How To Resolve TypeError: Cannot Unpack Non-Iterable numpy.float64 Object In Python

While programming, you have probably encountered the TypeError: cannot unpack non-iterable numpy.float64 object. In this article, I will give you the cause and three solutions: Unpack on a numpy array, use a try/except block, and reduce the number of variables used to unpack.

What causes the TypeError: cannot unpack non-iterable numpy.float64 object?

Numpy supports more arithmetic-related data types than other arithmetic data types in Python. NumPy numeric types are instances of dtype objects (data types), each with distinct characteristics. Including type numpy.float64: float: sign bit, 11-bit exponent, 52-bit mantissa.

TypeError: Python throws this error when you perform an unsupported operation on an object with an invalid data type.

The TypeError: cannot unpack non-iterable numpy.float64 object happens because the numpy.float64 object could not be packing.

Example:

import numpy as np

myFloat = np. float64 (2.4)
result1, result2 = myFloat

print(result1)
print(result2)

Output:

Traceback (most recent call last):
 File "./prog.py", line 4, in <module>
TypeError: cannot unpack non-iterable numpy.float64 object

How to solve this error?

Use numpy array

You can declare numpy.float64 objects as a function and then packed.

Syntax:

numpy.array(object, dtype=None, *, copy=True, order='K', subok=False, ndmin=0, like=None)

Example:

• Import the numpy module.
• Create a numpy array of the elements. In the array, I want to type numpy.float64, so dtype=np.float64.
• Unpack the numpy array and output the array’s numpy.float64 objects.

import numpy as np

myArray = np.array([1.2, 2.4, 3.4], dtype = np.float64)
result1, result2, result3 = myArray

print('Result 1:', result1)
print('Result 2:', result2)
print('Result 3:', result3)

Output:

Result 1: 1.2
Result 2: 2.4
Result 3: 3.4

Use a try/except block to check for exceptions

Example:

• Import the numpy module.
• Initialize a numpy.float64 object.
• The code between the first try-except clause is executed. If no exception occurs, only the try clause will run. The except clause will not run. If a KeyError exception occurs, only the except clause runs.

import numpy as np

myFloat = np.float64(2.4)

try:
    if type(myFloat) is not float :
        result1, result2 = myFloat
        print(result1, result2)
        
except TypeError:
    print('Recheck could not unpack the object.')

Output:

Recheck could not unpack the object.

Reduce the number of variables used to unpack

Example:

• Create a numpy.float64 object.
• Perform unpacking assigning only one variable to that numpy.float64 value will fix the error.

import numpy as np

myFloat = np.float64(2.4)

# Do the unpacking of only one variable
result1= myFloat

print('Result:', result1)

Output:

Result: 2.4

Summary

This is all I have to say about the TypeError: cannot unpack non-iterable numpy.float64 object in Python error. Method 1 and method 2 are easy to understand. You can use it for this problem. If there is a part that needs to be more reasonable and convincing enough, and I hope to understand, we will try to improve our article.

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Jason Wilson

My name is Jason Wilson, you can call me Jason. My major is information technology, and I am proficient in C++, Python, and Java. I hope my writings are useful to you while you study programming languages.

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Name of the university: HHAU
Major: IT
Programming Languages: C++, Python, Java