deprecate .asobject

Author: tp

asv_bench/benchmarks/index_object.py

@@ -12,7 +12,7 @@ def setup(self):
         if (self.rng.dtype == object):
             self.idx_rng = self.rng.view(Index)
         else:
-            self.idx_rng = self.rng.asobject
+            self.idx_rng = self.rng._asobject
         self.idx_rng2 = self.idx_rng[:(-1)]
 
         # other datetime

doc/source/whatsnew/v0.22.0.txt

@@ -84,7 +84,7 @@ Deprecations
 ~~~~~~~~~~~~
 
 - ``Series.from_array`` and ``SparseSeries.from_array`` are deprecated. Use the normal constructor ``Series(..)`` and ``SparseSeries(..)`` instead (:issue:`18213`).
--
+- ``Series.asobject`` and ``Date'timeIndex.asobject`` have been deprecated. Use 'astype(object).values' instead (:issue:`18477`)
 -
 
 .. _whatsnew_0220.prior_deprecations:

pandas/core/algorithms.py

@@ -369,7 +369,7 @@ def unique(values):
         # to return an object array of tz-aware Timestamps
 
         # TODO: it must return DatetimeArray with tz in pandas 2.0
-        uniques = uniques.asobject.values
+        uniques = uniques._asobject.values
 
     return uniques
 

pandas/core/dtypes/concat.py

@@ -401,7 +401,7 @@ def convert_to_pydatetime(x, axis):
         # if dtype is of datetimetz or timezone
         if x.dtype.kind == _NS_DTYPE.kind:
             if getattr(x, 'tz', None) is not None:
-                x = x.asobject.values
+                x = x._asobject.values
             else:
                 shape = x.shape
                 x = tslib.ints_to_pydatetime(x.view(np.int64).ravel(),
@@ -479,7 +479,7 @@ def _concat_index_asobject(to_concat, name=None):
     """
 
     klasses = ABCDatetimeIndex, ABCTimedeltaIndex, ABCPeriodIndex
-    to_concat = [x.asobject if isinstance(x, klasses) else x
+    to_concat = [x._asobject if isinstance(x, klasses) else x
                  for x in to_concat]
 
     from pandas import Index

pandas/core/frame.py

@@ -3305,7 +3305,7 @@ class    max    type
 
         def _maybe_casted_values(index, labels=None):
             if isinstance(index, PeriodIndex):
-                values = index.asobject.values
+                values = index._asobject.values
             elif isinstance(index, DatetimeIndex) and index.tz is not None:
                 values = index
             else:
@@ -5052,7 +5052,7 @@ def applymap(self, func):
         def infer(x):
             if x.empty:
                 return lib.map_infer(x, func)
-            return lib.map_infer(x.asobject, func)
+            return lib.map_infer(x._asobject, func)
 
         return self.apply(infer)
 

pandas/core/indexes/datetimelike.py

@@ -358,7 +358,7 @@ def map(self, f):
                 raise TypeError('The map function must return an Index object')
             return result
         except Exception:
-            return self.asobject.map(f)
+            return self._asobject.map(f)
 
     def sort_values(self, return_indexer=False, ascending=True):
         """
@@ -421,15 +421,22 @@ def _isnan(self):
         return (self.asi8 == iNaT)
 
     @property
-    def asobject(self):
+    def _asobject(self):
         """
         return object Index which contains boxed values
-
-        *this is an internal non-public method*
         """
         from pandas.core.index import Index
         return Index(self._box_values(self.asi8), name=self.name, dtype=object)
 
+    @property
+    def asobject(self):
+        """DEPRECATED: Use 'astype(object).values' instead.
+        """
+        __doc__ += self._asobject.__doc__
+        warnings.warn("'._asobject' is deprecated. Use 'astype(object).values'"
+                      " instead", FutureWarning, stacklevel=2)
+        return self._asobject
+
     def _convert_tolerance(self, tolerance, target):
         tolerance = np.asarray(to_timedelta(tolerance, box=False))
         if target.size != tolerance.size and tolerance.size > 1:
@@ -466,7 +473,7 @@ def tolist(self):
         """
         return a list of the underlying data
         """
-        return list(self.asobject)
+        return list(self._asobject)
 
     def min(self, axis=None, *args, **kwargs):
         """
@@ -744,7 +751,7 @@ def isin(self, values):
             try:
                 values = type(self)(values)
             except ValueError:
-                return self.asobject.isin(values)
+                return self._asobject.isin(values)
 
         return algorithms.isin(self.asi8, values.asi8)
 

pandas/core/indexes/datetimes.py

@@ -906,7 +906,7 @@ def to_datetime(self, dayfirst=False):
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if is_object_dtype(dtype):
-            return self.asobject
+            return self._asobject
         elif is_integer_dtype(dtype):
             return Index(self.values.astype('i8', copy=copy), name=self.name,
                          dtype='i8')
@@ -1678,7 +1678,7 @@ def time(self):
         Returns numpy array of datetime.time. The time part of the Timestamps.
         """
         return self._maybe_mask_results(libalgos.arrmap_object(
-            self.asobject.values,
+            self._asobject.values,
             lambda x: np.nan if x is libts.NaT else x.time()))
 
     @property
@@ -1785,7 +1785,7 @@ def insert(self, loc, item):
 
             # fall back to object index
             if isinstance(item, compat.string_types):
-                return self.asobject.insert(loc, item)
+                return self._asobject.insert(loc, item)
             raise TypeError(
                 "cannot insert DatetimeIndex with incompatible label")
 

pandas/core/indexes/period.py

@@ -418,7 +418,7 @@ def _int64index(self):
 
     @property
     def values(self):
-        return self.asobject.values
+        return self._asobject.values
 
     @property
     def _values(self):
@@ -428,7 +428,7 @@ def __array__(self, dtype=None):
         if is_integer_dtype(dtype):
             return self.asi8
         else:
-            return self.asobject.values
+            return self._asobject.values
 
     def __array_wrap__(self, result, context=None):
         """
@@ -476,7 +476,7 @@ def _to_embed(self, keep_tz=False, dtype=None):
         if dtype is not None:
             return self.astype(dtype)._to_embed(keep_tz=keep_tz)
 
-        return self.asobject.values
+        return self._asobject.values
 
     @property
     def _formatter_func(self):
@@ -506,7 +506,7 @@ def asof_locs(self, where, mask):
     def astype(self, dtype, copy=True, how='start'):
         dtype = pandas_dtype(dtype)
         if is_object_dtype(dtype):
-            return self.asobject
+            return self._asobject
         elif is_integer_dtype(dtype):
             if copy:
                 return self._int64index.copy()
@@ -656,7 +656,7 @@ def end_time(self):
 
     def _mpl_repr(self):
         # how to represent ourselves to matplotlib
-        return self.asobject.values
+        return self._asobject.values
 
     def to_timestamp(self, freq=None, how='start'):
         """
@@ -971,7 +971,7 @@ def _convert_tolerance(self, tolerance, target):
 
     def insert(self, loc, item):
         if not isinstance(item, Period) or self.freq != item.freq:
-            return self.asobject.insert(loc, item)
+            return self._asobject.insert(loc, item)
 
         idx = np.concatenate((self[:loc].asi8, np.array([item.ordinal]),
                               self[loc:].asi8))
@@ -1018,7 +1018,7 @@ def _apply_meta(self, rawarr):
     def _format_native_types(self, na_rep=u('NaT'), date_format=None,
                              **kwargs):
 
-        values = self.asobject.values
+        values = self._asobject.values
 
         if date_format:
             formatter = lambda dt: dt.strftime(date_format)

pandas/core/indexes/timedeltas.py

@@ -482,7 +482,7 @@ def astype(self, dtype, copy=True):
         dtype = np.dtype(dtype)
 
         if is_object_dtype(dtype):
-            return self.asobject
+            return self._asobject
         elif is_timedelta64_ns_dtype(dtype):
             if copy is True:
                 return self.copy()
@@ -881,7 +881,7 @@ def insert(self, loc, item):
 
             # fall back to object index
             if isinstance(item, compat.string_types):
-                return self.asobject.insert(loc, item)
+                return self._asobject.insert(loc, item)
             raise TypeError(
                 "cannot insert TimedeltaIndex with incompatible label")
 

pandas/core/indexing.py

@@ -405,7 +405,7 @@ def _setitem_with_indexer(self, indexer, value):
                             new_values = np.concatenate([self.obj._values,
                                                          new_values])
                         except TypeError:
-                            new_values = np.concatenate([self.obj.asobject,
+                            new_values = np.concatenate([self.obj._asobject,
                                                          new_values])
                     self.obj._data = self.obj._constructor(
                         new_values, index=new_index, name=self.obj.name)._data

pandas/core/internals.py

@@ -2190,7 +2190,7 @@ def _try_coerce_args(self, values, other):
 
         if isinstance(other, ABCDatetimeIndex):
             # to store DatetimeTZBlock as object
-            other = other.asobject.values
+            other = other._asobject.values
 
         return values, False, other, False
 

pandas/core/ops.py

@@ -850,7 +850,7 @@ def wrapper(self, other, axis=None):
                 # tested in test_nat_comparisons
                 # (pandas.tests.series.test_operators.TestSeriesOperators)
                 return self._constructor(na_op(self.values,
-                                               other.asobject.values),
+                                               other._asobject.values),
                                          index=self.index)
 
             return self._constructor(na_op(self.values, np.asarray(other)),

pandas/core/series.py

@@ -209,7 +209,7 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                             # coerce back to datetime objects for lookup
                             data = _dict_compat(data)
                             data = lib.fast_multiget(data,
-                                                     index.asobject.values,
+                                                     index._asobject.values,
                                                      default=np.nan)
                         else:
                             data = np.nan
@@ -433,13 +433,21 @@ def get_values(self):
         return self._data.get_values()
 
     @property
-    def asobject(self):
+    def _asobject(self):
         """
         return object Series which contains boxed values
+        """
+        return self._data._asobject
 
-        *this is an internal non-public method*
+    @property
+    def asobject(self):
+        """DEPRECATED: '.asobject' is deprecated. Use 'astype(object).values'
+        instead.
         """
-        return self._data.asobject
+        __doc__ += self._asobject.__doc__
+        warnings.warn("asobject is deprecated. Use 'astype(object).values'"
+                      " instead", FutureWarning, stacklevel=2)
+        return self._asobject
 
     # ops
     def ravel(self, order='C'):
@@ -1307,7 +1315,7 @@ def unique(self):
             # to return an object array of tz-aware Timestamps
 
             # TODO: it must return DatetimeArray with tz in pandas 2.0
-            result = result.asobject.values
+            result = result._asobject.values
 
         return result
 
@@ -2345,7 +2353,7 @@ def map(self, arg, na_action=None):
                 raise NotImplementedError
             map_f = lambda values, f: values.map(f)
         else:
-            values = self.asobject
+            values = self._asobject
 
             if na_action == 'ignore':
                 def map_f(values, f):
@@ -2567,7 +2575,7 @@ def apply(self, func, convert_dtype=True, args=(), **kwds):
             if is_extension_type(self.dtype):
                 mapped = self._values.map(f)
             else:
-                values = self.asobject
+                values = self._asobject
                 mapped = lib.map_infer(values, f, convert=convert_dtype)
 
         if len(mapped) and isinstance(mapped[0], Series):
@@ -3143,7 +3151,7 @@ def _sanitize_index(data, index, copy=False):
     if isinstance(data, ABCIndexClass) and not copy:
         pass
     elif isinstance(data, PeriodIndex):
-        data = data.asobject
+        data = data._asobject
     elif isinstance(data, DatetimeIndex):
         data = data._to_embed(keep_tz=True)
     elif isinstance(data, np.ndarray):

pandas/io/formats/format.py

@@ -2231,7 +2231,7 @@ class Datetime64TZFormatter(Datetime64Formatter):
     def _format_strings(self):
         """ we by definition have a TZ """
 
-        values = self.values.asobject
+        values = self.values._asobject
         is_dates_only = _is_dates_only(values)
         formatter = (self.formatter or
                      _get_format_datetime64(is_dates_only,

pandas/plotting/_converter.py

@@ -363,7 +363,7 @@ def __call__(self):
         tz = self.tz.tzname(None)
         st = _from_ordinal(dates.date2num(dmin))  # strip tz
         ed = _from_ordinal(dates.date2num(dmax))
-        all_dates = date_range(start=st, end=ed, freq=freq, tz=tz).asobject
+        all_dates = date_range(start=st, end=ed, freq=freq, tz=tz)._asobject
 
         try:
             if len(all_dates) > 0:

pandas/tests/frame/test_constructors.py

@@ -500,8 +500,8 @@ def test_constructor_period(self):
         assert df['b'].dtype == 'object'
 
         # list of periods
-        df = pd.DataFrame({'a': a.asobject.tolist(),
-                           'b': b.asobject.tolist()})
+        df = pd.DataFrame({'a': a._asobject.tolist(),
+                           'b': b._asobject.tolist()})
         assert df['a'].dtype == 'object'
         assert df['b'].dtype == 'object'