Which is not an example of a numerical value that is recognized by the Python interpreter? Group of answer choices A. 3.125e-24 B. 0.265 C. 6.0e+1234 D. 12345678900987654321
The correct answer and explanation is:
The correct answer is C. 6.0e+1234.
Explanation:
In Python, numerical values include integers, floating-point numbers, and numbers in scientific notation. Python can handle very large and very small numbers, but with some limits on floating-point numbers due to how they are stored internally.
Let’s analyze each option:
A. 3.125e-24
This is a floating-point number written in scientific notation, meaning 3.125×10−243.125 \times 10^{-24}. Python recognizes this as a valid floating-point literal and can handle very small numbers like this.
B. 0.265
This is a simple decimal floating-point number. Python recognizes this as a valid float.
C. 6.0e+1234
This represents 6.0×1012346.0 \times 10^{1234}, an extremely large floating-point number. Although it is syntactically valid, the value exceeds the maximum floating-point number that Python can represent. Python’s floating-point numbers are based on the IEEE 754 double precision standard, which typically allows exponents up to around 1030810^{308}. An exponent of 1234 is well beyond this limit. Attempting to use this number will result in Python interpreting it as positive infinity (inf), which is a special floating-point value, not a normal number. Thus, while the literal is accepted syntactically, it is not recognized as a normal finite numerical value by the Python interpreter.
D. 12345678900987654321
This is a very large integer. Python 3 supports arbitrarily large integers without overflow by automatically converting them to a long integer type internally. Therefore, this number is valid and recognized by Python as a proper integer.
In summary, option C is the one that is not properly recognized as a finite numerical value in Python because the exponent is too large for the floating-point representation. It will be treated as infinity, which makes it not a valid finite numerical value in practice.