Add nonzero() term under NumPy ndarray concept

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

@@ -0,0 +1,64 @@
+---
+Title: 'nonzero()'
+Description: 'Returns the indices of the array elements that are non-zero.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Array'
+  - 'Data'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`numpy.ndarray.nonzero()`** method returns the indices of elements in an [array](https://www.codecademy.com/resources/docs/numpy/ndarray) that are non-zero or evaluate to `True`. It is often used to locate positions of meaningful or valid data within an array.
+
+## Syntax
+
+```pseudo
+ndarray.nonzero()
+```
+
+**Parameters:**
+
+This method takes no parameters.
+
+**Return value:**
+
+Returns a [tuple](https://www.codecademy.com/resources/docs/python/tuples) of arrays, one for each dimension, containing the indices of elements that are non-zero.
+
+## Example: Finding Non-Zero Elements in a 1D Array
+
+In this example, the indices of all non-zero elements in a 1D NumPy array are returned:
+
+```py
+import numpy as np
+
+arr = np.array([0, 2, 0, 4, 5])
+result = arr.nonzero()
+print(result)
+```
+
+The output of this code is:
+
+```shell
+(array([1, 3, 4]),)
+```
+
+## Codebyte Example
+
+In this example, the positions of non-zero elements in a 2D array are identified:
+
+```codebyte/python
+import numpy as np
+
+a = np.array([[0, 5, 0],
+              [7, 0, 9]])
+
+rows, cols = a.nonzero()
+
+for r, c in zip(rows, cols):
+  print(f"Non-zero element {a[r, c]} found at position ({r}, {c})")
+```