update doctests

Author: jbrockmendel

pandas/core/arrays/datetimelike.py

@@ -1656,7 +1656,7 @@ def mean(self, *, skipna: bool = True, axis: AxisInt | None = 0):
         >>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit="D")
         >>> tdelta_idx
         TimedeltaIndex(['1 days', '2 days', '3 days'],
-                        dtype='timedelta64[ns]', freq=None)
+                        dtype='timedelta64[s]', freq=None)
         >>> tdelta_idx.mean()
         Timedelta('2 days 00:00:00')
         """

pandas/core/arrays/timedeltas.py

@@ -850,7 +850,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
         >>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit="D")
         >>> tdelta_idx
         TimedeltaIndex(['1 days', '2 days', '3 days'],
-                        dtype='timedelta64[ns]', freq=None)
+                        dtype='timedelta64[s]', freq=None)
         >>> tdelta_idx.to_pytimedelta()
         array([datetime.timedelta(days=1), datetime.timedelta(days=2),
                datetime.timedelta(days=3)], dtype=object)
@@ -883,7 +883,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
     0   1 days
     1   2 days
     2   3 days
-    dtype: timedelta64[ns]
+    dtype: timedelta64[s]
     >>> ser.dt.days
     0    1
     1    2
@@ -918,7 +918,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
     0   0 days 00:00:01
     1   0 days 00:00:02
     2   0 days 00:00:03
-    dtype: timedelta64[ns]
+    dtype: timedelta64[s]
     >>> ser.dt.seconds
     0    1
     1    2
@@ -930,7 +930,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
     >>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit='s')
     >>> tdelta_idx
     TimedeltaIndex(['0 days 00:00:01', '0 days 00:00:02', '0 days 00:00:03'],
-                   dtype='timedelta64[ns]', freq=None)
+                   dtype='timedelta64[s]', freq=None)
     >>> tdelta_idx.seconds
     Index([1, 2, 3], dtype='int32')"""
     )
@@ -958,7 +958,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
     0   0 days 00:00:00.000001
     1   0 days 00:00:00.000002
     2   0 days 00:00:00.000003
-    dtype: timedelta64[ns]
+    dtype: timedelta64[us]
     >>> ser.dt.microseconds
     0    1
     1    2
@@ -971,7 +971,7 @@ def to_pytimedelta(self) -> npt.NDArray[np.object_]:
     >>> tdelta_idx
     TimedeltaIndex(['0 days 00:00:00.000001', '0 days 00:00:00.000002',
                     '0 days 00:00:00.000003'],
-                   dtype='timedelta64[ns]', freq=None)
+                   dtype='timedelta64[us]', freq=None)
     >>> tdelta_idx.microseconds
     Index([1, 2, 3], dtype='int32')"""
     )

pandas/core/indexes/accessors.py

@@ -489,7 +489,7 @@ def to_pytimedelta(self) -> np.ndarray:
         2   2 days
         3   3 days
         4   4 days
-        dtype: timedelta64[ns]
+        dtype: timedelta64[s]
 
         >>> s.dt.to_pytimedelta()
         array([datetime.timedelta(0), datetime.timedelta(days=1),
@@ -535,7 +535,7 @@ def components(self) -> DataFrame:
         2   0 days 00:00:02
         3   0 days 00:00:03
         4   0 days 00:00:04
-        dtype: timedelta64[ns]
+        dtype: timedelta64[s]
         >>> s.dt.components
            days  hours  minutes  seconds  milliseconds  microseconds  nanoseconds
         0     0      0        0        0             0             0            0

pandas/core/indexes/datetimelike.py

@@ -132,7 +132,7 @@ def mean(self, *, skipna: bool = True, axis: int | None = 0):
         >>> tdelta_idx = pd.to_timedelta([1, 2, 3], unit="D")
         >>> tdelta_idx
         TimedeltaIndex(['1 days', '2 days', '3 days'],
-                        dtype='timedelta64[ns]', freq=None)
+                        dtype='timedelta64[s]', freq=None)
         >>> tdelta_idx.mean()
         Timedelta('2 days 00:00:00')
         """