experiment

pandas/_libs/lib.pyx

@@ -76,6 +76,9 @@ def values_from_object(obj: object):
     """ return my values or the object if we are say an ndarray """
     func: object
 
+    if getattr(obj, '_typ', '') == 'dataframe':
+        return obj.values
+
     func = getattr(obj, '_internal_get_values', None)
     if func is not None:
         obj = func()

pandas/core/arrays/categorical.py

@@ -1507,6 +1507,8 @@ def get_values(self):
                                                          fill_value=np.nan)
         return np.array(self)
 
+    _internal_get_values = get_values
+
     def check_for_ordered(self, op):
         """ assert that we are ordered """
         if not self.ordered:

pandas/core/arrays/sparse.py

@@ -454,7 +454,7 @@ def _sparse_array_op(
 
     if left.sp_index.ngaps == 0 or right.sp_index.ngaps == 0:
         with np.errstate(all='ignore'):
-            result = op(left.get_values(), right.get_values())
+            result = op(left.to_dense(), right.to_dense())
             fill = op(_get_fill(left), _get_fill(right))
 
         if left.sp_index.ngaps == 0:
@@ -1457,7 +1457,12 @@ def to_dense(self):
         return np.asarray(self, dtype=self.sp_values.dtype)
 
     # TODO: Look into deprecating this in favor of `to_dense`.
-    get_values = to_dense
+    # get_values = to_dense
+
+    def get_values(self):
+        raise Exception("USING GET_VALUES")
+
+    _internal_get_values = to_dense
 
     # ------------------------------------------------------------------------
     # IO

pandas/core/groupby/generic.py

@@ -1006,7 +1006,7 @@ def nunique(self, dropna=True):
         """
         ids, _, _ = self.grouper.group_info
 
-        val = self.obj.get_values()
+        val = self.obj._internal_get_values()
 
         try:
             sorter = np.lexsort((val, ids))
@@ -1080,7 +1080,7 @@ def value_counts(self, normalize=False, sort=True, ascending=False,
                               bins=bins)
 
         ids, _, _ = self.grouper.group_info
-        val = self.obj.get_values()
+        val = self.obj._internal_get_values()
 
         # groupby removes null keys from groupings
         mask = ids != -1
@@ -1194,7 +1194,7 @@ def count(self):
             Count of values within each group.
         """
         ids, _, ngroups = self.grouper.group_info
-        val = self.obj.get_values()
+        val = self.obj._internal_get_values()
 
         mask = (ids != -1) & ~isna(val)
         ids = ensure_platform_int(ids)

pandas/core/indexes/base.py

@@ -3717,6 +3717,8 @@ def get_values(self):
         """
         return self.values
 
+    _internal_get_values = get_values
+
     @Appender(IndexOpsMixin.memory_usage.__doc__)
     def memory_usage(self, deep=False):
         result = super().memory_usage(deep=deep)

pandas/core/indexes/category.py

@@ -357,6 +357,8 @@ def get_values(self):
         """ return the underlying data as an ndarray """
         return self._data.get_values()
 
+    _internal_get_values = get_values
+
     def tolist(self):
         return self._data.tolist()
 

pandas/core/ops.py

@@ -1894,7 +1894,7 @@ def wrapper(self, other, axis=None):
                                      name=res_name, dtype='bool')
 
         else:
-            values = self.get_values()
+            values = self.to_numpy()
 
             with np.errstate(all='ignore'):
                 res = na_op(values, other)

pandas/core/series.py

@@ -505,7 +505,8 @@ def get_values(self):
         numpy.ndarray
             Data of the Series.
         """
-        warnings.warn("deprecated", FutureWarning, stacklevel=2)
+        raise Exception("USING GET_VALUES")
+        #warnings.warn("deprecated", FutureWarning, stacklevel=2)
         return self._data.get_values()
 
     @property

pandas/core/sparse/frame.py

@@ -683,7 +683,7 @@ def _reindex_with_indexers(self, reindexers, method=None, fill_value=None,
             if col not in self:
                 continue
             if row_indexer is not None:
-                new_arrays[col] = algos.take_1d(self[col].get_values(),
+                new_arrays[col] = algos.take_1d(self[col]._internal_get_values(),
                                                 row_indexer,
                                                 fill_value=fill_value)
             else:

pandas/core/sparse/series.py

@@ -227,7 +227,7 @@ def __unicode__(self):
     def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
                 filter_type=None, **kwds):
         """ perform a reduction operation """
-        return op(self.get_values(), skipna=skipna, **kwds)
+        return op(self.array.to_dense(), skipna=skipna, **kwds)
 
     def __getstate__(self):
         # pickling

pandas/util/testing.py

@@ -1043,7 +1043,7 @@ def assert_series_equal(left, right, check_dtype=True,
             assert_attr_equal('dtype', left, right)
 
     if check_exact:
-        assert_numpy_array_equal(left.get_values(), right.get_values(),
+        assert_numpy_array_equal(left._internal_get_values(), right._internal_get_values(),
                                  check_dtype=check_dtype,
                                  obj='{obj}'.format(obj=obj),)
     elif check_datetimelike_compat:
@@ -1062,7 +1062,7 @@ def assert_series_equal(left, right, check_dtype=True,
                        '{right}.').format(left=left.values, right=right.values)
                 raise AssertionError(msg)
         else:
-            assert_numpy_array_equal(left.get_values(), right.get_values(),
+            assert_numpy_array_equal(left._internal_get_values(), right._internal_get_values(),
                                      check_dtype=check_dtype)
     elif is_interval_dtype(left) or is_interval_dtype(right):
         assert_interval_array_equal(left.array, right.array)
@@ -1077,7 +1077,7 @@ def assert_series_equal(left, right, check_dtype=True,
           is_extension_array_dtype(right) and not is_categorical_dtype(right)):
         assert_extension_array_equal(left.array, right.array)
     else:
-        _testing.assert_almost_equal(left.get_values(), right.get_values(),
+        _testing.assert_almost_equal(left._internal_get_values(), right._internal_get_values(),
                                      check_less_precise=check_less_precise,
                                      check_dtype=check_dtype,
                                      obj='{obj}'.format(obj=obj))