The main reason why Typeerror: float object cannot be interpreted as an integer occurs is using float datatype in the place of int datatype in functions like range(), bin(), etc. Although we can first convert the float value to integer datatype and then use them in these functions to fix this issue.
Typeerror: float object cannot be interpreted as an integer ( Solution multiple scenarios) –
The simplest fix for this issue is typecasting of float datatype to integer datatype. Let’s see this solution in various contexts.
Case 1 : range() function –
range() function accepts only integer values but in case we provide them float datatype , the python interpreter will throw this error.
Solution for range() function scenario –
The easiest solution for this is to typecast float value into an integer one. This is actually a universal solution for float objects that cannot be interpreted as an integer python error.
Case 2: bin() function –
This bin() function returns the binary string for any integer parameter. But when we parametrize any float value in the place of integer value
Solution – Similar to above, we need to first convert the float to int and then pass it into the bin function.
Case 3 : chr() function scenario –
chr() function also accepts an integer parameter and converts it into a corresponding character. Let’s see with an example-
Case 4 : hex() function –
This function takes an integer and returns the hexadecimal string corresponding for the same.
The purpose of the above scenario analysis is to understand the root cause for the error float object integer interpretation. Since python is a dynamically type language so typecasting of variables is piece of cake for these scenarios. Still, we miss the same and stuck in such error situations. Hope this article is helpful for you to resolve the same. Please suggest if you need more cases to cover.
Data Science Learner Team
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