For floating-point integers (I'll give my answer in terms of IEEE double-precision), every integer between 1 and 2^53 is exactly representable. Beyond 2^53, integers that are exactly …

Why do some numbers lose accuracy when stored as floating point numbers? For example, the decimal number 9.2 can be expressed exactly as a ratio of two decimal integers (92/10), both …

Apr 11, 2012 · The values for the float data type come from having 32 bits in total to represent the number which are allocated like this: 1 bit: sign bit 8 bits: exponent p 23 bits: mantissa The …

Jul 2, 2009 · 1 The main difference between float and double is precision. Wikipedia has more info about Single precision (float) and Double precision.

Jun 29, 2009 · What are the differences between numeric, float and decimal datatypes and which should be used in which situations? For any kind of financial transaction (e.g. for salary field), …

Jul 5, 2023 · Usually, float and double are binary32 and binary64 types respectively, and long double is binary128, an x87 80-bit extended floating-point number, or represented same as …

632 [float(i) for i in lst] to be precise, it creates a new list with float values. Unlike the map approach it will work in py3k.

Dec 14, 2015 · Just wondering over here, what is the point of having a variable store an infinite value in a program? Is there any actual use and is there any case where it would be preferable …

They may be equal, but usually, a float is a 32-bit type with 24 bits of precision, the largest finite number it can store is 3.4028235e38, the smallest positive number 1.0e-45, while double is a …

Jun 9, 2019 · Numpy's dtype documentation only shows "x bits exponent, y bits mantissa" for each float type, but I couldn't translate that to exactly how many digits …