# Limiting NumPy array values within a specific range - how to do it?

I’ve encountered the concept of constraining the values within an array, where you can limit the elements of an array to a specific range of maximum and minimum values, for example, restricting all the values in the array to be between 2 and 4. However, I couldn’t find a simple code example on the internet. Could someone provide a brief explanation of this concept using a simple example code snippet?

Thank you for your assistance!

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You can apply lower and upper limits to every element in a NumPy array using boolean indexing which is also easy to understand. Here’s an example:

In the given code, conditions are created using the `lower_limit` and `upper_limit` variables, and boolean indexing is used to adjust any values in the array that are below the lower limit to the lower limit value, and any values above the upper limit to the upper limit value.

I hope this code helps you and makes you understand the concept better!

You can achieve precise value constraints in a NumPy array with the following code:

• The code uses NumPy to manipulate the ‘arr’ array.
• Lower and upper limits, defined as ‘lower_limit’ and ‘upper_limit’, guide the constraints.
• A copy of the original array, `clipped_arr`, is created.
• The `np.where` function is used to set values below ‘lower_limit’ to ‘lower_limit’.
• Another `np.where` operation ensures values above ‘upper_limit’ are capped at ‘upper_limit’.
• The resulting array, reflecting applied constraints, is stored in ‘clipped_arr’.
• The modified array is then printed, showcasing the impact of the specified lower and upper limits.

I hope this explanation proves helpful in understanding the code and its applications.