pyarrow.FixedSizeBinaryType

class pyarrow.FixedSizeBinaryType

Bases: DataType

Concrete class for fixed-size binary data types.

Examples

Create an instance of fixed-size binary type:

>>> import pyarrow as pa
>>> pa.binary(3)
FixedSizeBinaryType(fixed_size_binary[3])
__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.

Attributes

bit_width

Bit width for fixed width type.

byte_width

The binary size in bytes.

id

num_buffers

Number of data buffers required to construct Array type excluding children.

num_fields

The number of child fields.

bit_width

Bit width for fixed width type.

Examples

>>> import pyarrow as pa
>>> pa.int64()
DataType(int64)
>>> pa.int64().bit_width
64
byte_width

The binary size in bytes.

Examples

>>> import pyarrow as pa
>>> t = pa.binary(3)
>>> t.byte_width
3
equals(self, other, *, check_metadata=False)

Return true if type is equivalent to passed value.

Parameters:
otherDataType or str convertible to DataType
check_metadatabool

Whether nested Field metadata equality should be checked as well.

Returns:
is_equalbool

Examples

>>> import pyarrow as pa
>>> pa.int64().equals(pa.string())
False
>>> pa.int64().equals(pa.int64())
True
field(self, i) Field
Parameters:
iint
Returns:
pyarrow.Field
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
to_pandas_dtype(self)

Return the equivalent NumPy / Pandas dtype.

Examples

>>> import pyarrow as pa
>>> pa.int64().to_pandas_dtype()
<class 'numpy.int64'>