pyarrow.Time32Type — Apache Arrow v20.0.0 (original) (raw)

class pyarrow.Time32Type#

Bases: DataType

Concrete class for time32 data types.

Supported time unit resolutions are ‘s’ [second] and ‘ms’ [millisecond].

Examples

Create an instance of time32 type:

import pyarrow as pa pa.time32('ms') Time32Type(time32[ms])

__init__(*args, **kwargs)#

Methods

Attributes

bit_width#

Bit width for fixed width type.

Examples

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

byte_width#

Byte width for fixed width type.

Examples

import pyarrow as pa pa.int64() DataType(int64) pa.int64().byte_width 8

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

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

to_pandas_dtype(self)#

Return the equivalent NumPy / Pandas dtype.

Examples

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

unit#

The time unit (‘s’ or ‘ms’).

Examples

import pyarrow as pa t = pa.time32('ms') t.unit 'ms'