pyarrow.Time32Type#
- 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
__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 for fixed width type.
Byte width for fixed width type.
Number of data buffers required to construct Array type excluding children.
The number of child fields.
The time unit ('s' or 'ms').
- 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:
- Returns:
- is_equalbool
Examples
>>> import pyarrow as pa >>> pa.int64().equals(pa.string()) False >>> pa.int64().equals(pa.int64()) 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'