lint and docs

Author: jreback

doc/source/user_guide/reshaping.rst

@@ -804,12 +804,12 @@ Note to subdivide over multiple columns we can pass in a list to the
 
 .. _reshaping.explode:
 
-Exploding a List-like Column
+Exploding a list-like column
 ----------------------------
 
 .. versionadded:: 0.25.0
 
-Sometimes the value column is list-like.
+Sometimes the values in a column are list-like.
 
 .. ipython:: python
 
@@ -818,7 +818,7 @@ Sometimes the value column is list-like.
    df = pd.DataFrame({'keys': keys, 'values': values})
    df
 
-We can 'explode' this transforming each element of a list-like to a row, by using :meth:`~Series.explode`. This will replicate the index values:
+We can 'explode' the ``values`` column, transforming each list-like to a separate row, by using :meth:`~Series.explode`. This will replicate the index values from the original row:
 
 .. ipython:: python
 

pandas/_libs/lib.pyx

@@ -932,15 +932,12 @@ def is_list_like(obj: object, allow_sets: bool = True):
 cdef inline bint c_is_list_like(object obj, bint allow_sets):
     return (
         isinstance(obj, abc.Iterable)
-        and
         # we do not count strings/unicode/bytes as list-like
-        not isinstance(obj, (str, bytes))
-        and
+        and not isinstance(obj, (str, bytes))
         # exclude zero-dimensional numpy arrays, effectively scalars
-        not (util.is_array(obj) and obj.ndim == 0)
-        and
+        and not (util.is_array(obj) and obj.ndim == 0)
         # exclude sets if allow_sets is False
-        not (allow_sets is False and isinstance(obj, abc.Set))
+        and not (allow_sets is False and isinstance(obj, abc.Set))
     )
 
 

pandas/core/frame.py

@@ -15,7 +15,7 @@
 import itertools
 import sys
 from textwrap import dedent
-from typing import FrozenSet, Iterable, List, Optional, Set, Type, Union
+from typing import FrozenSet, List, Optional, Set, Type, Union
 import warnings
 
 import numpy as np
@@ -6235,7 +6235,8 @@ def stack(self, level=-1, dropna=True):
 
     def explode(self, column: str) -> "DataFrame":
         """
-        Create new DataFrame expanding a specified list-like column.
+        Transforms each element of a list-like to a row, replicating the
+        index values.
 
         .. versionadded:: 0.25.0
 
@@ -6264,10 +6265,9 @@ def explode(self, column: str) -> "DataFrame":
         Notes
         -----
         This routine will explode list-likes including lists, tuples,
-            Series, and np.ndarray.
-        The result dtype of the subset rows will be object.
-        Scalars will be returned unchanged.
-        Empty list-likes will result in a np.nan for that row.
+        Series, and np.ndarray. The result dtype of the subset rows will
+        be object. Scalars will be returned unchanged. Empty list-likes will
+        result in a np.nan for that row.
 
         Examples
         --------
@@ -6288,7 +6288,6 @@ def explode(self, column: str) -> "DataFrame":
         2  NaN  1
         3    3  1
         3    4  1
-
         """
 
         if not is_scalar(column):

pandas/core/series.py

@@ -3634,7 +3634,8 @@ def reorder_levels(self, order):
 
     def explode(self) -> "Series":
         """
-        Create new Series expanding a list-like column.
+        Transforms each element of a list-like to a row, replicating the
+        index values.
 
         .. versionadded:: 0.25.0
 
@@ -3655,10 +3656,9 @@ def explode(self) -> "Series":
         Notes
         -----
         This routine will explode list-likes including lists, tuples,
-            Series, and np.ndarray.
-        The result dtype of the returned Series will always be object.
-        Scalars will be returned unchanged.
-        Empty list-likes will result in a np.nan for that row.
+        Series, and np.ndarray. The result dtype of the subset rows will
+        be object. Scalars will be returned unchanged. Empty list-likes will
+        result in a np.nan for that row.
 
         Examples
         --------
@@ -3679,7 +3679,6 @@ def explode(self) -> "Series":
         3      3
         3      4
         dtype: object
-
         """
         if not len(self) or not is_object_dtype(self):
             return self.copy()