PR09 Batch 2 (#29396)

Author: HughKelley

pandas/core/base.py

@@ -1073,7 +1073,7 @@ def argmax(self, axis=None, skipna=True, *args, **kwargs):
         Parameters
         ----------
         axis : {None}
-            Dummy argument for consistency with Series
+            Dummy argument for consistency with Series.
         skipna : bool, default True
 
         Returns
@@ -1096,7 +1096,7 @@ def min(self, axis=None, skipna=True, *args, **kwargs):
         Parameters
         ----------
         axis : {None}
-            Dummy argument for consistency with Series
+            Dummy argument for consistency with Series.
         skipna : bool, default True
 
         Returns
@@ -1137,7 +1137,7 @@ def argmin(self, axis=None, skipna=True, *args, **kwargs):
         Parameters
         ----------
         axis : {None}
-            Dummy argument for consistency with Series
+            Dummy argument for consistency with Series.
         skipna : bool, default True
 
         Returns
@@ -1486,7 +1486,7 @@ def memory_usage(self, deep=False):
         ----------
         deep : bool
             Introspect the data deeply, interrogate
-            `object` dtypes for system-level memory consumption
+            `object` dtypes for system-level memory consumption.
 
         Returns
         -------

pandas/core/indexes/base.py

@@ -176,11 +176,11 @@ class Index(IndexOpsMixin, PandasObject):
         If an actual dtype is provided, we coerce to that dtype if it's safe.
         Otherwise, an error will be raised.
     copy : bool
-        Make a copy of input ndarray
+        Make a copy of input ndarray.
     name : object
-        Name to be stored in the index
+        Name to be stored in the index.
     tupleize_cols : bool (default: True)
-        When True, attempt to create a MultiIndex if possible
+        When True, attempt to create a MultiIndex if possible.
 
     See Also
     --------
@@ -791,13 +791,13 @@ def astype(self, dtype, copy=True):
         Parameters
         ----------
         indices : list
-            Indices to be taken
+            Indices to be taken.
         axis : int, optional
             The axis over which to select values, always 0.
         allow_fill : bool, default True
         fill_value : bool, default None
             If allow_fill=True and fill_value is not None, indices specified by
-            -1 is regarded as NA. If Index doesn't hold NA, raise ValueError
+            -1 is regarded as NA. If Index doesn't hold NA, raise ValueError.
 
         Returns
         -------
@@ -1077,7 +1077,7 @@ def to_native_types(self, slicer=None, **kwargs):
             2) quoting : bool or None
                 Whether or not there are quoted values in `self`
             3) date_format : str
-                The format used to represent date-like values
+                The format used to represent date-like values.
 
         Returns
         -------
@@ -2001,7 +2001,7 @@ def notna(self):
         downcast : dict, default is None
             a dict of item->dtype of what to downcast if possible,
             or the string 'infer' which will try to downcast to an appropriate
-            equal type (e.g. float64 to int64 if possible)
+            equal type (e.g. float64 to int64 if possible).
 
         Returns
         -------
@@ -2056,7 +2056,7 @@ def dropna(self, how="any"):
         Parameters
         ----------
         level : int or str, optional, default None
-            Only return values from specified level (for MultiIndex)
+            Only return values from specified level (for MultiIndex).
 
             .. versionadded:: 0.23.0
 
@@ -3413,7 +3413,7 @@ def _reindex_non_unique(self, target):
         return_indexers : bool, default False
         sort : bool, default False
             Sort the join keys lexicographically in the result Index. If False,
-            the order of the join keys depends on the join type (how keyword)
+            the order of the join keys depends on the join type (how keyword).
 
         Returns
         -------
@@ -4923,9 +4923,9 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):
         Parameters
         ----------
         start : label, default None
-            If None, defaults to the beginning
+            If None, defaults to the beginning.
         end : label, default None
-            If None, defaults to the end
+            If None, defaults to the end.
         step : int, default None
         kind : str, default None
 
@@ -5122,11 +5122,11 @@ def slice_locs(self, start=None, end=None, step=None, kind=None):
         Parameters
         ----------
         start : label, default None
-            If None, defaults to the beginning
+            If None, defaults to the beginning.
         end : label, default None
-            If None, defaults to the end
+            If None, defaults to the end.
         step : int, defaults None
-            If None, defaults to 1
+            If None, defaults to 1.
         kind : {'ix', 'loc', 'getitem'} or None
 
         Returns

pandas/core/indexes/multi.py

@@ -737,19 +737,18 @@ def _set_levels(
 
     def set_levels(self, levels, level=None, inplace=False, verify_integrity=True):
         """
-        Set new levels on MultiIndex. Defaults to returning
-        new index.
+        Set new levels on MultiIndex. Defaults to returning new index.
 
         Parameters
         ----------
         levels : sequence or list of sequence
-            new level(s) to apply
+            New level(s) to apply.
         level : int, level name, or sequence of int/level names (default None)
-            level(s) to set (None for all levels)
+            Level(s) to set (None for all levels).
         inplace : bool
-            if True, mutates in place
+            If True, mutates in place.
         verify_integrity : bool (default True)
-            if True, checks that levels and codes are compatible
+            If True, checks that levels and codes are compatible.
 
         Returns
         -------

pandas/core/indexes/numeric.py

@@ -176,9 +176,9 @@ def _union(self, other, sort):
     data : array-like (1-dimensional)
     dtype : NumPy dtype (default: %(dtype)s)
     copy : bool
-        Make a copy of input ndarray
+        Make a copy of input ndarray.
     name : object
-        Name to be stored in the index
+        Name to be stored in the index.
 
     Attributes
     ----------

pandas/core/indexes/range.py

@@ -51,7 +51,7 @@ class RangeIndex(Int64Index):
     stop : int (default: 0)
     step : int (default: 1)
     name : object, optional
-        Name to be stored in the index
+        Name to be stored in the index.
     copy : bool, default False
         Unused, accepted for homogeneity with other index types.
 

pandas/core/reshape/tile.py

@@ -275,17 +275,18 @@ def qcut(
     duplicates: str = "raise",
 ):
     """
-    Quantile-based discretization function. Discretize variable into
-    equal-sized buckets based on rank or based on sample quantiles. For example
-    1000 values for 10 quantiles would produce a Categorical object indicating
-    quantile membership for each data point.
+    Quantile-based discretization function.
+
+    Discretize variable into equal-sized buckets based on rank or based
+    on sample quantiles. For example 1000 values for 10 quantiles would
+    produce a Categorical object indicating quantile membership for each data point.
 
     Parameters
     ----------
     x : 1d ndarray or Series
     q : int or list-like of int
         Number of quantiles. 10 for deciles, 4 for quartiles, etc. Alternately
-        array of quantiles, e.g. [0, .25, .5, .75, 1.] for quartiles
+        array of quantiles, e.g. [0, .25, .5, .75, 1.] for quartiles.
     labels : array or bool, default None
         Used as labels for the resulting bins. Must be of the same length as
         the resulting bins. If False, return only integer indicators of the