TermEntryNdarrayProd #7863

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

@@ -0,0 +1,84 @@
+---
+Title: '.prod()'
+Description: 'Calculates the product of all elements in a NumPy array, optionally along a specified axis.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Functions'
+  - 'Math'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`.prod()`** function in NumPy returns the product of array elements over a specified axis. It’s useful in mathematical and statistical operations, especially with multi-dimensional arrays where the product needs to be computed across rows, columns, or the entire array. This function is also available as the standalone function `numpy.prod()`.
+
+## Syntax
+
+```pseudo
+ndarray.prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)
+```
+
+**Parameters:**
+
+- `axis` (int or tuple of ints, optional): The axis or axes along which the product is computed.
+  - If `None` (default), the product of all elements in the array is returned.
+  - If an integer or tuple of integers, the product is computed along the specified axis or axes.
+- `dtype` (Optional): The data type of the returned array and of the accumulator used in the computation. If not specified, it’s inferred from the input to avoid overflow when possible.
+- `out` (ndarray, optional): An alternate output array in which to place the result. It must have the same shape as the expected output.
+- `keepdims` (bool, optional): If `True`, the reduced axes are kept in the result as dimensions with size one. Default is `False`.
+- `initial` (scalar, optional): The starting value for the product. The default is `1`.
+- `where` (array_like of bool, optional): A boolean array indicating elements to include in the product. Elements where `where` is `False` are ignored.
+
+**Return value:**
+
+Returns the product of array elements over the specified axis (or the entire array if `axis=None`). The returned type matches the input or the specified `dtype`.
+
+## Example
+
+The following example shows the use of the `.prod()` to calculate the product of all elements in a 1D array and the product along the columns in a 2D array:
+
+```py
+import numpy as np
+
+# 1D array example
+arr_1d = np.array([2, 3, 4])
+product_all = arr_1d.prod()
+
+# 2D array example
+# [[1, 2],
+#  [5, 6]]
+arr_2d = np.array([[1, 2], [5, 6]])
+
+# Product along columns (axis=0): (1*5, 2*6)
+product_cols = arr_2d.prod(axis=0)
+
+print(f"Product of all elements (1D): {product_all}")
+print(f"Product along columns (axis=0) in 2D: {product_cols}")
+```
+
+The code above generates the following output:
+
+```shell
+Product of all elements (1D): 24
+Product along columns (axis=0) in 2D: [ 5 12]
+```
+
+## Codebyte Example
+
+The following codebyte example demonstrates calculating the product of elements along the rows (`axis=1`) of a 2D array:
+
+```codebyte/python
+import numpy as np
+
+arr = np.array([[10, 1],
+                [3, 4]])
+
+# Product along rows (axis=1): (10*1, 3*4)
+product_rows = arr.prod(axis=1)
+
+print(product_rows)
+```