Numpy arrays are very versatile when it comes to performing numerical operations on them. Also, the Numpy library comes with a number of useful built-in functions to work with and manipulate the data in arrays. In this tutorial, we will look at how to reverse the sign of values in a Numpy array with the help of some examples.

## How to reverse the sign of values in a Numpy Array?

To reverse the sign of each value in a Numpy array, you can either multiply the entire array by `-1`

or use the `numpy.negative()`

function.

The following is the syntax –

## reverse the sign of array elements # multiply by -1 -1 * ar # use numpy.negative() numpy.negative(ar)

Both methods return a Numpy array with the sign of the values reversed.

## Examples

Let’s now look at a step-by-step example of using the above methods to reverse the sign of values in a Numpy array.

### Step 1 – Create a Numpy array

First, we will create a Numpy array that we will be using throughout the tutorial.

import numpy as np # create array ar = np.array([-2, -1, 0, 1, 2, 3, 3.4]) # display the array print(ar)

Output:

[-2. -1. 0. 1. 2. 3. 3.4]

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

function to create a Numpy array with some numeric values. You can see that the array contains both positive and negative values (along with a zero).

**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 – Reverse the sign of values in the array

There are two ways you can reverse the sign of each element –

#### Multiply the array by `-1`

Multiply the Numpy array with the scaler value `-1`

.

# reverse the sign -1*ar

Output:

array([ 2. , 1. , -0. , -1. , -2. , -3. , -3.4])

The resulting array has the sign of each value reversed.

### Use the `numpy.negative()`

function

Alternatively, you can also use the `numpy.negative()`

function. This function returns the element-wise numerical negative of the array.

Let’s apply this function to the same array we used above.

# reverse the sign np.negative(ar)

Output:

array([ 2. , 1. , -0. , -1. , -2. , -3. , -3.4])

We get the same result as above.

You can also similarly use these methods on higher dimensional arrays to reverse the sign.

You might also be interested in –

- Numpy – Get Absolute Value of Each Element
- Get the Natural Log of Each Element in Numpy Array
- Get the Exponential of Each Element in Numpy Array

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