CLN: Remove sparse

Author: TomAugspurger

pandas/__init__.py

@@ -116,8 +116,6 @@
 
 from pandas.core.sparse.api import (
     SparseArray,
-    SparseDataFrame,
-    SparseSeries,
     SparseDtype,
 )
 

pandas/core/arrays/sparse.py

@@ -43,7 +43,6 @@
     ABCIndexClass,
     ABCSeries,
     ABCSparseArray,
-    ABCSparseSeries,
 )
 from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
 
@@ -607,7 +606,7 @@ def __init__(
         if fill_value is None and isinstance(dtype, SparseDtype):
             fill_value = dtype.fill_value
 
-        if isinstance(data, (type(self), ABCSparseSeries)):
+        if isinstance(data, type(self)):
             # disable normal inference on dtype, sparse_index, & fill_value
             if sparse_index is None:
                 sparse_index = data.sp_index
@@ -1982,7 +1981,8 @@ def from_coo(cls, A, dense_index=False):
 
         Returns
         -------
-        s : SparseSeries
+        s : Series
+            A Series with sparse values.
 
         Examples
         --------
@@ -1996,7 +1996,7 @@ def from_coo(cls, A, dense_index=False):
         matrix([[ 0.,  0.,  1.,  2.],
                 [ 3.,  0.,  0.,  0.],
                 [ 0.,  0.,  0.,  0.]])
-        >>> ss = pd.SparseSeries.from_coo(A)
+        >>> ss = pd.Series.sparse.from_coo(A)
         >>> ss
         0  2    1
            3    2
@@ -2016,7 +2016,7 @@ def from_coo(cls, A, dense_index=False):
 
     def to_coo(self, row_levels=(0,), column_levels=(1,), sort_labels=False):
         """
-        Create a scipy.sparse.coo_matrix from a SparseSeries with MultiIndex.
+        Create a scipy.sparse.coo_matrix from a Series with MultiIndex.
 
         Use row_levels and column_levels to determine the row and column
         coordinates respectively. row_levels and column_levels are the names

pandas/core/dtypes/generic.py

@@ -52,12 +52,7 @@ def _check(cls, inst):
 
 ABCSeries = create_pandas_abc_type("ABCSeries", "_typ", ("series",))
 ABCDataFrame = create_pandas_abc_type("ABCDataFrame", "_typ", ("dataframe",))
-ABCSparseDataFrame = create_pandas_abc_type(
-    "ABCSparseDataFrame", "_subtyp", ("sparse_frame",)
-)
-ABCSparseSeries = create_pandas_abc_type(
-    "ABCSparseSeries", "_subtyp", ("sparse_series", "sparse_time_series")
-)
+
 ABCSparseArray = create_pandas_abc_type(
     "ABCSparseArray", "_subtyp", ("sparse_array", "sparse_series")
 )

pandas/core/groupby/generic.py

@@ -58,7 +58,6 @@
 import pandas.core.indexes.base as ibase
 from pandas.core.internals import BlockManager, make_block
 from pandas.core.series import Series
-from pandas.core.sparse.frame import SparseDataFrame
 
 from pandas.plotting import boxplot_frame_groupby
 
@@ -258,12 +257,6 @@ def aggregate(self, func, *args, **kwargs):
                         result.columns.levels[0], name=self._selected_obj.columns.name
                     )
 
-                    if isinstance(self.obj, SparseDataFrame):
-                        # Backwards compat for groupby.agg() with sparse
-                        # values. concat no longer converts DataFrame[Sparse]
-                        # to SparseDataFrame, so we do it here.
-                        result = SparseDataFrame(result._data)
-
         if not self.as_index:
             self._insert_inaxis_grouper_inplace(result)
             result.index = np.arange(len(result))

pandas/core/ops/__init__.py

@@ -32,7 +32,6 @@
     ABCExtensionArray,
     ABCIndexClass,
     ABCSeries,
-    ABCSparseSeries,
     ABCTimedeltaArray,
     ABCTimedeltaIndex,
 )
@@ -1151,8 +1150,6 @@ def wrapper(self, other):
         if isinstance(other, ABCDataFrame):
             return NotImplemented
         elif isinstance(other, ABCSeries):
-            if not isinstance(other, ABCSparseSeries):
-                other = other.to_sparse(fill_value=self.fill_value)
             return _sparse_series_op(self, other, op, op_name)
         elif is_scalar(other):
             with np.errstate(all="ignore"):

pandas/core/ops/methods.py

@@ -3,12 +3,7 @@
 """
 import operator
 
-from pandas.core.dtypes.generic import (
-    ABCDataFrame,
-    ABCSeries,
-    ABCSparseArray,
-    ABCSparseSeries,
-)
+from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries, ABCSparseArray
 
 from pandas.core.ops.roperator import (
     radd,
@@ -51,25 +46,15 @@ def _get_method_wrappers(cls):
     from pandas.core.ops import (
         _arith_method_FRAME,
         _arith_method_SERIES,
-        _arith_method_SPARSE_SERIES,
         _bool_method_SERIES,
         _comp_method_FRAME,
         _comp_method_SERIES,
         _flex_comp_method_FRAME,
         _flex_method_SERIES,
     )
 
-    if issubclass(cls, ABCSparseSeries):
-        # Be sure to catch this before ABCSeries and ABCSparseArray,
-        # as they will both come see SparseSeries as a subclass
-        arith_flex = _flex_method_SERIES
-        comp_flex = _flex_method_SERIES
-        arith_special = _arith_method_SPARSE_SERIES
-        comp_special = _arith_method_SPARSE_SERIES
-        bool_special = _bool_method_SERIES
-        # TODO: I don't think the functions defined by bool_method are tested
-    elif issubclass(cls, ABCSeries):
-        # Just Series; SparseSeries is caught above
+    if issubclass(cls, ABCSeries):
+        # Just Series
         arith_flex = _flex_method_SERIES
         comp_flex = _flex_method_SERIES
         arith_special = _arith_method_SERIES
@@ -176,7 +161,7 @@ def _create_methods(cls, arith_method, comp_method, bool_method, special):
     # constructors.
 
     have_divmod = issubclass(cls, ABCSeries)
-    # divmod is available for Series and SparseSeries
+    # divmod is available for Series
 
     # yapf: disable
     new_methods = dict(

pandas/core/reshape/concat.py

@@ -6,8 +6,6 @@
 
 import numpy as np
 
-from pandas.core.dtypes.generic import ABCSparseDataFrame
-
 from pandas import DataFrame, Index, MultiIndex, Series
 from pandas.core import common as com
 from pandas.core.arrays.categorical import (
@@ -715,15 +713,11 @@ def _get_series_result_type(result, objs=None):
     return appropriate class of Series concat
     input is either dict or array-like
     """
-    from pandas import SparseSeries, SparseDataFrame, DataFrame
+    from pandas import DataFrame
 
     # concat Series with axis 1
     if isinstance(result, dict):
-        # concat Series with axis 1
-        if all(isinstance(c, (SparseSeries, SparseDataFrame)) for c in result.values()):
-            return SparseDataFrame
-        else:
-            return DataFrame
+        return DataFrame
 
     # otherwise it is a SingleBlockManager (axis = 0)
     return objs[0]._constructor
@@ -735,10 +729,4 @@ def _get_frame_result_type(result, objs):
     if all blocks are sparse, return SparseDataFrame
     otherwise, return 1st obj
     """
-
-    if result.blocks and (any(isinstance(obj, ABCSparseDataFrame) for obj in objs)):
-        from pandas.core.sparse.api import SparseDataFrame
-
-        return SparseDataFrame
-    else:
-        return next(obj for obj in objs if not isinstance(obj, ABCSparseDataFrame))
+    return objs[0]

pandas/core/series.py

@@ -44,7 +44,6 @@
     ABCDatetimeIndex,
     ABCSeries,
     ABCSparseArray,
-    ABCSparseSeries,
 )
 from pandas.core.dtypes.missing import (
     isna,
@@ -246,7 +245,7 @@ def __init__(
 
             elif isinstance(data, np.ndarray):
                 pass
-            elif isinstance(data, (ABCSeries, ABCSparseSeries)):
+            elif isinstance(data, ABCSeries):
                 if name is None:
                     name = data.name
                 if index is None:

pandas/core/sparse/api.py

@@ -1,4 +1,3 @@
-# flake8: noqa
 from pandas.core.arrays.sparse import SparseArray, SparseDtype
-from pandas.core.sparse.frame import SparseDataFrame
-from pandas.core.sparse.series import SparseSeries
+
+__all__ = ["SparseArray", "SparseDtype"]