pyarrow.UnionType#
- classpyarrow.UnionType#
Bases:
DataTypeBase class for union data types.
Examples
Create an instance of a dense UnionType using
pa.union:>>>importpyarrowaspa>>>pa.union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())],...mode=pa.lib.UnionMode_DENSE),(DenseUnionType(dense_union<a: fixed_size_binary[10]=0, b: string=1>),)
Create an instance of a dense UnionType using
pa.dense_union:>>>pa.dense_union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())])DenseUnionType(dense_union<a: fixed_size_binary[10]=0, b: string=1>)
Create an instance of a sparse UnionType using
pa.union:>>>pa.union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())],...mode=pa.lib.UnionMode_SPARSE),(SparseUnionType(sparse_union<a: fixed_size_binary[10]=0, b: string=1>),)
Create an instance of a sparse UnionType using
pa.sparse_union:>>>pa.sparse_union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())])SparseUnionType(sparse_union<a: fixed_size_binary[10]=0, b: string=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)Return a child field by its numeric index.
to_pandas_dtype(self)Return the equivalent NumPy / Pandas dtype.
Attributes
Bit width for fixed width type.
Byte width for fixed width type.
If True, the number of expected buffers is only lower-bounded by num_buffers.
The mode of the union ("dense" or "sparse").
Number of data buffers required to construct Array type excluding children.
The number of child fields.
The type code to indicate each data type in this union.
- bit_width#
Bit width for fixed width type.
Examples
>>>importpyarrowaspa>>>pa.int64()DataType(int64)>>>pa.int64().bit_width64
- byte_width#
Byte width for fixed width type.
Examples
>>>importpyarrowaspa>>>pa.int64()DataType(int64)>>>pa.int64().byte_width8
- equals(self,other,*,check_metadata=False)#
Return true if type is equivalent to passed value.
- Parameters:
- Returns:
- is_equalbool
Examples
>>>importpyarrowaspa>>>pa.int64().equals(pa.string())False>>>pa.int64().equals(pa.int64())True
- field(self,i)→Field#
Return a child field by its numeric index.
- Parameters:
- i
int
- i
- Returns:
Examples
>>>importpyarrowaspa>>>union=pa.sparse_union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())])>>>union[0]pyarrow.Field<a: fixed_size_binary[10]>
- has_variadic_buffers#
If True, the number of expected buffers is onlylower-bounded by num_buffers.
Examples
>>>importpyarrowaspa>>>pa.int64().has_variadic_buffersFalse>>>pa.string_view().has_variadic_buffersTrue
- id#
- mode#
The mode of the union (“dense” or “sparse”).
Examples
>>>importpyarrowaspa>>>union=pa.sparse_union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())])>>>union.mode'sparse'
- num_buffers#
Number of data buffers required to construct Array typeexcluding children.
Examples
>>>importpyarrowaspa>>>pa.int64().num_buffers2>>>pa.string().num_buffers3
- num_fields#
The number of child fields.
Examples
>>>importpyarrowaspa>>>pa.int64()DataType(int64)>>>pa.int64().num_fields0>>>pa.list_(pa.string())ListType(list<item: string>)>>>pa.list_(pa.string()).num_fields1>>>struct=pa.struct({'x':pa.int32(),'y':pa.string()})>>>struct.num_fields2
- to_pandas_dtype(self)#
Return the equivalent NumPy / Pandas dtype.
Examples
>>>importpyarrowaspa>>>pa.int64().to_pandas_dtype()<class 'numpy.int64'>
- type_codes#
The type code to indicate each data type in this union.
Examples
>>>importpyarrowaspa>>>union=pa.sparse_union([pa.field('a',pa.binary(10)),pa.field('b',pa.string())])>>>union.type_codes[0, 1]