DOC: Fix PR06 errors in Series docstrings (#28253) (#28288)

Author: danielplawrence

pandas/core/base.py

@@ -1289,17 +1289,17 @@ def value_counts(
 
         Parameters
         ----------
-        normalize : boolean, default False
+        normalize : bool, default False
             If True then the object returned will contain the relative
             frequencies of the unique values.
-        sort : boolean, default True
+        sort : bool, default True
             Sort by frequencies.
-        ascending : boolean, default False
+        ascending : bool, default False
             Sort in ascending order.
-        bins : integer, optional
+        bins : int, optional
             Rather than count values, group them into half-open bins,
             a convenience for ``pd.cut``, only works with numeric data.
-        dropna : boolean, default True
+        dropna : bool, default True
             Don't include counts of NaN.
 
         Returns
@@ -1496,7 +1496,7 @@ def memory_usage(self, deep=False):
         size_hint="",
         sort=textwrap.dedent(
             """\
-            sort : boolean, default False
+            sort : bool, default False
                 Sort `uniques` and shuffle `labels` to maintain the
                 relationship.
             """

pandas/core/generic.py

@@ -2310,7 +2310,7 @@ def to_json(
             floating point values.
         force_ascii : bool, default True
             Force encoded string to be ASCII.
-        date_unit : string, default 'ms' (milliseconds)
+        date_unit : str, default 'ms' (milliseconds)
             The time unit to encode to, governs timestamp and ISO8601
             precision.  One of 's', 'ms', 'us', 'ns' for second, millisecond,
             microsecond, and nanosecond respectively.
@@ -2530,8 +2530,9 @@ def to_msgpack(self, path_or_buf=None, encoding="utf-8", **kwargs):
 
         Parameters
         ----------
-        path : string File path, buffer-like, or None
-            if None, return generated bytes
+        path : str, buffer-like, or None
+            Destination for the serialized object.
+            If None, return generated bytes
         append : bool whether to append to an existing msgpack
             (default is False)
         compress : type of compressor (zlib or blosc), default to None (no
@@ -4618,8 +4619,9 @@ def filter(self, items=None, like=None, regex=None, axis=None):
             Keep labels from axis for which "like in label == True".
         regex : str (regular expression)
             Keep labels from axis for which re.search(regex, label) == True.
-        axis : int or string axis name
-            The axis to filter on.  By default this is the info axis,
+        axis : {0 or ‘index’, 1 or ‘columns’, None}, default None
+            The axis to filter on, expressed either as an index (int)
+            or axis name (str). By default this is the info axis,
             'index' for Series, 'columns' for DataFrame.
 
         Returns
@@ -4852,7 +4854,7 @@ def sample(
         random_state : int or numpy.random.RandomState, optional
             Seed for the random number generator (if int), or numpy RandomState
             object.
-        axis : int or string, optional
+        axis : {0 or ‘index’, 1 or ‘columns’, None}, default None
             Axis to sample. Accepts axis number or name. Default is stat axis
             for given data type (0 for Series and DataFrames).
 
@@ -8456,7 +8458,7 @@ def first(self, offset):
 
         Parameters
         ----------
-        offset : string, DateOffset, dateutil.relativedelta
+        offset : str, DateOffset, dateutil.relativedelta
 
         Returns
         -------
@@ -8519,7 +8521,7 @@ def last(self, offset):
 
         Parameters
         ----------
-        offset : string, DateOffset, dateutil.relativedelta
+        offset : str, DateOffset, dateutil.relativedelta
 
         Returns
         -------
@@ -9127,7 +9129,7 @@ def _where(
 
         Parameters
         ----------
-        cond : boolean %(klass)s, array-like, or callable
+        cond : bool %(klass)s, array-like, or callable
             Where `cond` is %(cond)s, keep the original value. Where
             %(cond_rev)s, replace with corresponding value from `other`.
             If `cond` is callable, it is computed on the %(klass)s and
@@ -9434,9 +9436,10 @@ def tshift(self, periods=1, freq=None, axis=0):
         ----------
         periods : int
             Number of periods to move, can be positive or negative
-        freq : DateOffset, timedelta, or time rule string, default None
-            Increment to use from the tseries module or time rule (e.g. 'EOM')
-        axis : int or basestring
+        freq : DateOffset, timedelta, or str, default None
+            Increment to use from the tseries module
+            or time rule expressed as a string (e.g. 'EOM')
+        axis : {0 or ‘index’, 1 or ‘columns’, None}, default 0
             Corresponds to the axis that contains the Index
 
         Returns
@@ -9494,9 +9497,9 @@ def truncate(self, before=None, after=None, axis=None, copy=True):
 
         Parameters
         ----------
-        before : date, string, int
+        before : date, str, int
             Truncate all rows before this index value.
-        after : date, string, int
+        after : date, str, int
             Truncate all rows after this index value.
         axis : {0 or 'index', 1 or 'columns'}, optional
             Axis to truncate. Truncates the index (rows) by default.
@@ -10305,7 +10308,7 @@ def _check_percentile(self, q):
             How to handle NAs before computing percent changes.
         limit : int, default None
             The number of consecutive NAs to fill before stopping.
-        freq : DateOffset, timedelta, or offset alias string, optional
+        freq : DateOffset, timedelta, or str, optional
             Increment to use from time series API (e.g. 'M' or BDay()).
         **kwargs
             Additional keyword arguments are passed into

pandas/core/series.py

@@ -1785,7 +1785,7 @@ def to_sparse(self, kind="block", fill_value=None):
 
         Parameters
         ----------
-        kind : {'block', 'integer'}, default 'block'
+        kind : {'block', 'int'}, default 'block'
         fill_value : float, defaults to NaN (missing)
             Value to use for filling NaN values.
 

pandas/plotting/_core.py

@@ -1143,7 +1143,7 @@ def kde(self, bw_method=None, ind=None, **kwargs):
             'scott', 'silverman', a scalar constant or a callable.
             If None (default), 'scott' is used.
             See :class:`scipy.stats.gaussian_kde` for more information.
-        ind : NumPy array or integer, optional
+        ind : NumPy array or int, optional
             Evaluation points for the estimated PDF. If None (default),
             1000 equally spaced points are used. If `ind` is a NumPy array, the
             KDE is evaluated at the points passed. If `ind` is an integer,