Python中的调和_mean（）-yiteyi-C++库

调和平均数（也称为逆平均数）是几种平均数之一，尤其是毕达哥拉斯平均数之一。通常用于需要平均速率的情况。调和平均值也是一组给定观测值的倒数算术平均值的倒数。

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例如，1、4和4的调和平均值可以计算为：

调和平均值可以通过使用 调和平均 来自统计模块的函数。

语法： 调和平均值（[数据集]） 参数： [数据集] ：它是实数的列表、元组或迭代器。 返回类型： 返回给定数据集的调和平均值。 错误和例外： 统计误差 当传递空数据集时，或者如果数据集包含负值。 打字错误 用于非数值类型值的数据集。

注：调和平均值仅使用列表、集合或任何序列中的正值计算。 代码#1：

Python3

                         # Python3 code to demonstrate the                       
                         # working of harmonic_mean() function                       
           
                         # Import statistics module                       
                         import                                     statistics                       
           
                         # list of positive real valued numbers                       
                         data                                     =                                     [                                     1                                     ,                                     3                                     ,                                     5                                     ,                                     7                                     ,                                     9                                     ]                       
           
                         # using harmonic mean function to calculate                       
                         # the harmonic mean of the given data-set                       
                         print                                     (                                     "Harmonic Mean is % s "                                     %                                     (statistics.harmonic_mean(data)))                       

输出：

Harmonic Mean is 2.797513321492007

代码#2：

Python3

                         # Python3 program to demonstrate harmonic_mean()                       
                         # function from the statistics module                       
           
                         # Importing the statistics module                       
                         from                                     statistics                                     import                                     harmonic_mean                       
           
                         # Importing fractions module as fr                       
                         from                                     fractions                                     import                                     Fraction as fr                       
           
                         # tuple of positive integer numbers                       
                         data1                                     =                                     (                                     2                                     ,                                     3                                     ,                                     4                                     ,                                     5                                     ,                                     7                                     ,                                     9                                     ,                                     11                                     )                       
           
                         # tuple of a set of floating-point values                       
                         data2                                     =                                     (                                     2.4                                     ,                                     5.1                                     ,                                     6.7                                     ,                                     8.9                                     )                       
           
                         # tuple of a set of fractional numbers                       
                         data3                                     =                                     (fr(                                     1                                     ,                                     2                                     ), fr(                                     44                                     ,                                     12                                     ), fr(                                     10                                     ,                                     3                                     ), fr(                                     2                                     ,                                     3                                     ))                       
           
                         # dictionary of a set of values                       
                         # Only the keys are taken in                       
                         # consideration by harmonic_mean()                       
                         data4                                     =                                     {                                     1                                     :                                     "one"                                     ,                                     2                                     :                                     "two"                                     ,                                     3                                     :                                     "three"                                     }                       
           
                         # Printing the harmonic mean of above datasets                       
                         print                                     (                                     "Harmonic Mean of data set 1 is % s"                       
                                                 %                                     (harmonic_mean(data1)))                       
                                   
                         print                                     (                                     "Harmonic Mean of data set 2 is % s"                       
                                                 %                                     (harmonic_mean(data2)))                       
           
                         print                                     (                                     "Harmonic Mean of data set 3 is % s"                       
                                                 %                                     (harmonic_mean(data3)))                       
                                   
                         print                                     (                                     "Harmonic Mean of data set 4 is % s"                       
                                                 %                                     (harmonic_mean(data4)))                       

输出：

Harmonic Mean of data set 1 is 4.299197943900386Harmonic Mean of data set 2 is 4.574783168721765Harmonic Mean of data set 4 is 55/56Harmonic Mean of data set 5 is 1.6363636363636365

代码#3： 统计误差的证明

Python3

                         # Python code to demonstrate StatisticsError                       
                         # while using harmonic_mean()                       
           
                         # importing statistics module                       
                         import                                     statistics                       
           
                         # data-set of numbers containing                       
                         # a negative number                       
                         dat1                                     =                                     [                                     1                                     ,                                     -                                     1                                     ]                       
           
                         # Statistics Error is raised when the                       
                         # data-set passed as parameter is                       
                         # empty or contain a negative value                       
                         print                                     (statistics.harmonic_mean(dat1))                       

输出：

Traceback (most recent call last):  File "C:/Users/Souveek/PycharmProjects/Test.py", line 12, in     print(statistics.harmonic_mean((1, -1)))  File "C:UsersSouveekAppDataLocalProgramsPythonPython36-32Libstatistics.py", line 356, in harmonic_mean    T, total, count = _sum(1/x for x in _fail_neg(data, errmsg))  File "C:UsersSouveekAppDataLocalProgramsPythonPython36-32Libstatistics.py", line 148, in _sum    for n, d in map(_exact_ratio, values):  File "C:UsersSouveekAppDataLocalProgramsPythonPython36-32Libstatistics.py", line 356, in     T, total, count = _sum(1/x for x in _fail_neg(data, errmsg))  File "C:UsersSouveekAppDataLocalProgramsPythonPython36-32Libstatistics.py", line 285, in _fail_neg    raise StatisticsError(errmsg)statistics.StatisticsError: harmonic mean does not support negative values

注：以下代码可能不会在在线IDE上运行，因为在Python3中新引入了harmonic_mean（）函数。6. 应用： 调和平均是金融学中的许多重要工具之一。加权调和平均是对倍数（如市盈率（P/E））进行平均的较好方法，其中价格是分子。在算术平均值高估所需结果的地方，它也用于计算。

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