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62 lines
1.4 KiB
Python
62 lines
1.4 KiB
Python
"""
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This is the implementation of inter_quartile range (IQR).
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function takes the list of numeric values as input
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and return the IQR as output.
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Script inspired from its corresponding Wikipedia article
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https://en.wikipedia.org/wiki/Interquartile_range
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"""
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import numpy as np
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def find_median(x: np.array) -> float:
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"""
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This is the implementation of median.
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:param x: The list of numeric values
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:return: Median of the list
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>>> find_median(x=np.array([1,2,2,3,4]))
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2
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>>> find_median(np.array([1,2,2,3,4,4]))
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2.5
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"""
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length = len(x)
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if length % 2:
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return x[length // 2]
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return float((x[length // 2] + x[(length // 2) - 1]) / 2)
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def inter_quartile_range(x: np.array) -> float:
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"""
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This is the implementation of inter_quartile
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range for a list of numeric.
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:param x: The list of data point
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:return: Inter_quartile range
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>>> inter_quartile_range(x=np.array([4,1,2,3,2]))
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2.0
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>>> inter_quartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
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18.0
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"""
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length = len(x)
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if length == 0:
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raise ValueError
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x.sort()
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q1 = find_median(x[0 : length // 2])
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if length % 2:
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q3 = find_median(x[(length // 2) + 1 : length])
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else:
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q3 = find_median(x[length // 2 : 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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