  # Python Statistics | median_low () The statistics module in Python allows you to use three options for working with median / average elements in a dataset, namely ` median (), median_low () and median_high () ` .

Low Median is always a member of the dataset. If the number of data points is odd, the average is returned. When it is even, the lower of the two means is returned. Let`s see how `median_low() ` works.

` Syntax: ` median_low ( [data-set] )

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

` Returntype: ` Returns the low median of numeric data. Low median is a member of actual data-set.

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

Code # 1: Operation

 ` # Python code for demonstration ` ` # works with median_low () `   ` # import statistics module ` ` import ` ` statistics `   ` # simple list of a set of integers ` ` set1 ` ` = ` ` [` ` 1 ` `, ` ` 3 ` `, ` ` 3 ` `, ` ` 4 ` `, ` ` 5 ` `, ` ` 7 ` `] ` ` `  ` # Note: low median will always be ` ` # dataset member. `   ` # Display the low median of the dataset ` ` print ` ` (` ` "Low median of the data-set is% s" `  `% ` ` (statistics.median_low (set1))) `

Output:

` Low median of the data-set is 3 `

Code # 2: Working with median_low () and median to differentiate between them.

Output:

` Median of the set is 3.5 Low Median of the set is 3 `
Code # 3: How median_low () works with different data ranges

 ` # Python code for demonstration ` ` # works with median_low () `   ` # import statistics module ` ` import ` ` statistics `   ` # simple list of a set of integers ` ` set1 = [ 1 , 3 , 3 , 4 , 5 , 7 ] ``     # Print dataset median   # Average may or may not # are in the dataset print ( "Median of the set is% s"   % (statistics.median (set1)))    # Print the low median of the dataset print ( "Low Median of the set is% s"   % (statistics.median_low (set1))) `
 ` # Python code for demonstration ` ` # works with median_low () `   ` # import statistics module ` ` from ` ` statistics ` ` import ` ` median_low `   ` # Import fraction unit as fr ` ` from ` ` fractions ` ` import ` ` Fraction as fr ` ` `  ` # tuple of positive integers ` ` data1 ` ` = ` ` (` ` 2 ` `, ` ` 3 ` `, ` ` 4 ` `, 5 , 7 , 9 , 11 ) ``   # float tuple data2 = ( 2.4 , 5.1 , 6.7 , 8.9 )   # tuple and from a set of fractional numbers data3 = ( fr ( 1 , 2 ), fr ( 44 , 12 ), fr ( 10 , 3 ), fr ( 2 , 3 ))   # a tuple of negative integers data4 = ( - 5 , - 1 , - 12 , - 19 , - 3 )   # a tuple from a set of positive ones # and negative integers data5 = ( - 1 , - 2 , - 3 , - 4 , 4 , 3 , 2 , 1 )   # Print the low_median () of the given datasets print ( "Low Median of data-set 1 is% s" % (median_low (data1))) print ( "Low Median of data-set 2 is% s" % (median_low (data2))) print ( " Low Median of data-set 3 is% s " % (median_low (data3))) print ( "Low Median of data-set 4 is% s" % (median_low (data4))) print ( "Low Median of data-set 5 is% s" % ( median_low (data5))) `

Output:

` Low Median of data-set 1 is 5 Low Median of data-set 2 is 5.1 Low Median of data-set 3 is 2/3 Low Median of data-set 4 is -5 Low Median of data-set 5 is -1 `

Code # 4: Increased statistical error

` `

` # Code Python for demonstration # StatisticsError of median_low ()   # module import statistics from statistics import median_low   # create an empty set data empty = []   # will raise StatisticsError print (median_low (empty)) `

` `

Output:

``` Traceback (most recent call last): File "/home/5f3e758236f872d014f9d741743c30a4.py", line 10, in print (median_low (empty)) File "/usr/lib/python3.5/statistics.py", line 376, in median_low raise StatisticsError ("no median for empty data") statistics.StatisticsError: no median for empty data    Applications:    media n_low ()  is used when the data is discrete and would prefer the median to be an actual point in the data rather than extrapolated.

```