BUG: Fix nanosecond timedeltas

doc/source/whatsnew/v1.4.0.rst

@@ -714,6 +714,8 @@ Timedelta
 ^^^^^^^^^
 - Bug in division of all-``NaT`` :class:`TimeDeltaIndex`, :class:`Series` or :class:`DataFrame` column with object-dtype arraylike of numbers failing to infer the result as timedelta64-dtype (:issue:`39750`)
 - Bug in floor division of ``timedelta64[ns]`` data with a scalar returning garbage values (:issue:`44466`)
+- Bug in :class:`Timedelta` now properly taking into account any nanoseconds contribution of any kwarg (:issue:`43764`)
+-
 
 Timezones
 ^^^^^^^^^

pandas/_libs/tslibs/timedeltas.pyx

@@ -180,7 +180,7 @@ cpdef int64_t delta_to_nanoseconds(delta) except? -1:
     if PyDelta_Check(delta):
         try:
             return (
-                delta.days * 24 * 60 * 60 * 1_000_000
+                delta.days * 24 * 3600 * 1_000_000
                 + delta.seconds * 1_000_000
                 + delta.microseconds
             ) * 1000
@@ -1257,6 +1257,9 @@ class Timedelta(_Timedelta):
     truncated to nanoseconds.
     """
 
+    _req_any_kwargs_new = {"weeks", "days", "hours", "minutes", "seconds",
+                           "milliseconds", "microseconds", "nanoseconds"}
+
     def __new__(cls, object value=_no_input, unit=None, **kwargs):
         cdef _Timedelta td_base
 
@@ -1267,19 +1270,35 @@ class Timedelta(_Timedelta):
                                  "(days,seconds....)")
 
             kwargs = {key: _to_py_int_float(kwargs[key]) for key in kwargs}
-
-            nano = convert_to_timedelta64(kwargs.pop('nanoseconds', 0), 'ns')
-            try:
-                value = nano + convert_to_timedelta64(timedelta(**kwargs),
-                                                      'ns')
-            except TypeError as e:
+            if not cls._req_any_kwargs_new.intersection(kwargs):
                 raise ValueError(
                     "cannot construct a Timedelta from the passed arguments, "
                     "allowed keywords are "
                     "[weeks, days, hours, minutes, seconds, "
                     "milliseconds, microseconds, nanoseconds]"
                 )
 
+            # GH43764, convert any input to nanoseconds first and then
+            # create the timestamp. This ensures that any potential
+            # nanosecond contributions from kwargs parsed as floats
+            # are taken into consideration.
+            seconds = int((
+                (
+                    (kwargs.get('days', 0) + kwargs.get('weeks', 0) * 7) * 24
+                    + kwargs.get('hours', 0)
+                ) * 3600
+                + kwargs.get('minutes', 0) * 60
+                + kwargs.get('seconds', 0)
+                ) * 1_000_000_000
+            )
+
+            value = np.timedelta64(
+                int(kwargs.get('nanoseconds', 0))
+                + int(kwargs.get('microseconds', 0) * 1_000)
+                + int(kwargs.get('milliseconds', 0) * 1_000_000)
+                + seconds
+            )
+
         if unit in {'Y', 'y', 'M'}:
             raise ValueError(
                 "Units 'M', 'Y', and 'y' are no longer supported, as they do not "

pandas/tests/tslibs/test_timedeltas.py

@@ -15,6 +15,15 @@
         (np.timedelta64(14, "D"), 14 * 24 * 3600 * 1e9),
         (Timedelta(minutes=-7), -7 * 60 * 1e9),
         (Timedelta(minutes=-7).to_pytimedelta(), -7 * 60 * 1e9),
+        (Timedelta(seconds=1234e-9), 1234),  # GH43764, GH40946
+        (
+            Timedelta(seconds=1e-9, milliseconds=1e-5, microseconds=1e-1),
+            111,
+        ),  # GH43764
+        (
+            Timedelta(days=1, seconds=1e-9, milliseconds=1e-5, microseconds=1e-1),
+            24 * 3600e9 + 111,
+        ),  # GH43764
         (offsets.Nano(125), 125),
         (1, 1),
         (np.int64(2), 2),