DOC: Enforce Numpy Docstring Validation for DatetimeIndex

ci/code_checks.sh

@@ -107,22 +107,16 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.to_markdown SA01" \
         -i "pandas.DataFrame.to_parquet RT03" \
         -i "pandas.DataFrame.var PR01,RT03,SA01" \
-        -i "pandas.DatetimeIndex.ceil SA01" \
         -i "pandas.DatetimeIndex.date SA01" \
         -i "pandas.DatetimeIndex.day_of_year SA01" \
         -i "pandas.DatetimeIndex.dayofyear SA01" \
-        -i "pandas.DatetimeIndex.floor SA01" \
         -i "pandas.DatetimeIndex.freqstr SA01" \
         -i "pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
         -i "pandas.DatetimeIndex.indexer_between_time RT03" \
         -i "pandas.DatetimeIndex.inferred_freq SA01" \
         -i "pandas.DatetimeIndex.is_leap_year SA01" \
-        -i "pandas.DatetimeIndex.quarter SA01" \
-        -i "pandas.DatetimeIndex.round SA01" \
-        -i "pandas.DatetimeIndex.snap PR01,RT03,SA01" \
+        -i "pandas.DatetimeIndex.snap PR01,RT03" \
         -i "pandas.DatetimeIndex.std PR01,RT03" \
-        -i "pandas.DatetimeIndex.time SA01" \
-        -i "pandas.DatetimeIndex.timetz SA01" \
         -i "pandas.DatetimeIndex.to_period RT03" \
         -i "pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
         -i "pandas.DatetimeIndex.tz SA01" \
@@ -289,7 +283,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.div PR07" \
         -i "pandas.Series.droplevel SA01" \
         -i "pandas.Series.dt.as_unit PR01,PR02" \
-        -i "pandas.Series.dt.ceil PR01,PR02,SA01" \
+        -i "pandas.Series.dt.ceil PR01,PR02" \
         -i "pandas.Series.dt.components SA01" \
         -i "pandas.Series.dt.date SA01" \
         -i "pandas.Series.dt.day_name PR01,PR02" \
@@ -298,20 +292,17 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.dt.days SA01" \
         -i "pandas.Series.dt.days_in_month SA01" \
         -i "pandas.Series.dt.daysinmonth SA01" \
-        -i "pandas.Series.dt.floor PR01,PR02,SA01" \
+        -i "pandas.Series.dt.floor PR01,PR02" \
         -i "pandas.Series.dt.freq GL08" \
         -i "pandas.Series.dt.is_leap_year SA01" \
         -i "pandas.Series.dt.microseconds SA01" \
         -i "pandas.Series.dt.month_name PR01,PR02" \
         -i "pandas.Series.dt.nanoseconds SA01" \
         -i "pandas.Series.dt.normalize PR01" \
-        -i "pandas.Series.dt.quarter SA01" \
         -i "pandas.Series.dt.qyear GL08" \
-        -i "pandas.Series.dt.round PR01,PR02,SA01" \
+        -i "pandas.Series.dt.round PR01,PR02" \
         -i "pandas.Series.dt.seconds SA01" \
         -i "pandas.Series.dt.strftime PR01,PR02" \
-        -i "pandas.Series.dt.time SA01" \
-        -i "pandas.Series.dt.timetz SA01" \
         -i "pandas.Series.dt.to_period PR01,PR02,RT03" \
         -i "pandas.Series.dt.total_seconds PR01" \
         -i "pandas.Series.dt.tz SA01" \
@@ -432,14 +423,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timedelta.total_seconds SA01" \
         -i "pandas.Timedelta.view SA01" \
         -i "pandas.TimedeltaIndex.as_unit RT03,SA01" \
-        -i "pandas.TimedeltaIndex.ceil SA01" \
         -i "pandas.TimedeltaIndex.components SA01" \
         -i "pandas.TimedeltaIndex.days SA01" \
-        -i "pandas.TimedeltaIndex.floor SA01" \
         -i "pandas.TimedeltaIndex.inferred_freq SA01" \
         -i "pandas.TimedeltaIndex.microseconds SA01" \
         -i "pandas.TimedeltaIndex.nanoseconds SA01" \
-        -i "pandas.TimedeltaIndex.round SA01" \
         -i "pandas.TimedeltaIndex.seconds SA01" \
         -i "pandas.TimedeltaIndex.to_pytimedelta RT03,SA01" \
         -i "pandas.Timestamp PR07,SA01" \

pandas/core/arrays/datetimelike.py

@@ -1825,6 +1825,11 @@ def strftime(self, date_format: str) -> npt.NDArray[np.object_]:
     ------
     ValueError if the `freq` cannot be converted.
 
+    See Also
+    --------
+    DatetimeIndex.floor : Perform floor operation on the data to the specified `freq`.
+    DatetimeIndex.snap : Snap time stamps to nearest occurring frequency.
+
     Notes
     -----
     If the timestamps have a timezone, {op}ing will take place relative to the

pandas/core/arrays/datetimes.py

@@ -1391,6 +1391,14 @@ def time(self) -> npt.NDArray[np.object_]:
 
         The time part of the Timestamps.
 
+        See Also
+        --------
+        DatetimeIndex.timetz : Returns numpy array of :class:`datetime.time`
+            objects with timezones. The time part of the Timestamps.
+        DatetimeIndex.date : Returns numpy array of python :class:`datetime.date`
+            objects. Namely, the date part of Timestamps without time and timezone
+            information.
+
         Examples
         --------
         For Series:
@@ -1428,6 +1436,12 @@ def timetz(self) -> npt.NDArray[np.object_]:
 
         The time part of the Timestamps.
 
+        See Also
+        --------
+        DatetimeIndex.time : Returns numpy array of :class:`datetime.time` objects.
+            The time part of the Timestamps.
+        DatetimeIndex.tz : Return the timezone.
+
         Examples
         --------
         For Series:
@@ -1836,6 +1850,12 @@ def isocalendar(self) -> DataFrame:
         """
         The quarter of the date.
 
+        See Also
+        --------
+        DatetimeIndex.snap : Snap time stamps to nearest occurring frequency.
+        DatetimeIndex.time : Returns numpy array of datetime.time objects.
+            The time part of the Timestamps.
+
         Examples
         --------
         For Series:

pandas/core/indexes/datetimes.py

@@ -455,6 +455,13 @@ def snap(self, freq: Frequency = "S") -> DatetimeIndex:
         -------
         DatetimeIndex
 
+        See Also
+        --------
+        DatetimeIndex.round : Perform round operation on the data to the
+            specified `freq`.
+        DatetimeIndex.floor : Perform floor operation on the data to the
+            specified `freq`.
+
         Examples
         --------
         >>> idx = pd.DatetimeIndex(