CLN: annotate ndim, is_monotonic_decreasing, has_duplicates, is_, nlevels

pandas/_libs/indexing.pyx

@@ -11,7 +11,7 @@ cdef class _NDFrameIndexerBase:
         self._ndim = None
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         # Delay `ndim` instantiation until required as reading it
         # from `obj` isn't entirely cheap.
         ndim = self._ndim

pandas/core/base.py

@@ -686,7 +686,7 @@ def transpose(self, *args, **kwargs):
     )
 
     @property
-    def _is_homogeneous_type(self):
+    def _is_homogeneous_type(self) -> bool:
         """
         Whether the object has a single dtype.
 
@@ -711,7 +711,7 @@ def shape(self):
         return self._values.shape
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         """
         Number of dimensions of the underlying data, by definition 1.
         """
@@ -1467,7 +1467,7 @@ def is_monotonic(self):
     is_monotonic_increasing = is_monotonic
 
     @property
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         """
         Return boolean if values in the object are
         monotonic_decreasing.

pandas/core/computation/ops.py

@@ -167,7 +167,7 @@ def name(self):
         return self._name
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         return self._value.ndim
 
 

pandas/core/generic.py

@@ -569,7 +569,7 @@ def axes(self):
         return [self._get_axis(a) for a in self._AXIS_ORDERS]
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         """
         Return an int representing the number of axes / array dimensions.
 

pandas/core/indexes/base.py

@@ -607,7 +607,7 @@ def _update_inplace(self, result, **kwargs):
         # guard when called from IndexOpsMixin
         raise TypeError("Index can't be updated inplace")
 
-    def is_(self, other):
+    def is_(self, other) -> bool:
         """
         More flexible, faster check like ``is`` but that works through views.
 
@@ -1452,7 +1452,7 @@ def rename(self, name, inplace=False):
     # Level-Centric Methods
 
     @property
-    def nlevels(self):
+    def nlevels(self) -> int:
         """
         Number of levels.
         """
@@ -1677,7 +1677,7 @@ def is_monotonic_increasing(self):
         return self._engine.is_monotonic_increasing
 
     @property
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         """
         Return if the index is monotonic decreasing (only equal or
         decreasing) values.
@@ -1735,7 +1735,7 @@ def is_unique(self):
         return self._engine.is_unique
 
     @property
-    def has_duplicates(self):
+    def has_duplicates(self) -> bool:
         return not self.is_unique
 
     def is_boolean(self):

pandas/core/indexes/category.py

@@ -463,7 +463,7 @@ def is_monotonic_increasing(self):
         return self._engine.is_monotonic_increasing
 
     @property
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         return self._engine.is_monotonic_decreasing
 
     @Appender(_index_shared_docs["index_unique"] % _index_doc_kwargs)

pandas/core/indexes/interval.py

@@ -558,7 +558,7 @@ def is_monotonic_increasing(self):
         return self._engine.is_monotonic_increasing
 
     @cache_readonly
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         """
         Return True if the IntervalIndex is monotonic decreasing (only equal or
         decreasing values), else False

pandas/core/indexes/multi.py

@@ -675,7 +675,7 @@ def array(self):
         raise ValueError(msg)
 
     @property
-    def _is_homogeneous_type(self):
+    def _is_homogeneous_type(self) -> bool:
         """Whether the levels of a MultiIndex all have the same dtype.
 
         This looks at the dtypes of the levels.
@@ -1427,7 +1427,7 @@ def is_monotonic_increasing(self):
             return Index(self.values).is_monotonic
 
     @cache_readonly
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         """
         return if the index is monotonic decreasing (only equal or
         decreasing) values.

pandas/core/indexes/range.py

@@ -353,11 +353,11 @@ def is_monotonic_increasing(self):
         return self._range.step > 0 or len(self) <= 1
 
     @cache_readonly
-    def is_monotonic_decreasing(self):
+    def is_monotonic_decreasing(self) -> bool:
         return self._range.step < 0 or len(self) <= 1
 
     @property
-    def has_duplicates(self):
+    def has_duplicates(self) -> bool:
         return False
 
     def __contains__(self, key: Union[int, np.integer]) -> bool:

pandas/core/internals/managers.py

@@ -166,7 +166,7 @@ def shape(self):
         return tuple(len(ax) for ax in self.axes)
 
     @property
-    def ndim(self):
+    def ndim(self) -> int:
         return len(self.axes)
 
     def set_axis(self, axis, new_labels):