diff --git a/asv_bench/benchmarks/io/parsers.py b/asv_bench/benchmarks/io/parsers.py
index 40256e043a0087..c5e099bd44eacb 100644
--- a/asv_bench/benchmarks/io/parsers.py
+++ b/asv_bench/benchmarks/io/parsers.py
@@ -10,7 +10,7 @@
     pass
 
 
-class DoesStringLookLikeDatetime(object):
+class DoesStringLookLikeDatetime:
 
     params = (["2Q2005", "0.0", "10000"],)
     param_names = ["value"]
@@ -23,7 +23,7 @@ def time_check_datetimes(self, value):
             _does_string_look_like_datetime(obj)
 
 
-class ConcatDateCols(object):
+class ConcatDateCols:
 
     params = ([1234567890, "AAAA"], [1, 2])
     param_names = ["value", "dim"]
diff --git a/asv_bench/benchmarks/reshape.py b/asv_bench/benchmarks/reshape.py
index 32ca8e6b68d0b2..14505ad49dafa1 100644
--- a/asv_bench/benchmarks/reshape.py
+++ b/asv_bench/benchmarks/reshape.py
@@ -240,7 +240,7 @@ def time_qcut_datetime(self, bins):
         pd.qcut(self.datetime_series, bins)
 
 
-class Explode(object):
+class Explode
     param_names = ["n_rows", "max_list_length"]
     params = [[100, 1000, 10000], [3, 5, 10]]
 
@@ -250,10 +250,7 @@ def setup(self, n_rows, max_list_length):
         self.series = pd.Series(data)
 
     def time_explode(self, n_rows, max_list_length):
-        try:
-            self.series.explode()
-        except AttributeError:
-            pass
+        self.series.explode()
 
 
 from .pandas_vb_common import setup  # noqa: F401
diff --git a/asv_bench/benchmarks/series_methods.py b/asv_bench/benchmarks/series_methods.py
index e2835c5156f559..6038a2ab4bd9f9 100644
--- a/asv_bench/benchmarks/series_methods.py
+++ b/asv_bench/benchmarks/series_methods.py
@@ -219,7 +219,7 @@ def time_series_datetimeindex_repr(self):
         getattr(self.s, "a", None)
 
 
-class All(object):
+class All:
 
     params = [[10 ** 3, 10 ** 6], ["fast", "slow"]]
     param_names = ["N", "case"]
@@ -232,7 +232,7 @@ def time_all(self, N, case):
         self.s.all()
 
 
-class Any(object):
+class Any:
 
     params = [[10 ** 3, 10 ** 6], ["fast", "slow"]]
     param_names = ["N", "case"]
@@ -245,7 +245,7 @@ def time_any(self, N, case):
         self.s.any()
 
 
-class NanOps(object):
+class NanOps:
 
     params = [
         [
diff --git a/asv_bench/benchmarks/timeseries.py b/asv_bench/benchmarks/timeseries.py
index a74527df25f9bd..1020b773f8acbb 100644
--- a/asv_bench/benchmarks/timeseries.py
+++ b/asv_bench/benchmarks/timeseries.py
@@ -293,7 +293,7 @@ def time_format_YYYYMMDD(self):
         to_datetime(self.stringsD, format="%Y%m%d")
 
 
-class ToDatetimeCacheSmallCount(object):
+class ToDatetimeCacheSmallCount:
 
     params = ([True, False], [50, 500, 5000, 100000])
     param_names = ["cache", "count"]
diff --git a/ci/code_checks.sh b/ci/code_checks.sh
index fec2a882922806..96a8440d856947 100755
--- a/ci/code_checks.sh
+++ b/ci/code_checks.sh
@@ -156,7 +156,7 @@ if [[ -z "$CHECK" || "$CHECK" == "patterns" ]]; then
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
     MSG='Check for python2 new-style classes and for empty parentheses' ; echo $MSG
-    invgrep -R --include="*.py" --include="*.pyx" -E "class\s\S*\((object)?\):" pandas scripts
+    invgrep -R --include="*.py" --include="*.pyx" -E "class\s\S*\((object)?\):" pandas asv_bench/benchmarks scripts
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
     MSG='Check for backticks incorrectly rendering because of missing spaces' ; echo $MSG
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index a1989fd62b6ee0..886d1584b4963a 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6352,6 +6352,7 @@ def unstack(self, level=-1, fill_value=None):
     %(other)s
     pivot_table
     DataFrame.pivot
+    Series.explode
 
     Examples
     --------
diff --git a/pandas/core/series.py b/pandas/core/series.py
index fa913fcb54c96a..ec8fd9fa680938 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -3644,12 +3644,14 @@ def explode(self) -> "Series":
 
         Returns
         -------
-        exploded: Series
+        Series
+            exploded lists to rows; index will be duplicated for these rows
 
         See Also
         --------
-        Series.str.split: Split string values on specified separator.
-        Series.unstack: Unstack, a.k.a. pivot, Series with MultiIndex to produce DataFrame.
+        Series.str.split : Split string values on specified separator.
+        Series.unstack : Unstack, a.k.a. pivot, Series with MultiIndex to produce DataFrame.
+        DataFrame.melt : Unpivot a DataFrame from wide format to long format
 
         Notes
         -----