How to Fix numpy.float64 Object Cannot be Interpreted as an Integer

In Python, a TypeError is an exception occurs when the data type of the specified object in an operation is inappropriate. When working with numpy Arrays, if you try to pass the float value to a function that expects integer values, you will encounter a TypeError – ‘numpy.float64’ object cannot be interpreted as an integer. In this guide, we will discuss how to reproduce this error and fix it using astype() and int() methods.

Error: ‘numpy.float64’ object cannot be interpreted as an integer

The range() function in Python is used to return a sequence of numbers that starts from 0 and increments by 1. It accepts only integers, not float values. If we try to pass the float values to this function, it will result in an error.

To demonstrate, create a numpy array named camp_budgets with five values and try to display the range of values at each index by iterating the array inside the for loop.

Output

You can see that TypeError is encountered while converting float values in the range.

Solution 1: Using astype()

The astype() method is used for casting the given object to a specified data type. It takes the data type to be converted as the parameter. Here, we need to convert the float type to an integer (parameter – int). Let’s create the same array as above and display the range of values at each index by converting it into a range of values with the range() function.

Output

We can see that the TypeError is fixed and a range of values are displayed.

Solution 2: Using int()

The int() function in Python is used to convert the given string or number into an integer. Here, the input is float. So, we need to pass the parameter as float to this function.

Let’s create the same array as above and display the range of values at each index by converting it into a range of values with the range() function. Typecase the iterator with int() by passing as a parameter to this function.

Output

We can see that the TypeError is fixed and a range of values are displayed.

Conclusion

First, we reproduced the TypeError – ‘numpy.float64’ object cannot be interpreted as an integer by creating a numpy array with float values and converting it into a range of values. Next, we discovered two solutions that will convert float values to integers while creating the range, using the astype() and int() functions.