Fill True when tuple or list cond has np.nan/pd.NA

pandas-dev · sanggon6107 · Jan 23, 2025 · Jan 23, 2025 · Jan 23, 2025 · Jan 23, 2025
commit 8bac9979db2d8c44264b3f8b86ab9090537cf0ef
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
@@ -9698,15 +9698,19 @@ def _where(
  if axis is not None:
  axis = self._get_axis_number(axis)
 
+ cond = common.apply_if_callable(cond, self)
+
  # We should not be filling NA. See GH#60729
 # make sure we are boolean 
 fill_value = bool(inplace) 
 cond = cond.fillna(fill_value) 
 cond = cond.infer_objects() 
 # make sure we are boolean 
 fill_value = bool(inplace) 
 cond = cond.fillna(fill_value) 
 cond = cond.infer_objects() 
 if not isinstance(cond, ABCDataFrame): 
 # This is a single-dimensional object. 
 if not is_bool_dtype(cond): 
 raise TypeError(msg.format(dtype=cond.dtype)) 
 else: 
 for _dt in cond.dtypes: 
 if not is_bool_dtype(_dt): 
 raise TypeError(msg.format(dtype=_dt)) 
 if cond._mgr.any_extension_types: 
 # GH51574: avoid object ndarray conversion later on 
 cond = cond._constructor( 
 cond.to_numpy(dtype=bool, na_value=fill_value), 
 **cond._construct_axes_dict(), 
 ) 
 def where(self, other, cond) -> list[Block]: 
 arr = self.values.T 
 cond = extract_bool_array(cond) 
 def extract_bool_array(mask: ArrayLike) -> npt.NDArray[np.bool_]: 
 """ 
  If we have a SparseArray or BooleanArray, convert it to ndarray[bool]. 
  """ 
 if isinstance(mask, ExtensionArray): 
 # We could have BooleanArray, Sparse[bool], ... 
 # Except for BooleanArray, this is equivalent to just 
 # np.asarray(mask, dtype=bool) 
 mask = mask.to_numpy(dtype=bool, na_value=False) 
 mask = np.asarray(mask, dtype=bool) 
 return mask 
 # make sure we are boolean 
 fill_value = bool(inplace) 
 cond = cond.fillna(fill_value) 
 cond = cond.infer_objects() 
 # make sure we are boolean 
 fill_value = bool(inplace) 
 cond = cond.fillna(fill_value) 
 cond = cond.infer_objects() 
 if not isinstance(cond, ABCDataFrame): 
 # This is a single-dimensional object. 
 if not is_bool_dtype(cond): 
 raise TypeError(msg.format(dtype=cond.dtype)) 
 else: 
 for _dt in cond.dtypes: 
 if not is_bool_dtype(_dt): 
 raise TypeError(msg.format(dtype=_dt)) 
 if cond._mgr.any_extension_types: 
 # GH51574: avoid object ndarray conversion later on 
 cond = cond._constructor( 
 cond.to_numpy(dtype=bool, na_value=fill_value), 
 **cond._construct_axes_dict(), 
 ) 
 def where(self, other, cond) -> list[Block]: 
 arr = self.values.T 
 
 cond = extract_bool_array(cond) 
 
 def extract_bool_array(mask: ArrayLike) -> npt.NDArray[np.bool_]: 
 """ 
  If we have a SparseArray or BooleanArray, convert it to ndarray[bool]. 
  """ 
 if isinstance(mask, ExtensionArray): 
 # We could have BooleanArray, Sparse[bool], ... 
 # Except for BooleanArray, this is equivalent to just 
 # np.asarray(mask, dtype=bool) 
 mask = mask.to_numpy(dtype=bool, na_value=False) 
 
 mask = np.asarray(mask, dtype=bool) 
 return mask 
  if isinstance(cond, np.ndarray):
  cond = np.array(cond)
- cond[np.isnan(cond)] = True
+ cond[isna(cond)] = True
  elif isinstance(cond, NDFrame):
  cond = cond.fillna(True)
+ elif isinstance(cond, (list, tuple)):
+ cond = np.array(cond)
+ cond[isna(cond)] = True
 
  # align the cond to same shape as myself
- cond = common.apply_if_callable(cond, self)
  if isinstance(cond, NDFrame):
  # CoW: Make sure reference is not kept alive
  if cond.ndim == 1 and self.ndim == 2: