What is Floating point error and how to solve it?

Introduction

In this blog, we have discussed What is Floating point error and how to solve it? If you’ve ever tried to do any sort of numerical computation in Python, you’ve probably come across the dreaded “floating point error.” This error occurs when the computer is trying to store a number that is too large or too small for the available memory. The result is usually an approximation of the true value. One of the most common places you’ll see floating point errors is when you’re trying to compute the average of a list of numbers.  The reason is that the computer is storing the intermediate values in memory, and those values can only be so accurate. When you divide the total by the length of the list, you’re effectively losing precision.

 

 

Solutions to Avoid Floating Point Error

“Floating point error” in Python is often caused by division by zero, e.g.: 1/0 This results in an error because the division by zero produces an undefined result. To fix this error, you can use the Python built-in function float(), e.g.: float(1)/0 This will return the float Infinity, which is the correct result for division by zero.

 

There are a few ways to avoid this error. One is to use a different data type that can hold larger numbers. Another is to use a library that can handle big numbers. whichever way you choose to fix the error, it’s important to understand what causes it in the first place. Floating point errors usually happen when you’re working with very large or very small numbers.

 

Python uses a data type called “floating point” to represent numbers with decimal points. The problem is that floating point numbers can’t always be represented exactly. So, when you try to do something with a number that’s too big or too small, you’ll get an error. You can use the Decimal module from the Python standard library. This module allows you to specify the precision of your calculations.

 

Example :

1.2-0.3

This line of code must give you 0.9 but instead, it gives 0.8999 as the answer.

 

 

Also, read – What is IndexError and how to solve it?

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