feat: add GeoSeries.from_xy()

[arwas11]

Thank you for opening a Pull Request! Before submitting your PR, there are a few things you can do to make sure it goes smoothly:

• Make sure to open an issue as a bug/issue before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea
• Ensure the tests and linter pass
• Code coverage does not decrease (if any source code was changed)
• Appropriate docs were updated (if necessary)
  • from_xy: screen/3pW4NWMsvfvVeYd, screen/3SimxdQU93zjinv, screen/rfsK45NBkxkUdz7

Fixes #393394365 🦕

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[tswast]

Thanks!

[tswast]

Doctest failures:

FAILED third_party/bigframes_vendored/pandas/core/frame.py::frame.DataFrame.map
FAILED third_party/bigframes_vendored/pandas/core/frame.py::frame.DataFrame.apply
FAILED third_party/bigframes_vendored/pandas/core/series.py::series.Series.apply
FAILED third_party/bigframes_vendored/pandas/core/series.py::series.Series.map
FAILED third_party/bigframes_vendored/pandas/core/series.py::series.Series.mask
FAILED bigframes/dataframe.py::bigframes.dataframe.DataFrame.map
FAILED bigframes/dataframe.py::bigframes.dataframe.DataFrame.applymap
FAILED bigframes/pandas/io/api.py::bigframes.pandas.io.api.read_gbq_function
FAILED bigframes/session/__init__.py::bigframes.session.Session.read_gbq_function

These don't appear to be related to this change.

[tswast]

Notebook test failures:

Failed: generative_ai/bq_dataframes_llm_kmeans.ipynb
Failed: geo/geoseries.ipynb
Failed: getting_started/getting_started_bq_dataframes.ipynb
Failed: location/regionalized.ipynb_us-central1
Failed: location/regionalized.ipynb_us
Failed: remote_functions/remote_function.ipynb
Failed: remote_functions/remote_function_usecases.ipynb

The geoseries.ipynb one does look related. Let's fix before merging.

error

__ /tmpfs/src/github/python-bigquery-dataframes/notebooks/geo/geoseries.ipynb __
---------------------------------------------------------------------------
bigframes.geopandas.GeoSeries.from_xy(geo_points.x, geo_points.y)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
File /[tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/core/formatters.py:770](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/core/formatters.py?l=770), in PlainTextFormatter.__call__(self, obj)
763 stream = StringIO()
764 printer = pretty.RepresentationPrinter(stream, self.verbose,
765 self.max_width, self.newline,
766 max_seq_length=self.max_seq_length,
767 singleton_pprinters=self.singleton_printers,
768 type_pprinters=self.type_printers,
769 deferred_pprinters=self.deferred_printers)
--> 770 printer.pretty(obj)
771 printer.flush()
772 return stream.getvalue()
File /[tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/lib/pretty.py:419](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/lib/pretty.py?l=419), in RepresentationPrinter.pretty(self, obj)
408 return meth(obj, self, cycle)
409 if (
410 cls is not object
411 # check if cls defines __repr__
(...)
417 and callable(_safe_getattr(cls, "__repr__", None))
418 ):
--> 419 return _repr_pprint(obj, self, cycle)
421 return _default_pprint(obj, self, cycle)
422 finally:
File /[tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/lib/pretty.py:794](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/.nox/notebook-3-10/lib/python3.10/site-packages/IPython/lib/pretty.py?l=794), in _repr_pprint(obj, p, cycle)
792 """A pprint that just redirects to the normal repr function."""
793 # Find newlines and replace them with p.break_()
--> 794 output = repr(obj)
795 lines = output.splitlines()
796 with p.group():
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/log_adapter.py:147](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/log_adapter.py?l=147), in method_logger.<locals>.wrapper(self, *args, **kwargs)
144 _call_stack.append(full_method_name)
146 try:
--> 147 return method(self, *args, **kwargs)
148 except (NotImplementedError, TypeError) as e:
149 # Log method parameters that are implemented in pandas but either missing (TypeError)
150 # or not fully supported (NotImplementedError) in BigFrames.
151 # Logging is currently supported only when we can access the bqclient through
152 # self._block.expr.session.bqclient. Also, to avoid generating multiple queries
153 # because of internal calls, we log only when the method is directly invoked.
154 if hasattr(self, "_block") and len(_call_stack) == 1:
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/series.py:346](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/series.py?l=346), in Series.__repr__(self)
343 return formatter.repr_query_job(self._compute_dry_run())
345 self._cached()
--> 346 pandas_df, _, query_job = self._block.retrieve_repr_request_results(max_results)
347 self._set_internal_query_job(query_job)
349 pd_series = pandas_df.iloc[:, 0]
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/blocks.py:1453](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/blocks.py?l=1453), in Block.retrieve_repr_request_results(self, max_results)
1445 """
1446 Retrieves a pandas dataframe containing only max_results many rows for use
1447 with printing methods.
1448 1449 Returns a tuple of the dataframe and the overall number of rows of the query.
1450 """
1452 # head caches full underlying expression, so row_count will be free after
-> 1453 head_result = self.session._executor.head(self.expr, max_results)
1454 count = self.session._executor.get_row_count(self.expr)
1456 arrow = head_result.to_arrow_table()
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py:401](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py?l=401), in BigQueryCachingExecutor.head(self, array_value, n_rows)
399 maybe_row_count = self._local_get_row_count(array_value)
400 if (maybe_row_count is not None) and (maybe_row_count <= n_rows):
--> 401 return self.execute(array_value, ordered=True)
403 if not self.strictly_ordered and not array_value.node.explicitly_ordered:
404 # No user-provided ordering, so just get any N rows, its faster!
405 return self.peek(array_value, n_rows)
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py:286](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py?l=286), in BigQueryCachingExecutor.execute(self, array_value, ordered, col_id_overrides, use_explicit_destination, get_size_bytes, page_size, max_results)
283 # Runs strict validations to ensure internal type predictions and ibis are completely in sync
284 # Do not execute these validations outside of testing suite.
285 if "PYTEST_CURRENT_TEST" in os.environ and len(col_id_overrides) == 0:
--> 286 self._validate_result_schema(array_value, iterator.schema)
288 return ExecuteResult(
289 arrow_batches=iterator_supplier,
290 schema=adjusted_schema,
(...)
293 total_rows=iterator.total_rows,
294 )
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py:648](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/session/executor.py?l=648), in BigQueryCachingExecutor._validate_result_schema(self, array_value, bq_schema)
642 def _validate_result_schema(
643 self,
644 array_value: bigframes.core.ArrayValue,
645 bq_schema: list[bigquery.SchemaField],
646 ):
647 actual_schema = tuple(bq_schema)
--> 648 ibis_schema = bigframes.core.compile.test_only_ibis_inferred_schema(
649 self.replace_cached_subtrees(array_value.node)
650 )
651 internal_schema = array_value.schema
652 if not bigframes.features.PANDAS_VERSIONS.is_arrow_list_dtype_usable:
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/api.py:83](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/api.py?l=83), in test_only_ibis_inferred_schema(node)
81 node = _STRICT_COMPILER._preprocess(node)
82 compiled = _STRICT_COMPILER.compile_node(node)
---> 83 items = tuple(
84 bigframes.core.schema.SchemaItem(name, compiled.get_column_type(ibis_id))
85 for name, ibis_id in zip(node.schema.names, compiled.column_ids)
86 )
87 return bigframes.core.schema.ArraySchema(items)
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/api.py:84](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/api.py?l=84), in <genexpr>(.0)
81 node = _STRICT_COMPILER._preprocess(node)
82 compiled = _STRICT_COMPILER.compile_node(node)
83 items = tuple(
---> 84 bigframes.core.schema.SchemaItem(name, compiled.get_column_type(ibis_id))
85 for name, ibis_id in zip(node.schema.names, compiled.column_ids)
86 )
87 return bigframes.core.schema.ArraySchema(items)
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/compiled.py:154](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/compiled.py?l=154), in UnorderedIR.get_column_type(self, key)
147 def get_column_type(self, key: str) -> bigframes.dtypes.Dtype:
148 ibis_type = typing.cast(
149 bigframes.core.compile.ibis_types.IbisDtype,
150 self._get_ibis_column(key).type(),
151 )
152 return typing.cast(
153 bigframes.dtypes.Dtype,
--> 154 bigframes.core.compile.ibis_types.ibis_dtype_to_bigframes_dtype(ibis_type),
155 )
File /[tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/ibis_types.py:307](https://cs.corp.google.com/piper///depot/google3/tmpfs/src/github/python-bigquery-dataframes/bigframes/core/compile/ibis_types.py?l=307), in ibis_dtype_to_bigframes_dtype(ibis_dtype)
305 return IBIS_TO_BIGFRAMES[ibis_dtypes.string]
306 else:
--> 307 raise ValueError(
308 f"Unexpected Ibis data type {ibis_dtype}. {constants.FEEDBACK_LINK}"
309 )
ValueError: Unexpected Ibis data type point:geometry. Share your usecase with the BigQuery DataFrames team at the [https://bit.ly/bigframes-feedback](https://www.google.com/url?q=https://bit.ly/bigframes-feedback&sa=D) survey.You are currently running BigFrames version 1.35.0
Learn more about nbmake at [https://github.com/treebeardtech/nbmake](https://www.google.com/url?q=https://github.com/treebeardtech/nbmake&sa=D)

[tswast]

Per the notebook failure, please add some logic to ibis_dtype_to_bigframes_dtype looking for all ibis geography-y types and returning the gpd.array.GeometryDtype().

Something like

ifisinstance(ibis_dtype, ibis_dtypes.GeoSpatial):
returngpd.array.GeometryDtype()

around here: https://github.com/googleapis/python-bigquery-dataframes/blob/b9bdca8285ee54fecf3795fbf3cbea6f878ee8ca/bigframes/core/compile/ibis_types.py#L284

[tswast]

The reason we can look for ibis_dtypes.GeoSpatial is that all the geography-y types have it as a superclass. See: https://github.com/googleapis/python-bigquery-dataframes/blob/b9bdca8285ee54fecf3795fbf3cbea6f878ee8ca/third_party/bigframes_vendored/ibis/expr/datatypes/core.py#L974

[tswast]

Marking as request changes to cover the ibis_dtype_to_bigframes_dtype change for the notebook fix before merging.