DOC: Fixing EX01 - Added examples

ci/code_checks.sh

@@ -119,16 +119,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.Timestamp.utcoffset \
         pandas.Timestamp.utctimetuple \
         pandas.Timestamp.weekday \
-        pandas.arrays.DatetimeArray \
-        pandas.Timedelta.view \
-        pandas.Timedelta.as_unit \
-        pandas.Timedelta.ceil \
-        pandas.Timedelta.floor \
-        pandas.Timedelta.round \
-        pandas.Timedelta.to_pytimedelta \
-        pandas.Timedelta.to_timedelta64 \
-        pandas.Timedelta.to_numpy \
-        pandas.Timedelta.total_seconds \
         pandas.arrays.TimedeltaArray \
         pandas.Period.asfreq \
         pandas.Period.now \
@@ -261,7 +251,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         pandas.core.window.ewm.ExponentialMovingWindow.cov \
         pandas.api.indexers.BaseIndexer \
         pandas.api.indexers.VariableOffsetWindowIndexer \
-        pandas.core.groupby.SeriesGroupBy.fillna \
         pandas.io.formats.style.Styler \
         pandas.io.formats.style.Styler.from_custom_template \
         pandas.io.formats.style.Styler.set_caption \

pandas/_libs/tslibs/nattype.pyx

@@ -4,7 +4,6 @@ from cpython.datetime cimport (
     PyDelta_Check,
     datetime,
     import_datetime,
-    timedelta,
 )
 
 import_datetime()
@@ -440,7 +439,20 @@ class NaTType(_NaT):
         Monday == 1 ... Sunday == 7.
         """,
     )
-    total_seconds = _make_nan_func("total_seconds", timedelta.total_seconds.__doc__)
+    total_seconds = _make_nan_func(
+        "total_seconds",
+        """
+        Total seconds in the duration.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1min')
+        >>> td
+        Timedelta('0 days 00:01:00')
+        >>> td.total_seconds()
+        60.0
+        """,
+    )
     month_name = _make_nan_func(
         "month_name",
         """

pandas/_libs/tslibs/timedeltas.pyx

@@ -1112,7 +1112,17 @@ cdef class _Timedelta(timedelta):
         return self._ms * 1000 + self._us
 
     def total_seconds(self) -> float:
-        """Total seconds in the duration."""
+        """
+        Total seconds in the duration.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1min')
+        >>> td
+        Timedelta('0 days 00:01:00')
+        >>> td.total_seconds()
+        60.0
+        """
         # We need to override bc we overrode days/seconds/microseconds
         # TODO: add nanos/1e9?
         return self.days * 24 * 3600 + self.seconds + self.microseconds / 1_000_000
@@ -1274,6 +1284,14 @@ cdef class _Timedelta(timedelta):
         Notes
         -----
         Any nanosecond resolution will be lost.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('3D')
+        >>> td
+        Timedelta('3 days 00:00:00')
+        >>> td.to_pytimedelta()
+        datetime.timedelta(days=3)
         """
         if self._creso == NPY_FR_ns:
             return timedelta(microseconds=int(self._value) / 1000)
@@ -1287,6 +1305,14 @@ cdef class _Timedelta(timedelta):
     def to_timedelta64(self) -> np.timedelta64:
         """
         Return a numpy.timedelta64 object with 'ns' precision.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('3D')
+        >>> td
+        Timedelta('3 days 00:00:00')
+        >>> td.to_timedelta64()
+        numpy.timedelta64(259200000000000,'ns')
         """
         cdef:
             str abbrev = npy_unit_to_abbrev(self._creso)
@@ -1309,6 +1335,14 @@ cdef class _Timedelta(timedelta):
         See Also
         --------
         Series.to_numpy : Similar method for Series.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('3D')
+        >>> td
+        Timedelta('3 days 00:00:00')
+        >>> td.to_numpy()
+        numpy.timedelta64(259200000000000,'ns')
         """
         if dtype is not None or copy is not False:
             raise ValueError(
@@ -1324,6 +1358,14 @@ cdef class _Timedelta(timedelta):
         ----------
         dtype : str or dtype
             The dtype to view the underlying data as.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('3D')
+        >>> td
+        Timedelta('3 days 00:00:00')
+        >>> td.view(int)
+        259200000000000
         """
         return np.timedelta64(self._value).view(dtype)
 
@@ -1603,6 +1645,14 @@ cdef class _Timedelta(timedelta):
         Returns
         -------
         Timedelta
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1001ms')
+        >>> td
+        Timedelta('0 days 00:00:01.001000')
+        >>> td.as_unit('s')
+        Timedelta('0 days 00:00:01')
         """
         dtype = np.dtype(f"m8[{unit}]")
         reso = get_unit_from_dtype(dtype)
@@ -1875,6 +1925,14 @@ class Timedelta(_Timedelta):
         Raises
         ------
         ValueError if the freq cannot be converted
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1001ms')
+        >>> td
+        Timedelta('0 days 00:00:01.001000')
+        >>> td.round('s')
+        Timedelta('0 days 00:00:01')
         """
         return self._round(freq, RoundTo.NEAREST_HALF_EVEN)
 
@@ -1886,6 +1944,14 @@ class Timedelta(_Timedelta):
         ----------
         freq : str
             Frequency string indicating the flooring resolution.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1001ms')
+        >>> td
+        Timedelta('0 days 00:00:01.001000')
+        >>> td.floor('s')
+        Timedelta('0 days 00:00:01')
         """
         return self._round(freq, RoundTo.MINUS_INFTY)
 
@@ -1897,6 +1963,14 @@ class Timedelta(_Timedelta):
         ----------
         freq : str
             Frequency string indicating the ceiling resolution.
+
+        Examples
+        --------
+        >>> td = pd.Timedelta('1001ms')
+        >>> td
+        Timedelta('0 days 00:00:01.001000')
+        >>> td.ceil('s')
+        Timedelta('0 days 00:00:02')
         """
         return self._round(freq, RoundTo.PLUS_INFTY)
 

pandas/core/arrays/datetimes.py

@@ -183,6 +183,14 @@ class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):  # type: ignore[misc]
     Methods
     -------
     None
+
+    Examples
+    --------
+    >>> pd.arrays.DatetimeArray(pd.DatetimeIndex(['2023-01-01', '2023-01-02']),
+    ...                         freq='D')
+    <DatetimeArray>
+    ['2023-01-01 00:00:00', '2023-01-02 00:00:00']
+    Length: 2, dtype: datetime64[ns]
     """
 
     _typ = "datetimearray"

pandas/core/groupby/generic.py

@@ -914,6 +914,27 @@ def fillna(
         --------
         ffill : Forward fill values within a group.
         bfill : Backward fill values within a group.
+
+        Examples
+        --------
+        For SeriesGroupBy:
+
+        >>> lst = ['cat', 'cat', 'cat', 'mouse', 'mouse']
+        >>> ser = pd.Series([1, None, None, 2, None], index=lst)
+        >>> ser
+        cat    1.0
+        cat    NaN
+        cat    NaN
+        mouse  2.0
+        mouse  NaN
+        dtype: float64
+        >>> ser.groupby(level=0).fillna(0, limit=1)
+        cat    1.0
+        cat    0.0
+        cat    NaN
+        mouse  2.0
+        mouse  0.0
+        dtype: float64
         """
         result = self._op_via_apply(
             "fillna",