import matplotlib.pyplot as pltimport numpy as npimport csvdef get_a(x): a = 0.0 for i in x: a = a + (i * i) return adef get_b(x): a = 0.0 for i in x: a = a + i return adef get_c(x, y): a = 0.0 for i in range(len(x)): a = a + x[i] * y[i] return adef get_d(y): a = 0.0 for i in y: a = a + i return adef print_list(ilist): '打印数据，没啥用' for i in ilist: print(i, ",", end = "") print("n")plt.figure()#使用plt.figure定义一个图像窗口plt.title('regression')#图像标题plt.xlabel('x')#x轴标题plt.ylabel('y')#y轴标题#数据组listx = [10,8,13,9,11,14,6,4,12,7,5]listy = [8.04,6.95,7.58,8.81,8.33,9.96,7.24,4.26,10.84,4.82,5.68]plt.grid(True)#是否打开网格x = np.linspace(0, 20)#线性回归方程线#等式计算A = get_a(listx)B = get_b(listx)C = get_c(listx, listy)D = get_d(listy)n = len(listx)a = (B*D-C*n)/(dddm)b = (B*C-D*A)/(dddm)plt.scatter(listx, listy, c='b') #描点plt.plot(x, a * x + b, 'b-') #绘制线条#线性回归方程a = "%.4f" % ab = "%.4f" % bprint('y='+a+'*x'+'+'+'('+b+')')plt.pause(10)#画图延时
Python中scatter函数参数及用法详解：
https://www.jb51.net/article/127806.htm
参考原文：https://blog.csdn.net/qq_22510521/article/details/80058148