median_high() function in Python statistics module
Last Updated :
30 May, 2022
Median is often referred to as the robust measure of the central location and is less affected by the presence of outliers in data. statistics module in Python allows three options to deal with median / middle elements in a data set, which are median(), median_low() and median_high(). The high median is always a member of the data set. When the number of data points is odd, the middle value is returned. When it is even, the larger of the two middle values is returned. Let’s see how median_high() function works.
Syntax : median_high( [data – set] )
Parameters : [data-set] : Takes in a list, or an iterable 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.
Code #1 : Working
Python
import statistics
set1 = [ 1 , 3 , 2 , 8 , 5 , 4 ]
print ("High median of the data - set is % s "
% (statistics.median_high(set1)))
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Output :
High median of the data-set is 4
Code #2 : Working of median_high() and median() to demonstrate the difference between them.
Python3
import statistics
set1 = [ 1 , 3 , 3 , 4 , 5 , 7 ]
print ("Median of the set is % s"
% (statistics.median(set1)))
print ("High Median of the set is % s "
% (statistics.median_high(set1)))
|
Output :
Median of the set is 3.5
High Median of the set is 4
Code #3 : Working of median_high() on a varying range of data-values.
Python3
from statistics import median_high
from fractions import Fraction as fr
data1 = ( 2 , 3 , 4 , 5 , 7 , 9 , 11 )
data2 = ( 2.4 , 5.1 , 6.7 , 8.9 )
data3 = (fr( 1 , 2 ), fr( 44 , 12 ),
fr( 10 , 3 ), fr( 2 , 3 ))
data4 = ( - 5 , - 1 , - 12 , - 19 , - 3 )
data5 = ( - 1 , - 2 , - 3 , - 4 , 4 , 3 , 2 , 1 )
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)))
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Output :
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
Code #4 : Demonstration of StatisticsError
Python3
from statistics import median_high
empty = []
print (median_high(empty))
|
Output :
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
Applications : The high median is used only when the data is discrete and the prefer the median to be an actual median rather than an interpolated set of data.
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