DEPR: deprecate get_values (#26409)

doc/source/whatsnew/v0.25.0.rst

@@ -615,6 +615,9 @@ Other deprecations
   Use the public attributes :attr:`~RangeIndex.start`, :attr:`~RangeIndex.stop` and :attr:`~RangeIndex.step` instead (:issue:`26581`).
 - The :meth:`Series.ftype`, :meth:`Series.ftypes` and :meth:`DataFrame.ftypes` methods are deprecated and will be removed in a future version.
   Instead, use :meth:`Series.dtype` and :meth:`DataFrame.dtypes` (:issue:`26705`).
+- The :meth:`Series.get_values`, :meth:`DataFrame.get_values`, :meth:`Index.get_values`,
+  :meth:`SparseArray.get_values` and :meth:`Categorical.get_values` methods are deprecated.
+  One of ``np.asarray(..)`` or :meth:`~Series.to_numpy` can be used instead (:issue:`19617`).
 - :meth:`Timedelta.resolution` is deprecated and replaced with :meth:`Timedelta.resolution_string`.  In a future version, :meth:`Timedelta.resolution` will be changed to behave like the standard library :attr:`timedelta.resolution` (:issue:`21344`)
 - :func:`read_table` has been undeprecated. (:issue:`25220`)
 - :attr:`Index.dtype_str` is deprecated. (:issue:`18262`)

pandas/_libs/lib.pyx

@@ -76,7 +76,10 @@ def values_from_object(obj: object):
     """ return my values or the object if we are say an ndarray """
     func: object
 
-    func = getattr(obj, 'get_values', None)
+    if getattr(obj, '_typ', '') == 'dataframe':
+        return obj.values
+
+    func = getattr(obj, '_internal_get_values', None)
     if func is not None:
         obj = func()
 

pandas/_libs/src/ujson/python/objToJSON.c

@@ -269,9 +269,19 @@ static PyObject *get_values(PyObject *obj) {
         }
     }
 
-    if (!values && PyObject_HasAttrString(obj, "get_values")) {
+    if (!values && PyObject_HasAttrString(obj, "_internal_get_values")) {
         PRINTMARK();
-        values = PyObject_CallMethod(obj, "get_values", NULL);
+        values = PyObject_CallMethod(obj, "_internal_get_values", NULL);
+        if (values && !PyArray_CheckExact(values)) {
+            PRINTMARK();
+            Py_DECREF(values);
+            values = NULL;
+        }
+    }
+
+    if (!values && PyObject_HasAttrString(obj, "get_block_values")) {
+        PRINTMARK();
+        values = PyObject_CallMethod(obj, "get_block_values", NULL);
         if (values && !PyArray_CheckExact(values)) {
             PRINTMARK();
             Py_DECREF(values);

pandas/core/algorithms.py

@@ -1590,7 +1590,7 @@ def take_nd(arr, indexer, axis=0, out=None, fill_value=np.nan, mask_info=None,
         return arr.take(indexer, fill_value=fill_value, allow_fill=allow_fill)
 
     if is_sparse(arr):
-        arr = arr.get_values()
+        arr = arr.to_dense()
     elif isinstance(arr, (ABCIndexClass, ABCSeries)):
         arr = arr.values
 

pandas/core/arrays/categorical.py

@@ -1483,6 +1483,8 @@ def get_values(self):
         """
         Return the values.
 
+        .. deprecated:: 0.25.0
+
         For internal compatibility with pandas formatting.
 
         Returns
@@ -1491,6 +1493,11 @@ def get_values(self):
             A numpy array of the same dtype as categorical.categories.dtype or
             Index if datetime / periods.
         """
+        warn("The 'get_values' method is deprecated and will be removed in a "
+             "future version", FutureWarning, stacklevel=2)
+        return self._internal_get_values()
+
+    def _internal_get_values(self):
         # if we are a datetime and period index, return Index to keep metadata
         if is_datetimelike(self.categories):
             return self.categories.take(self._codes, fill_value=np.nan)
@@ -1923,7 +1930,7 @@ def __iter__(self):
         """
         Returns an Iterator over the values of this Categorical.
         """
-        return iter(self.get_values().tolist())
+        return iter(self._internal_get_values().tolist())
 
     def __contains__(self, key):
         """

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:
@@ -1468,8 +1468,21 @@ 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
+    def get_values(self):
+        """
+        Convert SparseArray to a NumPy array.
+
+        .. deprecated:: 0.25.0
+            Use `to_dense` instead.
+
+        """
+        warnings.warn(
+            "The 'get_values' method is deprecated and will be removed in a "
+            "future version. Use the 'to_dense' method instead.",
+            FutureWarning, stacklevel=2)
+        return self._internal_get_values()
+
+    _internal_get_values = to_dense
 
     # ------------------------------------------------------------------------
     # IO

pandas/core/dtypes/concat.py

@@ -194,7 +194,7 @@ def _concat_categorical(to_concat, axis=0):
             return union_categoricals(categoricals)
 
     # extract the categoricals & coerce to object if needed
-    to_concat = [x.get_values() if is_categorical_dtype(x.dtype)
+    to_concat = [x._internal_get_values() if is_categorical_dtype(x.dtype)
                  else np.asarray(x).ravel() if not is_datetime64tz_dtype(x)
                  else np.asarray(x.astype(object)) for x in to_concat]
     result = _concat_compat(to_concat)

pandas/core/frame.py

@@ -1616,7 +1616,8 @@ def to_records(self, index=True, convert_datetime64=None,
                 else:
                     ix_vals = [self.index.values]
 
-            arrays = ix_vals + [self[c].get_values() for c in self.columns]
+            arrays = ix_vals + [self[c]._internal_get_values()
+                                for c in self.columns]
 
             count = 0
             index_names = list(self.index.names)
@@ -1632,7 +1633,7 @@ def to_records(self, index=True, convert_datetime64=None,
             names = [str(name) for name in itertools.chain(index_names,
                                                            self.columns)]
         else:
-            arrays = [self[c].get_values() for c in self.columns]
+            arrays = [self[c]._internal_get_values() for c in self.columns]
             names = [str(c) for c in self.columns]
             index_names = []
 

pandas/core/generic.py

@@ -5220,6 +5220,9 @@ def get_values(self):
         """
         Return an ndarray after converting sparse values to dense.
 
+        .. deprecated:: 0.25.0
+            Use ``np.asarray(..)`` or :meth:`DataFrame.values` instead.
+
         This is the same as ``.values`` for non-sparse data. For sparse
         data contained in a `SparseArray`, the data are first
         converted to a dense representation.
@@ -5259,6 +5262,13 @@ def get_values(self):
                [nan,  2.],
                [nan,  3.]])
         """
+        warnings.warn(
+            "The 'get_values' method is deprecated and will be removed in a "
+            "future version. Use '.values' or 'np.asarray(..)' instead.",
+            FutureWarning, stacklevel=2)
+        return self._internal_get_values()
+
+    def _internal_get_values(self):
         return self.values
 
     def get_dtype_counts(self):

pandas/core/groupby/generic.py

@@ -1118,7 +1118,7 @@ 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))
@@ -1192,7 +1192,7 @@ 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
@@ -1306,7 +1306,7 @@ 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

@@ -3764,6 +3764,9 @@ def get_values(self):
         """
         Return `Index` data as an `numpy.ndarray`.
 
+        .. deprecated:: 0.25.0
+            Use :meth:`Index.to_numpy` or :attr:`Index.array` instead.
+
         Returns
         -------
         numpy.ndarray
@@ -3802,6 +3805,13 @@ def get_values(self):
         >>> midx.get_values().ndim
         1
         """
+        warnings.warn(
+            "The 'get_values' method is deprecated and will be removed in a "
+            "future version. Use '.to_numpy()' or '.array' instead.",
+            FutureWarning, stacklevel=2)
+        return self._internal_get_values()
+
+    def _internal_get_values(self):
         return self.values
 
     @Appender(IndexOpsMixin.memory_usage.__doc__)

pandas/core/indexes/category.py

@@ -355,9 +355,10 @@ def _wrap_setop_result(self, other, result):
         name = get_op_result_name(self, other)
         return self._shallow_copy(result, name=name)
 
-    def get_values(self):
-        """ return the underlying data as an ndarray """
-        return self._data.get_values()
+    def _internal_get_values(self):
+        # override base Index version to get the numpy array representation of
+        # the underlying Categorical
+        return self._data._internal_get_values()
 
     def tolist(self):
         return self._data.tolist()

pandas/core/indexes/multi.py

@@ -1246,7 +1246,7 @@ def values(self):
         for i in range(self.nlevels):
             vals = self._get_level_values(i)
             if is_categorical_dtype(vals):
-                vals = vals.get_values()
+                vals = vals._internal_get_values()
             if (isinstance(vals.dtype, ExtensionDtype)
                     or hasattr(vals, '_box_values')):
                 vals = vals.astype(object)

pandas/core/internals/blocks.py

@@ -177,6 +177,12 @@ def get_values(self, dtype=None):
             return self.values.astype(object)
         return self.values
 
+    def get_block_values(self, dtype=None):
+        """
+        This is used in the JSON C code
+        """
+        return self.get_values(dtype=dtype)
+
     def to_dense(self):
         return self.values.view()
 
@@ -2921,7 +2927,7 @@ def to_dense(self):
         # Categorical.get_values returns a DatetimeIndex for datetime
         # categories, so we can't simply use `np.asarray(self.values)` like
         # other types.
-        return self.values.get_values()
+        return self.values._internal_get_values()
 
     def to_native_types(self, slicer=None, na_rep='', quoting=None, **kwargs):
         """ convert to our native types format, slicing if desired """
@@ -3222,7 +3228,7 @@ def _putmask_preserve(nv, n):
     dtype, _ = maybe_promote(n.dtype)
 
     if is_extension_type(v.dtype) and is_object_dtype(dtype):
-        v = v.get_values(dtype)
+        v = v._internal_get_values(dtype)
     else:
         v = v.astype(dtype)
 

pandas/core/ops.py

@@ -1891,7 +1891,7 @@ 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

@@ -506,11 +506,21 @@ def get_values(self):
         """
         Same as values (but handles sparseness conversions); is a view.
 
+        .. deprecated:: 0.25.0
+            Use :meth:`Series.to_numpy` or :attr:`Series.array` instead.
+
         Returns
         -------
         numpy.ndarray
             Data of the Series.
         """
+        warnings.warn(
+            "The 'get_values' method is deprecated and will be removed in a "
+            "future version. Use '.to_numpy()' or '.array' instead.",
+            FutureWarning, stacklevel=2)
+        return self._internal_get_values()
+
+    def _internal_get_values(self):
         return self._data.get_values()
 
     @property

pandas/core/sparse/frame.py

@@ -493,7 +493,7 @@ def xs(self, key, axis=0, copy=False):
             return data
 
         i = self.index.get_loc(key)
-        data = self.take([i]).get_values()[0]
+        data = self.take([i])._internal_get_values()[0]
         return Series(data, index=self.columns)
 
     # ----------------------------------------------------------------------
@@ -694,9 +694,10 @@ 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(),
-                                                row_indexer,
-                                                fill_value=fill_value)
+                new_arrays[col] = algos.take_1d(
+                    self[col]._internal_get_values(),
+                    row_indexer,
+                    fill_value=fill_value)
             else:
                 new_arrays[col] = self[col]
 

pandas/core/sparse/series.py

@@ -224,7 +224,7 @@ def __repr__(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/io/formats/format.py

@@ -129,7 +129,7 @@ def _get_footer(self):
         return str(footer)
 
     def _get_formatted_values(self):
-        return format_array(self.categorical.get_values(), None,
+        return format_array(self.categorical._internal_get_values(), None,
                             float_format=None, na_rep=self.na_rep)
 
     def to_string(self):
@@ -1196,7 +1196,7 @@ def _format_strings(self):
 
         if is_categorical_dtype(values.dtype):
             # Categorical is special for now, so that we can preserve tzinfo
-            array = values.get_values()
+            array = values._internal_get_values()
         else:
             array = np.asarray(values)