maths/interquartile_range.py

@@ -1,10 +1,10 @@
 """
-An implementation of interquartile range (IQR) which is a measure of statistical
-dispersion, which is the spread of the data.
+This is the implementation of inter_quartile range (IQR).
 
-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
 """
 from __future__ import annotations
@@ -12,47 +12,52 @@ from __future__ import annotations
 
 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
     :return: Median of the list
-    >>> find_median(nums=([1, 2, 2, 3, 4]))
+    >>> find_median(nums=([1,2,2,3,4]))
     2
-    >>> find_median(nums=([1, 2, 2, 3, 4, 4]))
+
+    >>> find_median(nums=([1,2,2,3,4,4]))
     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)
-    if mod:
-        return nums[div]
-    return (nums[div] + nums[(div) - 1]) / 2
+    length = len(nums)
+    if length % 2:
+        return nums[length // 2]
+    return float((nums[length // 2] + nums[(length // 2) - 1]) / 2)
 
 
 def interquartile_range(nums: list[int | float]) -> float:
     """
-    Return the interquartile range for a list of numeric values.
-    :param nums: The list of numeric values.
-    :return: interquartile range
+    This is the implementation of inter_quartile
+    range for a list of numeric.
+    :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
-    >>> 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=[])
     Traceback (most recent call last):
     ...
     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.")
     nums.sort()
-    length = len(nums)
     div, mod = divmod(length, 2)
     q1 = find_median(nums[:div])
     half_length = sum((div, mod))