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68 lines
1.8 KiB
Python
68 lines
1.8 KiB
Python
"""
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An implementation of interquartile range (IQR) which is a measure of statistical
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dispersion, which is the spread of the data.
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The function takes the list of numeric values as input and returns the IQR.
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Script inspired by this Wikipedia article:
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https://en.wikipedia.org/wiki/Interquartile_range
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"""
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from __future__ import annotations
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def find_median(nums: list[int | float]) -> float:
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"""
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This is the implementation of the median.
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:param nums: The list of numeric nums
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:return: Median of the list
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>>> find_median(nums=([1, 2, 2, 3, 4]))
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2
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>>> find_median(nums=([1, 2, 2, 3, 4, 4]))
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2.5
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>>> find_median(nums=([-1, 2, 0, 3, 4, -4]))
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1.5
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>>> find_median(nums=([1.1, 2.2, 2, 3.3, 4.4, 4]))
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2.65
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"""
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div, mod = divmod(len(nums), 2)
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if mod:
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return nums[div]
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return (nums[div] + nums[(div) - 1]) / 2
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def interquartile_range(nums: list[int | float]) -> float:
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"""
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Return the interquartile range for a list of numeric values.
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:param nums: The list of numeric values.
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:return: interquartile range
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>>> interquartile_range(nums=[4, 1, 2, 3, 2])
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2.0
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>>> interquartile_range(nums = [-2, -7, -10, 9, 8, 4, -67, 45])
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17.0
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>>> interquartile_range(nums = [-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1])
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17.2
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>>> interquartile_range(nums = [0, 0, 0, 0, 0])
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0.0
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>>> interquartile_range(nums=[])
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Traceback (most recent call last):
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...
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ValueError: The list is empty. Provide a non-empty list.
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"""
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if not nums:
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raise ValueError("The list is empty. Provide a non-empty list.")
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nums.sort()
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length = len(nums)
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div, mod = divmod(length, 2)
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q1 = find_median(nums[:div])
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half_length = sum((div, mod))
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q3 = find_median(nums[half_length:length])
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return q3 - q1
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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