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the special values NaN, -INF, +INF, and negative zero are also supported Multiple valid types ( VisibleString, PrintableString, GeneralString, UniversalString, UTF8String ) Data specifications SET OF (unordered) and SEQUENCE OF (guaranteed order)
The comparison predicates are either signaling or non-signaling on quiet NaN operands; the signaling versions signal the invalid-operation exception for such comparisons (i.e., by default, this just sets the corresponding status flag in addition to the behavior of the non-signaling versions). The equality and inequality predicates are non ...
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.
NaN is sortable. NaN is treated as if it had a larger absolute value than Infinity (or any other floating-point numbers). (−NaN < −Infinity; +Infinity < +NaN.) qNaN and sNaN are treated as if qNaN had a larger absolute value than sNaN. (−qNaN < −sNaN; +sNaN < +qNaN.) NaN is then sorted according to the payload.
In Python's optional static type annotations, the general bottom type is typing.Never (introduced in version 3.11), [10] while typing.NoReturn (introduced in version 3.5) can be used as the return type of non-returning functions specifically (and doubled as the general bottom type prior to the introduction of Never). [11]
pow (whose intent is to return a non-NaN result when the exponent is an integer, like pown) treats 0 0 as 1. powr treats 0 0 as NaN (Not-a-Number) due to the indeterminate form; see § Continuous exponents. The pow variant is inspired by the pow function from C99, mainly for compatibility. [26] It is useful mostly for languages with a single ...
The IEEE 754 standard requires the same rounding to be applied to all fundamental algebraic operations, including square root and conversions, when there is a numeric (non-NaN) result. It means that the results of IEEE 754 operations are completely determined in all bits of the result, except for the representation of NaNs.
Subnormal numbers provide the guarantee that addition and subtraction of floating-point numbers never underflows; two nearby floating-point numbers always have a representable non-zero difference. Without gradual underflow, the subtraction a − b can underflow and produce zero even though the values are not equal.