Merge branch 'main' into main_chelsealin_sqlrefactor

Author: chelsea-lin

bigframes/core/compile/sqlglot/expressions/datetime_ops.py

@@ -371,7 +371,12 @@ def _(expr: TypedExpr, op: ops.ToDatetimeOp) -> sge.Expression:
         )
         return sge.Cast(this=result, to="DATETIME")
 
-    if expr.dtype in (dtypes.STRING_DTYPE, dtypes.TIMESTAMP_DTYPE):
+    if expr.dtype in (
+        dtypes.STRING_DTYPE,
+        dtypes.TIMESTAMP_DTYPE,
+        dtypes.DATETIME_DTYPE,
+        dtypes.DATE_DTYPE,
+    ):
         return sge.TryCast(this=expr.expr, to="DATETIME")
 
     value = expr.expr
@@ -396,7 +401,12 @@ def _(expr: TypedExpr, op: ops.ToTimestampOp) -> sge.Expression:
             "PARSE_TIMESTAMP", sge.convert(op.format), expr.expr, sge.convert("UTC")
         )
 
-    if expr.dtype in (dtypes.STRING_DTYPE, dtypes.DATETIME_DTYPE):
+    if expr.dtype in (
+        dtypes.STRING_DTYPE,
+        dtypes.DATETIME_DTYPE,
+        dtypes.TIMESTAMP_DTYPE,
+        dtypes.DATE_DTYPE,
+    ):
         return sge.func("TIMESTAMP", expr.expr)
 
     value = expr.expr

bigframes/pandas/core/methods/describe.py

@@ -56,9 +56,10 @@ def describe(
             "max",
         ]
     ).intersection(describe_block.column_labels.get_level_values(-1))
-    describe_block = describe_block.stack(override_labels=stack_cols)
-
-    return dataframe.DataFrame(describe_block).droplevel(level=0)
+    if not stack_cols.empty:
+        describe_block = describe_block.stack(override_labels=stack_cols)
+        return dataframe.DataFrame(describe_block).droplevel(level=0)
+    return dataframe.DataFrame(describe_block)
 
 
 def _describe(
@@ -120,5 +121,7 @@ def _get_aggs_for_dtype(dtype) -> list[aggregations.UnaryAggregateOp]:
         dtypes.TIME_DTYPE,
     ]:
         return [aggregations.count_op, aggregations.nunique_op]
+    elif dtypes.is_json_like(dtype) or dtype == dtypes.OBJ_REF_DTYPE:
+        return [aggregations.count_op]
     else:
         return []

tests/system/small/pandas/test_describe.py

@@ -15,6 +15,8 @@
 import pandas.testing
 import pytest
 
+import bigframes.pandas as bpd
+
 
 def test_df_describe_non_temporal(scalars_dfs):
     # TODO: supply a reason why this isn't compatible with pandas 1.x
@@ -352,3 +354,40 @@ def test_series_groupby_describe(scalars_dfs):
             check_dtype=False,
             check_index_type=False,
         )
+
+
+def test_describe_json_and_obj_ref_returns_count(session):
+    # Test describe() works on JSON and OBJ_REF types (without nunique, which fails)
+    sql = """
+        SELECT
+            PARSE_JSON('{"a": 1}') AS json_col,
+            'gs://cloud-samples-data/vision/ocr/sign.jpg' AS uri_col
+    """
+    df = session.read_gbq(sql)
+
+    df["obj_ref_col"] = df["uri_col"].str.to_blob()
+    df = df.drop(columns=["uri_col"])
+
+    res = df.describe(include="all").to_pandas()
+
+    assert "count" in res.index
+    assert res.loc["count", "json_col"] == 1.0
+    assert res.loc["count", "obj_ref_col"] == 1.0
+
+
+def test_describe_with_unsupported_type_returns_empty_dataframe(session):
+    df = session.read_gbq("SELECT ST_GEOGPOINT(1.0, 2.0) AS geo_col")
+
+    res = df.describe().to_pandas()
+
+    assert len(res.columns) == 0
+    assert len(res.index) == 1
+
+
+def test_describe_empty_dataframe_returns_empty_dataframe(session):
+    df = bpd.DataFrame()
+
+    res = df.describe().to_pandas()
+
+    assert len(res.columns) == 0
+    assert len(res.index) == 1