The Numpy library in Python comes with a number of built-in functions to help get common descriptive statistics like max, min, mean, median, etc. from arrays. In this tutorial, we will look at how to get the min value in a Numpy array with the help of some examples.

## How to find the min value of a Numpy array?

You can use the Numpy `amin()`

function to get the min value of a Numpy array. Pass the array as an argument to the function. The following is the syntax –

# min value in numpy array ar numpy.amin(ar)

It returns the minimum value in the array. You can also use the Numpy `amin()`

function to get the minimum value along a particular axis in a Numpy array (useful for 2-D or higher dimension arrays).

**Note – **The `numpy.min()`

function is an alias for the `numpy.amin()`

function. Thus, you can use anyone based on your preference to get the minimum value in an array or the minimum value along a particular axis in the array.

## Steps to Find the Min Value in Numpy Array

Let’s now look at a step-by-step example of using the above syntax to get the minimum value in a Numpy array.

### Step 1 – Create a Numpy array

First, we will create a Numpy array that we will be using throughout this tutorial. If you already have a Numpy array to operate on, skip this step.

import numpy as np # create numpy array ar = np.array([3, 5, 2, 1, 4]) # display the array print(ar)

Output:

[3 5 2 1 4]

Here, we used the `numpy.array()`

function to create a Numpy array of some integer values. You can see that the min value in the above array is 1.

**Data Science Programs By Skill Level**

**Introductory** ⭐

- Harvard University Data Science: Learn R Basics for Data Science
- Standford University Data Science: Introduction to Machine Learning
- UC Davis Data Science: Learn SQL Basics for Data Science
- IBM Data Science: Professional Certificate in Data Science
- IBM Data Analysis: Professional Certificate in Data Analytics
- Google Data Analysis: Professional Certificate in Data Analytics
- IBM Data Science: Professional Certificate in Python Data Science
- IBM Data Engineering Fundamentals: Python Basics for Data Science

**Intermediate ⭐⭐⭐**

- Harvard University Learning Python for Data Science: Introduction to Data Science with Python
- Harvard University Computer Science Courses: Using Python for Research
- IBM Python Data Science: Visualizing Data with Python
- DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization

**Advanced ⭐⭐⭐⭐⭐**

- UC San Diego Data Science: Python for Data Science
- UC San Diego Data Science: Probability and Statistics in Data Science using Python
- Google Data Analysis: Professional Certificate in Advanced Data Analytics
- MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
- MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science

**🔎 Find Data Science Programs 👨💻 111,889 already enrolled**

Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.

### Step 2 – Find the min value in the array using `numpy.amin()`

Pass the array as an argument to the Numpy `amin()`

function to get its minimum value.

# min value in numpy array print(np.amin(ar))

Output:

1

We get the minimum value in the array as 1 which is the correct answer.

You can also use the Numpy `min()`

function (which is an alias for the Numpy `amin()`

function) to get the minimum value of a Numpy array.

# min value in numpy array print(np.min(ar))

Output:

1

We get the same result as above.

## Summary – Find the Min Value of Numpy Array

In this tutorial, we looked at how to find the minimum value in a Numpy array. Some of the key takeaways from this tutorial are –

- Use the
`numpy.amin()`

function to get the min value in a Numpy array. You can also use it to get the min value along a particular axis in the array. - Alternatively, you can also use the
`numpy.min()`

function which is an alias for the`numpy.amin()`

function.

You might also be interested in –

**Subscribe to our newsletter for more informative guides and tutorials. ****We do not spam and you can opt out any time.**