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

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Author: mamtawardhani

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

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+---
+Title: 'argmin()'
+Description: 'Returns the index of the minimum value in a NumPy array or along a specified axis.'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Array'
+  - 'Data'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/data-science'
+---
+
+The **`ndarray.argmin()`** method returns the index of the minimum value in a NumPy array. The search can be performed on the flattened array or along a specified axis, and the result reflects where the smallest element appears rather than the value itself.
+
+## Syntax
+
+```pseudo
+ndarray.argmin(axis=None, out=None, *, keepdims=False)
+```
+
+**Parameters:**
+
+- `axis` (optional): Axis along which to find the minimum index.
+  - `None` (default): Searches the entire flattened array.
+  - `0`: Searches column-wise
+  - `1`: Searches row-wise
+- `out` (optional): Output array that receives the result. Must have the appropriate shape.
+- `keepdims` (optional): If `True`, the reduced axes are kept with size 1, preserving the dimension structure.
+
+**Return value:**
+
+An integer or array of integers representing the indices of the minimum values.
+
+## Example 1: Finding the Minimum Index in a 1D Array
+
+In this example, the smallest number in the array is identified, and its index is returned:
+
+```py
+import numpy as np
+
+arr = np.array([12, 5, 7, 3, 9])
+idx = arr.argmin()
+print(idx)
+```
+
+The output of this code is:
+
+```shell
+3
+```
+
+## Example 2: Finding Minimum Indices Along Rows
+
+In this example, `argmin()` is applied along `axis=1`, so each row returns the index of its smallest element:
+
+```py
+import numpy as np
+
+arr = np.array([[4, 9, 1],
+                [8, 3, 6]])
+
+idx = arr.argmin(axis=1)
+print(idx)
+```
+
+The output of this code is:
+
+```shell
+[2 1]
+```
+
+## Codebyte Example
+
+In this example, the minimum index is found both in the flattened array and along each column to show how the output changes with the `axis` parameter:
+
+```codebyte/python
+import numpy as np
+
+arr = np.array([[15, 7, 9],
+                [2, 11, 5],
+                [6, 4, 8]])
+
+flat_index = arr.argmin()
+col_indices = arr.argmin(axis=0)
+
+print("Index of minimum in flattened array:", flat_index)
+print("Index of minimum in each column:", col_indices)
+```
+
+## Frequently Asked Questions
+
+### 1. What does NumPy `argmin()` do?
+
+NumPy's `argmin()` returns the index location of the smallest element inside an array. Instead of giving the minimum value, it identifies where that value appears, which is essential for position-based analysis.
+
+### 2. What is the difference between `argmin()` and `nanargmin()`?
+
+`argmin()` considers all values, including NaNs, while `nanargmin()` ignores NaNs and returns the index of the smallest non-NaN value.
+
+### 3. What is the difference between `argmin()` and `min()` in Python?
+
+`min()` (or `ndarray.min()`) returns the smallest value itself, while `argmin()` returns the index where that value occurs. One answers “what is the smallest value”, and the other answers “where is that smallest value located”.