googleapis · gcf-merge-on-green · Mar 21, 2024 · Mar 20, 2024 · Mar 20, 2024 · Mar 20, 2024
@@ -632,6 +632,13 @@ def year_op_impl(x: ibis_types.Value):
    return typing.cast(ibis_types.TimestampValue, x).year().cast(ibis_dtypes.int64)


+@scalar_op_compiler.register_unary_op(ops.normalize_op)
+def normalize_op_impl(x: ibis_types.Value):
+    result_type = x.type()
+    result = x.truncate("D")
+    return result.cast(result_type)
+
+
 # Parameterized ops
 @scalar_op_compiler.register_unary_op(ops.StructFieldOp, pass_op=True)
 def struct_field_op_impl(x: ibis_types.Value, op: ops.StructFieldOp):

@@ -206,6 +206,7 @@ def create_ternary_op(
 second_op = create_unary_op(name="second", type_rule=op_typing.INTEGER)
 time_op = create_unary_op(name="time", type_rule=op_typing.INTEGER)
 year_op = create_unary_op(name="year", type_rule=op_typing.INTEGER)
+normalize_op = create_unary_op(name="normalize")
 ## Trigonometry Ops
 sin_op = create_unary_op(name="sin", type_rule=op_typing.REAL_NUMERIC)
 cos_op = create_unary_op(name="cos", type_rule=op_typing.REAL_NUMERIC)

@@ -94,3 +94,6 @@ def unit(self) -> str:

    def strftime(self, date_format: str) -> series.Series:
        return self._apply_unary_op(ops.StrftimeOp(date_format=date_format))
+
+    def normalize(self) -> series.Series:
+        return self._apply_unary_op(ops.normalize_op)
@@ -266,3 +266,19 @@ def test_dt_strftime_time():
        bf_result, expected_result, check_index_type=False, check_dtype=False
    )
    assert bf_result.dtype == "string[pyarrow]"
+
+
+@pytest.mark.parametrize(
+    ("col_name",),
+    DATETIME_COL_NAMES,
+)
+@skip_legacy_pandas
+def test_dt_normalize(scalars_dfs, col_name):
+    scalars_df, scalars_pandas_df = scalars_dfs
+    bf_result = scalars_df[col_name].dt.normalize().to_pandas()
+    pd_result = scalars_pandas_df[col_name].dt.normalize()
+
+    assert_series_equal(
+        pd_result.astype(scalars_df[col_name].dtype),  # normalize preserves type
+        bf_result,
+    )
@@ -36,3 +36,34 @@ def strftime(self, date_format: str):
            bigframes.series.Series of formatted strings.
        """
        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
+    def normalize(self):
+        """
+        Convert times to midnight.
+
+        The time component of the date-time is converted to midnight i.e.
+        00:00:00. This is useful in cases when the time does not matter.
+        The return dtype will match the source series.
+
+        This method is available on Series with datetime values under the
+        .dt accessor.
+
+        **Examples:**
+
+            >>> import pandas as pd
+            >>> import bigframes.pandas as bpd
+            >>> s = bpd.Series(pd.date_range(
+            ...     start='2014-08-01 10:00',
+            ...     freq='h',
+            ...     periods=3,
+            ...     tz='Asia/Calcutta')) # note timezones will be converted to UTC here
+            >>> s.dt.normalize()
+            0    2014-08-01 00:00:00+00:00
+            1    2014-08-01 00:00:00+00:00
+            2    2014-08-01 00:00:00+00:00
+            dtype: timestamp[us, tz=UTC][pyarrow]
+
+        Returns:
+            bigframes.series.Series of the same dtype as the data.
+        """
+        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)