googleapis · ashleyxuu · Nov 24, 2023 · Nov 22, 2023 · Nov 23, 2023 · Nov 23, 2023
@@ -2797,7 +2797,8 @@ def get_right_id(id):
        result = result[other_frame.columns]

        if isinstance(other, bf_series.Series):
-            result = result[other.name].rename()
+            # There should be exactly one column in the result
+            result = result[result.columns[0]].rename()

        return result


@@ -141,7 +141,7 @@ def _apply_binary_op(
        if isinstance(other, pd.Series):
            # TODO: Convert to BigQuery DataFrames series
            raise NotImplementedError(
-                f"Pandas series not supported supported as operand. {constants.FEEDBACK_LINK}"
+                f"Pandas series not supported as operand. {constants.FEEDBACK_LINK}"
            )
        if isinstance(other, series.Series):
            (left, right, block) = self._align(other, how=alignment)

@@ -3493,6 +3493,29 @@ def test_df_dot_operator(
    )


+def test_df_dot_series_inline():
+    left = [[1, 2, 3], [2, 5, 7]]
+    right = [2, 1, 3]
+
+    bf1 = dataframe.DataFrame(left)
+    bf2 = series.Series(right)
+    bf_result = bf1.dot(bf2).to_pandas()
+
+    df1 = pd.DataFrame(left)
+    df2 = pd.Series(right)
+    pd_result = df1.dot(df2)
+
+    # Patch pandas dtypes for testing parity
+    # Pandas result is int64 instead of Int64 (nullable) dtype.
+    pd_result = pd_result.astype(pd.Int64Dtype())
+    pd_result.index = pd_result.index.astype(pd.Int64Dtype())
+
+    pd.testing.assert_series_equal(
+        bf_result,
+        pd_result,
+    )
+
+
 def test_df_dot_series(
    matrix_2by3_df, matrix_2by3_pandas_df, matrix_3by4_df, matrix_3by4_pandas_df
 ):

@@ -3485,6 +3485,77 @@ def dot(self, other):
            The dot method for Series computes the inner product, instead of the
            matrix product here.

+        **Examples:**
+
+            >>> import bigframes.pandas as bpd
+            >>> bpd.options.display.progress_bar = None
+
+            >>> left = bpd.DataFrame([[0, 1, -2, -1], [1, 1, 1, 1]])
+            >>> left
+               0  1   2   3
+            0  0  1  -2  -1
+            1  1  1   1   1
+            <BLANKLINE>
+            [2 rows x 4 columns]
+            >>> right = bpd.DataFrame([[0, 1], [1, 2], [-1, -1], [2, 0]])
+            >>> right
+                0   1
+            0   0   1
+            1   1   2
+            2  -1  -1
+            3   2   0
+            <BLANKLINE>
+            [4 rows x 2 columns]
+            >>> left.dot(right)
+               0  1
+            0  1  4
+            1  2  2
+            <BLANKLINE>
+            [2 rows x 2 columns]
+
+        You can also use the operator ``@`` for the dot product:
+
+            >>> left @ right
+               0  1
+            0  1  4
+            1  2  2
+            <BLANKLINE>
+            [2 rows x 2 columns]
+
+        The right input can be a Series, in which case the result will also be a
+        Series:
+
+            >>> right = bpd.Series([1, 2, -1,0])
+            >>> left @ right
+            0    4
+            1    2
+            dtype: Int64
+
+        Any user defined index of the left matrix and columns of the right
+        matrix will reflect in the result.
+
+            >>> left = bpd.DataFrame([[1, 2, 3], [2, 5, 7]], index=["alpha", "beta"])
+            >>> left
+                   0  1  2
+            alpha  1  2  3
+            beta   2  5  7
+            <BLANKLINE>
+            [2 rows x 3 columns]
+            >>> right = bpd.DataFrame([[2, 4, 8], [1, 5, 10], [3, 6, 9]], columns=["red", "green", "blue"])
+            >>> right
+               red  green  blue
+            0    2      4     8
+            1    1      5    10
+            2    3      6     9
+            <BLANKLINE>
+            [3 rows x 3 columns]
+            >>> left.dot(right)
+                   red  green  blue
+            alpha   13     32    55
+            beta    30     75   129
+            <BLANKLINE>
+            [2 rows x 3 columns]
+
        Args:
            other (Series or DataFrame):
                The other object to compute the matrix product with.

@@ -631,6 +631,21 @@ def dot(self, other) -> Series | np.ndarray:
            BigQuery Dataframes does not validate this property and will produce
            incorrect results if indices are not equal.

+        **Examples:**
+
+            >>> import bigframes.pandas as bpd
+            >>> bpd.options.display.progress_bar = None
+
+            >>> s = bpd.Series([0, 1, 2, 3])
+            >>> other = bpd.Series([-1, 2, -3, 4])
+            >>> s.dot(other)
+            8
+
+        You can also use the operator ``@`` for the dot product:
+
+            >>> s @ other
+            8
+
        Args:
            other (Series):
                The other object to compute the dot product with its columns.