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Bases: DataType
Concrete class for list view data types.
Examples
Create an instance of ListViewType:
>>> import pyarrow as pa
>>> pa.list_view(pa.string())
ListViewType(list_view<item: string>)
Methods
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Return true if type is equivalent to passed value. |
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Return the equivalent NumPy / Pandas dtype. |
Attributes
Bit width for fixed width type. |
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Byte width for fixed width type. |
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If True, the number of expected buffers is only lower-bounded by num_buffers. |
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Number of data buffers required to construct Array type excluding children. |
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The number of child fields. |
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The field for list view values. |
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The data type of list view values. |
Bit width for fixed width type.
Examples
>>> import pyarrow as pa
>>> pa.int64()
DataType(int64)
>>> pa.int64().bit_width
64
Byte width for fixed width type.
Examples
>>> import pyarrow as pa
>>> pa.int64()
DataType(int64)
>>> pa.int64().byte_width
8
Return true if type is equivalent to passed value.
Examples
>>> import pyarrow as pa
>>> pa.int64().equals(pa.string())
False
>>> pa.int64().equals(pa.int64())
True
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
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
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
Return the equivalent NumPy / Pandas dtype.
Examples
>>> import pyarrow as pa
>>> pa.int64().to_pandas_dtype()
<class 'numpy.int64'>
The field for list view values.
Examples
>>> import pyarrow as pa
>>> pa.list_view(pa.string()).value_field
pyarrow.Field<item: string>
The data type of list view values.
Examples
>>> import pyarrow as pa
>>> pa.list_view(pa.string()).value_type
DataType(string)
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