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1.24
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Array objects
The N-dimensional array (
ndarray
)
Scalars
Data type objects (
dtype
)
numpy.dtype
numpy.dtype.type
numpy.dtype.kind
numpy.dtype.char
numpy.dtype.num
numpy.dtype.str
numpy.dtype.name
numpy.dtype.itemsize
numpy.dtype.byteorder
numpy.dtype.fields
numpy.dtype.names
numpy.dtype.subdtype
numpy.dtype.shape
numpy.dtype.hasobject
numpy.dtype.flags
numpy.dtype.isbuiltin
numpy.dtype.isnative
numpy.dtype.descr
numpy.dtype.alignment
numpy.dtype.base
numpy.dtype.metadata
numpy.dtype.newbyteorder
numpy.dtype.__reduce__
numpy.dtype.__setstate__
numpy.dtype.__class_getitem__
numpy.dtype.__ge__
numpy.dtype.__gt__
numpy.dtype.__le__
numpy.dtype.__lt__
Indexing routines
Iterating Over Arrays
Standard array subclasses
Masked arrays
The array interface protocol
Datetimes and Timedeltas
Array API Standard Compatibility
Constants
Universal functions (
ufunc
)
Routines
Typing (
numpy.typing
)
Global State
Packaging (
numpy.distutils
)
NumPy Distutils - Users Guide
Status of
numpy.distutils
and migration advice
NumPy C-API
CPU/SIMD Optimizations
NumPy security
NumPy and SWIG
On this page
dtype.__ge__
numpy.dtype.__ge__
#
method
dtype.
__ge__
(
value
,
/
)
#
Return self>=value.