059.2,534.9

黑龙江,5019.3,1804.4,3352.4,1018.9,2462.9,2011.5,2007.5,468.3

上海,10014.8,1834.8,13216,1868.2,4447.5,4533.5,2839.9,1102.1

江苏,7389.2,1809.5,6140.6,1616.2,3952.4,3163.9,1624.5,736.6

浙江,8467.3,1903.9,7385.4,1420.7,5100.9,3452.3,1691.9,645.3

安徽,6381.7,1491,3931.2,1118.4,2748.4,2233.3,1269.3,432.9

福建,8299.6,1443.5,6530.5,1393.4,3205.7,2461.5,1178.5,492.8

江西,5667.5,1472.2,3915.9,1028.6,2310.6,1963.9,887.4,449.6

山东,5929.4,1977.7,4473.1,1576.5,3002.5,2399.3,1610,526.9

河南,5067.7,1746.6,3753.4,1430.2,1993.8,2078.8,1524.5,492.8

湖北,6294.3,1557.4,4176.7,1163.8,2391.9,2228.4,1792,435.6

湖南,6407.7,1666.4,3918.7,1384.1,2837.1,3406.1,1362.6,437.4

广西,5937.2,886.3,3784.3,1032.8,2259.8,2003,1065.9,299.3

海南,7419.7,859.6,3527.7,954,2582.3,1931.3,1399.8,341

重庆,6883.9,1939.2,3801.1,1466,2573.9,2232.4,1700,434.4

四川,7118.4,1767.5,3756.5,1311.1,2697.6,2008.4,1423.4,577.1

贵州,6010.3,1525.4,3793.1,1270.2,2684.4,2493.5,1050.1,374.6

云南,5528.2,1195.5,3814.4,1135.1,2791.2,2217,1526.7,414.3

陕西,5422,1542.2,3681.5,1367.7,2455.7,2474,2016.7,409

甘肃,5777.3,1776.9,3752.6,1329.1,2517.9,2322.1,1583.4,479.9

青海,5975.7,1963.5,3809.4,1322.1,3064.3,2352.9,1750.4,614.9

宁夏,4889.2,1726.7,3770.5,1245.1,3896.5,2415.7,1874,546.6

新疆,6179.4,1966.1,3543.9,1543.8,3074.1,2404.9,1934.8,581.5

广东,9421.6,1583.4,6410.4,1721.9,4198.1,3103.4,1304.5,870.1

西藏,8727.8,1812.5,3614.5,983.0,2198.4,922.5,585.3,596.5

二、读入数据

df