![]() > from statistics import median > from math import isnan > from itertools import filterfalse > data = > sorted ( data ) # This has surprising behavior > median ( data ) # This result is unexpected 16.35 > sum ( map ( isnan, data )) # Number of missing values 2 > clean = list ( filterfalse ( isnan, data )) # Strip NaN values > clean > sorted ( clean ) # Sorting now works as expected > median ( clean ) # This result is now well defined 18.75 Averages and measures of central location ¶ ![]() The NaN values should be stripped before calling these ![]() Median_high(), median_grouped(), mode(), multimode(), and The functions affected are median(), median_low(), Undefined behaviors in the statistics functions that sort data or that count Since NaNs have unusual comparison semantics, they cause surprising or Some datasets use NaN (not a number) values to represent missing data. You may be able to use map() to ensure a consistent result, for If your input data consists of mixed types, Collections with a mix of types are also undefinedĪnd implementation-dependent. Unless explicitly noted, these functions support int,īehaviour with other types (whether in the numeric tower or not) isĬurrently unsupported. Statisticians such as Minitab, SAS and Matlab. Proprietary full-featured statistics packages aimed at professional The module is not intended to be a competitor to third-party libraries such ![]() This module provides functions for calculating mathematical statistics of ![]()
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