# NumPy Replace Values

Muhammad Maisam Abbas Jan 30, 2023 May 08, 2021

This tutorial will introduce how to replace values inside a NumPy array in Python.

## NumPy Replace Values With the `numpy.clip()` Function

If we need to replace all the greater values than a certain threshold in a NumPy array, we can use the `numpy.clip()` function. We can specify the upper and the lower limits of an array using the `numpy.clip()` function. The `numpy.clip()` function returns an array where the elements less than the specified limit are replaced with the lowest limit. The elements greater than the specified limit are replaced with the greatest limit. The following code example shows us how to replace values inside a NumPy array with the `numpy.clip()` function.

``````import numpy as np

array = np.array([1,2,3,4,5,5,6,7,8,8,9,9])

result = np.clip(array, 0, 5)
print(result)
``````

Output:

``````[1 2 3 4 5 5 5 5 5 5 5 5]
``````

We replaced the values greater than `5` inside the NumPy array `array` with the `np.clip()` function in the above code. We first created a NumPy array with the `np.array()` function. We then clipped the `array` by specifying a limit from `0` to `5` inside the `np.clip()` function and saved the result inside the `result` array.

## NumPy Replace Values With the `numpy.minimum()` and `numpy.maximum()` Functions

We can also use the `numpy.minimum()` and the `numpy.maximum()` functions to replace values in an array outside our specified limit. The `numpy.maximum()` function is used to replace the values less than the lower limit with the lower limit. And the `numpy.minimum()` function is used to replace values greater than the upper limit with the upper limit. The `numpy.maximum()` function takes the array and the lowest possible value as input parameters. The `numpy.minimum()` function takes the array and the greatest possible value as input parameters. See the following code example.

``````import numpy as np

array = np.array([1,2,3,4,5,5,6,7,8,8,9,9])

result1 = np.minimum(array, 5)

result2 = np.maximum(result1,0)
print(result2)
``````

Output:

``````[1 2 3 4 5 5 5 5 5 5 5 5]
``````

We replaced the values greater than `5` with `5` by using the `np.minimum()` function and the values less than `0` with `0` by using the `np.maximum()` function. We stored the result of these operations inside the `result2` array.

## NumPy Replace Values With the Array Indexing Method in Python

The simplest way of achieving the same goal as the previous two methods is to use the array indexing in Python. We can easily replace values greater than or less than a certain threshold with the array indexing method in NumPy. Rather than creating a new array like the previous two methods, this method modified the contents of our original array.

``````import numpy as np

array = np.array([1,2,3,4,5,5,6,7,8,8,9,9])

array[array > 5] = 5
print(array)
``````

Output:

``````[1 2 3 4 5 5 5 5 5 5 5 5]
``````

We replaced all the values inside the `array` greater than `5` with `5` by using `array[array > 5] = 5` in Python.

Maisam is a highly skilled and motivated Data Scientist. He has over 4 years of experience with Python programming language. He loves solving complex problems and sharing his results on the internet.