CLN: remove Block.merge

pandas/core/internals/blocks.py

@@ -307,9 +307,6 @@ def shape(self):
     def dtype(self):
         return self.values.dtype
 
-    def merge(self, other):
-        return _merge_blocks([self, other])
-
     def concat_same_type(self, to_concat):
         """
         Concatenate list of single blocks of the same type.
@@ -2903,32 +2900,6 @@ def _block_shape(values, ndim=1, shape=None):
     return values
 
 
-def _merge_blocks(blocks, dtype=None, _can_consolidate=True):
-
-    if len(blocks) == 1:
-        return blocks[0]
-
-    if _can_consolidate:
-
-        if dtype is None:
-            if len({b.dtype for b in blocks}) != 1:
-                raise AssertionError("_merge_blocks are invalid!")
-
-        # FIXME: optimization potential in case all mgrs contain slices and
-        # combination of those slices is a slice, too.
-        new_mgr_locs = np.concatenate([b.mgr_locs.as_array for b in blocks])
-        new_values = np.vstack([b.values for b in blocks])
-
-        argsort = np.argsort(new_mgr_locs)
-        new_values = new_values[argsort]
-        new_mgr_locs = new_mgr_locs[argsort]
-
-        return make_block(new_values, placement=new_mgr_locs)
-
-    # no merge
-    return blocks
-
-
 def _safe_reshape(arr, new_shape):
     """
     If possible, reshape `arr` to have shape `new_shape`,

pandas/core/internals/managers.py

@@ -43,7 +43,6 @@
     ExtensionBlock,
     ObjectValuesExtensionBlock,
     _extend_blocks,
-    _merge_blocks,
     _safe_reshape,
     get_block_type,
     make_block,
@@ -1891,12 +1890,40 @@ def _consolidate(blocks):
     new_blocks = []
     for (_can_consolidate, dtype), group_blocks in grouper:
         merged_blocks = _merge_blocks(
-            list(group_blocks), dtype=dtype, _can_consolidate=_can_consolidate
+            list(group_blocks), dtype=dtype, can_consolidate=_can_consolidate
         )
         new_blocks = _extend_blocks(merged_blocks, new_blocks)
     return new_blocks
 
 
+def _merge_blocks(
+    blocks: List[Block], dtype: DtypeObj, can_consolidate: bool
+) -> List[Block]:
+
+    if len(blocks) == 1:
+        return blocks
+
+    if can_consolidate:
+
+        if dtype is None:
+            if len({b.dtype for b in blocks}) != 1:
+                raise AssertionError("_merge_blocks are invalid!")
+
+        # TODO: optimization potential in case all mgrs contain slices and
+        # combination of those slices is a slice, too.
+        new_mgr_locs = np.concatenate([b.mgr_locs.as_array for b in blocks])
+        new_values = np.vstack([b.values for b in blocks])
+
+        argsort = np.argsort(new_mgr_locs)
+        new_values = new_values[argsort]
+        new_mgr_locs = new_mgr_locs[argsort]
+
+        return [make_block(new_values, placement=new_mgr_locs)]
+
+    # can't consolidate --> no merge
+    return blocks
+
+
 def _compare_or_regex_search(a, b, regex=False):
     """
     Compare two array_like inputs of the same shape or two scalar values

pandas/tests/internals/test_internals.py

@@ -232,21 +232,6 @@ def test_attrs(self):
         assert self.fblock.dtype == self.fblock.values.dtype
         assert len(self.fblock) == len(self.fblock.values)
 
-    def test_merge(self):
-        avals = tm.randn(2, 10)
-        bvals = tm.randn(2, 10)
-
-        ref_cols = Index(["e", "a", "b", "d", "f"])
-
-        ablock = make_block(avals, ref_cols.get_indexer(["e", "b"]))
-        bblock = make_block(bvals, ref_cols.get_indexer(["a", "d"]))
-        merged = ablock.merge(bblock)
-        tm.assert_numpy_array_equal(
-            merged.mgr_locs.as_array, np.array([0, 1, 2, 3], dtype=np.int64)
-        )
-        tm.assert_numpy_array_equal(merged.values[[0, 2]], np.array(avals))
-        tm.assert_numpy_array_equal(merged.values[[1, 3]], np.array(bvals))
-
     def test_copy(self):
         cop = self.fblock.copy()
         assert cop is not self.fblock