REGR: revert "CLN: _consolidate_inplace less" / fix regression in fillna()

pandas/core/generic.py

@@ -3506,6 +3506,8 @@ class   animal   locomotion
         if axis == 1:
             return self[key]
 
+        self._consolidate_inplace()
+
         index = self.index
         if isinstance(index, MultiIndex):
             loc, new_index = self.index.get_loc_level(key, drop_level=drop_level)
@@ -5428,6 +5430,7 @@ def values(self) -> np.ndarray:
                ['lion', 80.5, 1],
                ['monkey', nan, None]], dtype=object)
         """
+        self._consolidate_inplace()
         return self._mgr.as_array(transpose=self._AXIS_REVERSED)
 
     @property
@@ -6096,6 +6099,8 @@ def fillna(
         inplace = validate_bool_kwarg(inplace, "inplace")
         value, method = validate_fillna_kwargs(value, method)
 
+        self._consolidate_inplace()
+
         # set the default here, so functions examining the signaure
         # can detect if something was set (e.g. in groupby) (GH9221)
         if axis is None:
@@ -6530,6 +6535,8 @@ def replace(
         if not is_bool(regex) and to_replace is not None:
             raise AssertionError("'to_replace' must be 'None' if 'regex' is not a bool")
 
+        self._consolidate_inplace()
+
         if value is None:
             # passing a single value that is scalar like
             # when value is None (GH5319), for compat

pandas/core/internals/managers.py

@@ -378,6 +378,8 @@ def apply(self: T, f, align_keys=None, **kwargs) -> T:
         result_blocks: List[Block] = []
         # fillna: Series/DataFrame is responsible for making sure value is aligned
 
+        self._consolidate_inplace()
+
         aligned_args = {k: kwargs[k] for k in align_keys}
 
         for b in self.blocks:
@@ -410,6 +412,7 @@ def apply(self: T, f, align_keys=None, **kwargs) -> T:
     def quantile(
         self,
         axis: int = 0,
+        consolidate: bool = True,
         transposed: bool = False,
         interpolation="linear",
         qs=None,
@@ -423,6 +426,8 @@ def quantile(
         Parameters
         ----------
         axis: reduction axis, default 0
+        consolidate: bool, default True. Join together blocks having same
+            dtype
         transposed: bool, default False
             we are holding transposed data
         interpolation : type of interpolation, default 'linear'
@@ -437,6 +442,9 @@ def quantile(
         #  simplify some of the code here and in the blocks
         assert self.ndim >= 2
 
+        if consolidate:
+            self._consolidate_inplace()
+
         def get_axe(block, qs, axes):
             # Because Series dispatches to DataFrame, we will always have
             #  block.ndim == 2