DEPR: Deprecate Series/Dataframe.to_dense/to_sparse

pandas/core/frame.py

@@ -1888,6 +1888,7 @@ def from_csv(cls, path, header=0, sep=',', index_col=0, parse_dates=True,
     def to_sparse(self, fill_value=None, kind='block'):
         """
         Convert to SparseDataFrame.
+        .. deprecated:: 0.25.0
 
         Implement the sparse version of the DataFrame meaning that any data
         matching a specific value it's omitted in the representation.
@@ -1939,6 +1940,9 @@ def to_sparse(self, fill_value=None, kind='block'):
         >>> type(sdf)  # doctest: +SKIP
         <class 'pandas.core.sparse.frame.SparseDataFrame'>
         """
+        warnings.warn("DataFrame.to_sparse is deprecated and will be removed "
+                      "in a future version", FutureWarning, stacklevel=2)
+
         from pandas.core.sparse.api import SparseDataFrame
         return SparseDataFrame(self._series, index=self.index,
                                columns=self.columns, default_kind=kind,
@@ -2282,7 +2286,7 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
         text_col     5 non-null object
         float_col    5 non-null float64
         dtypes: float64(1), int64(1), object(1)
-        memory usage: 200.0+ bytes
+        memory usage: 248.0+ bytes
 
         Prints a summary of columns count and its dtypes but not per column
         information:
@@ -2292,7 +2296,7 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
         RangeIndex: 5 entries, 0 to 4
         Columns: 3 entries, int_col to float_col
         dtypes: float64(1), int64(1), object(1)
-        memory usage: 200.0+ bytes
+        memory usage: 248.0+ bytes
 
         Pipe output of DataFrame.info to buffer instead of sys.stdout, get
         buffer content and writes to a text file:
@@ -2494,7 +2498,7 @@ def memory_usage(self, index=True, deep=False):
         4      1      1.0    1.0+0.0j       1  True
 
         >>> df.memory_usage()
-        Index            80
+        Index           128
         int64         40000
         float64       40000
         complex128    80000
@@ -2513,7 +2517,7 @@ def memory_usage(self, index=True, deep=False):
         The memory footprint of `object` dtype columns is ignored by default:
 
         >>> df.memory_usage(deep=True)
-        Index             80
+        Index            128
         int64          40000
         float64        40000
         complex128     80000
@@ -2525,7 +2529,7 @@ def memory_usage(self, index=True, deep=False):
         many repeated values.
 
         >>> df['object'].astype('category').memory_usage(deep=True)
-        5168
+        5216
         """
         result = Series([c.memory_usage(index=False, deep=deep)
                          for col, c in self.iteritems()], index=self.columns)

pandas/core/series.py

@@ -1574,6 +1574,7 @@ def to_frame(self, name=None):
     def to_sparse(self, kind='block', fill_value=None):
         """
         Convert Series to SparseSeries.
+        .. deprecated:: 0.25.0
 
         Parameters
         ----------
@@ -1586,6 +1587,9 @@ def to_sparse(self, kind='block', fill_value=None):
         SparseSeries
             Sparse representation of the Series.
         """
+
+        warnings.warn("Series.to_sparse is deprecated and will be removed "
+                      "in a future version", FutureWarning, stacklevel=2)
         from pandas.core.sparse.series import SparseSeries
 
         values = SparseArray(self, kind=kind, fill_value=fill_value)
@@ -4010,7 +4014,7 @@ def memory_usage(self, index=True, deep=False):
         --------
         >>> s = pd.Series(range(3))
         >>> s.memory_usage()
-        104
+        152
 
         Not including the index gives the size of the rest of the data, which
         is necessarily smaller:
@@ -4024,9 +4028,9 @@ def memory_usage(self, index=True, deep=False):
         >>> s.values
         array(['a', 'b'], dtype=object)
         >>> s.memory_usage()
-        96
+        144
         >>> s.memory_usage(deep=True)
-        212
+        260
         """
         v = super().memory_usage(deep=deep)
         if index:

pandas/core/sparse/frame.py

@@ -242,6 +242,11 @@ def _init_spmatrix(self, data, index, columns, dtype=None,
     def to_coo(self):
         return SparseFrameAccessor(self).to_coo()
 
+    def __repr__(self):
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", "Sparse")
+            return super().__repr__()
+
     def __getstate__(self):
         # pickling
         return dict(_typ=self._typ, _subtyp=self._subtyp, _data=self._data,
@@ -277,6 +282,21 @@ def _unpickle_sparse_frame_compat(self, state):
 
     @Appender(SparseFrameAccessor.to_dense.__doc__)
     def to_dense(self):
+        """
+        .. deprecated:: 0.25.0
+            Use Dataframe.sparse.to_dense() instead
+        """
+
+        warning_message = """\
+SparseDataFrame.to_dense is deprecated and will be removed in a future version
+
+            Use Dataframe.sparse.to_dense() instead
+
+            >>> df = pd.DataFrame({"A": pd.SparseArray([0, 1, 0])})
+            >>> df.sparse.to_dense()
+            """
+        warnings.warn(warning_message, FutureWarning, stacklevel=2)
+
         return SparseFrameAccessor(self).to_dense()
 
     def _apply_columns(self, func):

pandas/core/sparse/series.py

@@ -214,10 +214,12 @@ def as_sparse_array(self, kind=None, fill_value=None, copy=False):
                            fill_value=fill_value, kind=kind, copy=copy)
 
     def __repr__(self):
-        series_rep = Series.__repr__(self)
-        rep = '{series}\n{index!r}'.format(series=series_rep,
-                                           index=self.sp_index)
-        return rep
+        with warnings.catch_warnings():
+            warnings.filterwarnings("ignore", "Sparse")
+            series_rep = Series.__repr__(self)
+            rep = '{series}\n{index!r}'.format(series=series_rep,
+                                               index=self.sp_index)
+            return rep
 
     def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
                 filter_type=None, **kwds):
@@ -429,11 +431,15 @@ def _set_values(self, key, value):
     def to_dense(self):
         """
         Convert SparseSeries to a Series.
-
+        .. deprecated:: 0.25.0
         Returns
         -------
         s : Series
         """
+        warnings.warn("SparseSeries.to_dense is deprecated "
+                      "and will be removed in a future version",
+                      FutureWarning, stacklevel=2)
+
         return Series(self.values.to_dense(), index=self.index,
                       name=self.name)