[Term Entry] Python NumPy - ndarray: size

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

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+---
+Title: 'size'
+Description: 'Returns the number of elements in a NumPy array.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Attributes'
+  - 'NumPy'
+  - 'Properties'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/computer-science'
+---
+
+NumPy’s **`size`** attribute is used to find the total number of elements in an array.
+
+## Syntax
+
+```pseudo
+ndarray.size
+```
+
+**Parameters:**
+
+`size` doesn’t take any parameters because it’s an attribute, not a method.
+
+**Return value:**
+
+Returns an integer representing the total number of elements in the array.
+
+## Example 1: Getting the Size of an Array Using `size`
+
+In this example, the code prints the total number of elements in the array:
+
+```py
+import numpy as np
+
+np_array = np.array([[1, 2, 3], [4, 5, 6]])
+print(np_array.size)
+```
+
+The output of this code is:
+
+```shell
+6
+```
+
+The array has 2 rows × 3 columns = 6 elements in total.
+
+## Example 2: Comparing `.shape` and `.size`
+
+In this example, `shape` displays the array’s dimensions, while `size` shows the total number of elements in the array:
+
+```py
+import numpy as np
+
+arr = np.array([[10, 20, 30], [40, 50, 60]])
+print("Shape:", arr.shape)
+print("Size:", arr.size)
+```
+
+The output of this code is:
+
+```shell
+Shape: (2, 3)
+Size: 6
+```
+
+`shape` returns the dimensions of the array, while `size` gives the total number of elements.
+
+## Codebyte Example: Using `.size` in a NumPy Operation
+
+In this example, `size` returns the total number of elements (12) in a reshaped 3×4 NumPy array:
+
+```codebyte/python
+import numpy as np
+
+array = np.arange(12).reshape(3, 4)
+print("Array:")
+print(array)
+
+print("Total elements:", array.size)
+```