BUG: Added deprecation warning to Timestamp constructor

doc/source/whatsnew/v3.0.0.rst

@@ -416,6 +416,7 @@ Other Deprecations
 - Deprecated allowing non-keyword arguments in :meth:`Series.to_string` except ``buf``. (:issue:`57280`)
 - Deprecated behavior of :meth:`.DataFrameGroupBy.groups` and :meth:`.SeriesGroupBy.groups`, in a future version ``groups`` by one element list will return tuple instead of scalar. (:issue:`58858`)
 - Deprecated behavior of :meth:`Series.dt.to_pytimedelta`, in a future version this will return a :class:`Series` containing python ``datetime.timedelta`` objects instead of an ``ndarray`` of timedelta; this matches the behavior of other :meth:`Series.dt` properties. (:issue:`57463`)
+- Deprecated empty string in :class:`Timestamp` (:issue:`61149`)
 - Deprecated lowercase strings ``d``, ``b`` and ``c`` denoting frequencies in :class:`Day`, :class:`BusinessDay` and :class:`CustomBusinessDay` in favour of ``D``, ``B`` and ``C`` (:issue:`58998`)
 - Deprecated lowercase strings ``w``, ``w-mon``, ``w-tue``, etc. denoting frequencies in :class:`Week` in favour of ``W``, ``W-MON``, ``W-TUE``, etc. (:issue:`58998`)
 - Deprecated parameter ``method`` in :meth:`DataFrame.reindex_like` / :meth:`Series.reindex_like` (:issue:`58667`)

pandas/_libs/tslibs/timestamps.pyx

@@ -2587,6 +2587,14 @@ class Timestamp(_Timestamp):
                 tzinfo is None):
             return ts_input
         elif isinstance(ts_input, str):
+            if ts_input == "":
+                warnings.warn(
+                    "Passing an empty string to Timestamp is deprecated and will raise "
+                    "a ValueError in a future version.",
+                    FutureWarning,
+                    stacklevel = find_stack_level()
+                )
+
             # User passed a date string to parse.
             # Check that the user didn't also pass a date attribute kwarg.
             if any(arg is not None for arg in _date_attributes):

pandas/tests/indexing/test_loc.py

@@ -39,7 +39,10 @@
     to_timedelta,
 )
 import pandas._testing as tm
-from pandas.api.types import is_scalar
+from pandas.api.types import (
+    is_datetime64_any_dtype,
+    is_scalar,
+)
 from pandas.core.indexing import _one_ellipsis_message
 from pandas.tests.indexing.common import check_indexing_smoketest_or_raises
 
@@ -2084,7 +2087,21 @@ def test_loc_setitem_with_expansion_nonunique_index(self, index):
         assert key not in index  # otherwise test is invalid
         # TODO: using a tuple key breaks here in many cases
 
-        exp_index = index.insert(len(index), key)
+        msg = "Passing an empty string to Timestamp"
+        contains_datetime = False
+        if isinstance(index, MultiIndex):
+            for i in range(index.nlevels):
+                if is_datetime64_any_dtype(index.get_level_values(i)):
+                    contains_datetime = True
+                    break
+            if contains_datetime:
+                with tm.assert_produces_warning(FutureWarning, match=msg):
+                    exp_index = index.insert(len(index), key)
+            else:
+                exp_index = index.insert(len(index), key)
+        else:
+            exp_index = index.insert(len(index), key)
+
         if isinstance(index, MultiIndex):
             assert exp_index[-1][0] == key
         else:
@@ -2094,19 +2111,32 @@ def test_loc_setitem_with_expansion_nonunique_index(self, index):
 
         # Add new row, but no new columns
         df = orig.copy()
-        df.loc[key, 0] = N
+        if contains_datetime:
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                df.loc[key, 0] = N
+        else:
+            df.loc[key, 0] = N
         tm.assert_frame_equal(df, expected)
 
         # add new row on a Series
         ser = orig.copy()[0]
-        ser.loc[key] = N
+        if contains_datetime:
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                ser.loc[key] = N
+        else:
+            ser.loc[key] = N
+        tm.assert_frame_equal(df, expected)
         # the series machinery lets us preserve int dtype instead of float
         expected = expected[0].astype(np.int64)
         tm.assert_series_equal(ser, expected)
 
         # add new row and new column
         df = orig.copy()
-        df.loc[key, 1] = N
+        if contains_datetime:
+            with tm.assert_produces_warning(FutureWarning, match=msg):
+                df.loc[key, 1] = N
+        else:
+            df.loc[key, 1] = N
         expected = DataFrame(
             {0: list(arr) + [np.nan], 1: [np.nan] * N + [float(N)]},
             index=exp_index,

pandas/tests/io/formats/test_to_csv.py

@@ -302,15 +302,19 @@ def test_to_csv_date_format_in_categorical(self):
         ser = pd.Series(pd.to_datetime(["2021-03-27", pd.NaT], format="%Y-%m-%d"))
         ser = ser.astype("category")
         expected = tm.convert_rows_list_to_csv_str(["0", "2021-03-27", '""'])
-        assert ser.to_csv(index=False) == expected
+        msg = "Passing an empty string to Timestamp"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert ser.to_csv(index=False) == expected
 
         ser = pd.Series(
             pd.date_range(
                 start="2021-03-27", freq="D", periods=1, tz="Europe/Berlin"
             ).append(pd.DatetimeIndex([pd.NaT]))
         )
         ser = ser.astype("category")
-        assert ser.to_csv(index=False, date_format="%Y-%m-%d") == expected
+        msg = "Passing an empty string to Timestamp"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            assert ser.to_csv(index=False, date_format="%Y-%m-%d") == expected
 
     def test_to_csv_float_ea_float_format(self):
         # GH#45991

pandas/tests/scalar/test_nat.py

@@ -109,7 +109,13 @@ def test_nat_vector_field_access():
     "value", [None, np.nan, iNaT, float("nan"), NaT, "NaT", "nat", "", "NAT"]
 )
 def test_identity(klass, value):
-    assert klass(value) is NaT
+    if value == "" and klass == Timestamp:
+        msg = "Passing an empty string to Timestamp"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            result = klass(value)
+    else:
+        result = klass(value)
+    assert result is NaT
 
 
 @pytest.mark.parametrize("klass", [Timestamp, Timedelta])

pandas/tests/scalar/timestamp/test_constructors.py

@@ -62,6 +62,11 @@ def test_constructor_float_not_round_with_YM_unit_raises(self):
         with pytest.raises(ValueError, match=msg):
             Timestamp(150.5, unit="M")
 
+    def test_constructor_with_empty_string(self):
+        msg = "Passing an empty string to Timestamp"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            Timestamp("")
+
     @pytest.mark.parametrize(
         "value, check_kwargs",
         [

pandas/tests/test_multilevel.py

@@ -313,7 +313,9 @@ def test_multiindex_dt_with_nan(self):
                 names=[None, "Date"],
             ),
         )
-        df = df.reset_index()
+        msg = "Passing an empty string to Timestamp"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            df = df.reset_index()
         result = df[df.columns[0]]
         expected = Series(["a", "b", "c", "d"], name=("sub", np.nan))
         tm.assert_series_equal(result, expected)