Abstract base class of all signed integer scalar types.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy

27 Elements

scipy.sparse.csgraph._tools.reconstruct_path

scipy.sparse._arrays.coo_array

scipy.signal._signaltools.correlate2d

scipy.special._orthogonal.chebyu

scipy.sparse._coo.coo_matrix

scipy.sparse._csr.csr_matrix

scipy.special._spherical_bessel.spherical_kn

scipy.special._orthogonal.jacobi

scipy.special._orthogonal.genlaguerre

scipy.special._spherical_bessel.spherical_yn

scipy.sparse._csc.csc_matrix

scipy.sparse._bsr.bsr_matrix

scipy.sparse._arrays.dia_array

scipy.special._orthogonal.chebyt

scipy.optimize._qap.quadratic_assignment

scipy.special._spherical_bessel.spherical_jn

scipy.sparse._construct.eye

scipy.special._orthogonal.laguerre

scipy.special._spherical_bessel.spherical_in

scipy.sparse.linalg._interface.aslinearoperator

scipy.special._basic.euler

scipy.sparse._dia.dia_matrix

scipy.sparse._arrays.csr_array

scipy.sparse._arrays.bsr_array

scipy.sparse._arrays.csc_array

scipy.signal.windows._windows.dpss

scipy.sparse.csgraph._tools.construct_dist_matrix

skimage

skimage.exposure.exposure.rescale_intensity

skimage.viewer.canvastools.recttool.RectangleTool

skimage.segmentation.random_walker_segmentation.random_walker

skimage.feature.brief.BRIEF

skimage.util._invert.invert

dask

dask.array.reductions.sum

dask.array.ufunc.bitwise_or

dask.array.routines.ptp

dask.array.reductions.prod

dask.array.ufunc.invert

pandas

pandas.core.dtypes.common.is_int64_dtype

pandas.core.dtypes.common.needs_i8_conversion

pandas.core.ops.missing.mask_zero_div_zero

pandas.core.reshape.reshape._Unstacker

pandas.core.frame.DataFrame

numpy

numpy.typing

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /numpy/__init__.py#None
type: <class 'type'>
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