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  • python 正态分布

     

    import numpy as np
    import matplotlib.pyplot as plt
    import pandas as pd
    from scipy.stats import norm
    from scipy.stats import shapiro
    import statistics
    data= pd.read_csv('ethercat3.csv',usecols=['Time'])
    clo_t = data['Time'].tolist()
    stat, p = shapiro(clo_t)
    print('stat=%.3f, p=%.3f \n' % (stat, p))
    if p > 0.05:
        print("Data follows Normal Distribution")
    else:
        print("Data does not follow Normal Distribution")
    [root@centos7 ~]# python3  norm_test.py 
    /usr/local/lib64/python3.6/site-packages/scipy/stats/morestats.py:1681: UserWarning: p-value may not be accurate for N > 5000.
      warnings.warn("p-value may not be accurate for N > 5000.")
    stat=0.636, p=0.000 
    
    Data does not follow Normal Distribution
    import numpy as np
    import matplotlib.pyplot as plt
    import pandas as pd
    from scipy.stats import norm
    from scipy.stats import shapiro
    import statistics
    data= pd.read_csv('ethercat3.csv',usecols=['Time'])
    clo_t = data['Time'].tolist()
    stat, p = shapiro(clo_t[0:4000])
    print('stat=%.3f, p=%.3f \n' % (stat, p))
    if p > 0.05:
        print("Data follows Normal Distribution")
    else:
        print("Data does not follow Normal Distribution")

    import matplotlib.pyplot as plt
    import numpy as np
    import matplotlib

    # 设置matplotlib正常显示中文和负号
    matplotlib.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文
    matplotlib.rcParams['axes.unicode_minus']=False # 正常显示负号
    # 随机生成(10000,)服从正态分布的数据
    data = np.random.randn(10000)
    """
    绘制直方图
    data:必选参数,绘图数据
    bins:直方图的长条形数目,可选项,默认为10
    normed:是否将得到的直方图向量归一化,可选项,默认为0,代表不归一化,显示频数。normed=1,表示归一化,显示频率。
    facecolor:长条形的颜色
    edgecolor:长条形边框的颜色
    alpha:透明度
    """
    plt.hist(data, bins=40, normed=0, facecolor="blue", edgecolor="black", alpha=0.7)
    # 显示横轴标签
    plt.xlabel("区间")
    # 显示纵轴标签
    plt.ylabel("频数/频率")
    # 显示图标题
    plt.title("频数/频率分布直方图")
    plt.show()

    Normality Test with Python in Data Science

    Is my data normal?

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  • 原文地址:https://www.cnblogs.com/dream397/p/15423887.html
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