DOC: Fixed PR08 and PR09 docstring errors in pandas.Series

pandas/core/accessor.py

@@ -71,7 +71,7 @@ def _add_delegate_accessors(cls, delegate, accessors, typ, overwrite=False):
         accessors : string list of accessors to add
         typ : 'property' or 'method'
         overwrite : boolean, default False
-           overwrite the method/property in the target class if it exists.
+           Overwrite the method/property in the target class if it exists.
         """
 
         def _create_delegator_property(name):
@@ -118,12 +118,12 @@ def delegate_names(delegate, accessors, typ, overwrite=False):
     Parameters
     ----------
     delegate : object
-        the class to get methods/properties & doc-strings
+        The class to get methods/properties & doc-strings.
     accessors : Sequence[str]
-        List of accessor to add
+        List of accessor to add.
     typ : {'property', 'method'}
     overwrite : boolean, default False
-       overwrite the method/property in the target class if it exists
+       Overwrite the method/property in the target class if it exists.
 
     Returns
     -------
@@ -157,11 +157,11 @@ class CachedAccessor:
     Parameters
     ----------
     name : str
-        The namespace this will be accessed under, e.g. ``df.foo``
+        The namespace this will be accessed under, e.g. ``df.foo``.
     accessor : cls
         The class with the extension methods. The class' __init__ method
         should expect one of a ``Series``, ``DataFrame`` or ``Index`` as
-        the single argument ``data``
+        the single argument ``data``.
     """
 
     def __init__(self, name, accessor):

pandas/core/arrays/categorical.py

@@ -910,24 +910,26 @@ def rename_categories(self, new_categories, inplace=False):
         ----------
         new_categories : list-like, dict-like or callable
 
-           * list-like: all items must be unique and the number of items in
-             the new categories must match the existing number of categories.
+            New categories which will replace old categories.
 
-           * dict-like: specifies a mapping from
-             old categories to new. Categories not contained in the mapping
-             are passed through and extra categories in the mapping are
-             ignored.
+            * list-like: all items must be unique and the number of items in
+              the new categories must match the existing number of categories.
 
-             .. versionadded:: 0.21.0
+            * dict-like: specifies a mapping from
+              old categories to new. Categories not contained in the mapping
+              are passed through and extra categories in the mapping are
+              ignored.
 
-           * callable : a callable that is called on all items in the old
-             categories and whose return values comprise the new categories.
+            .. versionadded:: 0.21.0.
 
-             .. versionadded:: 0.23.0
+            * callable : a callable that is called on all items in the old
+              categories and whose return values comprise the new categories.
+
+            .. versionadded:: 0.23.0.
 
         inplace : bool, default False
-           Whether or not to rename the categories inplace or return a copy of
-           this categorical with renamed categories.
+            Whether or not to rename the categories inplace or return a copy of
+            this categorical with renamed categories.
 
         Returns
         -------

pandas/core/arrays/datetimelike.py

@@ -207,7 +207,7 @@ class TimelikeOps:
               ambiguous times)
             - 'NaT' will return NaT where there are ambiguous times
             - 'raise' will raise an AmbiguousTimeError if there are ambiguous
-              times
+              times.
 
             .. versionadded:: 0.24.0
 
@@ -223,7 +223,7 @@ class TimelikeOps:
             - 'NaT' will return NaT where there are nonexistent times
             - timedelta objects will shift nonexistent times by the timedelta
             - 'raise' will raise an NonExistentTimeError if there are
-              nonexistent times
+              nonexistent times.
 
             .. versionadded:: 0.24.0
 

pandas/core/arrays/datetimes.py

@@ -993,7 +993,7 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise", errors=None):
               ambiguous times)
             - 'NaT' will return NaT where there are ambiguous times
             - 'raise' will raise an AmbiguousTimeError if there are ambiguous
-              times
+              times.
 
         nonexistent : 'shift_forward', 'shift_backward, 'NaT', timedelta, \
 default 'raise'
@@ -1007,11 +1007,12 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise", errors=None):
             - 'NaT' will return NaT where there are nonexistent times
             - timedelta objects will shift nonexistent times by the timedelta
             - 'raise' will raise an NonExistentTimeError if there are
-              nonexistent times
+              nonexistent times.
 
             .. versionadded:: 0.24.0
 
         errors : {'raise', 'coerce'}, default None
+            The method to handle errors:
 
             - 'raise' will raise a NonExistentTimeError if a timestamp is not
               valid in the specified time zone (e.g. due to a transition from
@@ -1871,7 +1872,7 @@ def sequence_to_dt64ns(
     dayfirst : bool, default False
     yearfirst : bool, default False
     ambiguous : str, bool, or arraylike, default 'raise'
-        See pandas._libs.tslibs.conversion.tz_localize_to_utc
+        See pandas._libs.tslibs.conversion.tz_localize_to_utc.
     int_as_wall_time : bool, default False
         Whether to treat ints as wall time in specified timezone, or as
         nanosecond-precision UNIX epoch (wall time in UTC).
@@ -2015,7 +2016,7 @@ def objects_to_datetime64ns(
     dayfirst : bool
     yearfirst : bool
     utc : bool, default False
-        Whether to convert timezone-aware timestamps to UTC
+        Whether to convert timezone-aware timestamps to UTC.
     errors : {'raise', 'ignore', 'coerce'}
     allow_object : bool
         Whether to return an object-dtype ndarray instead of raising if the

pandas/core/base.py

@@ -900,7 +900,7 @@ def to_numpy(self, dtype=None, copy=False):
         Parameters
         ----------
         dtype : str or numpy.dtype, optional
-            The dtype to pass to :meth:`numpy.asarray`
+            The dtype to pass to :meth:`numpy.asarray`.
         copy : bool, default False
             Whether to ensure that the returned value is a not a view on
             another array. Note that ``copy=False`` does not *ensure* that