Median is often referred to as the robust measure of 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 low 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 smaller of the two middle values is returned. Let’s see how
Syntax :median_low( [data-set] )
[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 : Working
Low median of the data-set is 3
Code #2 : Working of median_low() and median to distinguish between them.
Median of the set is 3.5 Low Median of the set is 3
Code #3 : Working of median_low() on a varying range of data-set
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 : Raising StatisticsError
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
median_low() is used when the data is discrete and prefer median to be actual point in data rather than an extrapolated one.
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