Fix/empty string datetimelike conversion/issue 36550

pandas/_libs/tslib.pyx

@@ -485,7 +485,16 @@ cpdef array_to_datetime(
                     # string
                     seen_string = True
 
-                    if len(val) == 0 or val in nat_strings:
+                    if len(val) == 0:
+                        if is_coerce:
+                            iresult[i] = NPY_NAT
+                            continue
+                        elif is_ignore:
+                            raise TypeError("Empty string is not a valid datetime")
+                        else:
+                            raise ValueError("Empty string is not a valid datetime")
+
+                    if val in nat_strings:
                         iresult[i] = NPY_NAT
                         continue
 
@@ -710,7 +719,10 @@ cdef array_to_datetime_object(
             # GH 25978. No need to parse NaT-like or datetime-like vals
             oresult[i] = val
         elif isinstance(val, str):
-            if len(val) == 0 or val in nat_strings:
+            if len(val) == 0:
+                oresult[i] = val
+                continue
+            if val in nat_strings:
                 oresult[i] = 'NaT'
                 continue
             try:

pandas/_libs/tslibs/conversion.pyx

@@ -596,7 +596,9 @@ cdef _TSObject _convert_str_to_tsobject(object ts, tzinfo tz, str unit,
         int out_local = 0, out_tzoffset = 0
         bint do_parse_datetime_string = False
 
-    if len(ts) == 0 or ts in nat_strings:
+    if len(ts) == 0:
+        raise ValueError("Empty string is not a valid timestamp")
+    elif ts in nat_strings:
         ts = NaT
     elif ts == 'now':
         # Issue 9000, we short-circuit rather than going

pandas/_libs/tslibs/timedeltas.pyx

@@ -294,7 +294,9 @@ cdef inline int64_t parse_timedelta_string(str ts) except? -1:
     # have_value : track if we have at least 1 leading unit
     # have_hhmmss : tracks if we have a regular format hh:mm:ss
 
-    if len(ts) == 0 or ts in nat_strings:
+    if len(ts) == 0:
+        raise ValueError("Empty string is not a valid timedelta")
+    if ts in nat_strings:
         return NPY_NAT
 
     for c in ts:

pandas/core/indexes/base.py

@@ -2182,7 +2182,7 @@ def isna(self):
         For datetimes, `NaT` (Not a Time) is considered as an NA value.
 
         >>> idx = pd.DatetimeIndex([pd.Timestamp('1940-04-25'),
-        ...                         pd.Timestamp(''), None, pd.NaT])
+        ...                         pd.Timestamp('NaT'), None, pd.NaT])
         >>> idx
         DatetimeIndex(['1940-04-25', 'NaT', 'NaT', 'NaT'],
                       dtype='datetime64[ns]', freq=None)

pandas/tests/groupby/test_apply.py

@@ -643,7 +643,7 @@ def predictions(tool):
         {
             "Key": ["B", "B", "A", "A"],
             "State": ["step1", "step2", "step1", "step2"],
-            "oTime": ["", "2016-09-19 05:24:33", "", "2016-09-19 23:59:04"],
+            "oTime": ["NaT", "2016-09-19 05:24:33", "NaT", "2016-09-19 23:59:04"],
             "Machine": ["23", "36L", "36R", "36R"],
         }
     )

pandas/tests/io/parser/test_parse_dates.py

@@ -1129,9 +1129,7 @@ def test_parse_dates_empty_string(all_parsers):
     data = "Date,test\n2012-01-01,1\n,2"
     result = parser.read_csv(StringIO(data), parse_dates=["Date"], na_filter=False)
 
-    expected = DataFrame(
-        [[datetime(2012, 1, 1), 1], [pd.NaT, 2]], columns=["Date", "test"]
-    )
+    expected = DataFrame([[datetime(2012, 1, 1), 1], ["", 2]], columns=["Date", "test"])
     tm.assert_frame_equal(result, expected)
 
 

pandas/tests/scalar/test_nat.py

@@ -104,8 +104,13 @@ def test_identity(klass, value):
 @pytest.mark.parametrize("klass", [Timestamp, Timedelta, Period])
 @pytest.mark.parametrize("value", ["", "nat", "NAT", None, np.nan])
 def test_equality(klass, value):
-    if klass is Period and value == "":
-        pytest.skip("Period cannot parse empty string")
+    if value == "":
+        if klass is Period and value == "":
+            pytest.skip("Period cannot parse empty string")
+        elif klass is Timedelta:
+            pytest.skip("Timedelta cannot parse empty string")
+        elif klass is Timestamp:
+            pytest.skip("Timestamp cannot parse empty string")
 
     assert klass(value).value == iNaT
 

pandas/tests/scalar/timedelta/test_constructors.py

@@ -131,6 +131,12 @@ def test_construction():
         Timedelta("foo bar")
 
 
+def test_construction_empty_string():
+    # Issue #36550, empty string
+    with pytest.raises(ValueError):
+        Timedelta("")
+
+
 @pytest.mark.parametrize(
     "item",
     list(

pandas/tests/scalar/timestamp/test_constructors.py

@@ -552,6 +552,10 @@ def test_constructor_fromisocalendar(self):
         assert result == expected_stdlib
         assert isinstance(result, Timestamp)
 
+    def test_constructior_empty_string(self):
+        with pytest.raises(ValueError):
+            Timestamp("")
+
 
 def test_constructor_ambigous_dst():
     # GH 24329

pandas/tests/series/methods/test_isin.py

@@ -80,3 +80,21 @@ def test_isin_empty(self, empty):
 
         result = s.isin(empty)
         tm.assert_series_equal(expected, result)
+
+    @pytest.mark.parametrize(
+        "values, in_list, expected",
+        [
+            ([""], ["", pd.Timedelta(0)], [True]),
+            (["", pd.Timedelta(0)], [""], [True, False]),
+            ([""], ["", pd.to_datetime("2020-01-01")], [True]),
+            (["", pd.to_datetime("2020-01-01")], [""], [True, False]),
+        ],
+    )
+    def test_empty_string_category(self, values, in_list, expected):
+        # Issue #36550
+        # Mixed empty string with datetimelike
+        s = pd.Series(values)
+        pd.testing.assert_series_equal(
+            s.isin(in_list),
+            pd.Series(expected),
+        )

pandas/tests/tools/test_to_datetime.py

@@ -1090,6 +1090,16 @@ def test_to_datetime_fixed_offset(self):
         result = to_datetime(dates)
         assert result.tz == fixed_off
 
+    def test_to_datetime_empty_string(self):
+        with pytest.raises(ValueError):
+            pd.to_datetime("", errors="raise")
+
+        result = pd.to_datetime("", errors="ignore")
+        assert result == ""
+
+        result = pd.to_datetime("", errors="coerce")
+        assert result is pd.NaT
+
 
 class TestToDatetimeUnit:
     @pytest.mark.parametrize("cache", [True, False])
@@ -1574,11 +1584,11 @@ def test_to_datetime_with_apply(self, cache):
     def test_to_datetime_types(self, cache):
 
         # empty string
-        result = to_datetime("", cache=cache)
-        assert result is NaT
+        with pytest.raises(ValueError):
+            result = to_datetime("", cache=cache)
 
-        result = to_datetime(["", ""], cache=cache)
-        assert isna(result).all()
+        with pytest.raises(ValueError):
+            result = to_datetime(["", ""], cache=cache)
 
         # ints
         result = Timestamp(0)

pandas/tests/tools/test_to_timedelta.py

@@ -4,15 +4,15 @@
 import pytest
 
 import pandas as pd
-from pandas import Series, TimedeltaIndex, isna, to_timedelta
+from pandas import Series, TimedeltaIndex, to_timedelta
 import pandas._testing as tm
 
 
 class TestTimedeltas:
     def test_to_timedelta(self):
 
-        result = to_timedelta(["", ""])
-        assert isna(result).all()
+        with pytest.raises(ValueError):
+            to_timedelta(["", ""])
 
         # pass thru
         result = to_timedelta(np.array([np.timedelta64(1, "s")]))