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