PR04 errors fix

ci/code_checks.sh

@@ -242,7 +242,7 @@ fi
 if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
 
     MSG='Validate docstrings (GL06, GL07, GL09, SS04, PR03, PR05, PR10, EX04, RT04, SS05, SA05)' ; echo $MSG
-    $BASE_DIR/scripts/validate_docstrings.py --format=azure --errors=GL06,GL07,GL09,SS04,PR03,PR05,EX04,RT04,SS05,SA05
+    $BASE_DIR/scripts/validate_docstrings.py --format=azure --errors=GL06,GL07,GL09,SS04,PR03,PR04,PR05,EX04,RT04,SS05,SA05
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
 fi

pandas/_libs/tslibs/timedeltas.pyx

@@ -1127,10 +1127,11 @@ class Timedelta(_Timedelta):
         'ms', 'milliseconds', 'millisecond', 'milli', 'millis', 'L',
         'us', 'microseconds', 'microsecond', 'micro', 'micros', 'U',
         'ns', 'nanoseconds', 'nano', 'nanos', 'nanosecond', 'N'}
-    days, seconds, microseconds,
-    milliseconds, minutes, hours, weeks : numeric, optional
+    **kwargs
+        Available kwargs: {days, seconds, microseconds,
+        milliseconds, minutes, hours, weeks}.
         Values for construction in compat with datetime.timedelta.
-        np ints and floats will be coerced to python ints and floats.
+        Numpy ints and floats will be coerced to python ints and floats.
 
     Notes
     -----

pandas/core/algorithms.py

@@ -563,7 +563,7 @@ def _factorize_array(values, na_sentinel=-1, size_hint=None,
         coerced to ndarrays before factorization.
     """),
     order=dedent("""\
-    order
+    order : None
         .. deprecated:: 0.23.0
 
            This parameter has no effect and is deprecated.

pandas/core/generic.py

@@ -648,6 +648,8 @@ def transpose(self, *args, **kwargs):
         copy : boolean, default False
             Make a copy of the underlying data. Mixed-dtype data will
             always result in a copy
+        **kwargs
+            Additional keyword arguments will be passed to the function.
 
         Returns
         -------

pandas/core/groupby/groupby.py

@@ -1835,7 +1835,7 @@ def rank(self, method='average', ascending=True, na_option='keep',
             The axis of the object over which to compute the rank.
 
         Returns
-        -----
+        -------
         DataFrame with ranking of values within each group
         """
         if na_option not in {'keep', 'top', 'bottom'}:

pandas/core/groupby/grouper.py

@@ -54,14 +54,17 @@ class Grouper(object):
     axis : number/name of the axis, defaults to 0
     sort : boolean, default to False
         whether to sort the resulting labels
-
-    additional kwargs to control time-like groupers (when `freq` is passed)
-
-    closed : closed end of interval; 'left' or 'right'
-    label : interval boundary to use for labeling; 'left' or 'right'
+    closed : {'left' or 'right'}
+        Closed end of interval. Only when `freq` parameter is passed.
+    label : {'left' or 'right'}
+        Interval boundary to use for labeling.
+        Only when `freq` parameter is passed.
     convention : {'start', 'end', 'e', 's'}
-        If grouper is PeriodIndex
-    base, loffset
+        If grouper is PeriodIndex and `freq` parameter is passed.
+    base : int, default 0
+        Only when `freq` parameter is passed.
+    loffset : string, DateOffset, timedelta object
+        Only when `freq` parameter is passed.
 
     Returns
     -------

pandas/core/panel.py

@@ -43,7 +43,7 @@
     axes_single_arg="{0, 1, 2, 'items', 'major_axis', 'minor_axis'}",
     optional_mapper='', optional_axis='', optional_labels='')
 _shared_doc_kwargs['args_transpose'] = (
-    "three positional arguments: each one of\n{ax_single}".format(
+    "{ax_single}\n\tThree positional arguments from given options.".format(
         ax_single=_shared_doc_kwargs['axes_single_arg']))
 
 
@@ -1009,7 +1009,8 @@ def apply(self, func, axis='major', **kwargs):
             DataFrames of items & major axis will be passed
         axis : {'items', 'minor', 'major'}, or {0, 1, 2}, or a tuple with two
             axes
-        Additional keyword arguments will be passed as keywords to the function
+        **kwargs
+            Additional keyword arguments will be passed to the function.
 
         Returns
         -------

pandas/core/resample.py

@@ -795,7 +795,7 @@ def std(self, ddof=1, *args, **kwargs):
         Parameters
         ----------
         ddof : integer, default 1
-        degrees of freedom
+            Degrees of freedom.
         """
         nv.validate_resampler_func('std', args, kwargs)
         return self._downsample('std', ddof=ddof)

pandas/io/formats/style.py

@@ -424,9 +424,11 @@ def render(self, **kwargs):
 
         Parameters
         ----------
-        `**kwargs` : Any additional keyword arguments are passed through
-        to ``self.template.render``. This is useful when you need to provide
-        additional variables for a custom template.
+        **kwargs
+            Any additional keyword arguments are passed
+            through to ``self.template.render``.
+            This is useful when you need to provide
+            additional variables for a custom template.
 
             .. versionadded:: 0.20
 

pandas/io/parquet.py

@@ -262,16 +262,17 @@ def read_parquet(path, engine='auto', columns=None, **kwargs):
     ----------
     path : string
         File path
-    columns : list, default=None
-        If not None, only these columns will be read from the file.
-
-        .. versionadded 0.21.1
     engine : {'auto', 'pyarrow', 'fastparquet'}, default 'auto'
         Parquet library to use. If 'auto', then the option
         ``io.parquet.engine`` is used. The default ``io.parquet.engine``
         behavior is to try 'pyarrow', falling back to 'fastparquet' if
         'pyarrow' is unavailable.
-    kwargs are passed to the engine
+    columns : list, default=None
+        If not None, only these columns will be read from the file.
+
+        .. versionadded 0.21.1
+    **kwargs
+        Any additional kwargs are passed to the engine.
 
     Returns
     -------