From 2b655efaf26f7802e4e41f2e64e1b9abdcaa6cd2 Mon Sep 17 00:00:00 2001
From: "Thomas J. Fan" <thomasjpfan@gmail.com>
Date: Wed, 19 Aug 2020 04:40:34 -0400
Subject: [PATCH] FIX Adds remainder in column transformer repr_html (#18167)

---
 doc/whats_new/v0.24.rst                       |  3 ++
 sklearn/compose/_column_transformer.py        | 17 +++++-
 .../compose/tests/test_column_transformer.py  | 52 +++++++++++++++++++
 3 files changed, 71 insertions(+), 1 deletion(-)

diff --git a/doc/whats_new/v0.24.rst b/doc/whats_new/v0.24.rst
index 7feaf21d3d3..aaf86a2f057 100644
--- a/doc/whats_new/v0.24.rst
+++ b/doc/whats_new/v0.24.rst
@@ -86,6 +86,9 @@ Changelog
   column selector is a list of bools that are False. :pr:`17616` by
   `Thomas Fan`_.
 
+- |FIX| :class:`compose.ColumnTransformer` now displays the remainder in the
+  diagram display. :pr:`18167` by `Thomas Fan`_.
+
 :mod:`sklearn.covariance`
 .........................
 
diff --git a/sklearn/compose/_column_transformer.py b/sklearn/compose/_column_transformer.py
index 66c155f1f82..7ee8f9d0271 100644
--- a/sklearn/compose/_column_transformer.py
+++ b/sklearn/compose/_column_transformer.py
@@ -639,7 +639,22 @@ class ColumnTransformer(TransformerMixin, _BaseComposition):
             return np.hstack(Xs)
 
     def _sk_visual_block_(self):
-        names, transformers, name_details = zip(*self.transformers)
+        if isinstance(self.remainder, str) and self.remainder == 'drop':
+            transformers = self.transformers
+        elif hasattr(self, "_remainder"):
+            remainder_columns = self._remainder[2]
+            if hasattr(self, '_df_columns'):
+                remainder_columns = (
+                    self._df_columns[remainder_columns].tolist()
+                )
+            transformers = chain(self.transformers,
+                                 [('remainder', self.remainder,
+                                   remainder_columns)])
+        else:
+            transformers = chain(self.transformers,
+                                 [('remainder', self.remainder, '')])
+
+        names, transformers, name_details = zip(*transformers)
         return _VisualBlock('parallel', transformers,
                             names=names, name_details=name_details)
 
diff --git a/sklearn/compose/tests/test_column_transformer.py b/sklearn/compose/tests/test_column_transformer.py
index bfbd43ccf89..4e58769e244 100644
--- a/sklearn/compose/tests/test_column_transformer.py
+++ b/sklearn/compose/tests/test_column_transformer.py
@@ -1381,3 +1381,55 @@ def test_feature_names_empty_columns(empty_col):
 
     ct.fit(df)
     assert ct.get_feature_names() == ['ohe__x0_a', 'ohe__x0_b', 'ohe__x1_z']
+
+
+@pytest.mark.parametrize('remainder', ["passthrough", StandardScaler()])
+def test_sk_visual_block_remainder(remainder):
+    # remainder='passthrough' or an estimator will be shown in repr_html
+    ohe = OneHotEncoder()
+    ct = ColumnTransformer(transformers=[('ohe', ohe, ["col1", "col2"])],
+                           remainder=remainder)
+    visual_block = ct._sk_visual_block_()
+    assert visual_block.names == ('ohe', 'remainder')
+    assert visual_block.name_details == (['col1', 'col2'], '')
+    assert visual_block.estimators == (ohe, remainder)
+
+
+def test_sk_visual_block_remainder_drop():
+    # remainder='drop' is not shown in repr_html
+    ohe = OneHotEncoder()
+    ct = ColumnTransformer(transformers=[('ohe', ohe, ["col1", "col2"])])
+    visual_block = ct._sk_visual_block_()
+    assert visual_block.names == ('ohe',)
+    assert visual_block.name_details == (['col1', 'col2'],)
+    assert visual_block.estimators == (ohe,)
+
+
+@pytest.mark.parametrize('remainder', ["passthrough", StandardScaler()])
+def test_sk_visual_block_remainder_fitted_pandas(remainder):
+    # Remainder shows the columns after fitting
+    pd = pytest.importorskip('pandas')
+    ohe = OneHotEncoder()
+    ct = ColumnTransformer(transformers=[('ohe', ohe, ["col1", "col2"])],
+                           remainder=remainder)
+    df = pd.DataFrame({"col1": ["a", "b", "c"], "col2": ["z", "z", "z"],
+                       "col3": [1, 2, 3], "col4": [3, 4, 5]})
+    ct.fit(df)
+    visual_block = ct._sk_visual_block_()
+    assert visual_block.names == ('ohe', 'remainder')
+    assert visual_block.name_details == (['col1', 'col2'], ['col3', 'col4'])
+    assert visual_block.estimators == (ohe, remainder)
+
+
+@pytest.mark.parametrize('remainder', ["passthrough", StandardScaler()])
+def test_sk_visual_block_remainder_fitted_numpy(remainder):
+    # Remainder shows the indices after fitting
+    X = np.array([[1, 2, 3], [4, 5, 6]], dtype=float)
+    scaler = StandardScaler()
+    ct = ColumnTransformer(transformers=[('scale', scaler, [0, 2])],
+                           remainder=remainder)
+    ct.fit(X)
+    visual_block = ct._sk_visual_block_()
+    assert visual_block.names == ('scale', 'remainder')
+    assert visual_block.name_details == ([0, 2], [1])
+    assert visual_block.estimators == (scaler, remainder)