[Term Entry] Python NumPy - ndarray: shape

* Add NumPy ndarray shape term entry (#7824)

* Enhance documentation for ndarray shape attribute

Added detailed explanations for parameters and return values of the shape attribute. Updated examples and FAQs for clarity.

* Fix syntax for ndarray shape reference

* Minor changes

---------

Author: AayushJB03

content/numpy/concepts/ndarray/terms/shape/shape.md

@@ -0,0 +1,84 @@
+---
+Title: '.shape'
+Description: 'Returns a tuple representing the dimensions of an ndarray.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Data Structures'
+  - 'NumPy'
+  - 'Tuples'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`.shape`** attribute of a NumPy `ndarray` returns a [tuple](https://www.codecademy.com/resources/docs/python/tuples) of integers specifying the size of the array in each dimension. It provides information about the structure and layout of the array.
+
+## Syntax
+
+```pseudo
+ndarray.shape
+```
+
+**Parameters:**
+
+This attribute does not take any parameters.
+
+**Return value:**
+
+Returns a tuple of integers representing the size of the array along each dimension.
+
+- For a 1D array, it returns a single value (e.g., `(5,)`).
+- For a 2D array, it returns two values i.e. rows and columns (e.g., `(3, 4)`).
+- For higher dimensions, it includes one integer per axis.
+
+## Example
+
+The following example demonstrates how to use the `.shape` attribute to get the dimensions of different ndarrays:
+
+```py
+import numpy as np
+
+# 1D array
+arr_1d = np.array([1, 2, 3, 4, 5])
+print(arr_1d.shape)
+
+# 2D array
+arr_2d = np.array([[1, 2, 3], [4, 5, 6]])
+print(arr_2d.shape)
+
+# 3D array
+arr_3d = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
+print(arr_3d.shape)
+```
+
+The output for the above code will be:
+
+```shell
+(5,)
+(2, 3)
+(2, 2, 2)
+```
+
+## Codebyte Example
+
+The following codebyte example shows how to use the `.shape` attribute and modify array dimensions:
+
+```codebyte/python
+import numpy as np
+
+# Create a 1D array
+original_array = np.array([1, 2, 3, 4, 5, 6])
+print("Original shape:", original_array.shape)
+
+# Reshape to 2D array
+reshaped_array = original_array.reshape(2, 3)
+print("Reshaped to 2D:", reshaped_array.shape)
+print(reshaped_array)
+
+# Reshape to 3D array
+reshaped_3d = original_array.reshape(2, 3, 1)
+print("Reshaped to 3D:", reshaped_3d.shape)
+```