Source code for bigframes.operations.structs

# Copyright 2023 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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from __future__ import annotations

import bigframes_vendored.pandas.core.arrays.arrow.accessors as vendoracessors
import pandas as pd

from bigframes.core import backports, log_adapter
import bigframes.dataframe
import bigframes.operations
import bigframes.series


[docs] @log_adapter.class_logger class StructAccessor(vendoracessors.StructAccessor): __doc__ = vendoracessors.StructAccessor.__doc__
[docs] def __init__(self, data: bigframes.series.Series): self._data = data
[docs] def field(self, name_or_index: str | int) -> bigframes.series.Series: series = self._data._apply_unary_op( bigframes.operations.StructFieldOp(name_or_index) ) if isinstance(name_or_index, str): name = name_or_index else: struct_field = self._data._dtype.pyarrow_dtype[name_or_index] name = struct_field.name return series.rename(name)
[docs] def explode(self) -> bigframes.dataframe.DataFrame: import bigframes.pandas pa_type = self._data._dtype.pyarrow_dtype return bigframes.pandas.concat( [ self.field(field.name) for field in backports.pyarrow_struct_type_fields(pa_type) ], axis="columns", )
@property def dtypes(self) -> pd.Series: pa_type = self._data._dtype.pyarrow_dtype return pd.Series( data=[ pd.ArrowDtype(field.type) for field in backports.pyarrow_struct_type_fields(pa_type) ], index=[ field.name for field in backports.pyarrow_struct_type_fields(pa_type) ], )
[docs] @log_adapter.class_logger class StructFrameAccessor(vendoracessors.StructFrameAccessor): __doc__ = vendoracessors.StructAccessor.__doc__
[docs] def __init__(self, data: bigframes.dataframe.DataFrame) -> None: self._parent = data
[docs] def explode(self, column, *, separator: str = ".") -> bigframes.dataframe.DataFrame: df = self._parent column_labels = bigframes.core.explode.check_column(column) for label in column_labels: position = df.columns.to_list().index(label) df = df.drop(columns=label) subfields = self._parent[label].struct.explode() for subfield in reversed(subfields.columns): df.insert( position, f"{label}{separator}{subfield}", subfields[subfield] ) return df