matplotlib----初探------5直方图

 

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 np
import matplotlib.pyplot as plt


mu = 100  # mean of distribution
sigma = 20  # standard deviation of distribution
x = 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 np
import matplotlib.pyplot as plt
mu = 10
sigma = 3
x = mu + sigma *np.random.rand((2000))
plt.hist(x,bins=50,density=True)
plt.show()

 

import numpy as np
import matplotlib.pyplot as plt
mu = 10
sigma = 3
x = 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 np
import matplotlib.pyplot as plt
mu_x = 1
mu_y = 5
x = mu_x + np.random.rand((2000))
y = mu_y + np.random.rand(2000)
plt.hist2d(x,y,bins=40)
plt.show()