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+# Concatenation of Arrays
+
+Concatenation of arrays in NumPy refers to combining multiple arrays into a single array, either along existing axes or by adding new axes. NumPy provides several functions for this purpose.
+
+# Functions of Concatenation
+
+## np.concatenate 
+
+Joins two or more arrays along an existing axis.
+
+### Syntax
+
+```python
+numpy.concatenate((arr1, arr2, ...), axis)
+```
+
+Args:
+- arr1, arr2, ...: Sequence of arrays to concatenate.
+- axis: Axis along which the arrays will be joined. Default is 0.
+
+### Example
+
+#### Concatenate along axis 0
+
+```python
+import numpy as np
+#creating 2 arrays
+arr1 = np.array([1 2 3],[7 8 9])
+arr2 = np.array([4 5 6],[10 11 12])
+
+result_1 = np.concatenate((arr1, arr2), axis=0)
+print(result_1)
+```
+
+#### Output
+```
+[[ 1  2  3]
+ [ 7  8  9]
+ [ 4  5  6]
+ [10 11 12]]
+```
+
+#### Concatenate along axis 1
+
+```python
+result_2 = np.concatenate((arr1, arr2), axis=1)
+print(result_2)
+```
+
+#### Output
+```
+[[ 1 2 3 4 5 6 ]
+ [ 7 8 9 10 11 12]]
+```
+
+## np.vstack
+
+Vertical stacking of arrays (row-wise).
+
+### Syntax
+
+```python
+numpy.vstack(arrays)
+```
+
+Args:
+- arrays: Sequence of arrays to stack.
+
+### Example
+
+```python
+import numpy as np
+#create arrays
+arr1= np.array([1 2 3], [7 8 9])
+arr2 = np.array([4 5 6],[10 11 12])
+
+result = np.vstack((arr1, arr2))
+print(result)
+```
+
+#### Output
+```
+[[ 1  2  3]
+ [ 7  8  9]
+ [ 4  5  6]
+ [10 11 12]]
+```
+
+## 3. np.hstack
+
+Stacks arrays horizontally (column-wise).
+
+### Syntax
+
+```python
+numpy.hstack(arrays)
+```
+
+Args:
+- arrays: Sequence of arrays to stack.
+
+### Example
+
+```python
+import numpy as np
+#create arrays
+arr1= np.array([1 2 3], [7 8 9])
+arr2 = np.array([4 5 6],[10 11 12])
+
+result = np.hstack((arr1, arr2))
+print(result)
+```
+
+#### Output
+```
+[[ 1  2  3] [ 4  5  6]
+ [ 7  8  9] [10 11 12]]
+```
+
+## np.dstack 
+
+Stacks arrays along the third axis (depth-wise).
+
+### Syntax
+
+```python
+numpy.dstack(arrays)
+```
+
+- arrays: Sequence of arrays to stack.
+
+### Example
+
+```python
+import numpy as np
+#create arrays
+arr1= np.array([1 2 3], [7 8 9])
+arr2 = np.array([4 5 6],[10 11 12])
+
+result = np.dstack((arr1, arr2))
+print(result)
+```
+
+#### Output
+```
+[[[ 1  4]
+  [ 2  5]
+  [ 3  6]]
+
+ [[ 7 10]
+  [ 8 11]
+  [ 9 12]]]
+```
+
+## np.stack
+
+Joins a sequence of arrays along a new axis.
+
+```python
+numpy.stack(arrays, axis)
+```
+
+Args:
+- arrays: Sequence of arrays to stack.
+
+### Example
+
+```python
+import numpy as np
+#create arrays
+arr1= np.array([1 2 3], [7 8 9])
+arr2 = np.array([4 5 6],[10 11 12])
+
+result = np.stack((arr1, arr2), axis=0)
+print(result)
+```
+
+#### Output
+```
+[[[ 1  2  3]
+  [ 7  8  9]]
+
+ [[ 4  5  6]
+  [10 11 12]]]
+```
+
+# Concatenation with Mixed Dimensions
+
+When concatenating arrays with different shapes, it's often necessary to reshape them to have compatible dimensions.
+
+## Example
+
+#### Concatenate along axis 0
+
+```python
+arr1 = np.array([[1, 2, 3], [4, 5, 6]])
+arr2 = np.array([7, 8, 9])
+
+result_0= np.concatenate((arr1, arr2[np.newaxis, :]), axis=0)
+print(result_0)
+```
+
+#### Output
+```
+[[1 2 3]
+ [4 5 6]
+ [7 8 9]]
+``` 
+
+#### Concatenate along axis 1
+
+```python
+result_1 = np.concatenate((arr1, arr2[:, np.newaxis]), axis=1)
+print(result_1)
+```
+
+#### Output
+```
+[[1 2 3 7]
+ [4 5 6 8]]
+```
+
+
diff --git a/contrib/numpy/index.md b/contrib/numpy/index.md
index b2d459a..fb07865 100644
--- a/contrib/numpy/index.md
+++ b/contrib/numpy/index.md
@@ -8,3 +8,4 @@
 - [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)
+- [Concatenation of Arrays](concatenation-of-arrays.md)