diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index e6fafc8b1b14c..7b252a0e8a03e 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/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`)
diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
index 23197b9a55afc..9c56f96fc138b 100644
--- a/pandas/_libs/tslibs/timestamps.pyx
+++ b/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):
diff --git a/pandas/tests/indexing/test_loc.py b/pandas/tests/indexing/test_loc.py
index 8838fc7eed2f7..aea75d29e361e 100644
--- a/pandas/tests/indexing/test_loc.py
+++ b/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,
diff --git a/pandas/tests/io/formats/test_to_csv.py b/pandas/tests/io/formats/test_to_csv.py
index 6d762fdeb8d79..d38387e523da9 100644
--- a/pandas/tests/io/formats/test_to_csv.py
+++ b/pandas/tests/io/formats/test_to_csv.py
@@ -302,7 +302,9 @@ 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(
@@ -310,7 +312,9 @@ def test_to_csv_date_format_in_categorical(self):
).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
diff --git a/pandas/tests/scalar/test_nat.py b/pandas/tests/scalar/test_nat.py
index b20df43dd49a6..c274670e2acdc 100644
--- a/pandas/tests/scalar/test_nat.py
+++ b/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])
diff --git a/pandas/tests/scalar/timestamp/test_constructors.py b/pandas/tests/scalar/timestamp/test_constructors.py
index 2c97c4a32e0aa..d7721b008ccad 100644
--- a/pandas/tests/scalar/timestamp/test_constructors.py
+++ b/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",
[
diff --git a/pandas/tests/test_multilevel.py b/pandas/tests/test_multilevel.py
index a23e6d9b3973a..321a68cad2f38 100644
--- a/pandas/tests/test_multilevel.py
+++ b/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)