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""" """
An implementation of interquartile range (IQR) which is a measure of statistical This is the implementation of inter_quartile range (IQR).
dispersion, which is the spread of the data.
The function takes the list of numeric values as input and returns the IQR. function takes the list of numeric values as input
and return the IQR as output.
Script inspired by this Wikipedia article: Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Interquartile_range https://en.wikipedia.org/wiki/Interquartile_range
""" """
from __future__ import annotations from __future__ import annotations
@ -12,47 +12,52 @@ from __future__ import annotations
def find_median(nums: list[int | float]) -> float: def find_median(nums: list[int | float]) -> float:
""" """
This is the implementation of the median. This is the implementation of median.
:param nums: The list of numeric nums :param nums: The list of numeric nums
:return: Median of the list :return: Median of the list
>>> find_median(nums=([1, 2, 2, 3, 4])) >>> find_median(nums=([1,2,2,3,4]))
2 2
>>> find_median(nums=([1, 2, 2, 3, 4, 4]))
>>> find_median(nums=([1,2,2,3,4,4]))
2.5 2.5
>>> find_median(nums=([-1, 2, 0, 3, 4, -4]))
1.5
>>> find_median(nums=([1.1, 2.2, 2, 3.3, 4.4, 4]))
2.65
""" """
div, mod = divmod(len(nums), 2) length = len(nums)
if mod: if length % 2:
return nums[div] return nums[length // 2]
return (nums[div] + nums[(div) - 1]) / 2 return float((nums[length // 2] + nums[(length // 2) - 1]) / 2)
def interquartile_range(nums: list[int | float]) -> float: def interquartile_range(nums: list[int | float]) -> float:
""" """
Return the interquartile range for a list of numeric values. This is the implementation of inter_quartile
:param nums: The list of numeric values. range for a list of numeric.
:return: interquartile range :param nums: The list of data point
:return: Inter_quartile range
>>> interquartile_range(nums=[4, 1, 2, 3, 2]) >>> interquartile_range(nums=[4,1,2,3,2])
2.0 2.0
>>> interquartile_range(nums = [-2, -7, -10, 9, 8, 4, -67, 45])
17.0
>>> interquartile_range(nums = [-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1])
17.2
>>> interquartile_range(nums = [0, 0, 0, 0, 0])
0.0
>>> interquartile_range(nums=[]) >>> interquartile_range(nums=[])
Traceback (most recent call last): Traceback (most recent call last):
... ...
ValueError: The list is empty. Provide a non-empty list. ValueError: The list is empty. Provide a non-empty list.
>>> interquartile_range(nums = [-2,-7,-10,9,8,4, -67, 45])
17.0
>>> interquartile_range(nums = [0,0,0,0,0])
0.0
""" """
if not nums: length = len(nums)
if length == 0:
raise ValueError("The list is empty. Provide a non-empty list.") raise ValueError("The list is empty. Provide a non-empty list.")
nums.sort() nums.sort()
length = len(nums)
div, mod = divmod(length, 2) div, mod = divmod(length, 2)
q1 = find_median(nums[:div]) q1 = find_median(nums[:div])
half_length = sum((div, mod)) half_length = sum((div, mod))