DEPR: Remove top level numpy/datetime/Sparse object imports

doc/source/whatsnew/v0.19.0.rst

@@ -1245,10 +1245,9 @@ Previously, sparse data were ``float64`` dtype by default, even if all inputs we
 As of v0.19.0, sparse data keeps the input dtype, and uses more appropriate ``fill_value`` defaults (``0`` for ``int64`` dtype, ``False`` for ``bool`` dtype).
 
 .. ipython:: python
-   :okwarning:
 
-   pd.SparseArray([1, 2, 0, 0], dtype=np.int64)
-   pd.SparseArray([True, False, False, False])
+   pd.arrays.SparseArray([1, 2, 0, 0], dtype=np.int64)
+   pd.arrays.SparseArray([True, False, False, False])
 
 See the :ref:`docs <sparse.dtype>` for more details.
 

doc/source/whatsnew/v0.25.0.rst

@@ -359,9 +359,8 @@ When passed DataFrames whose values are sparse, :func:`concat` will now return a
 :class:`Series` or :class:`DataFrame` with sparse values, rather than a :class:`SparseDataFrame` (:issue:`25702`).
 
 .. ipython:: python
-   :okwarning:
 
-   df = pd.DataFrame({"A": pd.SparseArray([0, 1])})
+   df = pd.DataFrame({"A": pd.arrays.SparseArray([0, 1])})
 
 *Previous behavior*:
 
@@ -918,9 +917,8 @@ by a ``Series`` or ``DataFrame`` with sparse values.
 **New way**
 
 .. ipython:: python
-   :okwarning:
 
-   df = pd.DataFrame({"A": pd.SparseArray([0, 0, 1, 2])})
+   df = pd.DataFrame({"A": pd.arrays.SparseArray([0, 0, 1, 2])})
    df.dtypes
 
 The memory usage of the two approaches is identical. See :ref:`sparse.migration` for more (:issue:`19239`).

doc/source/whatsnew/v2.0.0.rst

@@ -190,6 +190,10 @@ Removal of prior version deprecations/changes
 - Remove :meth:`DataFrameGroupBy.pad` and :meth:`DataFrameGroupBy.backfill` (:issue:`45076`)
 - Remove ``numpy`` argument from :func:`read_json` (:issue:`30636`)
 - Removed the ``center`` keyword in :meth:`DataFrame.expanding` (:issue:`20647`)
+- Removed the ``pandas.datetime`` submodule (:issue:`30489`)
+- Removed the ``pandas.np`` submodule (:issue:`30296`)
+- Removed ``pandas.SparseArray`` in favor of :class:`arrays.SparseArray` (:issue:`30642`)
+- Removed ``pandas.SparseSeries`` and ``pandas.SparseDataFrame`` (:issue:`30642`)
 - Enforced disallowing a string column label into ``times`` in :meth:`DataFrame.ewm` (:issue:`43265`)
 - Enforced :meth:`Rolling.count` with ``min_periods=None`` to default to the size of the window (:issue:`31302`)
 -

pandas/__init__.py

@@ -212,54 +212,6 @@ def __getattr__(name):
             "Int64Index": Int64Index,
             "UInt64Index": UInt64Index,
         }[name]
-    elif name == "datetime":
-        warnings.warn(
-            "The pandas.datetime class is deprecated "
-            "and will be removed from pandas in a future version. "
-            "Import from datetime module instead.",
-            FutureWarning,
-            stacklevel=2,
-        )
-
-        from datetime import datetime as dt
-
-        return dt
-
-    elif name == "np":
-
-        warnings.warn(
-            "The pandas.np module is deprecated "
-            "and will be removed from pandas in a future version. "
-            "Import numpy directly instead.",
-            FutureWarning,
-            stacklevel=2,
-        )
-        import numpy as np
-
-        return np
-
-    elif name in {"SparseSeries", "SparseDataFrame"}:
-        warnings.warn(
-            f"The {name} class is removed from pandas. Accessing it from "
-            "the top-level namespace will also be removed in the next version.",
-            FutureWarning,
-            stacklevel=2,
-        )
-
-        return type(name, (), {})
-
-    elif name == "SparseArray":
-
-        warnings.warn(
-            "The pandas.SparseArray class is deprecated "
-            "and will be removed from pandas in a future version. "
-            "Use pandas.arrays.SparseArray instead.",
-            FutureWarning,
-            stacklevel=2,
-        )
-        from pandas.core.arrays.sparse import SparseArray as _SparseArray
-
-        return _SparseArray
 
     raise AttributeError(f"module 'pandas' has no attribute '{name}'")
 

pandas/core/arrays/sparse/accessor.py

@@ -66,9 +66,9 @@ def from_coo(cls, A, dense_index: bool = False) -> Series:
         ----------
         A : scipy.sparse.coo_matrix
         dense_index : bool, default False
-            If False (default), the SparseSeries index consists of only the
+            If False (default), the index consists of only the
             coords of the non-null entries of the original coo_matrix.
-            If True, the SparseSeries index consists of the full sorted
+            If True, the index consists of the full sorted
             (row, col) coordinates of the coo_matrix.
 
         Returns

pandas/core/arrays/sparse/scipy_sparse.py

@@ -177,7 +177,7 @@ def coo_to_sparse_series(
     A: scipy.sparse.coo_matrix, dense_index: bool = False
 ) -> Series:
     """
-    Convert a scipy.sparse.coo_matrix to a SparseSeries.
+    Convert a scipy.sparse.coo_matrix to a Series with type sparse.
 
     Parameters
     ----------

pandas/tests/api/test_api.py

@@ -45,9 +45,6 @@ class TestPDApi(Base):
     ]
     private_lib = ["compat", "core", "pandas", "util"]
 
-    # these are already deprecated; awaiting removal
-    deprecated_modules: list[str] = ["np", "datetime"]
-
     # misc
     misc = ["IndexSlice", "NaT", "NA"]
 
@@ -101,9 +98,6 @@ class TestPDApi(Base):
     # these are already deprecated; awaiting removal
     deprecated_classes: list[str] = ["Float64Index", "Int64Index", "UInt64Index"]
 
-    # these should be deprecated in the future
-    deprecated_classes_in_future: list[str] = ["SparseArray"]
-
     # external modules exposed in pandas namespace
     modules: list[str] = []
 
@@ -237,9 +231,7 @@ def test_api_all(self):
 
     def test_depr(self):
         deprecated_list = (
-            self.deprecated_modules
-            + self.deprecated_classes
-            + self.deprecated_classes_in_future
+            self.deprecated_classes
             + self.deprecated_funcs
             + self.deprecated_funcs_in_future
         )
@@ -248,35 +240,6 @@ def test_depr(self):
                 _ = getattr(pd, depr)
 
 
-def test_datetime():
-    from datetime import datetime
-    import warnings
-
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", FutureWarning)
-        assert datetime(2015, 1, 2, 0, 0) == datetime(2015, 1, 2, 0, 0)
-
-        assert isinstance(datetime(2015, 1, 2, 0, 0), datetime)
-
-
-def test_sparsearray():
-    import warnings
-
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", FutureWarning)
-        assert isinstance(pd.array([1, 2, 3], dtype="Sparse"), pd.SparseArray)
-
-
-def test_np():
-    import warnings
-
-    import numpy as np
-
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", FutureWarning)
-        assert (pd.np.arange(0, 10) == np.arange(0, 10)).all()
-
-
 class TestApi(Base):
     allowed = ["types", "extensions", "indexers", "interchange"]
 

pandas/tests/arrays/sparse/test_arithmetics.py

@@ -13,7 +13,7 @@
 
 @pytest.fixture(params=["integer", "block"])
 def kind(request):
-    """kind kwarg to pass to SparseArray/SparseSeries"""
+    """kind kwarg to pass to SparseArray"""
     return request.param