# numpy.min() in Python | np.min() in Python

Numpy `min()` function is used to get a minimum value along a specified axis.

## Syntax of Numpy.min()

`np.min(a, axis=None)`

`a` parameter refers to the array on which you want to apply np.min() function.

`axis` parameter is optional and helps us to specify the axis on which we want to find the minimum values.

## Python program to find minimum value on 1-Dimensional Numpy Array

```import numpy as np

a = np.array([50, 15, 23, 89, 64])
print('Minimum value in arr: ', np.min(a))```

Output of the above program

`Minimum value in arr: 15`

In 1-Dimensional, it is optional to pass axis parameter to np.min() function. ## Python program to find minimum value on 2-Dimensional Numpy Array

```import numpy as np

a = np.array([[50, 15, 89, 23, 64],
[45, 98, 25, 17, 55],
[35, 37, 9, 100, 61]])
print('Minimum value in arr: ', np.min(a))
print('Minimum value in arr along axis 0: ', np.min(a, axis=0))
print('Minimum value in arr along axis 1: ', np.min(a, axis=1))```

Output of the above program

```Minimum value in arr:  9
Minimum value in arr along axis 0:  [35 15  9 17 55]
Minimum value in arr along axis 1:  [15 17  9]```

When axis value is not passed to min() function, then it returns the minimum element present in the array- When `axis=0` is passed to min() function, then it works like this- When `axis=1` is passed to min() function, then it works like this- 