diff --git a/contrib/numpy/index.md b/contrib/numpy/index.md
index 18ed17a..b2d459a 100644
--- a/contrib/numpy/index.md
+++ b/contrib/numpy/index.md
@@ -7,3 +7,4 @@
 - [Operations on Arrays in NumPy](operations-on-arrays.md)
 - [Loading Arrays from Files](loading_arrays_from_files.md)
 - [Saving Numpy Arrays into FIles](saving_numpy_arrays_to_files.md)
+- [Sorting NumPy Arrays](sorting-array.md)
diff --git a/contrib/numpy/sorting-array.md b/contrib/numpy/sorting-array.md
new file mode 100644
index 0000000..65e9c25
--- /dev/null
+++ b/contrib/numpy/sorting-array.md
@@ -0,0 +1,104 @@
+# Sorting NumPy Arrays
+- Sorting arrays is a common operation in data manipulation and analysis.
+- NumPy provides various functions to sort arrays efficiently.
+- The primary methods are `numpy.sort`,`numpy.argsort`, and `numpy.lexsort`
+
+### 1. numpy.sort()
+
+The `numpy.sort` function returns a sorted copy of an array.
+
+#### Syntax :
+
+```python
+numpy.sort(arr, axis=-1, kind=None, order=None)
+```
+- **arr** : Array to be sorted.
+- **axis** : Axis along which to sort. (By Default is -1)
+- **kind** : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort')
+- **order** : When arr is an array with fields defined, this argument specifies which fields to compare first.
+
+#### Example :
+
+```python
+import numpy as np
+
+arr = np.array([1,7,0,4,6])
+sarr = np.sort(arr)
+print(sarr)
+```
+
+**Output** :
+```python
+[0 1 4 6 7]
+```
+
+### 2. numpy.argsort()
+
+The `numpy.argsort` function returns the indices that would sort an array. Using those indices you can sort the array.
+
+#### Syntax :
+
+```python
+numpy.argsort(a, axis=-1, kind=None, order=None)
+```
+- **arr** : Array to be sorted.
+- **axis** : Axis along which to sort. (By Default is -1)
+- **kind** : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort')
+- **order** : When arr is an array with fields defined, this argument specifies which fields to compare first.
+
+#### Example :
+
+```python
+import numpy as np
+
+arr = np.array([2.1,7,4.2,4.3,6])
+indices = np.argsort(arr)
+print(indices)
+s_arr = arr[indices]
+print(s_arr)
+```
+
+**Output** :
+```python
+[0 2 3 4 1]
+[2.1 4.2 4.3 6. 7. ]
+```
+
+### 3. np.lexsort()
+
+The np.lexsort function performs an indirect stable sort using a sequence of keys.
+
+#### Syntax :
+
+```python
+numpy.lexsort(keys, axis=-1)
+```
+- **keys**: Sequence of arrays to sort by. The last key is the primary sort key.
+- **axis**: Axis to be indirectly sorted.(By Default -1)
+
+#### Example :
+
+```python
+import numpy as np
+
+a = np.array([5,4,3,2])
+b = np.array(['a','d','c','b'])
+indices = np.lexsort((a,b))
+print(indices)
+
+s_arr = a[indices]
+print(s_arr)
+
+s_arr = b[indices]
+print(s_arr)
+```
+
+**Output** :
+```python
+[0 3 2 1]
+[2 3 4 5]
+['a' 'b' 'c' 'd']
+```
+
+NumPy provides powerful and flexible functions for sorting arrays, including `np.sort`, `np.argsort`, and `np.lexsort`. 
+These functions support sorting along different axes, using various algorithms, and sorting by multiple keys, making them suitable for a wide range of data manipulation tasks.