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  • 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()

    
    
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  • 原文地址:https://www.cnblogs.com/dushuhubian/p/10299002.html
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