From 8303f9761119c6e24c742a93d1f15a57706ca043 Mon Sep 17 00:00:00 2001
From: frankdupree <frankyotana@yahoo.com>
Date: Fri, 9 Mar 2018 15:37:38 +0100
Subject: [PATCH 1/3] DOC: Improved the docstring of pandas.Series.any

---
 pandas/core/generic.py | 34 +++++++++++++++++++++++++++++-----
 1 file changed, 29 insertions(+), 5 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index a893b2ba1a189..d2c1d13a419d4 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -7522,7 +7522,7 @@ def _add_numeric_operations(cls):
 
         cls.any = _make_logical_function(
             cls, 'any', name, name2, axis_descr,
-            'Return whether any element is True over requested axis',
+            'Return whether any element is True over requested axis.',
             nanops.nanany)
         cls.all = _make_logical_function(
             cls, 'all', name, name2, axis_descr,
@@ -7784,25 +7784,49 @@ def _doc_parms(cls):
 %(outname)s : %(name1)s or %(name2)s (if level specified)\n"""
 
 _bool_doc = """
-
 %(desc)s
+Returns True if one (or more) elements are non-zero,
+not-empty or not-False.
+
+Also note that a series consisting of different
+data types returns the first occurence of the
+non-zero, not-empty or not-False element.
 
 Parameters
 ----------
 axis : %(axis_descr)s
 skipna : boolean, default True
     Exclude NA/null values. If an entire row/column is NA, the result
-    will be NA
+    will be NA.
 level : int or level name, default None
     If the axis is a MultiIndex (hierarchical), count along a
-    particular level, collapsing into a %(name1)s
+    particular level, collapsing into a %(name1)s.
 bool_only : boolean, default None
     Include only boolean columns. If None, will attempt to use everything,
     then use only boolean data. Not implemented for Series.
+**kwargs :
+    Additional keywords have no effect but might be accepted for
+    compatibility with numpy.
 
 Returns
 -------
-%(outname)s : %(name1)s or %(name2)s (if level specified)\n"""
+%(outname)s : %(name1)s or %(name2)s (if level specified)
+
+Examples
+--------
+>>> s1 = pd.Series([1,2,3])
+>>> s1.any()
+True
+
+>>> import numpy as np
+>>> s2 = pd.Series([np.NaN,np.NaN,np.NaN])
+>>> s2.any()
+False
+
+>>> s3 = pd.Series([1,2,3,"Hobbit"])
+>>> s3.any()
+1
+"""
 
 _cnum_doc = """
 

From 8737e316d73367ffaf35f61200dcd7ebebe854e1 Mon Sep 17 00:00:00 2001
From: frankdupree <frankyotana@yahoo.com>
Date: Fri, 9 Mar 2018 20:59:02 +0100
Subject: [PATCH 2/3] Updates: removed documentation on bug.

---
 pandas/core/generic.py | 13 +++----------
 1 file changed, 3 insertions(+), 10 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index d2c1d13a419d4..a118521f0b5ff 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -7785,13 +7785,10 @@ def _doc_parms(cls):
 
 _bool_doc = """
 %(desc)s
+
 Returns True if one (or more) elements are non-zero,
 not-empty or not-False.
 
-Also note that a series consisting of different
-data types returns the first occurence of the
-non-zero, not-empty or not-False element.
-
 Parameters
 ----------
 axis : %(axis_descr)s
@@ -7814,18 +7811,14 @@ def _doc_parms(cls):
 
 Examples
 --------
->>> s1 = pd.Series([1,2,3])
+>>> s1 = pd.Series([1, 2, 3])
 >>> s1.any()
 True
 
 >>> import numpy as np
->>> s2 = pd.Series([np.NaN,np.NaN,np.NaN])
+>>> s2 = pd.Series([np.NaN, np.NaN, np.NaN])
 >>> s2.any()
 False
-
->>> s3 = pd.Series([1,2,3,"Hobbit"])
->>> s3.any()
-1
 """
 
 _cnum_doc = """

From 680f48c2c1ff6b40df1b9d69630da2eb2ddb5078 Mon Sep 17 00:00:00 2001
From: frankdupree <frankyotana@yahoo.com>
Date: Sat, 10 Mar 2018 06:02:49 +0100
Subject: [PATCH 3/3] DOC: Improved the docstring of Series.any()

---
 pandas/core/generic.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index a118521f0b5ff..6e0a92a3cd93a 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -7801,8 +7801,7 @@ def _doc_parms(cls):
 bool_only : boolean, default None
     Include only boolean columns. If None, will attempt to use everything,
     then use only boolean data. Not implemented for Series.
-**kwargs :
-    Additional keywords have no effect but might be accepted for
+**kwargs : Additional keywords have no effect but might be accepted for
     compatibility with numpy.
 
 Returns