DOC: Fixed PR08, PR09 doctring issues in pandas.core.groupby (pandas-dev#28709)

Author: dayoreke

pandas/core/groupby/generic.py

@@ -709,7 +709,7 @@ def filter(self, func, dropna=True, *args, **kwargs):
         f : function
             Function to apply to each subframe. Should return True or False.
         dropna : Drop groups that do not pass the filter. True by default;
-            if False, groups that evaluate False are filled with NaNs.
+            If False, groups that evaluate False are filled with NaNs.
 
         Returns
         -------

pandas/core/groupby/groupby.py

@@ -212,9 +212,9 @@ class providing the base-class of operations.
     string indicating the keyword of `callable` that expects the
     %(klass)s object.
 args : iterable, optional
-       positional arguments passed into `func`.
+       Positional arguments passed into `func`.
 kwargs : dict, optional
-         a dictionary of keyword arguments passed into `func`.
+         A dictionary of keyword arguments passed into `func`.
 
 Returns
 -------
@@ -664,11 +664,11 @@ def get_group(self, name, obj=None):
         Parameters
         ----------
         name : object
-            the name of the group to get as a DataFrame
+            The name of the group to get as a DataFrame.
         obj : DataFrame, default None
-            the DataFrame to take the DataFrame out of.  If
+            The DataFrame to take the DataFrame out of.  If
             it is None, the object groupby was called on will
-            be used
+            be used.
 
         Returns
         -------
@@ -1114,7 +1114,7 @@ def any(self, skipna=True):
         Parameters
         ----------
         skipna : bool, default True
-            Flag to ignore nan values during truth testing
+            Flag to ignore nan values during truth testing.
 
         Returns
         -------
@@ -1131,7 +1131,7 @@ def all(self, skipna=True):
         Parameters
         ----------
         skipna : bool, default True
-            Flag to ignore nan values during truth testing
+            Flag to ignore nan values during truth testing.
 
         Returns
         -------
@@ -1252,7 +1252,7 @@ def std(self, ddof=1, *args, **kwargs):
         Parameters
         ----------
         ddof : int, default 1
-            degrees of freedom
+            Degrees of freedom.
 
         Returns
         -------
@@ -1275,7 +1275,7 @@ def var(self, ddof=1, *args, **kwargs):
         Parameters
         ----------
         ddof : int, default 1
-            degrees of freedom
+            Degrees of freedom.
 
         Returns
         -------
@@ -1310,7 +1310,7 @@ def sem(self, ddof=1):
         Parameters
         ----------
         ddof : int, default 1
-            degrees of freedom
+            Degrees of freedom.
 
         Returns
         -------
@@ -1622,7 +1622,7 @@ def pad(self, limit=None):
         Parameters
         ----------
         limit : int, optional
-            limit of how many values to fill
+            Limit of how many values to fill.
 
         Returns
         -------
@@ -1648,7 +1648,7 @@ def backfill(self, limit=None):
         Parameters
         ----------
         limit : int, optional
-            limit of how many values to fill
+            Limit of how many values to fill.
 
         Returns
         -------
@@ -1680,10 +1680,10 @@ def nth(self, n: Union[int, List[int]], dropna: Optional[str] = None) -> DataFra
         Parameters
         ----------
         n : int or list of ints
-            a single nth value for the row or a list of nth values
+            A single nth value for the row or a list of nth values.
         dropna : None or str, optional
-            apply the specified dropna operation before counting which row is
-            the nth row. Needs to be None, 'any' or 'all'
+            Apply the specified dropna operation before counting which row is
+            the nth row. Needs to be None, 'any' or 'all'.
 
         Returns
         -------
@@ -2098,13 +2098,13 @@ def rank(
             * first: ranks assigned in order they appear in the array
             * dense: like 'min', but rank always increases by 1 between groups
         ascending : bool, default True
-            False for ranks by high (1) to low (N)
+            False for ranks by high (1) to low (N).
         na_option :  {'keep', 'top', 'bottom'}, default 'keep'
             * keep: leave NA values where they are
             * top: smallest rank if ascending
             * bottom: smallest rank if descending
         pct : bool, default False
-            Compute percentage rank of data within each group
+            Compute percentage rank of data within each group.
         axis : int, default 0
             The axis of the object over which to compute the rank.
 
@@ -2312,7 +2312,7 @@ def shift(self, periods=1, freq=None, axis=0, fill_value=None):
         Parameters
         ----------
         periods : int, default 1
-            number of periods to shift
+            Number of periods to shift.
         freq : frequency string
         axis : axis to shift, default 0
         fill_value : optional