Scalars — NumPy v2.6.dev0 Manual

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Building from source

NumPy’s module structure

The N-dimensional array (ndarray)

numpy.generic.flags

numpy.generic.shape

numpy.generic.strides

numpy.generic.ndim

numpy.generic.data

numpy.generic.size

numpy.generic.itemsize

numpy.generic.base

numpy.generic.dtype

numpy.generic.real

numpy.generic.imag

numpy.generic.flat

numpy.generic.__array_interface__

numpy.generic.__array_struct__

numpy.generic.__array_priority__

numpy.generic.__array_wrap__

numpy.generic.__array__

numpy.generic.squeeze

numpy.generic.byteswap

numpy.generic.__reduce__

numpy.generic.__setstate__

numpy.generic.setflags

numpy.number.__class_getitem__

Data type objects (dtype)

Data type promotion in NumPy

Iterating over arrays

Standard array subclasses

The array interface protocol

Datetimes and timedeltas

Universal functions (ufunc)

Routines and objects by topic

Typing (numpy.typing)

Array API standard compatibility

CPU/SIMD optimizations

Global Configuration Options

Testing guidelines

Status of numpy.distutils and migration advice

Built-in scalar types#

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

Built-in scalar types#

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

format_float_positional

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

format_float_scientific

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

Built-in scalar types#

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

Structured datatypes

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

NPY_SCALAR_PRIORITY

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

numpy.ndarray.ctypes

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b

numpy.ndarray.base

Python defines only one type of a particular data class (there is only one integer type, one floating-point type, etc.). This can be convenient in applications that don’t need to be concerned with all the ways data can b