You can find the index of the minimum value in list in python using NumPy. To do this you can use the argmin() to get the index of the minimum value of the NumPy. In this post you will know all the steps to find the index of the minimum value of the list.

## What is the argmin() function?

The numpy.argmin() function returns the indices of the minimum values along an axis in a NumPy array. Below is the syntax of the function.

```
numpy.argmin(a, axis=None, out=None)
```

Explanation of the parameters are the below.

**a:**Input array.**axis:**Axis or axes along which to operate. By default, it operates on the flattened array.**out:**Output array in which to place the result. It must have the same shape as the expected output. If not provided, a new array is created.

Below is the sample code for the implementation of the argmin() function.

```
import numpy as np
arr = np.array([[40, 20, 70],
[30, 50, 10],
[80, 60, 90]])
min_index = np.argmin(arr)
print("Index of the minimum value:", min_index)
```

**Output**

```
Index of the minimum value: 5
```

Steps to Find index of Minimum Value in List in Python using NumPy

### Step 1: Import NumPy

The first step is to import the numpy package. Make sure you have NumPy installed, and then import it.

`import numpy as np`

### Step 2: Create a NumPy array:

Create a sample list and convert it to a NumPy array using the numpy.array() function.

```
my_list = [30, 10, 40, 10, 50, 90, 20, 60, 50, 30, 50]
my_array = np.array(my_list)
```

### Step 3: Find the index of the minimum value

You will Use the `argmin()`

function to get the index of the minimum value in the array.

` min_index = np.argmin(my_array)`

Now, `min_index`

contains the index of the minimum value in the array.

Below is the complete code.

```
import numpy as np
my_list = [30, 10, 40, 10, 50, 90, 20, 60, 50, 30, 50]
my_array = np.array(my_list)
min_index = np.argmin(my_array)
print("Index of the minimum value:", min_index)
```

**Output**

`Index of the minimum value: 1`

In this example, the minimum value is `1`

, and its index is `1`

. Note that the index is zero-based, so the first element of the array has an index of `0`

.

## Conclusion

Most of the time you have to find the lowest element in the list to find the peaks and troughs. The above steps allow you to find the index of the minimum element of the list using the numpy package. Here you will use the argmin() function for that.

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