pyarrow.StructType#
- class pyarrow.StructType#
Bases:
DataType
Concrete class for struct data types.
StructType
supports direct indexing using[...]
(implemented via__getitem__
) to access its fields. It will return the struct field with the given index or name.Examples
>>> import pyarrow as pa
Accessing fields using direct indexing:
>>> struct_type = pa.struct({'x': pa.int32(), 'y': pa.string()}) >>> struct_type[0] pyarrow.Field<x: int32> >>> struct_type['y'] pyarrow.Field<y: string>
Accessing fields using
field()
:>>> struct_type.field(1) pyarrow.Field<y: string> >>> struct_type.field('x') pyarrow.Field<x: int32>
# Creating a schema from the struct type’s fields: >>> pa.schema(list(struct_type)) x: int32 y: string
- __init__(*args, **kwargs)#
Methods
__init__
(*args, **kwargs)equals
(self, other, *[, check_metadata])Return true if type is equivalent to passed value.
field
(self, i)Select a field by its column name or numeric index.
get_all_field_indices
(self, name)Return sorted list of indices for the fields with the given name.
get_field_index
(self, name)Return index of the unique field with the given name.
to_pandas_dtype
(self)Return the equivalent NumPy / Pandas dtype.
Attributes
Bit width for fixed width type.
Byte width for fixed width type.
Lists all fields within the StructType.
Lists the field names.
Number of data buffers required to construct Array type excluding children.
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#
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
- field(self, i) Field #
Select a field by its column name or numeric index.
- Parameters:
- Returns:
Examples
>>> import pyarrow as pa >>> struct_type = pa.struct({'x': pa.int32(), 'y': pa.string()})
Select the second field:
>>> struct_type.field(1) pyarrow.Field<y: string>
Select the field named ‘x’:
>>> struct_type.field('x') pyarrow.Field<x: int32>
- fields#
Lists all fields within the StructType.
Examples
>>> import pyarrow as pa >>> struct_type = pa.struct([('a', pa.int64()), ('b', pa.float64()), ('c', pa.string())]) >>> struct_type.fields [pyarrow.Field<a: int64>, pyarrow.Field<b: double>, pyarrow.Field<c: string>]
- get_all_field_indices(self, name)#
Return sorted list of indices for the fields with the given name.
Examples
>>> import pyarrow as pa >>> struct_type = pa.struct({'x': pa.int32(), 'y': pa.string()}) >>> struct_type.get_all_field_indices('x') [0]
- get_field_index(self, name)#
Return index of the unique field with the given name.
- Parameters:
- name
str
The name of the field to look up.
- name
- Returns:
- index
int
The index of the field with the given name; -1 if the name isn’t found or there are several fields with the given name.
- index
Examples
>>> import pyarrow as pa >>> struct_type = pa.struct({'x': pa.int32(), 'y': pa.string()})
Index of the field with a name ‘y’:
>>> struct_type.get_field_index('y') 1
Index of the field that does not exist:
>>> struct_type.get_field_index('z') -1
- id#
- names#
Lists the field names.
Examples
>>> import pyarrow as pa >>> struct_type = pa.struct([('a', pa.int64()), ('b', pa.float64()), ('c', pa.string())]) >>> struct_type.names ['a', 'b', 'c']
- 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'>