support non-numeric col

Author: chelsea-lin

bigframes/dataframe.py

@@ -1026,17 +1026,17 @@ def corr(self, method="pearson", min_periods=None, numeric_only=False) -> DataFr
             raise NotImplementedError(
                 f"min_periods not yet supported. {constants.FEEDBACK_LINK}"
             )
-        # TODO(chelsealin): Support non-numeric columns correlation.
-        if not numeric_only:
-            raise NotImplementedError(
-                f"Only numeric columns' correlation is currently supported. {constants.FEEDBACK_LINK}"
-            )
         if len(self.columns) > 30:
             raise NotImplementedError(
-                f"Only work with dataframes containing fewer than 30 columns. Current: {self.columns}. {constants.FEEDBACK_LINK}"
+                f"Only work with dataframes containing fewer than 30 columns. Current: {len(self.columns)}. {constants.FEEDBACK_LINK}"
             )
-        # TODO(chelsealin): Support multi-index dataframes' correlation.
-        return DataFrame(self._block.corr())
+
+        if not numeric_only:
+            frame = self._raise_on_non_numeric("corr")
+        else:
+            frame = self._drop_non_numeric()
+
+        return DataFrame(frame._block.corr())
 
     def to_pandas(
         self,

tests/system/small/test_dataframe.py

@@ -1783,12 +1783,26 @@ def test_combine_first(
     pd.testing.assert_frame_equal(bf_result, pd_result, check_dtype=False)
 
 
-def test_corr_w_numeric_only(scalars_dfs):
-    columns = ["int64_too", "int64_col", "float64_col"]
+@pytest.mark.parametrize(
+    ("columns", "numeric_only"),
+    [
+        (["bool_col", "int64_col", "float64_col", "numeric_col"], True),
+        (["bool_col", "int64_col", "float64_col", "numeric_col"], False),
+        (["bool_col", "int64_col", "float64_col", "numeric_col", "string_col"], True),
+        pytest.param(
+            ["bool_col", "int64_col", "float64_col", "numeric_col", "string_col"],
+            False,
+            marks=pytest.mark.xfail(
+                raises=NotImplementedError,
+            ),
+        ),
+    ],
+)
+def test_corr_w_numeric_only(scalars_dfs, columns, numeric_only):
     scalars_df, scalars_pandas_df = scalars_dfs
 
-    bf_result = scalars_df[columns].corr(numeric_only=True).to_pandas()
-    pd_result = scalars_pandas_df[columns].corr(numeric_only=True)
+    bf_result = scalars_df[columns].corr(numeric_only=numeric_only).to_pandas()
+    pd_result = scalars_pandas_df[columns].corr(numeric_only=numeric_only)
 
     # BigFrames and Pandas differ in their data type handling:
     # - Column types: BigFrames uses Float64, Pandas uses float64.
@@ -1808,9 +1822,6 @@ def test_corr_w_invalid_parameters(scalars_dfs):
     with pytest.raises(NotImplementedError):
         scalars_df[columns].corr(min_periods=1)
 
-    with pytest.raises(NotImplementedError):
-        scalars_df[columns].corr(numeric_only=False)
-
 
 @pytest.mark.parametrize(
     ("op"),