Pr09 batch 3 (pandas-dev#29434)

Author: HughKelley

pandas/_libs/lib.pyx

@@ -125,7 +125,7 @@ def is_scalar(val: object) -> bool:
         - Interval
         - DateOffset
         - Fraction
-        - Number
+        - Number.
 
     Returns
     -------
@@ -867,9 +867,10 @@ def is_list_like(obj: object, allow_sets: bool = True):
 
     Parameters
     ----------
-    obj : The object to check
-    allow_sets : boolean, default True
-        If this parameter is False, sets will not be considered list-like
+    obj : object
+        The object to check.
+    allow_sets : bool, default True
+        If this parameter is False, sets will not be considered list-like.
 
         .. versionadded:: 0.24.0
 

pandas/core/arrays/interval.py

@@ -260,9 +260,9 @@ def _from_factorized(cls, values, original):
         Whether the intervals are closed on the left-side, right-side, both
         or neither.
     copy : bool, default False
-        copy the data
+        Copy the data.
     dtype : dtype or None, default None
-        If None, dtype will be inferred
+        If None, dtype will be inferred.
 
         .. versionadded:: 0.23.0
 
@@ -383,16 +383,16 @@ def from_arrays(cls, left, right, closed="right", copy=False, dtype=None):
     Parameters
     ----------
     data : array-like (1-dimensional)
-        Array of tuples
+        Array of tuples.
     closed : {'left', 'right', 'both', 'neither'}, default 'right'
         Whether the intervals are closed on the left-side, right-side, both
         or neither.
     copy : bool, default False
-        by-default copy the data, this is compat only and ignored
+        By-default copy the data, this is compat only and ignored.
     dtype : dtype or None, default None
-        If None, dtype will be inferred
+        If None, dtype will be inferred.
 
-        ..versionadded:: 0.23.0
+        .. versionadded:: 0.23.0
 
     Returns
     -------

pandas/core/dtypes/concat.py

@@ -185,13 +185,14 @@ def concat_categorical(to_concat, axis=0):
 
 def union_categoricals(to_union, sort_categories=False, ignore_order=False):
     """
-    Combine list-like of Categorical-like, unioning categories. All
-    categories must have the same dtype.
+    Combine list-like of Categorical-like, unioning categories.
+
+    All categories must have the same dtype.
 
     Parameters
     ----------
-    to_union : list-like of Categorical, CategoricalIndex,
-               or Series with dtype='category'
+    to_union : list-like
+        Categorical, CategoricalIndex, or Series with dtype='category'.
     sort_categories : bool, default False
         If true, resulting categories will be lexsorted, otherwise
         they will be ordered as they appear in the data.
@@ -201,7 +202,7 @@ def union_categoricals(to_union, sort_categories=False, ignore_order=False):
 
     Returns
     -------
-    result : Categorical
+    Categorical
 
     Raises
     ------

pandas/core/resample.py

@@ -441,7 +441,7 @@ def pad(self, limit=None):
         Parameters
         ----------
         limit : int, optional
-            limit of how many values to fill
+            Limit of how many values to fill.
 
         Returns
         -------
@@ -856,7 +856,7 @@ def var(self, ddof=1, *args, **kwargs):
         Parameters
         ----------
         ddof : int, default 1
-            degrees of freedom
+            Degrees of freedom.
 
         Returns
         -------
@@ -1237,11 +1237,11 @@ def _upsample(self, method, limit=None, fill_value=None):
         Parameters
         ----------
         method : string {'backfill', 'bfill', 'pad', 'ffill'}
-            method for upsampling
+            Method for upsampling.
         limit : int, default None
-            Maximum size gap to fill when reindexing
+            Maximum size gap to fill when reindexing.
         fill_value : scalar, default None
-            Value to use for missing values
+            Value to use for missing values.
 
         See Also
         --------

pandas/io/html.py

@@ -960,7 +960,7 @@ def read_html(
         This value is converted to a regular expression so that there is
         consistent behavior between Beautiful Soup and lxml.
 
-    flavor : str or None, container of strings
+    flavor : str or None
         The parsing engine to use. 'bs4' and 'html5lib' are synonymous with
         each other, they are both there for backwards compatibility. The
         default of ``None`` tries to use ``lxml`` to parse and if that fails it
@@ -974,7 +974,7 @@ def read_html(
         The column (or list of columns) to use to create the index.
 
     skiprows : int or list-like or slice or None, optional
-        0-based. Number of rows to skip after parsing the column integer. If a
+        Number of rows to skip after parsing the column integer. 0-based. If a
         sequence of integers or a slice is given, will skip the rows indexed by
         that sequence.  Note that a single element sequence means 'skip the nth
         row' whereas an integer means 'skip n rows'.
@@ -1024,18 +1024,19 @@ def read_html(
         transformed content.
 
     na_values : iterable, default None
-        Custom NA values
+        Custom NA values.
 
     keep_default_na : bool, default True
         If na_values are specified and keep_default_na is False the default NaN
-        values are overridden, otherwise they're appended to
+        values are overridden, otherwise they're appended to.
 
     displayed_only : bool, default True
-        Whether elements with "display: none" should be parsed
+        Whether elements with "display: none" should be parsed.
 
     Returns
     -------
-    dfs : list of DataFrames
+    dfs
+        A list of DataFrames.
 
     See Also
     --------

pandas/util/testing.py

@@ -593,14 +593,14 @@ def assert_index_equal(
     check_less_precise : bool or int, default False
         Specify comparison precision. Only used when check_exact is False.
         5 digits (False) or 3 digits (True) after decimal points are compared.
-        If int, then specify the digits to compare
+        If int, then specify the digits to compare.
     check_exact : bool, default True
         Whether to compare number exactly.
     check_categorical : bool, default True
         Whether to compare internal Categorical exactly.
     obj : str, default 'Index'
         Specify object name being compared, internally used to show appropriate
-        assertion message
+        assertion message.
     """
     __tracebackhide__ = True
 
@@ -1273,10 +1273,7 @@ def assert_frame_equal(
         check whether it is equivalent to 1 within the specified precision.
     check_names : bool, default True
         Whether to check that the `names` attribute for both the `index`
-        and `column` attributes of the DataFrame is identical, i.e.
-
-        * left.index.names == right.index.names
-        * left.columns.names == right.columns.names
+        and `column` attributes of the DataFrame is identical.
     by_blocks : bool, default False
         Specify how to compare internal data. If False, compare by columns.
         If True, compare by blocks.