ENH: add empty() methods for DataFrame and Series

pandas/core/frame.py

@@ -29,6 +29,7 @@
     _maybe_box_datetimelike, is_categorical_dtype, is_object_dtype,
     is_internal_type, is_datetimetz, _possibly_infer_to_datetimelike,
     _dict_compat)
+from pandas.core.dtypes import ExtensionDtype
 from pandas.core.generic import NDFrame, _shared_docs
 from pandas.core.index import Index, MultiIndex, _ensure_index
 from pandas.core.indexing import (maybe_droplevels, convert_to_index_sliceable,
@@ -771,6 +772,36 @@ def dot(self, other):
         else:  # pragma: no cover
             raise TypeError('unsupported type: %s' % type(other))
 
+    @classmethod
+    def empty(cls, shape, dtype=float):
+        """
+        Return a new DataFrame of given shape and type, without initializing entries.
+
+        Parameters
+        ----------
+        shape : int or tuple of int
+            Shape of the empty DataFrame
+        dtype : data-type, optional
+            Desired output data-type
+
+        Returns
+        -------
+        out : DataFrame
+            DataFrame of uninitialized (arbitrary) data
+            with the given shape and dtype.
+
+        See Also
+        --------
+        numpy.empty : initializes an empty array of given shape and type
+        Series.empty : initializes an empty Series of given length and type
+
+        """
+        if ExtensionDtype.is_dtype(dtype):
+            return cls(np.empty(shape, dtype=object).tolist(), dtype=dtype)
+
+        else:
+            return cls(np.empty(shape, dtype=dtype))
+
     # ----------------------------------------------------------------------
     # IO methods (to / from other formats)
 

pandas/core/series.py

@@ -26,6 +26,7 @@
                                 _coerce_to_dtype, SettingWithCopyError,
                                 _maybe_box_datetimelike, ABCDataFrame,
                                 _dict_compat)
+from pandas.core.dtypes import ExtensionDtype
 from pandas.core.index import (Index, MultiIndex, InvalidIndexError,
                                Float64Index, _ensure_index)
 from pandas.core.indexing import check_bool_indexer, maybe_convert_indices
@@ -243,6 +244,36 @@ def from_array(cls, arr, index=None, name=None, dtype=None, copy=False,
         return cls(arr, index=index, name=name, dtype=dtype, copy=copy,
                    fastpath=fastpath)
 
+    @classmethod
+    def empty(cls, length, dtype=float):
+        """
+        Return a new Series of given length and type, without initializing entries.
+
+        Parameters
+        ----------
+        length : int
+            Length of the empty Series
+        dtype : data-type, optional
+            Desired output data-type
+
+        Returns
+        -------
+        out : Series
+            Series of uninitialized (arbitrary) data
+            with the given length and dtype.
+
+        See Also
+        --------
+        numpy.empty : initializes an empty array of given shape and type
+        DataFrame.empty : initializes an empty DataFrame of given shape and type
+
+        """
+        if ExtensionDtype.is_dtype(dtype):
+            return cls.from_array(np.empty(length, dtype=object), dtype=dtype)
+
+        else:
+            return cls(np.empty(length, dtype=dtype))
+
     @property
     def _constructor(self):
         return Series

pandas/tests/frame/test_constructors.py

@@ -1995,3 +1995,24 @@ def test_from_records_len0_with_columns(self):
         self.assertTrue(np.array_equal(result.columns, ['bar']))
         self.assertEqual(len(result), 0)
         self.assertEqual(result.index.name, 'foo')
+
+    def test_empty(self):
+        from pandas.core.dtypes import DatetimeTZDtype
+
+        df = DataFrame({'dt': pd.date_range(
+            "2015-01-01", periods=3, tz='Europe/Brussels')})
+        dt = df.values.dtype
+
+        params = [
+            (dt, (4, 8), dt),
+            (None, (7, 1), float),
+            (np.int64, (3, 5), np.int64),
+            (DatetimeTZDtype, (2, 3), object),
+        ]
+
+        for in_dt, shape, out_dt in params:
+            df = DataFrame.empty(shape, dtype=in_dt)
+            self.assertEqual(df.shape, shape)
+
+            for col in df.columns:
+                self.assertEqual(df[col].dtype, out_dt)

pandas/tests/series/test_constructors.py

@@ -706,3 +706,22 @@ def f():
         self.assertEqual(s.dtype, 'timedelta64[ns]')
         s = Series([pd.NaT, np.nan, '1 Day'])
         self.assertEqual(s.dtype, 'timedelta64[ns]')
+
+    def test_empty(self):
+        from pandas.core.dtypes import DatetimeTZDtype
+
+        df = pd.DataFrame({'dt': pd.date_range(
+            "2015-01-01", periods=3, tz='Europe/Brussels')})
+        dt = df.values.dtype
+
+        params = [
+            (dt, 6, dt),
+            (None, 3, float),
+            (np.int64, 10, np.int64),
+            (DatetimeTZDtype, 5, object),
+        ]
+
+        for in_dt, length, out_dt in params:
+            s = Series.empty(length, dtype=in_dt)
+            self.assertEqual(s.size, length)
+            self.assertEqual(s.dtype, out_dt)