diff --git a/maths/interquartile_range.py b/maths/interquartile_range.py
index b54ef3704..8ef59b267 100644
--- a/maths/interquartile_range.py
+++ b/maths/interquartile_range.py
@@ -7,51 +7,63 @@ and return the IQR as output.
 Script inspired from its corresponding Wikipedia article
 https://en.wikipedia.org/wiki/Interquartile_range
 """
+from __future__ import annotations
 
 import numpy as np
 
 
-def find_median(x: np.array) -> float:
+def find_median(nums: list[int | float]) -> float:
     """
     This is the implementation of median.
-    :param x: The list of numeric values
+    :param nums: The list of numeric nums
     :return: Median of the list
-    >>> find_median(x=np.array([1,2,2,3,4]))
+    >>> find_median(nums=([1,2,2,3,4]))
     2
 
-    >>> find_median(np.array([1,2,2,3,4,4]))
+    >>> find_median(nums=([1,2,2,3,4,4]))
     2.5
 
 
     """
-    length = len(x)
+    length = len(nums)
     if length % 2:
-        return x[length // 2]
-    return float((x[length // 2] + x[(length // 2) - 1]) / 2)
+        return nums[length // 2]
+    return float((nums[length // 2] + nums[(length // 2) - 1]) / 2)
 
 
-def interquartile_range(x: np.array) -> float:
+def interquartile_range(nums: list[int | float]) -> float:
     """
     This is the implementation of inter_quartile
     range for a list of numeric.
-    :param x: The list of data point
+    :param nums: The list of data point
     :return: Inter_quartile range
 
-    >>> interquartile_range(x=np.array([4,1,2,3,2]))
+    >>> interquartile_range(nums=[4,1,2,3,2])
     2.0
 
 
-    >>> interquartile_range(x=np.array([25,32,49,21,37,43,27,45,31]))
-    18.0
+    >>> 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
+
+
+
     """
-    length = len(x)
+    length = len(nums)
     if length == 0:
         raise ValueError("The list is empty. Provide a non-empty list.")
-    x.sort()
+    nums.sort()
     div, mod = divmod(length, 2)
-    q1 = find_median(x[:div])
+    q1 = find_median(nums[:div])
     half_length = sum((div, mod))
-    q3 = find_median(x[half_length:length])
+    q3 = find_median(nums[half_length:length])
     return q3 - q1