Python统计模块中的 median_high()函数

中位数通常被称为中心位置的稳健度量，受数据中异常值的影响较小。

Python中的统计模块允许三个选项来处理数据集中的中值/中间元素，它们是median(), median_low() and median_high() 。

高中位数始终是数据集的成员。当数据点数为奇数时，返回中间值。如果是偶数，则返回两个中间值中较大的一个。让我们看看median_high()函数是如何工作的。

Syntax : median_high( [data – set] )

Parameters :
[data-set] : Takes in a list, or an interable set of numeric data.

Returntype : Returns the high median of the numeric data (always in actual data-set).

Exceptions : StatisticsError is raised when data-set is empty.

编程需要懂一点英语

代码#1：工作

# Python code to demonstrate working of
# median_high() on a data-set
  
# importing the statistics module
import statistics
  
# simple list of a set of integers
set1 = [1, 3, 2, 8, 5, 4]
  
# Print high median of the data-set
print("High median of the data-set is %s " 
        % (statistics.median_high(set1)))

输出：

High median of the data-set is 4

代码#2：使用 median_high() 和 median() 来展示它们之间的区别。

# Working of median_high() and median() to
# demonstrate the difference between them.
  
# importing the statistics module
import statistics
  
# simple list of a set of integers
set1 = [1, 3, 3, 4, 5, 7]
  
# Print median of the data-set
  
# Median value may or may not
# lie within the data-set
print("Median of the set is %s" 
      % (statistics.median(set1)))
  
# Print high median of the data-set
print("High Median of the set is %s " 
      % (statistics.median_high(set1)))

输出：

Median of the set is 3.5
High Median of the set is 4

代码 #3：在不同范围的数据值上使用 median_high()。

# Python code to demonstrate the
# working of median_high()
  
# importing statistics module
from statistics import median_high
  
# 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))
  
# tuple of a set of negative integers
data4 = (-5, -1, -12, -19, -3)
  
# tuple of set of positive
# and negative integers
data5 = (-1, -2, -3, -4, 4, 3, 2, 1)
  
# Print the high_median() of the given data-sets
print("High Median of data-set 1 is %s" % (median_high(data1)))
print("High Median of data-set 2 is %s" % (median_high(data2)))
print("High Median of data-set 3 is %s" % (median_high(data3)))
print("High Median of data-set 4 is %s" % (median_high(data4)))
print("High Median of data-set 5 is %s" % (median_high(data5)))

输出：

High Median of data-set 1 is 5
High Median of data-set 2 is 6.7
High Median of data-set 3 is 10/3
High Median of data-set 4 is -5
High Median of data-set 5 is 1

代码 #4： StatisticsError 的演示

# Python code to demonstrate
# StatisticsError of median_high()
  
# importing the statistics module
from statistics import median_high
  
# creating an empty data-set
empty = []
  
# will raise StatisticsError
print(median_high(empty))

输出：

Traceback (most recent call last):
  File "/home/fc2eae1616bfaa0987b261d9d40f4602.py", line 10, in 
    print(median_high(empty))
  File "/usr/lib/python3.5/statistics.py", line 398, in median_high
    raise StatisticsError("no median for empty data")
statistics.StatisticsError: no median for empty data

应用：
仅当数据是离散的并且更喜欢将中值作为实际中值而不是插值数据集时才使用高中值。