POC using proper logic

Author: jorisvandenbossche

pandas/_libs/tslibs/timedeltas.pyx

@@ -246,6 +246,47 @@ def array_to_timedelta64(object[:] values, unit='ns', errors='raise'):
     return iresult.base  # .base to access underlying np.ndarray
 
 
+def precision_from_unit(object unit):
+    cdef:
+        int64_t m
+        int p
+
+    if unit == 'Y':
+        m = 1000000000L * 31556952
+        p = 9
+    elif unit == 'M':
+        m = 1000000000L * 2629746
+        p = 9
+    elif unit == 'W':
+        m = 1000000000L * DAY_SECONDS * 7
+        p = 9
+    elif unit == 'D' or unit == 'd':
+        m = 1000000000L * DAY_SECONDS
+        p = 9
+    elif unit == 'h':
+        m = 1000000000L * 3600
+        p = 9
+    elif unit == 'm':
+        m = 1000000000L * 60
+        p = 9
+    elif unit == 's':
+        m = 1000000000L
+        p = 9
+    elif unit == 'ms':
+        m = 1000000L
+        p = 6
+    elif unit == 'us':
+        m = 1000L
+        p = 3
+    elif unit == 'ns' or unit is None:
+        m = 1L
+        p = 0
+    else:
+        raise ValueError("cannot cast unit {unit}".format(unit=unit))
+
+    return m, p
+
+
 cdef inline int64_t cast_from_unit(object ts, object unit) except? -1:
     """ return a casting of the unit represented to nanoseconds
         round the fractional part of a float to our precision, p """

pandas/core/arrays/timedeltas.py

@@ -11,7 +11,7 @@
 from pandas._libs.tslibs import NaT, Timedelta, Timestamp, iNaT
 from pandas._libs.tslibs.fields import get_timedelta_field
 from pandas._libs.tslibs.timedeltas import (
-    array_to_timedelta64, parse_timedelta_unit)
+    array_to_timedelta64, parse_timedelta_unit, precision_from_unit)
 import pandas.compat as compat
 from pandas.util._decorators import Appender
 
@@ -918,9 +918,16 @@ def sequence_to_td64ns(data, copy=False, unit="ns", errors="raise"):
         copy = copy and not copy_made
 
     elif is_float_dtype(data.dtype):
-        # object_to_td64ns has custom logic for float -> int conversion
-        # to avoid precision issues
-        data = objects_to_td64ns(data, unit=unit, errors=errors)
+        # cast the unit, multiply base/frace separately
+        # to avoid precision issues from float -> int
+        mask = np.isnan(data)
+        m, p = precision_from_unit(unit)
+        base = data.astype(np.int64)
+        frac = data - base
+        if p:
+            frac = np.round(frac, p)
+        data = (base * m + (frac * m).astype(np.int64)).view('timedelta64[ns]')
+        data[mask] = iNaT
         copy = False
 
     elif is_timedelta64_dtype(data.dtype):