代码如下:
#-*- encoding:utf-8 -*- import sys reload(sys) sys.setdefaultencoding from sklearn import linear_model import numpy as np import pandas as pd #读取数据并创建数据表,名称为cost_and_click year_population=pd.DataFrame(pd.read_excel('year_population.xls')) X=np.array(year_population['year']) X=X.tolist() #将点击量设为因变量Y Y=np.array(year_population['population']) Y=Y.tolist() #--------------------------------------------------------------- z1 = np.polyfit(X, Y, 4) #多项式拟合 p1 = np.poly1d(z1) print"-"*40 print z1 #多项式系数 print"-"*40 print p1 # 完整的输出 print"☆☆☆☆☆☆☆☆开始预测☆☆☆☆☆☆☆☆☆☆" print p1(2010)
数据如下:
year population 1790 3.9 1800 5.3 1810 7.2 1820 9.6 1830 12.9 1840 17.1 1850 23.2 1860 31.4 1870 38.6 1880 50.2 1890 62.9 1900 76 1910 92 1920 106.5 1930 123.2 1940 131.7 1950 150.7 1960 179.3 1970 204 1980 226.5 1990 251.4 2000 281.4