[Term Entry] Python NumPy - ndarray: cumprod()

* cumprod.md

* refined the entire entry

* Minor changes

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Author: prakhar14-op

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

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+---
+Title: '.cumprod()'
+Description: 'Returns the cumulative product of array elements along a specified axis.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Linear Algebra'
+  - 'Matrices'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+In NumPy, the **`.cumprod()`** method returns the cumulative product of the array elements over a particular axis. This method belongs to the `ndarray` class.
+
+## Syntax
+
+```pseudo
+ndarray.cumprod(axis=None, dtype=None, out=None)
+```
+
+**Parameters:**
+
+- `axis` (optional): Axis along which the cumulative product is computed. The default (None) flattens the array.
+- `dtype` (optional): The data type of the output array. Useful when input elements are of smaller types and may overflow.
+- `out` (optional): An alternative output array where results will be stored. It must have the same shape as the expected output.
+
+**Return value:**
+
+Returns a new array that contains the cumulative product of elements along the specified axis. If `out` is provided, the result is placed into it.
+
+## Example 1: Cumulative Product of a 1D Array
+
+This example computes the cumulative product of all elements in a one-dimensional array:
+
+```py
+import numpy as np
+
+a = np.array([1, 2, 3, 4])
+print("Original array:", a)
+
+result = a.cumprod()
+print("Cumulative product:", result)
+```
+
+The output of this code is:
+
+```shell
+Original array: [1 2 3 4]
+Cumulative product: [ 1  2  6 24]
+```
+
+Each element in the output represents the product of all elements up to that index in the input array.
+
+## Example 2: Cumulative Product Along Different Axes
+
+This example shows how `.cumprod()` behaves when applied across rows and columns of a 2D array:
+
+```py
+import numpy as np
+
+b = np.array([[1, 2, 3],
+              [4, 5, 6]])
+
+print("Original array:")
+print(b)
+
+# Cumulative product along rows (axis=1)
+row_cumprod = b.cumprod(axis=1)
+print("\nCumulative product along rows (axis=1):")
+print(row_cumprod)
+
+# Cumulative product along columns (axis=0)
+col_cumprod = b.cumprod(axis=0)
+print("\nCumulative product along columns (axis=0):")
+print(col_cumprod)
+```
+
+The output of this code is:
+
+```shell
+Original array:
+[[1 2 3]
+ [4 5 6]]
+
+Cumulative product along rows (axis=1):
+[[  1   2   6]
+ [  4  20 120]]
+
+Cumulative product along columns (axis=0):
+[[ 1  2  3]
+ [ 4 10 18]]
+```
+
+- When `axis=1`, the cumulative product is computed across each row.
+- When `axis=0`, it’s computed down each column.
+
+## Codebyte Example
+
+Run this interactive example to experiment with `.cumprod()` on a 2D array:
+
+```codebyte/python
+import numpy as np
+
+a = np.array([[2, 3, 4],
+              [5, 6, 7]])
+
+print("Original array:")
+print(a)
+
+print("\nCumulative product (flattened):", a.cumprod())
+print("\nCumulative product along axis=0:\n", a.cumprod(axis=0))
+print("\nCumulative product along axis=1:\n", a.cumprod(axis=1))
+```