Python统计模块中的 median_grouped()函数

谈到统计函数，数据集的中位数是稳健集中趋势的度量，它受数据中异常值的影响较小。如前所述，未分组数据集的中位数使用median() 、 median_high() 、 median_low()函数。
Python还提供了计算分组和连续数据函数的中位数的选项，这是这种强大且方便的语言的最佳部分。统计模块下的median_grouped()函数，有助于从一组连续数据中计算中值。
假设数据被分组为宽度间隔的间隔。数组中的每个数据点都是包含真值的区间的中点。中值是通过在中值区间（包含中值的区间）内插值计算的，假设该区间内的真实值均匀分布：

median = L + interval * (N / 2 - CF) / FL = lower limit of the median interval
N = total number of data points
CF = number of data points below the median interval
F = number of data points in the median interval

Syntax : median_grouped( [data-set], interval)
Parameters : 
[data-set] : List or tuple or an iterable with a set of numeric values. 
interval (1 by default) : Determines the width of grouped data and changing. It will also change the interpolation of calculated median.
Returntype : Return the median of grouped continuous data, calculated as 50^th perecentile.
Exceptions : StatisticsError is raised when iterable passed is empty or when list is null. 
 

代码#1：

Python3

# Python3 code to demonstrate median_grouped()
 
# importing median_grouped from
# the statistics module
from statistics import median_grouped
 
# creating an simple data-set
data1 = [15, 20, 25, 30, 35]
 
# printing median_grouped for the set
print("Grouped Median of the median is %s"
                %(median_grouped(data1)))

输出 ：

Grouped Median of the median is 25.0

代码 #2 ：对一系列不同数据进行中位数分组的工作

Python3

# Python code to demonstrate the
# working of median_grouped()
 
# importing statistics module
from statistics import median_grouped
 
# tuple of a set of positive integers
set1 = [2, 5, 3, 4, 8, 9]
 
# tuple of a set of negative integers
set2 = [-6, -2, -9, -12]
 
# tuple of a set of positive
# and negative integers
set3 = [2, 4, 8, 9, -2, -3, -5, -6]
 
# Printing grouped median for
# the given set of data
print("Grouped Median of set 1 is % s" % (median_grouped(set1)))
print("Grouped Median of set 2 is % s" % (median_grouped(set2)))
print("Grouped Median of set 3 is % s" % (median_grouped(set3)))

输出 ：

Grouped Median of set 1 is 4.5
Grouped Median of set 2 is -6.5
Grouped Median of set 3 is 1.5

代码#3：区间工作

Python3

# Python code to demonstrate the working of
# interval in median_grouped() function
 
# importing statistics module
from statistics import median_grouped
 
# creating a tuple of simple data
set1 = (10, 12, 13, 12, 13, 15)
 
# Printing median_grouped()
# keeping default interval at 1
print("Grouped Median for Interval set as "\
      "(default) 1 is % s" %(median_grouped(set1)))
 
# For interval value of 2
print("Grouped Median for Interval set as "\
      "2 is % s" %(median_grouped(set1, interval = 2)))
 
# Now for interval value of 5
print("Grouped Median for Interval set as "\
      "5 is % s" %(median_grouped(set1, interval = 5)))

输出 ：

Grouped Median for Interval set as (default) 1 is 12.5
Grouped Median for Interval set as 2 is 12.0
Grouped Median for Interval set as 5 is 10.5
Grouped Median for Interval set as 10 is 8.0

注意：观察一个模式，随着区间值的增加，中值减小。代码 #4：展示 StatisticsError

Python3

# Python code to demonstrate StatisticsError
 
# importing the statistics module
import statistics
 
# creating an empty dataset
list1 = []
 
# Will raise StatisticsError
print(statistics.median_grouped(list1))

输出 ：

Traceback (most recent call last):
  File "/home/0990a4a3f5206c7cd12a596cf82a1587.py", line 10, in 
    print(statistics.median_grouped(list1))
  File "/usr/lib/python3.5/statistics.py", line 431, in median_grouped
    raise StatisticsError("no median for empty data")
statistics.StatisticsError: no median for empty data

应用：
分组中位数与中位数具有所有相同的应用。它通常用于涉及大量数据的计算，例如银行和金融。它是统计的重要组成部分，是数据计算中最强大的工具。