feat: add update and align methods to dataframe (#57)

TrevorBergeron · web-flow · commit bf050cf475ad · 2023-09-28T15:51:25.000-07:00
* feat: add update and align methods to dataframe
diff --git a/bigframes/core/block_transforms.py b/bigframes/core/block_transforms.py
@@ -504,3 +504,75 @@ def _kurt_from_moments_and_count(
         kurt_id, na_cond_id, ops.partial_arg3(ops.where_op, None)
     )
     return block, kurt_id
+
+
+def align(
+    left_block: blocks.Block,
+    right_block: blocks.Block,
+    join: str = "outer",
+    axis: typing.Union[str, int, None] = None,
+) -> typing.Tuple[blocks.Block, blocks.Block]:
+    axis_n = core.utils.get_axis_number(axis) if axis is not None else None
+    # Must align columns first as other way will likely create extra joins
+    if (axis_n is None) or axis_n == 1:
+        left_block, right_block = align_columns(left_block, right_block, join=join)
+    if (axis_n is None) or axis_n == 0:
+        left_block, right_block = align_rows(left_block, right_block, join=join)
+    return left_block, right_block
+
+
+def align_rows(
+    left_block: blocks.Block,
+    right_block: blocks.Block,
+    join: str = "outer",
+):
+    joined_index, (get_column_left, get_column_right) = left_block.index.join(
+        right_block.index, how=join
+    )
+    left_columns = [get_column_left(col) for col in left_block.value_columns]
+    right_columns = [get_column_right(col) for col in right_block.value_columns]
+
+    left_block = joined_index._block.select_columns(left_columns)
+    right_block = joined_index._block.select_columns(right_columns)
+    return left_block, right_block
+
+
+def align_columns(
+    left_block: blocks.Block,
+    right_block: blocks.Block,
+    join: str = "outer",
+):
+    columns, lcol_indexer, rcol_indexer = left_block.column_labels.join(
+        right_block.column_labels, how=join, return_indexers=True
+    )
+    column_indices = zip(
+        lcol_indexer if (lcol_indexer is not None) else range(len(columns)),
+        rcol_indexer if (rcol_indexer is not None) else range(len(columns)),
+    )
+    left_column_ids = []
+    right_column_ids = []
+
+    original_left_block = left_block
+    original_right_block = right_block
+
+    for left_index, right_index in column_indices:
+        if left_index >= 0:
+            left_col_id = original_left_block.value_columns[left_index]
+        else:
+            dtype = right_block.dtypes[right_index]
+            left_block, left_col_id = left_block.create_constant(
+                None, dtype=dtype, label=original_right_block.column_labels[right_index]
+            )
+        left_column_ids.append(left_col_id)
+
+        if right_index >= 0:
+            right_col_id = original_right_block.value_columns[right_index]
+        else:
+            dtype = original_left_block.dtypes[left_index]
+            right_block, right_col_id = right_block.create_constant(
+                None, dtype=dtype, label=left_block.column_labels[left_index]
+            )
+        right_column_ids.append(right_col_id)
+    left_final = left_block.select_columns(left_column_ids)
+    right_final = right_block.select_columns(right_column_ids)
+    return left_final, right_final
diff --git a/bigframes/dataframe.py b/bigframes/dataframe.py
@@ -745,6 +745,55 @@ def rpow(
 
     __rpow__ = rpow
 
+    def align(
+        self,
+        other: typing.Union[DataFrame, bigframes.series.Series],
+        join: str = "outer",
+        axis: typing.Union[str, int, None] = None,
+    ) -> typing.Tuple[
+        typing.Union[DataFrame, bigframes.series.Series],
+        typing.Union[DataFrame, bigframes.series.Series],
+    ]:
+        axis_n = utils.get_axis_number(axis) if axis else None
+        if axis_n == 1 and isinstance(other, bigframes.series.Series):
+            raise NotImplementedError(
+                f"align with series and axis=1 not supported. {constants.FEEDBACK_LINK}"
+            )
+        left_block, right_block = block_ops.align(
+            self._block, other._block, join=join, axis=axis
+        )
+        return DataFrame(left_block), other.__class__(right_block)
+
+    def update(self, other, join: str = "left", overwrite=True, filter_func=None):
+        other = other if isinstance(other, DataFrame) else DataFrame(other)
+        if join != "left":
+            raise ValueError("Only 'left' join supported for update")
+
+        if filter_func is not None:  # Will always take other if possible
+
+            def update_func(
+                left: bigframes.series.Series, right: bigframes.series.Series
+            ) -> bigframes.series.Series:
+                return left.mask(right.notna() & filter_func(left), right)
+
+        elif overwrite:
+
+            def update_func(
+                left: bigframes.series.Series, right: bigframes.series.Series
+            ) -> bigframes.series.Series:
+                return left.mask(right.notna(), right)
+
+        else:
+
+            def update_func(
+                left: bigframes.series.Series, right: bigframes.series.Series
+            ) -> bigframes.series.Series:
+                return left.mask(left.isna(), right)
+
+        result = self.combine(other, update_func, how=join)
+
+        self._set_block(result._block)
+
     def combine(
         self,
         other: DataFrame,
@@ -753,56 +802,31 @@ def combine(
         ],
         fill_value=None,
         overwrite: bool = True,
+        *,
+        how: str = "outer",
     ) -> DataFrame:
-        # Join rows
-        joined_index, (get_column_left, get_column_right) = self._block.index.join(
-            other._block.index, how="outer"
-        )
-        columns, lcol_indexer, rcol_indexer = self.columns.join(
-            other.columns, how="outer", return_indexers=True
-        )
+        l_aligned, r_aligned = block_ops.align(self._block, other._block, join=how)
 
-        column_indices = zip(
-            lcol_indexer if (lcol_indexer is not None) else range(len(columns)),
-            rcol_indexer if (lcol_indexer is not None) else range(len(columns)),
+        other_missing_labels = self._block.column_labels.difference(
+            other._block.column_labels
         )
 
-        block = joined_index._block
+        l_frame = DataFrame(l_aligned)
+        r_frame = DataFrame(r_aligned)
         results = []
-        for left_index, right_index in column_indices:
-            if left_index >= 0 and right_index >= 0:  # -1 indices indicate missing
-                left_col_id = get_column_left(self._block.value_columns[left_index])
-                right_col_id = get_column_right(other._block.value_columns[right_index])
-                left_series = bigframes.series.Series(block.select_column(left_col_id))
-                right_series = bigframes.series.Series(
-                    block.select_column(right_col_id)
-                )
+        for (label, lseries), (_, rseries) in zip(l_frame.items(), r_frame.items()):
+            if not ((label in other_missing_labels) and not overwrite):
                 if fill_value is not None:
-                    left_series = left_series.fillna(fill_value)
-                    right_series = right_series.fillna(fill_value)
-                results.append(func(left_series, right_series))
-            elif left_index >= 0:
-                # Does not exist in other
-                if overwrite:
-                    dtype = self.dtypes[left_index]
-                    block, null_col_id = block.create_constant(None, dtype=dtype)
-                    result = bigframes.series.Series(block.select_column(null_col_id))
-                    results.append(result)
+                    result = func(
+                        lseries.fillna(fill_value), rseries.fillna(fill_value)
+                    )
                 else:
-                    left_col_id = get_column_left(self._block.value_columns[left_index])
-                    result = bigframes.series.Series(block.select_column(left_col_id))
-                    if fill_value is not None:
-                        result = result.fillna(fill_value)
-                    results.append(result)
-            elif right_index >= 0:
-                right_col_id = get_column_right(other._block.value_columns[right_index])
-                result = bigframes.series.Series(block.select_column(right_col_id))
-                if fill_value is not None:
-                    result = result.fillna(fill_value)
-                results.append(result)
+                    result = func(lseries, rseries)
             else:
-                # Should not be possible
-                raise ValueError("No right or left index.")
+                result = (
+                    lseries.fillna(fill_value) if fill_value is not None else lseries
+                )
+            results.append(result)
 
         if all([isinstance(val, bigframes.series.Series) for val in results]):
             import bigframes.core.reshape as rs
diff --git a/tests/system/small/test_dataframe.py b/tests/system/small/test_dataframe.py
@@ -1211,6 +1211,77 @@ def test_combine(
     pd.testing.assert_frame_equal(bf_result, pd_result, check_dtype=False)
 
 
+@pytest.mark.parametrize(
+    ("overwrite", "filter_func"),
+    [
+        (True, None),
+        (False, None),
+        (True, lambda x: x.isna() | (x % 2 == 0)),
+    ],
+    ids=[
+        "default",
+        "overwritefalse",
+        "customfilter",
+    ],
+)
+def test_df_update(overwrite, filter_func):
+    if pd.__version__.startswith("1."):
+        pytest.skip("dtype handled differently in pandas 1.x.")
+    index1 = pandas.Index([1, 2, 3, 4], dtype="Int64")
+    index2 = pandas.Index([1, 2, 4, 5], dtype="Int64")
+    pd_df1 = pandas.DataFrame(
+        {"a": [1, None, 3, 4], "b": [5, 6, None, 8]}, dtype="Int64", index=index1
+    )
+    pd_df2 = pandas.DataFrame(
+        {"a": [None, 20, 30, 40], "c": [90, None, 110, 120]},
+        dtype="Int64",
+        index=index2,
+    )
+
+    bf_df1 = dataframe.DataFrame(pd_df1)
+    bf_df2 = dataframe.DataFrame(pd_df2)
+
+    bf_df1.update(bf_df2, overwrite=overwrite, filter_func=filter_func)
+    pd_df1.update(pd_df2, overwrite=overwrite, filter_func=filter_func)
+
+    pd.testing.assert_frame_equal(bf_df1.to_pandas(), pd_df1)
+
+
+@pytest.mark.parametrize(
+    ("join", "axis"),
+    [
+        ("outer", None),
+        ("outer", 0),
+        ("outer", 1),
+        ("left", 0),
+        ("right", 1),
+        ("inner", None),
+        ("inner", 1),
+    ],
+)
+def test_df_align(join, axis):
+    index1 = pandas.Index([1, 2, 3, 4], dtype="Int64")
+    index2 = pandas.Index([1, 2, 4, 5], dtype="Int64")
+    pd_df1 = pandas.DataFrame(
+        {"a": [1, None, 3, 4], "b": [5, 6, None, 8]}, dtype="Int64", index=index1
+    )
+    pd_df2 = pandas.DataFrame(
+        {"a": [None, 20, 30, 40], "c": [90, None, 110, 120]},
+        dtype="Int64",
+        index=index2,
+    )
+
+    bf_df1 = dataframe.DataFrame(pd_df1)
+    bf_df2 = dataframe.DataFrame(pd_df2)
+
+    bf_result1, bf_result2 = bf_df1.align(bf_df2, join=join, axis=axis)
+    pd_result1, pd_result2 = pd_df1.align(pd_df2, join=join, axis=axis)
+
+    # Don't check dtype as pandas does unnecessary float conversion
+    pd.testing.assert_frame_equal(bf_result1.to_pandas(), pd_result1, check_dtype=False)
+    pd.testing.assert_frame_equal(bf_result2.to_pandas(), pd_result2, check_dtype=False)
+
+
 def test_combine_first(
     scalars_df_index,
     scalars_df_2_index,
@@ -1232,11 +1303,6 @@ def test_combine_first(
     pd_df_b.columns = ["b", "a", "d"]
     pd_result = pd_df_a.combine_first(pd_df_b)
 
-    print("pandas")
-    print(pd_result.to_string())
-    print("bigframes")
-    print(bf_result.to_string())
-
     # Some dtype inconsistency for all-NULL columns
     pd.testing.assert_frame_equal(bf_result, pd_result, check_dtype=False)
 
diff --git a/third_party/bigframes_vendored/pandas/core/frame.py b/third_party/bigframes_vendored/pandas/core/frame.py
@@ -503,6 +503,35 @@ def drop(
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+    def align(
+        self,
+        other,
+        join="outer",
+        axis=None,
+    ) -> tuple:
+        """
+        Align two objects on their axes with the specified join method.
+
+        Join method is specified for each axis Index.
+
+        Args:
+            other (DataFrame or Series):
+            join ({{'outer', 'inner', 'left', 'right'}}, default 'outer'):
+                Type of alignment to be performed.
+                left: use only keys from left frame, preserve key order.
+                right: use only keys from right frame, preserve key order.
+                outer: use union of keys from both frames, sort keys lexicographically.
+                inner: use intersection of keys from both frames,
+                preserve the order of the left keys.
+
+            axis (allowed axis of the other object, default None):
+                Align on index (0), columns (1), or both (None).
+
+        Returns:
+            tuple of (DataFrame, type of other): Aligned objects.
+        """
+        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
     def rename(
         self,
         *,
@@ -1265,6 +1294,39 @@ def combine_first(self, other) -> DataFrame:
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
+    def update(
+        self, other, join: str = "left", overwrite: bool = True, filter_func=None
+    ) -> DataFrame:
+        """
+        Modify in place using non-NA values from another DataFrame.
+
+        Aligns on indices. There is no return value.
+
+        Args:
+            other (DataFrame, or object coercible into a DataFrame):
+                Should have at least one matching index/column label
+                with the original DataFrame. If a Series is passed,
+                its name attribute must be set, and that will be
+                used as the column name to align with the original DataFrame.
+            join ({'left'}, default 'left'):
+                Only left join is implemented, keeping the index and columns of the
+                original object.
+            overwrite (bool, default True):
+                How to handle non-NA values for overlapping keys:
+                True: overwrite original DataFrame's values
+                with values from `other`.
+                False: only update values that are NA in
+                the original DataFrame.
+
+            filter_func (callable(1d-array) -> bool 1d-array, optional):
+                Can choose to replace values other than NA. Return True for values
+                that should be updated.
+
+        Returns:
+            None: This method directly changes calling object.
+        """
+        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+
     # ----------------------------------------------------------------------
     # Data reshaping
 
