概念

由一系列高度不等的纵向条形组成，表示数据分布的情况。

例如某年级同学的身高分布情况

注意和条形图的区别

>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

import numpy as npimport matplotlib.pyplot as pltmu = 100  # mean of distributionsigma = 20  # standard deviation of distributionx = mu + sigma * np.random.randn(2000)plt.hist(x, bins=10,color='red',density=True)plt.show()plt.hist(x, bins=50,color='green',density=False)plt.show()

>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

import numpy as np import matplotlib.pyplot as plt x = np.random.randn(1000)+2 y = np.random.randn(1000)+3 plt.hist2d(x, y, bins=40) plt.show()

>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

作业：

1.

随机生成2000个数据，均值为10，方差为3

绘制两个直方图，bins分别为10和50，density分别为true和false

import numpy as npimport matplotlib.pyplot as pltmu = 10sigma = 3x = mu + sigma *np.random.rand((2000))plt.hist(x,bins=50,density=True)plt.show()

 

import numpy as npimport matplotlib.pyplot as pltmu = 10sigma = 3x = mu + sigma *np.random.rand((2000))plt.hist(x,bins=50,density=False)plt.show()

 

2.随机生成x和y，分别2000个, x均值为1，y均值为5

绘制2-D直方图，bins为40个

import numpy as npimport matplotlib.pyplot as pltmu_x = 1mu_y = 5x = mu_x + np.random.rand((2000))y = mu_y + np.random.rand(2000)plt.hist2d(x,y,bins=40)plt.show()