pyarrow.FixedShapeTensorType#
- class pyarrow.FixedShapeTensorType#
Bases:
BaseExtensionType
Concrete class for fixed shape tensor extension type.
Examples
Create an instance of fixed shape tensor extension type:
>>> import pyarrow as pa >>> pa.fixed_shape_tensor(pa.int32(), [2, 2]) FixedShapeTensorType(extension<arrow.fixed_shape_tensor[value_type=int32, shape=[2,2]]>)
Create an instance of fixed shape tensor extension type with permutation:
>>> tensor_type = pa.fixed_shape_tensor(pa.int8(), (2, 2, 3), ... permutation=[0, 2, 1]) >>> tensor_type.permutation [0, 2, 1]
- __init__(*args, **kwargs)#
Methods
__init__
(*args, **kwargs)equals
(self, other, *[, check_metadata])Return true if type is equivalent to passed value.
field
(self, i)- Parameters:
to_pandas_dtype
(self)Return the equivalent NumPy / Pandas dtype.
wrap_array
(self, storage)Wrap the given storage array as an extension array.
Attributes
The bit width of the extension type.
The byte width of the extension type.
Explicit names of the dimensions.
The extension type name.
If True, the number of expected buffers is only lower-bounded by num_buffers.
Number of data buffers required to construct Array type excluding children.
The number of child fields.
Indices of the dimensions ordering.
Shape of the tensors.
The underlying storage type.
Data type of an individual tensor.
- bit_width#
The bit width of the extension type.
- byte_width#
The byte width of the extension type.
- dim_names#
Explicit names of the dimensions.
- equals(self, other, *, check_metadata=False)#
Return true if type is equivalent to passed value.
- Parameters:
- Returns:
- is_equalbool
Examples
>>> import pyarrow as pa >>> pa.int64().equals(pa.string()) False >>> pa.int64().equals(pa.int64()) True
- extension_name#
The extension type name.
- has_variadic_buffers#
If True, the number of expected buffers is only lower-bounded by num_buffers.
Examples
>>> import pyarrow as pa >>> pa.int64().has_variadic_buffers False >>> pa.string_view().has_variadic_buffers True
- id#
- num_buffers#
Number of data buffers required to construct Array type excluding children.
Examples
>>> import pyarrow as pa >>> pa.int64().num_buffers 2 >>> pa.string().num_buffers 3
- num_fields#
The number of child fields.
Examples
>>> import pyarrow as pa >>> pa.int64() DataType(int64) >>> pa.int64().num_fields 0 >>> pa.list_(pa.string()) ListType(list<item: string>) >>> pa.list_(pa.string()).num_fields 1 >>> struct = pa.struct({'x': pa.int32(), 'y': pa.string()}) >>> struct.num_fields 2
- permutation#
Indices of the dimensions ordering.
- shape#
Shape of the tensors.
- storage_type#
The underlying storage type.
- to_pandas_dtype(self)#
Return the equivalent NumPy / Pandas dtype.
Examples
>>> import pyarrow as pa >>> pa.int64().to_pandas_dtype() <class 'numpy.int64'>
- value_type#
Data type of an individual tensor.
- wrap_array(self, storage)#
Wrap the given storage array as an extension array.
- Parameters:
- storage
Array
orChunkedArray
- storage
- Returns:
- array
Array
orChunkedArray
Extension array wrapping the storage array
- array