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+---
+Title: '.diagonal()'
+Description: 'Returns the specified diagonal elements of an array.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Linear Algebra'
+  - 'Matrices'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`.diagonal()`** method returns the specified diagonal elements of a NumPy array. For 2D arrays, the diagonal consists of elements where the row index equals the column index (or with an offset). For multi-dimensional arrays, the axes specified by `axis1` and `axis2` define the matrix dimensions from which to extract the diagonal.
+
+Unlike [`.trace()`](https://www.codecademy.com/resources/docs/numpy/ndarray/trace), which returns the sum of diagonal elements, `.diagonal()` returns the actual diagonal elements as an array. This method typically returns a view rather than a copy, making it memory-efficient for large arrays.
+
+## Syntax
+
+```pseudo
+ndarray.diagonal(offset=0, axis1=0, axis2=1)
+```
+
+**Parameters:**
+
+- `offset` (Optional): The diagonal offset from the main diagonal. A positive value selects a diagonal above the main diagonal, while a negative value selects one below. Default is `0` (main diagonal).
+- `axis1` (Optional): The axis to be used as the first axis of the 2D sub-arrays from which the diagonals should be taken. Default is `0`.
+- `axis2` (Optional): The axis to be used as the second axis of the 2D sub-arrays from which the diagonals should be taken. Default is `1`.
+
+**Return value:**
+
+Returns an array containing the diagonal elements. For 2D arrays, this is a 1D array. For higher-dimensional arrays, the result has one fewer dimension than the input.
+
+## Example 1: Extracting Diagonals from 2D and Rectangular Arrays
+
+This example demonstrates how to extract diagonals from both square and rectangular arrays using different `offset` values:
+
+```py
+import numpy as np
+
+# Create a 3×3 square array
+square = np.array([[1, 2, 3],
+                   [4, 5, 6],
+                   [7, 8, 9]])
+
+print("Square array:")
+print(square)
+
+print("\nMain diagonal:", square.diagonal())
+print("Upper diagonal (offset=1):", square.diagonal(offset=1))
+print("Lower diagonal (offset=-1):", square.diagonal(offset=-1))
+
+# Create a 4×3 rectangular array
+rectangular = np.array([[1, 2, 3],
+                        [4, 5, 6],
+                        [7, 8, 9],
+                        [10, 11, 12]])
+
+print("\nRectangular array:")
+print(rectangular)
+
+print("\nMain diagonal:", rectangular.diagonal())
+print("Upper diagonal (offset=1):", rectangular.diagonal(offset=1))
+print("Lower diagonal (offset=-2):", rectangular.diagonal(offset=-2))
+```
+
+The output produced by this code is:
+
+```shell
+Square array:
+[[1 2 3]
+ [4 5 6]
+ [7 8 9]]
+
+Main diagonal: [1 5 9]
+Upper diagonal (offset=1): [2 6]
+Lower diagonal (offset=-1): [4 8]
+
+Rectangular array:
+[[ 1  2  3]
+ [ 4  5  6]
+ [ 7  8  9]
+ [10 11 12]]
+
+Main diagonal: [1 5 9]
+Upper diagonal (offset=1): [2 6]
+Lower diagonal (offset=-2): [7 11]
+```
+
+For rectangular matrices, the diagonal length is determined by the smaller dimension, and different offsets extract parallel diagonals above or below the main one.
+
+## Example 2: Using `.diagonal()` with Multi-Dimensional Arrays
+
+This example demonstrates how to extract diagonals from higher-dimensional arrays by specifying axes:
+
+```py
+import numpy as np
+
+# Create a 3D array (2x3x3)
+array_3d = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+                     [[10, 11, 12], [13, 14, 15], [16, 17, 18]]])
+print("3D array shape:", array_3d.shape)
+print("3D array:")
+print(array_3d)
+
+# Extract diagonal from the last two dimensions
+diag_default = array_3d.diagonal()
+print("\nDiagonal (axis1=0, axis2=1):")
+print(diag_default)
+
+# Extract diagonal with different axes
+diag_12 = array_3d.diagonal(axis1=1, axis2=2)
+print("\nDiagonal (axis1=1, axis2=2):")
+print(diag_12)
+```
+
+The output produced by this code is:
+
+```shell
+3D array shape: (2, 3, 3)
+3D array:
+[[[ 1  2  3]
+  [ 4  5  6]
+  [ 7  8  9]]
+
+ [[10 11 12]
+  [13 14 15]
+  [16 17 18]]]
+
+Diagonal (axis1=0, axis2=1):
+[[ 1 13]
+ [ 2 14]
+ [ 3 15]]
+
+Diagonal (axis1=1, axis2=2):
+[[ 1  5  9]
+ [10 14 18]]
+```
+
+For 3D arrays, `.diagonal()` extracts diagonal elements from 2D slices defined by the specified axes, resulting in an array with one fewer dimension.
+
+## Codebyte Example
+
+Run the following codebyte example to understand the usage of the `.diagonal()` method:
+
+```codebyte/python
+import numpy as np
+
+# Create a 4x4 matrix
+matrix = np.array([[1, 2, 3, 4],
+                   [5, 6, 7, 8],
+                   [9, 10, 11, 12],
+                   [13, 14, 15, 16]])
+print("Original matrix:")
+print(matrix)
+
+# Extract and display different diagonals
+print("\nMain diagonal:", matrix.diagonal())
+print("First upper diagonal:", matrix.diagonal(1))
+print("Second upper diagonal:", matrix.diagonal(2))
+print("First lower diagonal:", matrix.diagonal(-1))
+```