PERF: to_datetime with uint (#43268)

Author: debnathshoham

asv_bench/benchmarks/inference.py

@@ -115,19 +115,27 @@ def time_maybe_convert_objects(self):
 class ToDatetimeFromIntsFloats:
     def setup(self):
         self.ts_sec = Series(range(1521080307, 1521685107), dtype="int64")
+        self.ts_sec_uint = Series(range(1521080307, 1521685107), dtype="uint64")
         self.ts_sec_float = self.ts_sec.astype("float64")
 
         self.ts_nanosec = 1_000_000 * self.ts_sec
+        self.ts_nanosec_uint = 1_000_000 * self.ts_sec_uint
         self.ts_nanosec_float = self.ts_nanosec.astype("float64")
 
-    # speed of int64 and float64 paths should be comparable
+    # speed of int64, uint64 and float64 paths should be comparable
 
     def time_nanosec_int64(self):
         to_datetime(self.ts_nanosec, unit="ns")
 
+    def time_nanosec_uint64(self):
+        to_datetime(self.ts_nanosec_uint, unit="ns")
+
     def time_nanosec_float64(self):
         to_datetime(self.ts_nanosec_float, unit="ns")
 
+    def time_sec_uint64(self):
+        to_datetime(self.ts_sec_uint, unit="s")
+
     def time_sec_int64(self):
         to_datetime(self.ts_sec, unit="s")
 

doc/source/whatsnew/v1.4.0.rst

@@ -245,7 +245,7 @@ Performance improvements
 - Performance improvement in :meth:`DataFrame.corr` for ``method=pearson`` on data without missing values (:issue:`40956`)
 - Performance improvement in some :meth:`GroupBy.apply` operations (:issue:`42992`)
 - Performance improvement in :func:`read_stata` (:issue:`43059`)
--
+- Performance improvement in :meth:`to_datetime` with ``uint`` dtypes (:issue:`42606`)
 
 .. ---------------------------------------------------------------------------
 

pandas/_libs/tslib.pyx

@@ -248,7 +248,7 @@ def array_with_unit_to_datetime(
         # if we have nulls that are not type-compat
         # then need to iterate
 
-        if values.dtype.kind == "i" or values.dtype.kind == "f":
+        if values.dtype.kind in ["i", "f", "u"]:
             iresult = values.astype("i8", copy=False)
             # fill missing values by comparing to NPY_NAT
             mask = iresult == NPY_NAT
@@ -263,7 +263,7 @@ def array_with_unit_to_datetime(
             ):
                 raise OutOfBoundsDatetime(f"cannot convert input with unit '{unit}'")
 
-            if values.dtype.kind == "i":
+            if values.dtype.kind in ["i", "u"]:
                 result = (iresult * m).astype("M8[ns]")
 
             elif values.dtype.kind == "f":