From 91ab671350128cc390e1b11dba3cf593dc3231bc Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:47:42 -0500
Subject: [PATCH 01/18] fix Summary does not end with a period error

---
 pandas/core/accessor.py           |   2 +-
 pandas/core/arrays/categorical.py |   6 ++---
 pandas/core/arrays/datetimes.py   |  18 +++++++--------
 pandas/core/base.py               |   6 ++---
 pandas/core/dtypes/dtypes.py      |   2 +-
 pandas/core/generic.py            |  36 +++++++++++++++---------------
 pandas/core/indexes/accessors.py  |   2 +-
 pandas/plotting/_core.py          |  18 +++++++--------
 scripts/tmp.xlsx                  | Bin 0 -> 5418 bytes
 9 files changed, 45 insertions(+), 45 deletions(-)
 create mode 100644 scripts/tmp.xlsx

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index fa1dc751c17da..1beb097f58bdf 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class
+        add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 6e96fc75daec9..2cf9af16f0fdb 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -477,7 +477,7 @@ def categories(self, categories):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self.dtype.ordered
 
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered
+        Sets the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered
+        Sets the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index b74ede4547249..d176e5d244cd1 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1065,19 +1065,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime\n")
+    year = _field_accessor('year', 'Y', "\n The year of the datetime.\n")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12 \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime\n")
+                            "\n The month as January=1, December=12. \n")
+    day = _field_accessor('day', 'D', "\nThe days of the datetime.\n")
+    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime.\n")
+    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime.\n")
+    second = _field_accessor('second', 's', "\nThe seconds of the datetime.\n")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime\n")
+                                  "\nThe microseconds of the datetime.\n")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime\n")
+                                 "\nThe nanoseconds of the datetime.\n")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year\n")
+                                 "\nThe week ordinal of the year.\n")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 1d2a0a2544dbc..161bf8fbf3482 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -1244,7 +1244,7 @@ def nunique(self, dropna=True):
     @property
     def is_unique(self):
         """
-        Return boolean if values in the object are unique
+        Return boolean if values in the object are unique.
 
         Returns
         -------
@@ -1256,7 +1256,7 @@ def is_unique(self):
     def is_monotonic(self):
         """
         Return boolean if values in the object are
-        monotonic_increasing
+        monotonic_increasing.
 
         .. versionadded:: 0.19.0
 
@@ -1273,7 +1273,7 @@ def is_monotonic(self):
     def is_monotonic_decreasing(self):
         """
         Return boolean if values in the object are
-        monotonic_decreasing
+        monotonic_decreasing.
 
         .. versionadded:: 0.19.0
 
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 0db76cd934d19..24407850d44a8 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -463,7 +463,7 @@ def categories(self):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self._ordered
 
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 1e26c3f45f660..1a2c04cd1a267 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -671,7 +671,7 @@ def transpose(self, *args, **kwargs):
 
     def swapaxes(self, axis1, axis2, copy=True):
         """
-        Interchange axes and swap values axes appropriately
+        Interchange axes and swap values axes appropriately.
 
         Returns
         -------
@@ -1907,7 +1907,7 @@ def __array_wrap__(self, result, context=None):
 
     def to_dense(self):
         """
-        Return dense representation of NDFrame (as opposed to sparse)
+        Return dense representation of NDFrame (as opposed to sparse).
         """
         # compat
         return self
@@ -3597,7 +3597,7 @@ class   animal   locomotion
 
     def select(self, crit, axis=0):
         """
-        Return data corresponding to axis labels matching criteria
+        Return data corresponding to axis labels matching criteria.
 
         .. deprecated:: 0.21.0
             Use df.loc[df.index.map(crit)] to select via labels
@@ -4841,7 +4841,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
         return self.take(locs, axis=axis, is_copy=False)
 
     _shared_docs['pipe'] = (r"""
-        Apply func(self, \*args, \*\*kwargs)
+        Apply func(self, \*args, \*\*kwargs).
 
         Parameters
         ----------
@@ -5533,7 +5533,7 @@ def as_blocks(self, copy=True):
     @property
     def blocks(self):
         """
-        Internal property, property synonym for as_blocks()
+        Internal property, property synonym for as_blocks().
 
         .. deprecated:: 0.21.0
         """
@@ -5918,7 +5918,7 @@ def infer_objects(self):
     def fillna(self, value=None, method=None, axis=None, inplace=False,
                limit=None, downcast=None):
         """
-        Fill NA/NaN values using the specified method
+        Fill NA/NaN values using the specified method.
 
         Parameters
         ----------
@@ -6103,14 +6103,14 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
@@ -8251,7 +8251,7 @@ def rank(self, axis=0, method='average', numeric_only=None,
              na_option='keep', ascending=True, pct=False):
         """
         Compute numerical data ranks (1 through n) along axis. Equal values are
-        assigned a rank that is the average of the ranks of those values
+        assigned a rank that is the average of the ranks of those values.
 
         Parameters
         ----------
@@ -8313,7 +8313,7 @@ def ranker(data):
 
     _shared_docs['align'] = ("""
         Align two objects on their axes with the
-        specified join method for each axis Index
+        specified join method for each axis Index.
 
         Parameters
         ----------
@@ -9902,7 +9902,7 @@ def _add_numeric_operations(cls):
 
         @Substitution(outname='mad',
                       desc="Return the mean absolute deviation of the values "
-                           "for the requested axis",
+                           "for the requested axis.",
                       name1=name, name2=name2, axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9944,7 +9944,7 @@ def mad(self, axis=None, skipna=None, level=None):
 
         @Substitution(outname='compounded',
                       desc="Return the compound percentage of the values for "
-                      "the requested axis", name1=name, name2=name2,
+                      "the requested axis.", name1=name, name2=name2,
                       axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9974,31 +9974,31 @@ def compound(self, axis=None, skipna=None, level=None):
 
         cls.sum = _make_min_count_stat_function(
             cls, 'sum', name, name2, axis_descr,
-            'Return the sum of the values for the requested axis',
+            'Return the sum of the values for the requested axis.',
             nanops.nansum, _sum_examples)
         cls.mean = _make_stat_function(
             cls, 'mean', name, name2, axis_descr,
-            'Return the mean of the values for the requested axis',
+            'Return the mean of the values for the requested axis.',
             nanops.nanmean)
         cls.skew = _make_stat_function(
             cls, 'skew', name, name2, axis_descr,
-            'Return unbiased skew over requested axis\nNormalized by N-1',
+            'Return unbiased skew over requested axis\nNormalized by N-1.',
             nanops.nanskew)
         cls.kurt = _make_stat_function(
             cls, 'kurt', name, name2, axis_descr,
             "Return unbiased kurtosis over requested axis using Fisher's "
             "definition of\nkurtosis (kurtosis of normal == 0.0). Normalized "
-            "by N-1",
+            "by N-1.",
             nanops.nankurt)
         cls.kurtosis = cls.kurt
         cls.prod = _make_min_count_stat_function(
             cls, 'prod', name, name2, axis_descr,
-            'Return the product of the values for the requested axis',
+            'Return the product of the values for the requested axis.',
             nanops.nanprod, _prod_examples)
         cls.product = cls.prod
         cls.median = _make_stat_function(
             cls, 'median', name, name2, axis_descr,
-            'Return the median of the values for the requested axis',
+            'Return the median of the values for the requested axis.',
             nanops.nanmedian)
         cls.max = _make_stat_function(
             cls, 'max', name, name2, axis_descr,
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 82b6b22be4a79..ecc96ca1ecc94 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -130,7 +130,7 @@ class DatetimeProperties(Properties):
 
     def to_pydatetime(self):
         """
-        Return the data as an array of native Python datetime objects
+        Return the data as an array of native Python datetime objects.
 
         Timezone information is retained if present.
 
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index ec6743e205848..52d40f84cb1d9 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2417,7 +2417,7 @@ def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
                 xrot=None, ylabelsize=None, yrot=None, figsize=None,
                 bins=10, **kwds):
     """
-    Draw histogram of the input series using matplotlib
+    Draw histogram of the input series using matplotlib.
 
     Parameters
     ----------
@@ -2706,7 +2706,7 @@ def __call__(self, *args, **kwargs):
 
 class SeriesPlotMethods(BasePlotMethods):
     """
-    Series plotting accessor and method
+    Series plotting accessor and method.
 
     Examples
     --------
@@ -2739,7 +2739,7 @@ def __call__(self, kind='line', ax=None,
 
     def line(self, **kwds):
         """
-        Line plot
+        Line plot.
 
         Parameters
         ----------
@@ -2764,7 +2764,7 @@ def line(self, **kwds):
 
     def bar(self, **kwds):
         """
-        Vertical bar plot
+        Vertical bar plot.
 
         Parameters
         ----------
@@ -2780,7 +2780,7 @@ def bar(self, **kwds):
 
     def barh(self, **kwds):
         """
-        Horizontal bar plot
+        Horizontal bar plot.
 
         Parameters
         ----------
@@ -2796,7 +2796,7 @@ def barh(self, **kwds):
 
     def box(self, **kwds):
         """
-        Boxplot
+        Boxplot.
 
         Parameters
         ----------
@@ -2812,7 +2812,7 @@ def box(self, **kwds):
 
     def hist(self, bins=10, **kwds):
         """
-        Histogram
+        Histogram.
 
         Parameters
         ----------
@@ -2873,7 +2873,7 @@ def kde(self, bw_method=None, ind=None, **kwds):
 
     def area(self, **kwds):
         """
-        Area plot
+        Area plot.
 
         Parameters
         ----------
@@ -2889,7 +2889,7 @@ def area(self, **kwds):
 
     def pie(self, **kwds):
         """
-        Pie chart
+        Pie chart.
 
         Parameters
         ----------
diff --git a/scripts/tmp.xlsx b/scripts/tmp.xlsx
new file mode 100644
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From b3668195d18bd4f4f55f6d9f58cb1b4645a4929d Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:57:49 -0500
Subject: [PATCH 02/18] fixed generic.py PEP8 - line too long issues

---
 pandas/core/generic.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 1a2c04cd1a267..1ea8ac55540a7 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6103,14 +6103,16 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`.
+        Synonym for :meth:`DataFrame.fillna(method='ffill') 
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`.
+        Synonym for :meth:`DataFrame.fillna(method='bfill') 
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)

From 88d6664afaa5911055fd6bd0aac136813c13119c Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:59:21 -0500
Subject: [PATCH 03/18] fixed generic.py PEP8 - trailing whitespace issues

---
 pandas/core/generic.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 1ea8ac55540a7..e52a0b60c610e 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6103,7 +6103,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') 
+        Synonym for :meth:`DataFrame.fillna(method='ffill')
             <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
@@ -6111,7 +6111,7 @@ def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') 
+        Synonym for :meth:`DataFrame.fillna(method='bfill')
             <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,

From ad50026108437989ba2b2035bba29718b32aeccd Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 21:35:25 -0500
Subject: [PATCH 04/18] fixed minor errors

---
 pandas/core/accessor.py           |   2 +-
 pandas/core/arrays/categorical.py |   4 ++--
 pandas/core/arrays/datetimes.py   |  18 +++++++++---------
 scripts/tmp.xlsx                  | Bin 5418 -> 0 bytes
 4 files changed, 12 insertions(+), 12 deletions(-)
 delete mode 100644 scripts/tmp.xlsx

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index 1beb097f58bdf..93b4ce31a1e25 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class.
+        Add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 2cf9af16f0fdb..b2c580ac435db 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered.
+        Set the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered.
+        Set the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index d176e5d244cd1..4b4c49f0f0617 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1065,19 +1065,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime.\n")
+    year = _field_accessor('year', 'Y', " The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12. \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime.\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime.\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime.\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime.\n")
+                            " The month as January=1, December=12. ")
+    day = _field_accessor('day', 'D', "The days of the datetime.")
+    hour = _field_accessor('hour', 'h', "The hours of the datetime.")
+    minute = _field_accessor('minute', 'm', "The minutes of the datetime.")
+    second = _field_accessor('second', 's', "The seconds of the datetime.")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime.\n")
+                                  "The microseconds of the datetime.")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime.\n")
+                                 "The nanoseconds of the datetime.")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year.\n")
+                                 "The week ordinal of the year.")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/scripts/tmp.xlsx b/scripts/tmp.xlsx
deleted file mode 100644
index 030a0f83d63206d20e884777e6a90cc587791dbd..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From d3d0bd013efd0a2f993a57a6f07ba599b00e27b6 Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 21:37:39 -0500
Subject: [PATCH 05/18] removed a few more \n

---
 pandas/core/arrays/datetimes.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 4b4c49f0f0617..7401b2534a237 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
         return result
 
     f.__name__ = name
-    f.__doc__ = "\n{}\n".format(docstring)
+    f.__doc__ = "{}".format(docstring)
     return property(f)
 
 
@@ -1119,7 +1119,7 @@ def date(self):
     weekday_name = _field_accessor(
         'weekday_name',
         'weekday_name',
-        "The name of day in a week (ex: Friday)\n\n.. deprecated:: 0.23.0")
+        "The name of day in a week (ex: Friday).. deprecated:: 0.23.0")
 
     dayofyear = _field_accessor('dayofyear', 'doy',
                                 "The ordinal day of the year.")

From 97444fb8b7d1dedd0437ba995feceb2d61b15f6f Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 21:46:50 -0500
Subject: [PATCH 06/18] added back required \n

---
 pandas/core/arrays/datetimes.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 7401b2534a237..9e8116bd15611 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1119,7 +1119,7 @@ def date(self):
     weekday_name = _field_accessor(
         'weekday_name',
         'weekday_name',
-        "The name of day in a week (ex: Friday).. deprecated:: 0.23.0")
+        "The name of day in a week (ex: Friday)\n\n.. deprecated:: 0.23.0")
 
     dayofyear = _field_accessor('dayofyear', 'doy',
                                 "The ordinal day of the year.")

From dc0a303baaf9293965b9946b05d22414a0a7a8f2 Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Sun, 9 Dec 2018 21:53:53 -0500
Subject: [PATCH 07/18] Update pandas/core/arrays/datetimes.py

Co-Authored-By: YuechengWu <ywu194@myseneca.ca>
---
 pandas/core/arrays/datetimes.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 9e8116bd15611..7bacb951c1dca 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1065,7 +1065,7 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', " The year of the datetime.")
+    year = _field_accessor('year', 'Y', "The year of the datetime.")
     month = _field_accessor('month', 'M',
                             " The month as January=1, December=12. ")
     day = _field_accessor('day', 'D', "The days of the datetime.")

From 86398414357506cf49cb1260a0d3962894c2fccf Mon Sep 17 00:00:00 2001
From: Marc Garcia <garcia.marc@gmail.com>
Date: Sun, 9 Dec 2018 21:54:09 -0500
Subject: [PATCH 08/18] Update pandas/core/arrays/datetimes.py

Co-Authored-By: YuechengWu <ywu194@myseneca.ca>
---
 pandas/core/arrays/datetimes.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 7bacb951c1dca..ab848bad93cc6 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1067,7 +1067,7 @@ def date(self):
 
     year = _field_accessor('year', 'Y', "The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            " The month as January=1, December=12. ")
+                            "The month as January=1, December=12. ")
     day = _field_accessor('day', 'D', "The days of the datetime.")
     hour = _field_accessor('hour', 'h', "The hours of the datetime.")
     minute = _field_accessor('minute', 'm', "The minutes of the datetime.")

From b052287c38a9919ecee94e3035d614cfc62cb60c Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:47:42 -0500
Subject: [PATCH 09/18] fix Summary does not end with a period error

---
 pandas/core/accessor.py           |   2 +-
 pandas/core/arrays/categorical.py |   6 ++---
 pandas/core/arrays/datetimes.py   |  18 +++++++--------
 pandas/core/base.py               |   6 ++---
 pandas/core/dtypes/dtypes.py      |   2 +-
 pandas/core/generic.py            |  36 +++++++++++++++---------------
 pandas/core/indexes/accessors.py  |   2 +-
 pandas/plotting/_core.py          |  18 +++++++--------
 scripts/tmp.xlsx                  | Bin 0 -> 5418 bytes
 9 files changed, 45 insertions(+), 45 deletions(-)
 create mode 100644 scripts/tmp.xlsx

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index fa1dc751c17da..1beb097f58bdf 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class
+        add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index abadd64b441b4..c85c347b523d0 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -477,7 +477,7 @@ def categories(self, categories):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self.dtype.ordered
 
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered
+        Sets the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered
+        Sets the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 72ab400b41c0c..70b95d64608db 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1070,19 +1070,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime\n")
+    year = _field_accessor('year', 'Y', "\n The year of the datetime.\n")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12 \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime\n")
+                            "\n The month as January=1, December=12. \n")
+    day = _field_accessor('day', 'D', "\nThe days of the datetime.\n")
+    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime.\n")
+    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime.\n")
+    second = _field_accessor('second', 's', "\nThe seconds of the datetime.\n")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime\n")
+                                  "\nThe microseconds of the datetime.\n")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime\n")
+                                 "\nThe nanoseconds of the datetime.\n")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year\n")
+                                 "\nThe week ordinal of the year.\n")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 1d2a0a2544dbc..161bf8fbf3482 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -1244,7 +1244,7 @@ def nunique(self, dropna=True):
     @property
     def is_unique(self):
         """
-        Return boolean if values in the object are unique
+        Return boolean if values in the object are unique.
 
         Returns
         -------
@@ -1256,7 +1256,7 @@ def is_unique(self):
     def is_monotonic(self):
         """
         Return boolean if values in the object are
-        monotonic_increasing
+        monotonic_increasing.
 
         .. versionadded:: 0.19.0
 
@@ -1273,7 +1273,7 @@ def is_monotonic(self):
     def is_monotonic_decreasing(self):
         """
         Return boolean if values in the object are
-        monotonic_decreasing
+        monotonic_decreasing.
 
         .. versionadded:: 0.19.0
 
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 0db76cd934d19..24407850d44a8 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -463,7 +463,7 @@ def categories(self):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self._ordered
 
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index ba50b971b6ff9..1d7e4eadea7e1 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -671,7 +671,7 @@ def transpose(self, *args, **kwargs):
 
     def swapaxes(self, axis1, axis2, copy=True):
         """
-        Interchange axes and swap values axes appropriately
+        Interchange axes and swap values axes appropriately.
 
         Returns
         -------
@@ -1907,7 +1907,7 @@ def __array_wrap__(self, result, context=None):
 
     def to_dense(self):
         """
-        Return dense representation of NDFrame (as opposed to sparse)
+        Return dense representation of NDFrame (as opposed to sparse).
         """
         # compat
         return self
@@ -3597,7 +3597,7 @@ class   animal   locomotion
 
     def select(self, crit, axis=0):
         """
-        Return data corresponding to axis labels matching criteria
+        Return data corresponding to axis labels matching criteria.
 
         .. deprecated:: 0.21.0
             Use df.loc[df.index.map(crit)] to select via labels
@@ -4841,7 +4841,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
         return self.take(locs, axis=axis, is_copy=False)
 
     _shared_docs['pipe'] = (r"""
-        Apply func(self, \*args, \*\*kwargs)
+        Apply func(self, \*args, \*\*kwargs).
 
         Parameters
         ----------
@@ -5533,7 +5533,7 @@ def as_blocks(self, copy=True):
     @property
     def blocks(self):
         """
-        Internal property, property synonym for as_blocks()
+        Internal property, property synonym for as_blocks().
 
         .. deprecated:: 0.21.0
         """
@@ -5918,7 +5918,7 @@ def infer_objects(self):
     def fillna(self, value=None, method=None, axis=None, inplace=False,
                limit=None, downcast=None):
         """
-        Fill NA/NaN values using the specified method
+        Fill NA/NaN values using the specified method.
 
         Parameters
         ----------
@@ -6103,14 +6103,14 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
@@ -8254,7 +8254,7 @@ def rank(self, axis=0, method='average', numeric_only=None,
              na_option='keep', ascending=True, pct=False):
         """
         Compute numerical data ranks (1 through n) along axis. Equal values are
-        assigned a rank that is the average of the ranks of those values
+        assigned a rank that is the average of the ranks of those values.
 
         Parameters
         ----------
@@ -8316,7 +8316,7 @@ def ranker(data):
 
     _shared_docs['align'] = ("""
         Align two objects on their axes with the
-        specified join method for each axis Index
+        specified join method for each axis Index.
 
         Parameters
         ----------
@@ -9905,7 +9905,7 @@ def _add_numeric_operations(cls):
 
         @Substitution(outname='mad',
                       desc="Return the mean absolute deviation of the values "
-                           "for the requested axis",
+                           "for the requested axis.",
                       name1=name, name2=name2, axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9947,7 +9947,7 @@ def mad(self, axis=None, skipna=None, level=None):
 
         @Substitution(outname='compounded',
                       desc="Return the compound percentage of the values for "
-                      "the requested axis", name1=name, name2=name2,
+                      "the requested axis.", name1=name, name2=name2,
                       axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9977,31 +9977,31 @@ def compound(self, axis=None, skipna=None, level=None):
 
         cls.sum = _make_min_count_stat_function(
             cls, 'sum', name, name2, axis_descr,
-            'Return the sum of the values for the requested axis',
+            'Return the sum of the values for the requested axis.',
             nanops.nansum, _sum_examples)
         cls.mean = _make_stat_function(
             cls, 'mean', name, name2, axis_descr,
-            'Return the mean of the values for the requested axis',
+            'Return the mean of the values for the requested axis.',
             nanops.nanmean)
         cls.skew = _make_stat_function(
             cls, 'skew', name, name2, axis_descr,
-            'Return unbiased skew over requested axis\nNormalized by N-1',
+            'Return unbiased skew over requested axis\nNormalized by N-1.',
             nanops.nanskew)
         cls.kurt = _make_stat_function(
             cls, 'kurt', name, name2, axis_descr,
             "Return unbiased kurtosis over requested axis using Fisher's "
             "definition of\nkurtosis (kurtosis of normal == 0.0). Normalized "
-            "by N-1",
+            "by N-1.",
             nanops.nankurt)
         cls.kurtosis = cls.kurt
         cls.prod = _make_min_count_stat_function(
             cls, 'prod', name, name2, axis_descr,
-            'Return the product of the values for the requested axis',
+            'Return the product of the values for the requested axis.',
             nanops.nanprod, _prod_examples)
         cls.product = cls.prod
         cls.median = _make_stat_function(
             cls, 'median', name, name2, axis_descr,
-            'Return the median of the values for the requested axis',
+            'Return the median of the values for the requested axis.',
             nanops.nanmedian)
         cls.max = _make_stat_function(
             cls, 'max', name, name2, axis_descr,
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 82b6b22be4a79..ecc96ca1ecc94 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -130,7 +130,7 @@ class DatetimeProperties(Properties):
 
     def to_pydatetime(self):
         """
-        Return the data as an array of native Python datetime objects
+        Return the data as an array of native Python datetime objects.
 
         Timezone information is retained if present.
 
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index ec6743e205848..52d40f84cb1d9 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2417,7 +2417,7 @@ def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
                 xrot=None, ylabelsize=None, yrot=None, figsize=None,
                 bins=10, **kwds):
     """
-    Draw histogram of the input series using matplotlib
+    Draw histogram of the input series using matplotlib.
 
     Parameters
     ----------
@@ -2706,7 +2706,7 @@ def __call__(self, *args, **kwargs):
 
 class SeriesPlotMethods(BasePlotMethods):
     """
-    Series plotting accessor and method
+    Series plotting accessor and method.
 
     Examples
     --------
@@ -2739,7 +2739,7 @@ def __call__(self, kind='line', ax=None,
 
     def line(self, **kwds):
         """
-        Line plot
+        Line plot.
 
         Parameters
         ----------
@@ -2764,7 +2764,7 @@ def line(self, **kwds):
 
     def bar(self, **kwds):
         """
-        Vertical bar plot
+        Vertical bar plot.
 
         Parameters
         ----------
@@ -2780,7 +2780,7 @@ def bar(self, **kwds):
 
     def barh(self, **kwds):
         """
-        Horizontal bar plot
+        Horizontal bar plot.
 
         Parameters
         ----------
@@ -2796,7 +2796,7 @@ def barh(self, **kwds):
 
     def box(self, **kwds):
         """
-        Boxplot
+        Boxplot.
 
         Parameters
         ----------
@@ -2812,7 +2812,7 @@ def box(self, **kwds):
 
     def hist(self, bins=10, **kwds):
         """
-        Histogram
+        Histogram.
 
         Parameters
         ----------
@@ -2873,7 +2873,7 @@ def kde(self, bw_method=None, ind=None, **kwds):
 
     def area(self, **kwds):
         """
-        Area plot
+        Area plot.
 
         Parameters
         ----------
@@ -2889,7 +2889,7 @@ def area(self, **kwds):
 
     def pie(self, **kwds):
         """
-        Pie chart
+        Pie chart.
 
         Parameters
         ----------
diff --git a/scripts/tmp.xlsx b/scripts/tmp.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..030a0f83d63206d20e884777e6a90cc587791dbd
GIT binary patch
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From 41e4757eb4f3f98e656ab87523af694630d55996 Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:57:49 -0500
Subject: [PATCH 10/18] fixed generic.py PEP8 - line too long issues

---
 pandas/core/generic.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 1d7e4eadea7e1..94fb48f0aae8d 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6103,14 +6103,16 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`.
+        Synonym for :meth:`DataFrame.fillna(method='ffill') 
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`.
+        Synonym for :meth:`DataFrame.fillna(method='bfill') 
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)

From 074b925c08d3a24b193ac1d4cccff215c3be0669 Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 19:59:21 -0500
Subject: [PATCH 11/18] fixed generic.py PEP8 - trailing whitespace issues

---
 pandas/core/generic.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 94fb48f0aae8d..11d1333851794 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6103,7 +6103,7 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') 
+        Synonym for :meth:`DataFrame.fillna(method='ffill')
             <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
@@ -6111,7 +6111,7 @@ def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') 
+        Synonym for :meth:`DataFrame.fillna(method='bfill')
             <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,

From a1e0df232f95f712104634cb76a1952109ee0067 Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 21:35:25 -0500
Subject: [PATCH 12/18] fixed minor errors

---
 pandas/core/accessor.py           |   2 +-
 pandas/core/arrays/categorical.py |   4 ++--
 pandas/core/arrays/datetimes.py   |  18 +++++++++---------
 scripts/tmp.xlsx                  | Bin 5418 -> 0 bytes
 4 files changed, 12 insertions(+), 12 deletions(-)
 delete mode 100644 scripts/tmp.xlsx

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index 1beb097f58bdf..93b4ce31a1e25 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class.
+        Add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index c85c347b523d0..101d03cd55d40 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered.
+        Set the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered.
+        Set the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 70b95d64608db..721d90723c0c7 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1070,19 +1070,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime.\n")
+    year = _field_accessor('year', 'Y', " The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12. \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime.\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime.\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime.\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime.\n")
+                            " The month as January=1, December=12. ")
+    day = _field_accessor('day', 'D', "The days of the datetime.")
+    hour = _field_accessor('hour', 'h', "The hours of the datetime.")
+    minute = _field_accessor('minute', 'm', "The minutes of the datetime.")
+    second = _field_accessor('second', 's', "The seconds of the datetime.")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime.\n")
+                                  "The microseconds of the datetime.")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime.\n")
+                                 "The nanoseconds of the datetime.")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year.\n")
+                                 "The week ordinal of the year.")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/scripts/tmp.xlsx b/scripts/tmp.xlsx
deleted file mode 100644
index 030a0f83d63206d20e884777e6a90cc587791dbd..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From 860bb8d931b78db27b4c690f28d00374cb9cb65b Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Sun, 9 Dec 2018 21:37:39 -0500
Subject: [PATCH 13/18] removed a few more \n

---
 pandas/core/arrays/datetimes.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 721d90723c0c7..64d2ab0f43847 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
         return result
 
     f.__name__ = name
-    f.__doc__ = "\n{}\n".format(docstring)
+    f.__doc__ = "{}".format(docstring)
     return property(f)
 
 
@@ -1124,7 +1124,7 @@ def date(self):
     weekday_name = _field_accessor(
         'weekday_name',
         'weekday_name',
-        "The name of day in a week (ex: Friday)\n\n.. deprecated:: 0.23.0")
+        "The name of day in a week (ex: Friday).. deprecated:: 0.23.0")
 
     dayofyear = _field_accessor('dayofyear', 'doy',
                                 "The ordinal day of the year.")

From ce03033227ec250211efad0dde968a4c72b1f24c Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Tue, 11 Dec 2018 02:10:36 -0500
Subject: [PATCH 14/18] revert back \n

---
 pandas/core/arrays/datetimes.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 64d2ab0f43847..721d90723c0c7 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
         return result
 
     f.__name__ = name
-    f.__doc__ = "{}".format(docstring)
+    f.__doc__ = "\n{}\n".format(docstring)
     return property(f)
 
 
@@ -1124,7 +1124,7 @@ def date(self):
     weekday_name = _field_accessor(
         'weekday_name',
         'weekday_name',
-        "The name of day in a week (ex: Friday).. deprecated:: 0.23.0")
+        "The name of day in a week (ex: Friday)\n\n.. deprecated:: 0.23.0")
 
     dayofyear = _field_accessor('dayofyear', 'doy',
                                 "The ordinal day of the year.")

From c10e7c5b2d3f1e24a009c1d4009fc58df798eafd Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Tue, 11 Dec 2018 08:43:07 -0500
Subject: [PATCH 15/18] revert \n

---
 pandas/core/arrays/datetimes.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 6d504a331bdf0..4849ee1e3e665 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
         return result
 
     f.__name__ = name
-    f.__doc__ = "{}".format(docstring)
+    f.__doc__ = "\n{}\n".format(docstring)
     return property(f)
 
 

From 5f67556a1dc8952ee6dd79a599e7bae8f874cc3a Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Tue, 11 Dec 2018 09:32:20 -0500
Subject: [PATCH 16/18] all my changes in a single commit

---
 pandas/core/accessor.py           |  2 +-
 pandas/core/arrays/categorical.py |  6 ++---
 pandas/core/arrays/datetimes.py   | 18 +++++++--------
 pandas/core/base.py               |  6 ++---
 pandas/core/dtypes/dtypes.py      |  2 +-
 pandas/core/generic.py            | 38 ++++++++++++++++---------------
 pandas/core/indexes/accessors.py  |  2 +-
 pandas/plotting/_core.py          | 18 +++++++--------
 8 files changed, 47 insertions(+), 45 deletions(-)

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index fa1dc751c17da..93b4ce31a1e25 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class
+        Add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index abadd64b441b4..101d03cd55d40 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -477,7 +477,7 @@ def categories(self, categories):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self.dtype.ordered
 
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered
+        Set the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered
+        Set the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 72ab400b41c0c..4849ee1e3e665 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1070,19 +1070,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime\n")
+    year = _field_accessor('year', 'Y', "The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12 \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime\n")
+                            "The month as January=1, December=12. ")
+    day = _field_accessor('day', 'D', "The days of the datetime.")
+    hour = _field_accessor('hour', 'h', "The hours of the datetime.")
+    minute = _field_accessor('minute', 'm', "The minutes of the datetime.")
+    second = _field_accessor('second', 's', "The seconds of the datetime.")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime\n")
+                                  "The microseconds of the datetime.")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime\n")
+                                 "The nanoseconds of the datetime.")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year\n")
+                                 "The week ordinal of the year.")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 1d2a0a2544dbc..161bf8fbf3482 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -1244,7 +1244,7 @@ def nunique(self, dropna=True):
     @property
     def is_unique(self):
         """
-        Return boolean if values in the object are unique
+        Return boolean if values in the object are unique.
 
         Returns
         -------
@@ -1256,7 +1256,7 @@ def is_unique(self):
     def is_monotonic(self):
         """
         Return boolean if values in the object are
-        monotonic_increasing
+        monotonic_increasing.
 
         .. versionadded:: 0.19.0
 
@@ -1273,7 +1273,7 @@ def is_monotonic(self):
     def is_monotonic_decreasing(self):
         """
         Return boolean if values in the object are
-        monotonic_decreasing
+        monotonic_decreasing.
 
         .. versionadded:: 0.19.0
 
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 0db76cd934d19..24407850d44a8 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -463,7 +463,7 @@ def categories(self):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self._ordered
 
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index ba50b971b6ff9..11d1333851794 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -671,7 +671,7 @@ def transpose(self, *args, **kwargs):
 
     def swapaxes(self, axis1, axis2, copy=True):
         """
-        Interchange axes and swap values axes appropriately
+        Interchange axes and swap values axes appropriately.
 
         Returns
         -------
@@ -1907,7 +1907,7 @@ def __array_wrap__(self, result, context=None):
 
     def to_dense(self):
         """
-        Return dense representation of NDFrame (as opposed to sparse)
+        Return dense representation of NDFrame (as opposed to sparse).
         """
         # compat
         return self
@@ -3597,7 +3597,7 @@ class   animal   locomotion
 
     def select(self, crit, axis=0):
         """
-        Return data corresponding to axis labels matching criteria
+        Return data corresponding to axis labels matching criteria.
 
         .. deprecated:: 0.21.0
             Use df.loc[df.index.map(crit)] to select via labels
@@ -4841,7 +4841,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
         return self.take(locs, axis=axis, is_copy=False)
 
     _shared_docs['pipe'] = (r"""
-        Apply func(self, \*args, \*\*kwargs)
+        Apply func(self, \*args, \*\*kwargs).
 
         Parameters
         ----------
@@ -5533,7 +5533,7 @@ def as_blocks(self, copy=True):
     @property
     def blocks(self):
         """
-        Internal property, property synonym for as_blocks()
+        Internal property, property synonym for as_blocks().
 
         .. deprecated:: 0.21.0
         """
@@ -5918,7 +5918,7 @@ def infer_objects(self):
     def fillna(self, value=None, method=None, axis=None, inplace=False,
                limit=None, downcast=None):
         """
-        Fill NA/NaN values using the specified method
+        Fill NA/NaN values using the specified method.
 
         Parameters
         ----------
@@ -6103,14 +6103,16 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='ffill')
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='bfill')
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
@@ -8254,7 +8256,7 @@ def rank(self, axis=0, method='average', numeric_only=None,
              na_option='keep', ascending=True, pct=False):
         """
         Compute numerical data ranks (1 through n) along axis. Equal values are
-        assigned a rank that is the average of the ranks of those values
+        assigned a rank that is the average of the ranks of those values.
 
         Parameters
         ----------
@@ -8316,7 +8318,7 @@ def ranker(data):
 
     _shared_docs['align'] = ("""
         Align two objects on their axes with the
-        specified join method for each axis Index
+        specified join method for each axis Index.
 
         Parameters
         ----------
@@ -9905,7 +9907,7 @@ def _add_numeric_operations(cls):
 
         @Substitution(outname='mad',
                       desc="Return the mean absolute deviation of the values "
-                           "for the requested axis",
+                           "for the requested axis.",
                       name1=name, name2=name2, axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9947,7 +9949,7 @@ def mad(self, axis=None, skipna=None, level=None):
 
         @Substitution(outname='compounded',
                       desc="Return the compound percentage of the values for "
-                      "the requested axis", name1=name, name2=name2,
+                      "the requested axis.", name1=name, name2=name2,
                       axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9977,31 +9979,31 @@ def compound(self, axis=None, skipna=None, level=None):
 
         cls.sum = _make_min_count_stat_function(
             cls, 'sum', name, name2, axis_descr,
-            'Return the sum of the values for the requested axis',
+            'Return the sum of the values for the requested axis.',
             nanops.nansum, _sum_examples)
         cls.mean = _make_stat_function(
             cls, 'mean', name, name2, axis_descr,
-            'Return the mean of the values for the requested axis',
+            'Return the mean of the values for the requested axis.',
             nanops.nanmean)
         cls.skew = _make_stat_function(
             cls, 'skew', name, name2, axis_descr,
-            'Return unbiased skew over requested axis\nNormalized by N-1',
+            'Return unbiased skew over requested axis\nNormalized by N-1.',
             nanops.nanskew)
         cls.kurt = _make_stat_function(
             cls, 'kurt', name, name2, axis_descr,
             "Return unbiased kurtosis over requested axis using Fisher's "
             "definition of\nkurtosis (kurtosis of normal == 0.0). Normalized "
-            "by N-1",
+            "by N-1.",
             nanops.nankurt)
         cls.kurtosis = cls.kurt
         cls.prod = _make_min_count_stat_function(
             cls, 'prod', name, name2, axis_descr,
-            'Return the product of the values for the requested axis',
+            'Return the product of the values for the requested axis.',
             nanops.nanprod, _prod_examples)
         cls.product = cls.prod
         cls.median = _make_stat_function(
             cls, 'median', name, name2, axis_descr,
-            'Return the median of the values for the requested axis',
+            'Return the median of the values for the requested axis.',
             nanops.nanmedian)
         cls.max = _make_stat_function(
             cls, 'max', name, name2, axis_descr,
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 82b6b22be4a79..ecc96ca1ecc94 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -130,7 +130,7 @@ class DatetimeProperties(Properties):
 
     def to_pydatetime(self):
         """
-        Return the data as an array of native Python datetime objects
+        Return the data as an array of native Python datetime objects.
 
         Timezone information is retained if present.
 
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index ec6743e205848..52d40f84cb1d9 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2417,7 +2417,7 @@ def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
                 xrot=None, ylabelsize=None, yrot=None, figsize=None,
                 bins=10, **kwds):
     """
-    Draw histogram of the input series using matplotlib
+    Draw histogram of the input series using matplotlib.
 
     Parameters
     ----------
@@ -2706,7 +2706,7 @@ def __call__(self, *args, **kwargs):
 
 class SeriesPlotMethods(BasePlotMethods):
     """
-    Series plotting accessor and method
+    Series plotting accessor and method.
 
     Examples
     --------
@@ -2739,7 +2739,7 @@ def __call__(self, kind='line', ax=None,
 
     def line(self, **kwds):
         """
-        Line plot
+        Line plot.
 
         Parameters
         ----------
@@ -2764,7 +2764,7 @@ def line(self, **kwds):
 
     def bar(self, **kwds):
         """
-        Vertical bar plot
+        Vertical bar plot.
 
         Parameters
         ----------
@@ -2780,7 +2780,7 @@ def bar(self, **kwds):
 
     def barh(self, **kwds):
         """
-        Horizontal bar plot
+        Horizontal bar plot.
 
         Parameters
         ----------
@@ -2796,7 +2796,7 @@ def barh(self, **kwds):
 
     def box(self, **kwds):
         """
-        Boxplot
+        Boxplot.
 
         Parameters
         ----------
@@ -2812,7 +2812,7 @@ def box(self, **kwds):
 
     def hist(self, bins=10, **kwds):
         """
-        Histogram
+        Histogram.
 
         Parameters
         ----------
@@ -2873,7 +2873,7 @@ def kde(self, bw_method=None, ind=None, **kwds):
 
     def area(self, **kwds):
         """
-        Area plot
+        Area plot.
 
         Parameters
         ----------
@@ -2889,7 +2889,7 @@ def area(self, **kwds):
 
     def pie(self, **kwds):
         """
-        Pie chart
+        Pie chart.
 
         Parameters
         ----------

From 1950b089191e4a50e9116c76ea1c4654c1216a79 Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Tue, 11 Dec 2018 14:44:05 -0500
Subject: [PATCH 17/18] All my changes in a single commit

---
 pandas/core/accessor.py           |  2 +-
 pandas/core/arrays/categorical.py |  6 ++---
 pandas/core/arrays/datetimes.py   | 18 +++++++--------
 pandas/core/base.py               |  6 ++---
 pandas/core/dtypes/dtypes.py      |  2 +-
 pandas/core/generic.py            | 38 ++++++++++++++++---------------
 pandas/core/indexes/accessors.py  |  2 +-
 pandas/plotting/_core.py          | 18 +++++++--------
 8 files changed, 47 insertions(+), 45 deletions(-)

diff --git a/pandas/core/accessor.py b/pandas/core/accessor.py
index fa1dc751c17da..93b4ce31a1e25 100644
--- a/pandas/core/accessor.py
+++ b/pandas/core/accessor.py
@@ -59,7 +59,7 @@ def _delegate_method(self, name, *args, **kwargs):
     def _add_delegate_accessors(cls, delegate, accessors, typ,
                                 overwrite=False):
         """
-        add accessors to cls from the delegate class
+        Add accessors to cls from the delegate class.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index abadd64b441b4..101d03cd55d40 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -477,7 +477,7 @@ def categories(self, categories):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self.dtype.ordered
 
@@ -782,7 +782,7 @@ def set_ordered(self, value, inplace=False):
 
     def as_ordered(self, inplace=False):
         """
-        Sets the Categorical to be ordered
+        Set the Categorical to be ordered.
 
         Parameters
         ----------
@@ -795,7 +795,7 @@ def as_ordered(self, inplace=False):
 
     def as_unordered(self, inplace=False):
         """
-        Sets the Categorical to be unordered
+        Set the Categorical to be unordered.
 
         Parameters
         ----------
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 72ab400b41c0c..4849ee1e3e665 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1070,19 +1070,19 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', "\n The year of the datetime\n")
+    year = _field_accessor('year', 'Y', "The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            "\n The month as January=1, December=12 \n")
-    day = _field_accessor('day', 'D', "\nThe days of the datetime\n")
-    hour = _field_accessor('hour', 'h', "\nThe hours of the datetime\n")
-    minute = _field_accessor('minute', 'm', "\nThe minutes of the datetime\n")
-    second = _field_accessor('second', 's', "\nThe seconds of the datetime\n")
+                            "The month as January=1, December=12. ")
+    day = _field_accessor('day', 'D', "The days of the datetime.")
+    hour = _field_accessor('hour', 'h', "The hours of the datetime.")
+    minute = _field_accessor('minute', 'm', "The minutes of the datetime.")
+    second = _field_accessor('second', 's', "The seconds of the datetime.")
     microsecond = _field_accessor('microsecond', 'us',
-                                  "\nThe microseconds of the datetime\n")
+                                  "The microseconds of the datetime.")
     nanosecond = _field_accessor('nanosecond', 'ns',
-                                 "\nThe nanoseconds of the datetime\n")
+                                 "The nanoseconds of the datetime.")
     weekofyear = _field_accessor('weekofyear', 'woy',
-                                 "\nThe week ordinal of the year\n")
+                                 "The week ordinal of the year.")
     week = weekofyear
     _dayofweek_doc = """
     The day of the week with Monday=0, Sunday=6.
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 1d2a0a2544dbc..161bf8fbf3482 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -1244,7 +1244,7 @@ def nunique(self, dropna=True):
     @property
     def is_unique(self):
         """
-        Return boolean if values in the object are unique
+        Return boolean if values in the object are unique.
 
         Returns
         -------
@@ -1256,7 +1256,7 @@ def is_unique(self):
     def is_monotonic(self):
         """
         Return boolean if values in the object are
-        monotonic_increasing
+        monotonic_increasing.
 
         .. versionadded:: 0.19.0
 
@@ -1273,7 +1273,7 @@ def is_monotonic(self):
     def is_monotonic_decreasing(self):
         """
         Return boolean if values in the object are
-        monotonic_decreasing
+        monotonic_decreasing.
 
         .. versionadded:: 0.19.0
 
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 0db76cd934d19..24407850d44a8 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -463,7 +463,7 @@ def categories(self):
     @property
     def ordered(self):
         """
-        Whether the categories have an ordered relationship
+        Whether the categories have an ordered relationship.
         """
         return self._ordered
 
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index ba50b971b6ff9..11d1333851794 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -671,7 +671,7 @@ def transpose(self, *args, **kwargs):
 
     def swapaxes(self, axis1, axis2, copy=True):
         """
-        Interchange axes and swap values axes appropriately
+        Interchange axes and swap values axes appropriately.
 
         Returns
         -------
@@ -1907,7 +1907,7 @@ def __array_wrap__(self, result, context=None):
 
     def to_dense(self):
         """
-        Return dense representation of NDFrame (as opposed to sparse)
+        Return dense representation of NDFrame (as opposed to sparse).
         """
         # compat
         return self
@@ -3597,7 +3597,7 @@ class   animal   locomotion
 
     def select(self, crit, axis=0):
         """
-        Return data corresponding to axis labels matching criteria
+        Return data corresponding to axis labels matching criteria.
 
         .. deprecated:: 0.21.0
             Use df.loc[df.index.map(crit)] to select via labels
@@ -4841,7 +4841,7 @@ def sample(self, n=None, frac=None, replace=False, weights=None,
         return self.take(locs, axis=axis, is_copy=False)
 
     _shared_docs['pipe'] = (r"""
-        Apply func(self, \*args, \*\*kwargs)
+        Apply func(self, \*args, \*\*kwargs).
 
         Parameters
         ----------
@@ -5533,7 +5533,7 @@ def as_blocks(self, copy=True):
     @property
     def blocks(self):
         """
-        Internal property, property synonym for as_blocks()
+        Internal property, property synonym for as_blocks().
 
         .. deprecated:: 0.21.0
         """
@@ -5918,7 +5918,7 @@ def infer_objects(self):
     def fillna(self, value=None, method=None, axis=None, inplace=False,
                limit=None, downcast=None):
         """
-        Fill NA/NaN values using the specified method
+        Fill NA/NaN values using the specified method.
 
         Parameters
         ----------
@@ -6103,14 +6103,16 @@ def fillna(self, value=None, method=None, axis=None, inplace=False,
 
     def ffill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='ffill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='ffill')
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='ffill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
 
     def bfill(self, axis=None, inplace=False, limit=None, downcast=None):
         """
-        Synonym for :meth:`DataFrame.fillna(method='bfill') <DataFrame.fillna>`
+        Synonym for :meth:`DataFrame.fillna(method='bfill')
+            <DataFrame.fillna>`.
         """
         return self.fillna(method='bfill', axis=axis, inplace=inplace,
                            limit=limit, downcast=downcast)
@@ -8254,7 +8256,7 @@ def rank(self, axis=0, method='average', numeric_only=None,
              na_option='keep', ascending=True, pct=False):
         """
         Compute numerical data ranks (1 through n) along axis. Equal values are
-        assigned a rank that is the average of the ranks of those values
+        assigned a rank that is the average of the ranks of those values.
 
         Parameters
         ----------
@@ -8316,7 +8318,7 @@ def ranker(data):
 
     _shared_docs['align'] = ("""
         Align two objects on their axes with the
-        specified join method for each axis Index
+        specified join method for each axis Index.
 
         Parameters
         ----------
@@ -9905,7 +9907,7 @@ def _add_numeric_operations(cls):
 
         @Substitution(outname='mad',
                       desc="Return the mean absolute deviation of the values "
-                           "for the requested axis",
+                           "for the requested axis.",
                       name1=name, name2=name2, axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9947,7 +9949,7 @@ def mad(self, axis=None, skipna=None, level=None):
 
         @Substitution(outname='compounded',
                       desc="Return the compound percentage of the values for "
-                      "the requested axis", name1=name, name2=name2,
+                      "the requested axis.", name1=name, name2=name2,
                       axis_descr=axis_descr,
                       min_count='', examples='')
         @Appender(_num_doc)
@@ -9977,31 +9979,31 @@ def compound(self, axis=None, skipna=None, level=None):
 
         cls.sum = _make_min_count_stat_function(
             cls, 'sum', name, name2, axis_descr,
-            'Return the sum of the values for the requested axis',
+            'Return the sum of the values for the requested axis.',
             nanops.nansum, _sum_examples)
         cls.mean = _make_stat_function(
             cls, 'mean', name, name2, axis_descr,
-            'Return the mean of the values for the requested axis',
+            'Return the mean of the values for the requested axis.',
             nanops.nanmean)
         cls.skew = _make_stat_function(
             cls, 'skew', name, name2, axis_descr,
-            'Return unbiased skew over requested axis\nNormalized by N-1',
+            'Return unbiased skew over requested axis\nNormalized by N-1.',
             nanops.nanskew)
         cls.kurt = _make_stat_function(
             cls, 'kurt', name, name2, axis_descr,
             "Return unbiased kurtosis over requested axis using Fisher's "
             "definition of\nkurtosis (kurtosis of normal == 0.0). Normalized "
-            "by N-1",
+            "by N-1.",
             nanops.nankurt)
         cls.kurtosis = cls.kurt
         cls.prod = _make_min_count_stat_function(
             cls, 'prod', name, name2, axis_descr,
-            'Return the product of the values for the requested axis',
+            'Return the product of the values for the requested axis.',
             nanops.nanprod, _prod_examples)
         cls.product = cls.prod
         cls.median = _make_stat_function(
             cls, 'median', name, name2, axis_descr,
-            'Return the median of the values for the requested axis',
+            'Return the median of the values for the requested axis.',
             nanops.nanmedian)
         cls.max = _make_stat_function(
             cls, 'max', name, name2, axis_descr,
diff --git a/pandas/core/indexes/accessors.py b/pandas/core/indexes/accessors.py
index 82b6b22be4a79..ecc96ca1ecc94 100644
--- a/pandas/core/indexes/accessors.py
+++ b/pandas/core/indexes/accessors.py
@@ -130,7 +130,7 @@ class DatetimeProperties(Properties):
 
     def to_pydatetime(self):
         """
-        Return the data as an array of native Python datetime objects
+        Return the data as an array of native Python datetime objects.
 
         Timezone information is retained if present.
 
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index ec6743e205848..52d40f84cb1d9 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2417,7 +2417,7 @@ def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
                 xrot=None, ylabelsize=None, yrot=None, figsize=None,
                 bins=10, **kwds):
     """
-    Draw histogram of the input series using matplotlib
+    Draw histogram of the input series using matplotlib.
 
     Parameters
     ----------
@@ -2706,7 +2706,7 @@ def __call__(self, *args, **kwargs):
 
 class SeriesPlotMethods(BasePlotMethods):
     """
-    Series plotting accessor and method
+    Series plotting accessor and method.
 
     Examples
     --------
@@ -2739,7 +2739,7 @@ def __call__(self, kind='line', ax=None,
 
     def line(self, **kwds):
         """
-        Line plot
+        Line plot.
 
         Parameters
         ----------
@@ -2764,7 +2764,7 @@ def line(self, **kwds):
 
     def bar(self, **kwds):
         """
-        Vertical bar plot
+        Vertical bar plot.
 
         Parameters
         ----------
@@ -2780,7 +2780,7 @@ def bar(self, **kwds):
 
     def barh(self, **kwds):
         """
-        Horizontal bar plot
+        Horizontal bar plot.
 
         Parameters
         ----------
@@ -2796,7 +2796,7 @@ def barh(self, **kwds):
 
     def box(self, **kwds):
         """
-        Boxplot
+        Boxplot.
 
         Parameters
         ----------
@@ -2812,7 +2812,7 @@ def box(self, **kwds):
 
     def hist(self, bins=10, **kwds):
         """
-        Histogram
+        Histogram.
 
         Parameters
         ----------
@@ -2873,7 +2873,7 @@ def kde(self, bw_method=None, ind=None, **kwds):
 
     def area(self, **kwds):
         """
-        Area plot
+        Area plot.
 
         Parameters
         ----------
@@ -2889,7 +2889,7 @@ def area(self, **kwds):
 
     def pie(self, **kwds):
         """
-        Pie chart
+        Pie chart.
 
         Parameters
         ----------

From 18350bf3c69612e875500049840a4a1fe0b2612d Mon Sep 17 00:00:00 2001
From: Yuecheng Wu <ywu194@myseneca.ca>
Date: Tue, 11 Dec 2018 14:54:05 -0500
Subject: [PATCH 18/18] clean up branch history

---
 azure-pipelines.yml                           |  16 +-
 ci/azure/linux.yml                            |  79 ---
 ci/azure/{macos.yml => posix.yml}             |  30 +-
 ci/azure/windows-py27.yml                     |  58 --
 ci/azure/windows.yml                          |  14 +-
 doc/source/10min.rst                          |  14 +-
 doc/source/advanced.rst                       |   3 +-
 doc/source/api.rst                            |   3 +-
 doc/source/categorical.rst                    |   2 +-
 doc/source/contributing_docstring.rst         |   6 +-
 doc/source/developer.rst                      |   2 +
 doc/source/dsintro.rst                        |  61 +-
 doc/source/ecosystem.rst                      |   2 +
 doc/source/enhancingperf.rst                  |   2 +-
 doc/source/extending.rst                      |  10 +-
 doc/source/merging.rst                        |  52 +-
 doc/source/options.rst                        |   9 +-
 doc/source/overview.rst                       |   2 +-
 doc/source/r_interface.rst                    |   1 -
 doc/source/releases.rst                       |   2 +
 doc/source/reshaping.rst                      |  25 +-
 doc/source/tutorials.rst                      |   2 +
 doc/source/visualization.rst                  |  55 +-
 doc/source/whatsnew/v0.22.0.rst               |   4 +-
 doc/source/whatsnew/v0.23.0.rst               |  53 +-
 doc/source/whatsnew/v0.23.1.rst               |  12 +-
 doc/source/whatsnew/v0.23.2.rst               |   5 -
 doc/source/whatsnew/v0.23.4.rst               |   5 -
 doc/source/whatsnew/v0.24.0.rst               | 105 ++--
 pandas/_libs/tslibs/timestamps.pyx            |  45 +-
 pandas/core/arrays/base.py                    |   2 +
 pandas/core/arrays/categorical.py             |  12 +-
 pandas/core/arrays/datetimes.py               |  13 +-
 pandas/core/arrays/sparse.py                  |   2 +
 pandas/core/computation/ops.py                |   2 +-
 pandas/core/generic.py                        | 100 ++--
 pandas/core/indexes/base.py                   |   3 +-
 pandas/core/indexes/category.py               |   5 +-
 pandas/core/internals/blocks.py               |  82 ++-
 .../tests/arrays/categorical/test_indexing.py | 121 ++++
 pandas/tests/arrays/interval/test_interval.py |  14 +-
 pandas/tests/arrays/sparse/test_array.py      |   4 +-
 pandas/tests/arrays/test_period.py            |  15 +
 pandas/tests/extension/base/methods.py        |  35 +-
 pandas/tests/extension/conftest.py            |   6 +-
 pandas/tests/extension/json/test_json.py      |  11 +
 pandas/tests/extension/test_categorical.py    |  15 +-
 pandas/tests/extension/test_sparse.py         |  31 +
 pandas/tests/frame/test_analytics.py          |  15 +-
 .../indexes/datetimes/test_date_range.py      |  11 +
 .../tests/indexing/multiindex/test_getitem.py | 562 +++++++++---------
 pandas/tests/series/test_analytics.py         |  20 +-
 scripts/validate_docstrings.py                |   1 +
 setup.cfg                                     |  25 +-
 tmp.xlsx                                      | Bin 5417 -> 0 bytes
 55 files changed, 1029 insertions(+), 757 deletions(-)
 delete mode 100644 ci/azure/linux.yml
 rename ci/azure/{macos.yml => posix.yml} (69%)
 delete mode 100644 ci/azure/windows-py27.yml
 delete mode 100644 tmp.xlsx

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
index 409b1ac8c9df3..1e4e43ac03815 100644
--- a/azure-pipelines.yml
+++ b/azure-pipelines.yml
@@ -1,28 +1,20 @@
 # Adapted from https://github.com/numba/numba/blob/master/azure-pipelines.yml
 jobs:
-# Mac and Linux could potentially use the same template
-# except it isn't clear how to use a different build matrix
-# for each, so for now they are separate
-- template: ci/azure/macos.yml
+# Mac and Linux use the same template
+- template: ci/azure/posix.yml
   parameters:
     name: macOS
     vmImage: xcode9-macos10.13
-- template: ci/azure/linux.yml
+- template: ci/azure/posix.yml
   parameters:
     name: Linux
     vmImage: ubuntu-16.04
 
-# Windows Python 2.7 needs VC 9.0 installed, and not sure
-# how to make that a conditional task, so for now these are
-# separate templates as well
+# Windows Python 2.7 needs VC 9.0 installed, handled in the template
 - template: ci/azure/windows.yml
   parameters:
     name: Windows
     vmImage: vs2017-win2016
-- template: ci/azure/windows-py27.yml
-  parameters:
-    name: WindowsPy27
-    vmImage: vs2017-win2016
 
 - job: 'Checks_and_doc'
   pool:
diff --git a/ci/azure/linux.yml b/ci/azure/linux.yml
deleted file mode 100644
index fe64307e9d08f..0000000000000
--- a/ci/azure/linux.yml
+++ /dev/null
@@ -1,79 +0,0 @@
-parameters:
-  name: ''
-  vmImage: ''
-
-jobs:
-- job: ${{ parameters.name }}
-  pool:
-    vmImage: ${{ parameters.vmImage }}
-  strategy:
-    maxParallel: 11
-    matrix:
-      py27_np_120:
-        ENV_FILE: ci/deps/azure-27-compat.yaml
-        CONDA_PY: "27"
-        PATTERN: "not slow and not network"
-
-      py37_locale:
-        ENV_FILE: ci/deps/azure-37-locale.yaml
-        CONDA_PY: "37"
-        PATTERN: "not slow and not network"
-        LOCALE_OVERRIDE: "zh_CN.UTF-8"
-
-      py36_locale_slow:
-        ENV_FILE: ci/deps/azure-36-locale_slow.yaml
-        CONDA_PY: "36"
-        PATTERN: "not slow and not network"
-        LOCALE_OVERRIDE: "it_IT.UTF-8"
-
-  steps:
-    - script: |
-        if [ "$(uname)" == "Linux" ]; then sudo apt-get install -y libc6-dev-i386; fi
-        echo "Installing Miniconda"{
-        ci/incremental/install_miniconda.sh
-        export PATH=$HOME/miniconda3/bin:$PATH
-        echo "Setting up Conda environment"
-        ci/incremental/setup_conda_environment.sh
-      displayName: 'Before Install'
-    - script: |
-        export PATH=$HOME/miniconda3/bin:$PATH
-        source activate pandas-dev
-        ci/incremental/build.sh
-      displayName: 'Build'
-    - script: |
-        export PATH=$HOME/miniconda3/bin:$PATH
-        source activate pandas-dev
-        ci/run_tests.sh
-      displayName: 'Test'
-    - script: |
-        export PATH=$HOME/miniconda3/bin:$PATH
-        source activate pandas-dev && pushd /tmp && python -c "import pandas; pandas.show_versions();" && popd
-    - task: PublishTestResults@2
-      inputs:
-        testResultsFiles: 'test-data-*.xml'
-        testRunTitle: 'Linux'
-    - powershell: |
-        $junitXml = "test-data-single.xml"
-        $(Get-Content $junitXml | Out-String) -match 'failures="(.*?)"'
-        if ($matches[1] -eq 0)
-        {
-          Write-Host "No test failures in test-data-single"
-        }
-        else
-        {
-          # note that this will produce $LASTEXITCODE=1
-          Write-Error "$($matches[1]) tests failed"
-        }
-
-        $junitXmlMulti = "test-data-multiple.xml"
-        $(Get-Content $junitXmlMulti | Out-String) -match 'failures="(.*?)"'
-        if ($matches[1] -eq 0)
-        {
-          Write-Host "No test failures in test-data-multi"
-        }
-        else
-        {
-          # note that this will produce $LASTEXITCODE=1
-          Write-Error "$($matches[1]) tests failed"
-        }
-      displayName: Check for test failures
diff --git a/ci/azure/macos.yml b/ci/azure/posix.yml
similarity index 69%
rename from ci/azure/macos.yml
rename to ci/azure/posix.yml
index 98409576a5a87..374a82a5ed7d0 100644
--- a/ci/azure/macos.yml
+++ b/ci/azure/posix.yml
@@ -7,12 +7,30 @@ jobs:
   pool:
     vmImage: ${{ parameters.vmImage }}
   strategy:
-    maxParallel: 11
     matrix:
-      py35_np_120:
-        ENV_FILE: ci/deps/azure-macos-35.yaml
-        CONDA_PY: "35"
-        PATTERN: "not slow and not network"
+      ${{ if eq(parameters.name, 'macOS') }}:
+        py35_np_120:
+          ENV_FILE: ci/deps/azure-macos-35.yaml
+          CONDA_PY: "35"
+          PATTERN: "not slow and not network"
+
+      ${{ if eq(parameters.name, 'Linux') }}:
+        py27_np_120:
+          ENV_FILE: ci/deps/azure-27-compat.yaml
+          CONDA_PY: "27"
+          PATTERN: "not slow and not network"
+
+        py37_locale:
+          ENV_FILE: ci/deps/azure-37-locale.yaml
+          CONDA_PY: "37"
+          PATTERN: "not slow and not network"
+          LOCALE_OVERRIDE: "zh_CN.UTF-8"
+
+        py36_locale_slow:
+          ENV_FILE: ci/deps/azure-36-locale_slow.yaml
+          CONDA_PY: "36"
+          PATTERN: "not slow and not network"
+          LOCALE_OVERRIDE: "it_IT.UTF-8"
 
   steps:
     - script: |
@@ -39,7 +57,7 @@ jobs:
     - task: PublishTestResults@2
       inputs:
         testResultsFiles: 'test-data-*.xml'
-        testRunTitle: 'MacOS-35'
+        testRunTitle: ${{ format('{0}-$(CONDA_PY)', parameters.name) }}
     - powershell: |
         $junitXml = "test-data-single.xml"
         $(Get-Content $junitXml | Out-String) -match 'failures="(.*?)"'
diff --git a/ci/azure/windows-py27.yml b/ci/azure/windows-py27.yml
deleted file mode 100644
index 0d9aea816c4ad..0000000000000
--- a/ci/azure/windows-py27.yml
+++ /dev/null
@@ -1,58 +0,0 @@
-parameters:
-  name: ''
-  vmImage: ''
-
-jobs:
-- job: ${{ parameters.name }}
-  pool:
-    vmImage: ${{ parameters.vmImage }}
-  strategy:
-    maxParallel: 11
-    matrix:
-      py36_np121:
-        ENV_FILE: ci/deps/azure-windows-27.yaml
-        CONDA_PY: "27"
-
-  steps:
-    - task: CondaEnvironment@1
-      inputs:
-        updateConda: no
-        packageSpecs: ''
-
-    # Need to install VC 9.0 only for Python 2.7
-    # Once we understand how to do tasks conditional on build matrix variables
-    # we could merge this into azure-windows.yml
-    - powershell: |
-        $wc = New-Object net.webclient
-        $wc.Downloadfile("https://download.microsoft.com/download/7/9/6/796EF2E4-801B-4FC4-AB28-B59FBF6D907B/VCForPython27.msi", "VCForPython27.msi")
-        Start-Process "VCForPython27.msi" /qn -Wait
-      displayName: 'Install VC 9.0'
-
-    - script: |
-        ci\\incremental\\setup_conda_environment.cmd
-      displayName: 'Before Install'
-    - script: |
-        call activate pandas-dev
-        ci\\incremental\\build.cmd
-      displayName: 'Build'
-    - script: |
-        call activate pandas-dev
-        pytest -m "not slow and not network" --junitxml=test-data.xml pandas -n 2 -r sxX --strict --durations=10 %*
-      displayName: 'Test'
-    - task: PublishTestResults@2
-      inputs:
-        testResultsFiles: 'test-data.xml'
-        testRunTitle: 'Windows 27'
-    - powershell: |
-        $junitXml = "test-data.xml"
-        $(Get-Content $junitXml | Out-String) -match 'failures="(.*?)"'
-        if ($matches[1] -eq 0)
-        {
-          Write-Host "No test failures in test-data"
-        }
-        else
-        {
-          # note that this will produce $LASTEXITCODE=1
-          Write-Error "$($matches[1]) tests failed"
-        }
-      displayName: Check for test failures
diff --git a/ci/azure/windows.yml b/ci/azure/windows.yml
index b69c210ca27ba..cece002024936 100644
--- a/ci/azure/windows.yml
+++ b/ci/azure/windows.yml
@@ -7,18 +7,28 @@ jobs:
   pool:
     vmImage: ${{ parameters.vmImage }}
   strategy:
-    maxParallel: 11
     matrix:
       py36_np14:
         ENV_FILE: ci/deps/azure-windows-36.yaml
         CONDA_PY: "36"
 
+      py27_np121:
+        ENV_FILE: ci/deps/azure-windows-27.yaml
+        CONDA_PY: "27"
+
   steps:
     - task: CondaEnvironment@1
       inputs:
         updateConda: no
         packageSpecs: ''
 
+    - powershell: |
+        $wc = New-Object net.webclient
+        $wc.Downloadfile("https://download.microsoft.com/download/7/9/6/796EF2E4-801B-4FC4-AB28-B59FBF6D907B/VCForPython27.msi", "VCForPython27.msi")
+        Start-Process "VCForPython27.msi" /qn -Wait
+      displayName: 'Install VC 9.0 only for Python 2.7'
+      condition: eq(variables.CONDA_PY, '27')
+
     - script: |
         ci\\incremental\\setup_conda_environment.cmd
       displayName: 'Before Install'
@@ -33,7 +43,7 @@ jobs:
     - task: PublishTestResults@2
       inputs:
         testResultsFiles: 'test-data.xml'
-        testRunTitle: 'Windows 36'
+        testRunTitle: 'Windows-$(CONDA_PY)'
     - powershell: |
         $junitXml = "test-data.xml"
         $(Get-Content $junitXml | Out-String) -match 'failures="(.*?)"'
diff --git a/doc/source/10min.rst b/doc/source/10min.rst
index 53618e008a403..a7557e6e1d1c2 100644
--- a/doc/source/10min.rst
+++ b/doc/source/10min.rst
@@ -51,7 +51,7 @@ Creating a ``DataFrame`` by passing a dict of objects that can be converted to s
                        'F': 'foo'})
    df2
 
-The columns of the resulting ``DataFrame`` have different 
+The columns of the resulting ``DataFrame`` have different
 :ref:`dtypes <basics.dtypes>`.
 
 .. ipython:: python
@@ -65,7 +65,7 @@ will be completed:
 .. ipython::
 
    @verbatim
-   In [1]: df2.<TAB>
+   In [1]: df2.<TAB>  # noqa: E225, E999
    df2.A                  df2.bool
    df2.abs                df2.boxplot
    df2.add                df2.C
@@ -495,7 +495,7 @@ Another example that can be given is:
 Append
 ~~~~~~
 
-Append rows to a dataframe. See the :ref:`Appending <merging.concatenation>` 
+Append rows to a dataframe. See the :ref:`Appending <merging.concatenation>`
 section.
 
 .. ipython:: python
@@ -528,14 +528,14 @@ See the :ref:`Grouping section <groupby>`.
                       'D': np.random.randn(8)})
    df
 
-Grouping and then applying the :meth:`~DataFrame.sum` function to the resulting 
+Grouping and then applying the :meth:`~DataFrame.sum` function to the resulting
 groups.
 
 .. ipython:: python
 
    df.groupby('A').sum()
 
-Grouping by multiple columns forms a hierarchical index, and again we can 
+Grouping by multiple columns forms a hierarchical index, and again we can
 apply the ``sum`` function.
 
 .. ipython:: python
@@ -671,7 +671,7 @@ Convert the raw grades to a categorical data type.
     df["grade"] = df["raw_grade"].astype("category")
     df["grade"]
 
-Rename the categories to more meaningful names (assigning to 
+Rename the categories to more meaningful names (assigning to
 ``Series.cat.categories`` is inplace!).
 
 .. ipython:: python
@@ -720,7 +720,7 @@ See the :ref:`Plotting <visualization>` docs.
    @savefig series_plot_basic.png
    ts.plot()
 
-On a DataFrame, the :meth:`~DataFrame.plot` method is a convenience to plot all 
+On a DataFrame, the :meth:`~DataFrame.plot` method is a convenience to plot all
 of the columns with labels:
 
 .. ipython:: python
diff --git a/doc/source/advanced.rst b/doc/source/advanced.rst
index 822bc7407a0c7..483921393f3ea 100644
--- a/doc/source/advanced.rst
+++ b/doc/source/advanced.rst
@@ -563,7 +563,8 @@ they need to be sorted. As with any index, you can use :meth:`~DataFrame.sort_in
 
 .. ipython:: python
 
-   import random; random.shuffle(tuples)
+   import random
+   random.shuffle(tuples)
    s = pd.Series(np.random.randn(8), index=pd.MultiIndex.from_tuples(tuples))
    s
    s.sort_index()
diff --git a/doc/source/api.rst b/doc/source/api.rst
index 49c89a53e7b17..bcef5567c23e5 100644
--- a/doc/source/api.rst
+++ b/doc/source/api.rst
@@ -1,6 +1,7 @@
-.. currentmodule:: pandas
 .. _api:
 
+{{ header }}
+
 *************
 API Reference
 *************
diff --git a/doc/source/categorical.rst b/doc/source/categorical.rst
index e57fd0ac0f96d..721e032b8bb92 100644
--- a/doc/source/categorical.rst
+++ b/doc/source/categorical.rst
@@ -782,7 +782,7 @@ Setting values by assigning categorical data will also check that the `categorie
     df
     try:
         df.loc["j":"k", "cats"] = pd.Categorical(["b", "b"],
-                                                  categories=["a", "b", "c"])
+                                                 categories=["a", "b", "c"])
     except ValueError as e:
         print("ValueError:", str(e))
 
diff --git a/doc/source/contributing_docstring.rst b/doc/source/contributing_docstring.rst
index 2f8ffc2e07c71..7c7847a47a1a2 100644
--- a/doc/source/contributing_docstring.rst
+++ b/doc/source/contributing_docstring.rst
@@ -1,13 +1,11 @@
 .. _docstring:
 
+{{ header }}
+
 ======================
 pandas docstring guide
 ======================
 
-.. note::
-  `Video tutorial: Pandas docstring guide
-  <https://www.youtube.com/watch?v=EOA0lUeW4NI>`_ by Frank Akogun.
-
 About docstrings and standards
 ------------------------------
 
diff --git a/doc/source/developer.rst b/doc/source/developer.rst
index ba6cec93d02e4..a283920ae4377 100644
--- a/doc/source/developer.rst
+++ b/doc/source/developer.rst
@@ -1,5 +1,7 @@
 .. _developer:
 
+{{ header }}
+
 .. currentmodule:: pandas
 
 *********
diff --git a/doc/source/dsintro.rst b/doc/source/dsintro.rst
index 8bdb0005de53c..d4a83b6807fd5 100644
--- a/doc/source/dsintro.rst
+++ b/doc/source/dsintro.rst
@@ -71,7 +71,7 @@ Series can be instantiated from dicts:
 
 .. ipython:: python
 
-   d = {'b' : 1, 'a' : 0, 'c' : 2}
+   d = {'b': 1, 'a': 0, 'c': 2}
    pd.Series(d)
 
 .. note::
@@ -92,7 +92,7 @@ index will be pulled out.
 
 .. ipython:: python
 
-   d = {'a' : 0., 'b' : 1., 'c' : 2.}
+   d = {'a': 0., 'b': 1., 'c': 2.}
    pd.Series(d)
    pd.Series(d, index=['b', 'c', 'd', 'a'])
 
@@ -304,8 +304,8 @@ keys.
 
 .. ipython:: python
 
-    d = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
-         'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}
+    d = {'one': pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
+         'two': pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}
     df = pd.DataFrame(d)
     df
 
@@ -334,8 +334,8 @@ result will be ``range(n)``, where ``n`` is the array length.
 
 .. ipython:: python
 
-   d = {'one' : [1., 2., 3., 4.],
-        'two' : [4., 3., 2., 1.]}
+   d = {'one': [1., 2., 3., 4.],
+        'two': [4., 3., 2., 1.]}
    pd.DataFrame(d)
    pd.DataFrame(d, index=['a', 'b', 'c', 'd'])
 
@@ -346,8 +346,8 @@ This case is handled identically to a dict of arrays.
 
 .. ipython:: python
 
-   data = np.zeros((2,), dtype=[('A', 'i4'),('B', 'f4'),('C', 'a10')])
-   data[:] = [(1,2.,'Hello'), (2,3.,"World")]
+   data = np.zeros((2, ), dtype=[('A', 'i4'), ('B', 'f4'), ('C', 'a10')])
+   data[:] = [(1, 2., 'Hello'), (2, 3., "World")]
 
    pd.DataFrame(data)
    pd.DataFrame(data, index=['first', 'second'])
@@ -507,8 +507,7 @@ derived from existing columns.
 
    iris = pd.read_csv('data/iris.data')
    iris.head()
-
-   (iris.assign(sepal_ratio = iris['SepalWidth'] / iris['SepalLength'])
+   (iris.assign(sepal_ratio=iris['SepalWidth'] / iris['SepalLength'])
         .head())
 
 In the example above, we inserted a precomputed value. We can also pass in
@@ -516,8 +515,7 @@ a function of one argument to be evaluated on the DataFrame being assigned to.
 
 .. ipython:: python
 
-   iris.assign(sepal_ratio = lambda x: (x['SepalWidth'] /
-                                        x['SepalLength'])).head()
+   iris.assign(sepal_ratio=lambda x: (x['SepalWidth'] / x['SepalLength'])).head()
 
 ``assign`` **always** returns a copy of the data, leaving the original
 DataFrame untouched.
@@ -532,8 +530,8 @@ greater than 5, calculate the ratio, and plot:
 
    @savefig basics_assign.png
    (iris.query('SepalLength > 5')
-        .assign(SepalRatio = lambda x: x.SepalWidth / x.SepalLength,
-                PetalRatio = lambda x: x.PetalWidth / x.PetalLength)
+        .assign(SepalRatio=lambda x: x.SepalWidth / x.SepalLength,
+                PetalRatio=lambda x: x.PetalWidth / x.PetalLength)
         .plot(kind='scatter', x='SepalRatio', y='PetalRatio'))
 
 Since a function is passed in, the function is computed on the DataFrame
@@ -705,8 +703,8 @@ Boolean operators work as well:
 
 .. ipython:: python
 
-   df1 = pd.DataFrame({'a' : [1, 0, 1], 'b' : [0, 1, 1] }, dtype=bool)
-   df2 = pd.DataFrame({'a' : [0, 1, 1], 'b' : [1, 1, 0] }, dtype=bool)
+   df1 = pd.DataFrame({'a': [1, 0, 1], 'b': [0, 1, 1]}, dtype=bool)
+   df2 = pd.DataFrame({'a': [0, 1, 1], 'b': [1, 1, 0]}, dtype=bool)
    df1 & df2
    df1 | df2
    df1 ^ df2
@@ -746,7 +744,7 @@ Similarly, the dot method on Series implements dot product:
 
 .. ipython:: python
 
-   s1 = pd.Series(np.arange(5,10))
+   s1 = pd.Series(np.arange(5, 10))
    s1.dot(s1)
 
 DataFrame is not intended to be a drop-in replacement for ndarray as its
@@ -777,7 +775,7 @@ R package):
    :okwarning:
 
    # restore GlobalPrintConfig
-   pd.reset_option('^display\.')
+   pd.reset_option(r'^display\.')
 
 However, using ``to_string`` will return a string representation of the
 DataFrame in tabular form, though it won't always fit the console width:
@@ -798,7 +796,7 @@ option:
 
 .. ipython:: python
 
-   pd.set_option('display.width', 40) # default is 80
+   pd.set_option('display.width', 40)  # default is 80
 
    pd.DataFrame(np.random.randn(3, 12))
 
@@ -806,14 +804,14 @@ You can adjust the max width of the individual columns by setting ``display.max_
 
 .. ipython:: python
 
-   datafile={'filename': ['filename_01','filename_02'],
-             'path': ["media/user_name/storage/folder_01/filename_01",
-                      "media/user_name/storage/folder_02/filename_02"]}
+   datafile = {'filename': ['filename_01', 'filename_02'],
+               'path': ["media/user_name/storage/folder_01/filename_01",
+                        "media/user_name/storage/folder_02/filename_02"]}
 
-   pd.set_option('display.max_colwidth',30)
+   pd.set_option('display.max_colwidth', 30)
    pd.DataFrame(datafile)
 
-   pd.set_option('display.max_colwidth',100)
+   pd.set_option('display.max_colwidth', 100)
    pd.DataFrame(datafile)
 
 .. ipython:: python
@@ -833,8 +831,8 @@ accessed like an attribute:
 
 .. ipython:: python
 
-   df = pd.DataFrame({'foo1' : np.random.randn(5),
-                      'foo2' : np.random.randn(5)})
+   df = pd.DataFrame({'foo1': np.random.randn(5),
+                      'foo2': np.random.randn(5)})
    df
    df.foo1
 
@@ -843,7 +841,7 @@ completion mechanism so they can be tab-completed:
 
 .. code-block:: ipython
 
-    In [5]: df.fo<TAB>
+    In [5]: df.fo<TAB>  # noqa: E225, E999
     df.foo1  df.foo2
 
 .. _basics.panel:
@@ -890,8 +888,8 @@ From dict of DataFrame objects
 .. ipython:: python
    :okwarning:
 
-   data = {'Item1' : pd.DataFrame(np.random.randn(4, 3)),
-           'Item2' : pd.DataFrame(np.random.randn(4, 2))}
+   data = {'Item1': pd.DataFrame(np.random.randn(4, 3)),
+           'Item2': pd.DataFrame(np.random.randn(4, 2))}
    pd.Panel(data)
 
 Note that the values in the dict need only be **convertible to
@@ -947,8 +945,9 @@ From DataFrame using ``to_panel`` method
 .. ipython:: python
    :okwarning:
 
-   midx = pd.MultiIndex(levels=[['one', 'two'], ['x','y']], codes=[[1,1,0,0],[1,0,1,0]])
-   df = pd.DataFrame({'A' : [1, 2, 3, 4], 'B': [5, 6, 7, 8]}, index=midx)
+   midx = pd.MultiIndex(levels=[['one', 'two'], ['x', 'y']],
+                        codes=[[1, 1, 0, 0], [1, 0, 1, 0]])
+   df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8]}, index=midx)
    df.to_panel()
 
 .. _dsintro.panel_item_selection:
diff --git a/doc/source/ecosystem.rst b/doc/source/ecosystem.rst
index ad389bbe35b71..e0c47e2f2ba7e 100644
--- a/doc/source/ecosystem.rst
+++ b/doc/source/ecosystem.rst
@@ -1,5 +1,7 @@
 .. _ecosystem:
 
+{{ header }}
+
 ****************
 pandas Ecosystem
 ****************
diff --git a/doc/source/enhancingperf.rst b/doc/source/enhancingperf.rst
index c0546d653d532..429ff91d88e41 100644
--- a/doc/source/enhancingperf.rst
+++ b/doc/source/enhancingperf.rst
@@ -469,7 +469,7 @@ These operations are supported by :func:`pandas.eval`:
 * Simple variable evaluation, e.g., ``pd.eval('df')`` (this is not very useful)
 * Math functions: `sin`, `cos`, `exp`, `log`, `expm1`, `log1p`,
   `sqrt`, `sinh`, `cosh`, `tanh`, `arcsin`, `arccos`, `arctan`, `arccosh`,
-  `arcsinh`, `arctanh`, `abs` and `arctan2`.
+  `arcsinh`, `arctanh`, `abs`, `arctan2` and `log10`.
 
 This Python syntax is **not** allowed:
 
diff --git a/doc/source/extending.rst b/doc/source/extending.rst
index 7046981a3a364..35d0dab7c3a77 100644
--- a/doc/source/extending.rst
+++ b/doc/source/extending.rst
@@ -1,5 +1,7 @@
 .. _extending:
 
+{{ header }}
+
 ****************
 Extending Pandas
 ****************
@@ -160,6 +162,8 @@ your ``MyExtensionArray`` class, as follows:
 
 .. code-block:: python
 
+    from pandas.core.arrays import ExtensionArray, ExtensionScalarOpsMixin
+
     class MyExtensionArray(ExtensionArray, ExtensionScalarOpsMixin):
         pass
 
@@ -269,7 +273,7 @@ Below example shows how to define ``SubclassedSeries`` and ``SubclassedDataFrame
 
 .. code-block:: python
 
-   class SubclassedSeries(Series):
+   class SubclassedSeries(pd.Series):
 
        @property
        def _constructor(self):
@@ -280,7 +284,7 @@ Below example shows how to define ``SubclassedSeries`` and ``SubclassedDataFrame
            return SubclassedDataFrame
 
 
-   class SubclassedDataFrame(DataFrame):
+   class SubclassedDataFrame(pd.DataFrame):
 
        @property
        def _constructor(self):
@@ -342,7 +346,7 @@ Below is an example to define two original properties, "internal_cache" as a tem
 
 .. code-block:: python
 
-   class SubclassedDataFrame2(DataFrame):
+   class SubclassedDataFrame2(pd.DataFrame):
 
        # temporary properties
        _internal_names = pd.DataFrame._internal_names + ['internal_cache']
diff --git a/doc/source/merging.rst b/doc/source/merging.rst
index af767d7687749..6f7ee4917f494 100644
--- a/doc/source/merging.rst
+++ b/doc/source/merging.rst
@@ -5,6 +5,7 @@
 .. ipython:: python
    :suppress:
 
+   from matplotlib import pyplot as plt
    import pandas.util._doctools as doctools
    p = doctools.TablePlotter()
 
@@ -38,19 +39,19 @@ a simple example:
                        'B': ['B0', 'B1', 'B2', 'B3'],
                        'C': ['C0', 'C1', 'C2', 'C3'],
                        'D': ['D0', 'D1', 'D2', 'D3']},
-                       index=[0, 1, 2, 3])
+                      index=[0, 1, 2, 3])
 
    df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
                        'B': ['B4', 'B5', 'B6', 'B7'],
                        'C': ['C4', 'C5', 'C6', 'C7'],
                        'D': ['D4', 'D5', 'D6', 'D7']},
-                        index=[4, 5, 6, 7])
+                      index=[4, 5, 6, 7])
 
    df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
                        'B': ['B8', 'B9', 'B10', 'B11'],
                        'C': ['C8', 'C9', 'C10', 'C11'],
                        'D': ['D8', 'D9', 'D10', 'D11']},
-                       index=[8, 9, 10, 11])
+                      index=[8, 9, 10, 11])
 
    frames = [df1, df2, df3]
    result = pd.concat(frames)
@@ -379,7 +380,7 @@ Through the ``keys`` argument we can override the existing column names.
 
 .. ipython:: python
 
-   pd.concat([s3, s4, s5], axis=1, keys=['red','blue','yellow'])
+   pd.concat([s3, s4, s5], axis=1, keys=['red', 'blue', 'yellow'])
 
 Let's consider a variation of the very first example presented:
 
@@ -436,8 +437,8 @@ do so using the ``levels`` argument:
 .. ipython:: python
 
    result = pd.concat(pieces, keys=['x', 'y', 'z'],
-                   levels=[['z', 'y', 'x', 'w']],
-                   names=['group_key'])
+                      levels=[['z', 'y', 'x', 'w']],
+                      names=['group_key'])
 
 .. ipython:: python
    :suppress:
@@ -725,9 +726,9 @@ Here is another example with duplicate join keys in DataFrames:
 
 .. ipython:: python
 
-   left = pd.DataFrame({'A' : [1,2], 'B' : [2, 2]})
+   left = pd.DataFrame({'A': [1, 2], 'B': [2, 2]})
 
-   right = pd.DataFrame({'A' : [4,5,6], 'B': [2,2,2]})
+   right = pd.DataFrame({'A': [4, 5, 6], 'B': [2, 2, 2]})
 
    result = pd.merge(left, right, on='B', how='outer')
 
@@ -800,8 +801,8 @@ that takes on values:
 
 .. ipython:: python
 
-   df1 = pd.DataFrame({'col1': [0, 1], 'col_left':['a', 'b']})
-   df2 = pd.DataFrame({'col1': [1, 2, 2],'col_right':[2, 2, 2]})
+   df1 = pd.DataFrame({'col1': [0, 1], 'col_left': ['a', 'b']})
+   df2 = pd.DataFrame({'col1': [1, 2, 2], 'col_right': [2, 2, 2]})
    pd.merge(df1, df2, on='col1', how='outer', indicator=True)
 
 The ``indicator`` argument will also accept string arguments, in which case the indicator function will use the value of the passed string as the name for the indicator column.
@@ -856,7 +857,8 @@ The left frame.
    X = X.astype(CategoricalDtype(categories=['foo', 'bar']))
 
    left = pd.DataFrame({'X': X,
-                        'Y': np.random.choice(['one', 'two', 'three'], size=(10,))})
+                        'Y': np.random.choice(['one', 'two', 'three'],
+                                              size=(10,))})
    left
    left.dtypes
 
@@ -864,11 +866,9 @@ The right frame.
 
 .. ipython:: python
 
-   right = pd.DataFrame({
-        'X': pd.Series(['foo', 'bar'],
-                       dtype=CategoricalDtype(['foo', 'bar'])),
-        'Z': [1, 2]
-   })
+   right = pd.DataFrame({'X': pd.Series(['foo', 'bar'],
+                                        dtype=CategoricalDtype(['foo', 'bar'])),
+                        'Z': [1, 2]})
    right
    right.dtypes
 
@@ -902,11 +902,11 @@ potentially differently-indexed ``DataFrames`` into a single result
 
    left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
                         'B': ['B0', 'B1', 'B2']},
-                        index=['K0', 'K1', 'K2'])
+                       index=['K0', 'K1', 'K2'])
 
    right = pd.DataFrame({'C': ['C0', 'C2', 'C3'],
                          'D': ['D0', 'D2', 'D3']},
-                         index=['K0', 'K2', 'K3'])
+                        index=['K0', 'K2', 'K3'])
 
    result = left.join(right)
 
@@ -998,7 +998,7 @@ join key), using ``join`` may be more convenient. Here is a simple example:
 
    right = pd.DataFrame({'C': ['C0', 'C1'],
                          'D': ['D0', 'D1']},
-                         index=['K0', 'K1'])
+                        index=['K0', 'K1'])
 
    result = left.join(right, on='key')
 
@@ -1037,8 +1037,8 @@ To join on multiple keys, the passed DataFrame must have a ``MultiIndex``:
    index = pd.MultiIndex.from_tuples([('K0', 'K0'), ('K1', 'K0'),
                                      ('K2', 'K0'), ('K2', 'K1')])
    right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
-                      'D': ['D0', 'D1', 'D2', 'D3']},
-                     index=index)
+                         'D': ['D0', 'D1', 'D2', 'D3']},
+                        index=index)
 
 Now this can be joined by passing the two key column names:
 
@@ -1133,12 +1133,12 @@ the left argument, as in this example:
 
    leftindex = pd.MultiIndex.from_product([list('abc'), list('xy'), [1, 2]],
                                           names=['abc', 'xy', 'num'])
-   left = pd.DataFrame({'v1' : range(12)}, index=leftindex)
+   left = pd.DataFrame({'v1': range(12)}, index=leftindex)
    left
 
    rightindex = pd.MultiIndex.from_product([list('abc'), list('xy')],
                                            names=['abc', 'xy'])
-   right = pd.DataFrame({'v2': [100*i for i in range(1, 7)]}, index=rightindex)
+   right = pd.DataFrame({'v2': [100 * i for i in range(1, 7)]}, index=rightindex)
    right
 
    left.join(right, on=['abc', 'xy'], how='inner')
@@ -1153,17 +1153,17 @@ done using the following code.
                                          names=['key', 'X'])
    left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
                         'B': ['B0', 'B1', 'B2']},
-                        index=leftindex)
+                       index=leftindex)
 
    rightindex = pd.MultiIndex.from_tuples([('K0', 'Y0'), ('K1', 'Y1'),
                                            ('K2', 'Y2'), ('K2', 'Y3')],
                                           names=['key', 'Y'])
    right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
                          'D': ['D0', 'D1', 'D2', 'D3']},
-                         index=rightindex)
+                        index=rightindex)
 
    result = pd.merge(left.reset_index(), right.reset_index(),
-                     on=['key'], how='inner').set_index(['key','X','Y'])
+                     on=['key'], how='inner').set_index(['key', 'X', 'Y'])
 
 .. ipython:: python
    :suppress:
diff --git a/doc/source/options.rst b/doc/source/options.rst
index dc4d0da32008c..31359c337fdb8 100644
--- a/doc/source/options.rst
+++ b/doc/source/options.rst
@@ -1,13 +1,6 @@
 .. _options:
 
-.. currentmodule:: pandas
-
-.. ipython:: python
-   :suppress:
-
-   import pandas as pd
-   import numpy as np
-   np.random.seed(123456)
+{{ header }}
 
 ********************
 Options and Settings
diff --git a/doc/source/overview.rst b/doc/source/overview.rst
index b71f4bfa2f3be..351cc09c07cab 100644
--- a/doc/source/overview.rst
+++ b/doc/source/overview.rst
@@ -1,6 +1,6 @@
 .. _overview:
 
-.. currentmodule:: pandas
+{{ header }}
 
 ****************
 Package overview
diff --git a/doc/source/r_interface.rst b/doc/source/r_interface.rst
index 4ec43a64cf98a..9839bba4884d4 100644
--- a/doc/source/r_interface.rst
+++ b/doc/source/r_interface.rst
@@ -2,7 +2,6 @@
 
 {{ header }}
 
-
 ******************
 rpy2 / R interface
 ******************
diff --git a/doc/source/releases.rst b/doc/source/releases.rst
index 0167903cce8bc..491569c69115b 100644
--- a/doc/source/releases.rst
+++ b/doc/source/releases.rst
@@ -1,5 +1,7 @@
 .. _release:
 
+{{ header }}
+
 *************
 Release Notes
 *************
diff --git a/doc/source/reshaping.rst b/doc/source/reshaping.rst
index 059e6eb2138f3..d9fbb52f2e56a 100644
--- a/doc/source/reshaping.rst
+++ b/doc/source/reshaping.rst
@@ -18,12 +18,12 @@ Reshaping by pivoting DataFrame objects
    tm.N = 3
 
    def unpivot(frame):
-      N, K = frame.shape
-      data = {'value': frame.to_numpy().ravel('F'),
-              'variable': np.asarray(frame.columns).repeat(N),
-              'date': np.tile(np.asarray(frame.index), K)}
-      columns = ['date', 'variable', 'value']
-      return pd.DataFrame(data, columns=columns)
+       N, K = frame.shape
+       data = {'value': frame.to_numpy().ravel('F'),
+               'variable': np.asarray(frame.columns).repeat(N),
+               'date': np.tile(np.asarray(frame.index), K)}
+       columns = ['date', 'variable', 'value']
+       return pd.DataFrame(data, columns=columns)
 
    df = unpivot(tm.makeTimeDataFrame())
 
@@ -371,8 +371,8 @@ Consider a data set like this:
                       'C': ['foo', 'foo', 'foo', 'bar', 'bar', 'bar'] * 4,
                       'D': np.random.randn(24),
                       'E': np.random.randn(24),
-                      'F': [datetime.datetime(2013, i, 1) for i in range(1, 13)] +
-                           [datetime.datetime(2013, i, 15) for i in range(1, 13)]})
+                      'F': [datetime.datetime(2013, i, 1) for i in range(1, 13)]
+                      + [datetime.datetime(2013, i, 15) for i in range(1, 13)]})
    df
 
 We can produce pivot tables from this data very easily:
@@ -397,7 +397,8 @@ Also, you can use ``Grouper`` for ``index`` and ``columns`` keywords. For detail
 
 .. ipython:: python
 
-   pd.pivot_table(df, values='D', index=pd.Grouper(freq='M', key='F'), columns='C')
+   pd.pivot_table(df, values='D', index=pd.Grouper(freq='M', key='F'),
+                  columns='C')
 
 You can render a nice output of the table omitting the missing values by
 calling ``to_string`` if you wish:
@@ -693,6 +694,7 @@ handling of NaN:
 
 .. code-block:: ipython
 
+    In [1]: x = pd.Series(['A', 'A', np.nan, 'B', 3.14, np.inf])
     In [2]: pd.factorize(x, sort=True)
     Out[2]:
     (array([ 2,  2, -1,  3,  0,  1]),
@@ -721,7 +723,8 @@ DataFrame will be pivoted in the answers below.
    n = 20
 
    cols = np.array(['key', 'row', 'item', 'col'])
-   df = cols + pd.DataFrame((np.random.randint(5, size=(n, 4)) // [2, 1, 2, 1]).astype(str))
+   df = cols + pd.DataFrame((np.random.randint(5, size=(n, 4))
+                            // [2, 1, 2, 1]).astype(str))
    df.columns = cols
    df = df.join(pd.DataFrame(np.random.rand(n, 2).round(2)).add_prefix('val'))
 
@@ -734,7 +737,7 @@ Suppose we wanted to pivot ``df`` such that the ``col`` values are columns,
 ``row`` values are the index, and the mean of ``val0`` are the values? In
 particular, the resulting DataFrame should look like:
 
-.. code-block:: ipython
+.. note::
 
    col   col0   col1   col2   col3  col4
    row
diff --git a/doc/source/tutorials.rst b/doc/source/tutorials.rst
index d5da7df347573..c07319fff777b 100644
--- a/doc/source/tutorials.rst
+++ b/doc/source/tutorials.rst
@@ -1,5 +1,7 @@
 .. _tutorials:
 
+{{ header }}
+
 *********
 Tutorials
 *********
diff --git a/doc/source/visualization.rst b/doc/source/visualization.rst
index ce3c335b431ad..23207a0e11a65 100644
--- a/doc/source/visualization.rst
+++ b/doc/source/visualization.rst
@@ -26,7 +26,7 @@ libraries that go beyond the basics documented here.
 Basic Plotting: ``plot``
 ------------------------
 
-We will demonstrate the basics, see the :ref:`cookbook<cookbook.plotting>` for 
+We will demonstrate the basics, see the :ref:`cookbook<cookbook.plotting>` for
 some advanced strategies.
 
 The ``plot`` method on Series and DataFrame is just a simple wrapper around
@@ -87,7 +87,7 @@ You can plot one column versus another using the `x` and `y` keywords in
 
 .. note::
 
-   For more formatting and styling options, see 
+   For more formatting and styling options, see
    :ref:`formatting <visualization.formatting>` below.
 
 .. ipython:: python
@@ -129,7 +129,7 @@ You can also create these other plots using the methods ``DataFrame.plot.<kind>`
 
     In [14]: df = pd.DataFrame()
 
-    In [15]: df.plot.<TAB>
+    In [15]: df.plot.<TAB>  # noqa: E225, E999
     df.plot.area     df.plot.barh     df.plot.density  df.plot.hist     df.plot.line     df.plot.scatter
     df.plot.bar      df.plot.box      df.plot.hexbin   df.plot.kde      df.plot.pie
 
@@ -163,7 +163,8 @@ For labeled, non-time series data, you may wish to produce a bar plot:
    plt.figure();
 
    @savefig bar_plot_ex.png
-   df.iloc[5].plot.bar(); plt.axhline(0, color='k')
+   df.iloc[5].plot.bar()
+   plt.axhline(0, color='k');
 
 Calling a DataFrame's :meth:`plot.bar() <DataFrame.plot.bar>` method produces a multiple
 bar plot:
@@ -231,7 +232,7 @@ Histograms can be drawn by using the :meth:`DataFrame.plot.hist` and :meth:`Seri
 
    plt.close('all')
 
-A histogram can be stacked using ``stacked=True``. Bin size can be changed 
+A histogram can be stacked using ``stacked=True``. Bin size can be changed
 using the ``bins`` keyword.
 
 .. ipython:: python
@@ -246,8 +247,8 @@ using the ``bins`` keyword.
 
    plt.close('all')
 
-You can pass other keywords supported by matplotlib ``hist``. For example, 
-horizontal and cumulative histograms can be drawn by 
+You can pass other keywords supported by matplotlib ``hist``. For example,
+horizontal and cumulative histograms can be drawn by
 ``orientation='horizontal'`` and ``cumulative=True``.
 
 .. ipython:: python
@@ -477,7 +478,7 @@ keyword, will affect the output type as well:
 
    plt.close('all')
 
-The subplots above are split by the numeric columns first, then the value of 
+The subplots above are split by the numeric columns first, then the value of
 the ``g`` column. Below the subplots are first split by the value of ``g``,
 then by the numeric columns.
 
@@ -579,8 +580,8 @@ each point:
 
    plt.close('all')
 
-You can pass other keywords supported by matplotlib 
-:meth:`scatter <matplotlib.axes.Axes.scatter>`. The example  below shows a 
+You can pass other keywords supported by matplotlib
+:meth:`scatter <matplotlib.axes.Axes.scatter>`. The example  below shows a
 bubble chart using a column of the ``DataFrame`` as the bubble size.
 
 .. ipython:: python
@@ -684,15 +685,15 @@ A ``ValueError`` will be raised if there are any negative values in your data.
 
    plt.close('all')
 
-For pie plots it's best to use square figures, i.e. a figure aspect ratio 1. 
-You can create the figure with equal width and height, or force the aspect ratio 
-to be equal after plotting by calling ``ax.set_aspect('equal')`` on the returned 
+For pie plots it's best to use square figures, i.e. a figure aspect ratio 1.
+You can create the figure with equal width and height, or force the aspect ratio
+to be equal after plotting by calling ``ax.set_aspect('equal')`` on the returned
 ``axes`` object.
 
-Note that pie plot with :class:`DataFrame` requires that you either specify a 
-target column by the ``y`` argument or ``subplots=True``. When ``y`` is 
-specified, pie plot of selected column will be drawn. If ``subplots=True`` is 
-specified, pie plots for each column are drawn as subplots. A legend will be 
+Note that pie plot with :class:`DataFrame` requires that you either specify a
+target column by the ``y`` argument or ``subplots=True``. When ``y`` is
+specified, pie plot of selected column will be drawn. If ``subplots=True`` is
+specified, pie plots for each column are drawn as subplots. A legend will be
 drawn in each pie plots by default; specify ``legend=False`` to hide it.
 
 .. ipython:: python
@@ -918,7 +919,7 @@ Lag Plot
 Lag plots are used to check if a data set or time series is random. Random
 data should not exhibit any structure in the lag plot. Non-random structure
 implies that the underlying data are not random. The ``lag`` argument may
-be passed, and when ``lag=1`` the plot is essentially ``data[:-1]`` vs. 
+be passed, and when ``lag=1`` the plot is essentially ``data[:-1]`` vs.
 ``data[1:]``.
 
 .. ipython:: python
@@ -954,7 +955,7 @@ If time series is random, such autocorrelations should be near zero for any and
 all time-lag separations. If time series is non-random then one or more of the
 autocorrelations will be significantly non-zero. The horizontal lines displayed
 in the plot correspond to 95% and 99% confidence bands. The dashed line is 99%
-confidence band. See the 
+confidence band. See the
 `Wikipedia entry <https://en.wikipedia.org/wiki/Correlogram>`__ for more about
 autocorrelation plots.
 
@@ -1446,9 +1447,9 @@ Plotting with matplotlib table is now supported in  :meth:`DataFrame.plot` and :
 
    plt.close('all')
 
-Also, you can pass a different :class:`DataFrame` or :class:`Series` to the 
-``table`` keyword. The data will be drawn as displayed in print method 
-(not transposed automatically). If required, it should be transposed manually 
+Also, you can pass a different :class:`DataFrame` or :class:`Series` to the
+``table`` keyword. The data will be drawn as displayed in print method
+(not transposed automatically). If required, it should be transposed manually
 as seen in the example below.
 
 .. ipython:: python
@@ -1463,9 +1464,9 @@ as seen in the example below.
 
    plt.close('all')
 
-There also exists a helper function ``pandas.plotting.table``, which creates a 
-table from :class:`DataFrame` or :class:`Series`, and adds it to an 
-``matplotlib.Axes`` instance. This function can accept keywords which the 
+There also exists a helper function ``pandas.plotting.table``, which creates a
+table from :class:`DataFrame` or :class:`Series`, and adds it to an
+``matplotlib.Axes`` instance. This function can accept keywords which the
 matplotlib `table <http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.table>`__ has.
 
 .. ipython:: python
@@ -1597,8 +1598,8 @@ Plotting directly with matplotlib
 
 In some situations it may still be preferable or necessary to prepare plots
 directly with matplotlib, for instance when a certain type of plot or
-customization is not (yet) supported by pandas. ``Series`` and ``DataFrame`` 
-objects behave like arrays and can therefore be passed directly to 
+customization is not (yet) supported by pandas. ``Series`` and ``DataFrame``
+objects behave like arrays and can therefore be passed directly to
 matplotlib functions without explicit casts.
 
 pandas also automatically registers formatters and locators that recognize date
diff --git a/doc/source/whatsnew/v0.22.0.rst b/doc/source/whatsnew/v0.22.0.rst
index 1fb87c9f5433f..b38fcd9d62af4 100644
--- a/doc/source/whatsnew/v0.22.0.rst
+++ b/doc/source/whatsnew/v0.22.0.rst
@@ -137,8 +137,8 @@ sum and ``1`` for product.
 .. code-block:: ipython
 
    In [11]: s = pd.Series([1, 1, np.nan, np.nan],
-      ...:                index=pd.date_range('2017', periods=4))
-      ...:  s
+      ....:               index=pd.date_range('2017', periods=4))
+      ....: s
    Out[11]:
    2017-01-01    1.0
    2017-01-02    1.0
diff --git a/doc/source/whatsnew/v0.23.0.rst b/doc/source/whatsnew/v0.23.0.rst
index d8eb337fd27d2..e52a36a922bd9 100644
--- a/doc/source/whatsnew/v0.23.0.rst
+++ b/doc/source/whatsnew/v0.23.0.rst
@@ -53,10 +53,10 @@ A ``DataFrame`` can now be written to and subsequently read back via JSON while
 .. ipython:: python
 
    df = pd.DataFrame({'foo': [1, 2, 3, 4],
-		      'bar': ['a', 'b', 'c', 'd'],
-		      'baz': pd.date_range('2018-01-01', freq='d', periods=4),
-		      'qux': pd.Categorical(['a', 'b', 'c', 'c'])
-		      }, index=pd.Index(range(4), name='idx'))
+                      'bar': ['a', 'b', 'c', 'd'],
+                      'baz': pd.date_range('2018-01-01', freq='d', periods=4),
+                      'qux': pd.Categorical(['a', 'b', 'c', 'c'])},
+                     index=pd.Index(range(4), name='idx'))
    df
    df.dtypes
    df.to_json('test.json', orient='table')
@@ -97,7 +97,7 @@ The :func:`DataFrame.assign` now accepts dependent keyword arguments for python
 
     df = pd.DataFrame({'A': [1, 2, 3]})
     df
-    df.assign(B=df.A, C=lambda x:x['A']+ x['B'])
+    df.assign(B=df.A, C=lambda x: x['A'] + x['B'])
 
 .. warning::
 
@@ -122,7 +122,7 @@ The :func:`DataFrame.assign` now accepts dependent keyword arguments for python
 
   .. ipython:: python
 
-      df.assign(A=df.A+1, C= lambda df: df.A* -1)
+      df.assign(A=df.A + 1, C=lambda df: df.A * -1)
 
 
 
@@ -284,7 +284,7 @@ For pivotting operations, this behavior is *already* controlled by the ``dropna`
                          categories=["a", "b", "z"], ordered=True)
    cat2 = pd.Categorical(["c", "d", "c", "d"],
                          categories=["c", "d", "y"], ordered=True)
-   df = DataFrame({"A": cat1, "B": cat2, "values": [1, 2, 3, 4]})
+   df = pd.DataFrame({"A": cat1, "B": cat2, "values": [1, 2, 3, 4]})
    df
 
 .. ipython:: python
@@ -336,7 +336,8 @@ outside the existing valid values while preserving those inside.  (:issue:`16284
 
 .. ipython:: python
 
-   ser = pd.Series([np.nan, np.nan, 5, np.nan, np.nan, np.nan, 13, np.nan, np.nan])
+   ser = pd.Series([np.nan, np.nan, 5, np.nan, np.nan,
+                    np.nan, 13, np.nan, np.nan])
    ser
 
 Fill one consecutive inside value in both directions
@@ -600,15 +601,16 @@ Previous Behavior (and current behavior if on Python < 3.6):
 
 .. code-block:: ipython
 
-   pd.Series({'Income': 2000,
-              'Expenses': -1500,
-              'Taxes': -200,
-              'Net result': 300})
-   Expenses     -1500
-   Income        2000
-   Net result     300
-   Taxes         -200
-   dtype: int64
+    In [16]: pd.Series({'Income': 2000,
+       ....:            'Expenses': -1500,
+       ....:            'Taxes': -200,
+       ....:            'Net result': 300})
+    Out[16]:
+    Expenses     -1500
+    Income        2000
+    Net result     300
+    Taxes         -200
+    dtype: int64
 
 Note the Series above is ordered alphabetically by the index values.
 
@@ -696,7 +698,8 @@ where a list-like (e.g. ``tuple`` or ``list`` is returned) (:issue:`16353`, :iss
 
 .. ipython:: python
 
-    df = pd.DataFrame(np.tile(np.arange(3), 6).reshape(6, -1) + 1, columns=['A', 'B', 'C'])
+    df = pd.DataFrame(np.tile(np.arange(3), 6).reshape(6, -1) + 1,
+                      columns=['A', 'B', 'C'])
     df
 
 Previous Behavior: if the returned shape happened to match the length of original columns, this would return a ``DataFrame``.
@@ -750,7 +753,7 @@ Returning a ``Series`` allows one to control the exact return structure and colu
 
 .. ipython:: python
 
-    df.apply(lambda x: Series([1, 2, 3], index=['D', 'E', 'F']), axis=1)
+    df.apply(lambda x: pd.Series([1, 2, 3], index=['D', 'E', 'F']), axis=1)
 
 .. _whatsnew_0230.api_breaking.concat:
 
@@ -825,10 +828,12 @@ Current Behavior:
 .. ipython:: python
 
     index = pd.Int64Index([-1, 0, 1])
-    # division by zero gives -infinity where negative, +infinity where positive, and NaN for 0 / 0
+    # division by zero gives -infinity where negative,
+    # +infinity where positive, and NaN for 0 / 0
     index / 0
 
-    # The result of division by zero should not depend on whether the zero is int or float
+    # The result of division by zero should not depend on
+    # whether the zero is int or float
     index / 0.0
 
     index = pd.UInt64Index([0, 1])
@@ -853,7 +858,7 @@ Previous Behavior:
 
     In [1]: s = pd.Series(['number 10', '12 eggs'])
 
-    In [2]: extracted = s.str.extract('.*(\d\d).*')
+    In [2]: extracted = s.str.extract(r'.*(\d\d).*')
 
     In [3]: extracted
     Out [3]:
@@ -870,7 +875,7 @@ New Behavior:
 .. ipython:: python
 
     s = pd.Series(['number 10', '12 eggs'])
-    extracted = s.str.extract('.*(\d\d).*')
+    extracted = s.str.extract(r'.*(\d\d).*')
     extracted
     type(extracted)
 
@@ -879,7 +884,7 @@ To restore previous behavior, simply set ``expand`` to ``False``:
 .. ipython:: python
 
     s = pd.Series(['number 10', '12 eggs'])
-    extracted = s.str.extract('.*(\d\d).*', expand=False)
+    extracted = s.str.extract(r'.*(\d\d).*', expand=False)
     extracted
     type(extracted)
 
diff --git a/doc/source/whatsnew/v0.23.1.rst b/doc/source/whatsnew/v0.23.1.rst
index f8bfced171a7c..f6af2990c935b 100644
--- a/doc/source/whatsnew/v0.23.1.rst
+++ b/doc/source/whatsnew/v0.23.1.rst
@@ -5,11 +5,6 @@ What's New in 0.23.1 (June 12, 2018)
 
 {{ header }}
 
-.. ipython:: python
-   :suppress:
-
-   from pandas import * # noqa F401, F403
-
 
 This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes
 and bug fixes. We recommend that all users upgrade to this version.
@@ -43,19 +38,20 @@ To summarize, here's the behavior in 0.22.0, 0.23.0, 0.23.1:
 .. code-block:: python
 
    # 0.22.0... Silently coerce the datetime.date
-   >>> Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
+   >>> import datetime
+   >>> pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
    0     True
    1    False
    dtype: bool
 
    # 0.23.0... Do not coerce the datetime.date
-   >>> Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
+   >>> pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
    0    False
    1    False
    dtype: bool
 
    # 0.23.1... Coerce the datetime.date with a warning
-   >>> Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
+   >>> pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1)
    /bin/python:1: FutureWarning: Comparing Series of datetimes with 'datetime.date'.  Currently, the
    'datetime.date' is coerced to a datetime. In the future pandas will
    not coerce, and the values not compare equal to the 'datetime.date'.
diff --git a/doc/source/whatsnew/v0.23.2.rst b/doc/source/whatsnew/v0.23.2.rst
index 9523724827722..cae2415e3374e 100644
--- a/doc/source/whatsnew/v0.23.2.rst
+++ b/doc/source/whatsnew/v0.23.2.rst
@@ -5,11 +5,6 @@ What's New in 0.23.2 (July 5, 2018)
 
 {{ header }}
 
-.. ipython:: python
-   :suppress:
-
-   from pandas import * # noqa F401, F403
-
 
 This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes
 and bug fixes. We recommend that all users upgrade to this version.
diff --git a/doc/source/whatsnew/v0.23.4.rst b/doc/source/whatsnew/v0.23.4.rst
index 75fb18a648d0a..01f904e129f80 100644
--- a/doc/source/whatsnew/v0.23.4.rst
+++ b/doc/source/whatsnew/v0.23.4.rst
@@ -5,11 +5,6 @@ What's New in 0.23.4 (August 3, 2018)
 
 {{ header }}
 
-.. ipython:: python
-   :suppress:
-
-   from pandas import * # noqa F401, F403
-
 
 This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes
 and bug fixes. We recommend that all users upgrade to this version.
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 4c78fcb76f4c6..4d0373e4571da 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -10,11 +10,6 @@ What's New in 0.24.0 (Month XX, 2018)
 
 {{ header }}
 
-.. ipython:: python
-   :suppress:
-
-   from pandas import * # noqa F401, F403
-
 
 These are the changes in pandas 0.24.0. See :ref:`release` for a full changelog
 including other versions of pandas.
@@ -252,7 +247,7 @@ convenient way to apply users' predefined styling functions, and can help reduce
 
 .. ipython:: python
 
-    df = pandas.DataFrame({'N': [1250, 1500, 1750], 'X': [0.25, 0.35, 0.50]})
+    df = pd.DataFrame({'N': [1250, 1500, 1750], 'X': [0.25, 0.35, 0.50]})
 
     def format_and_align(styler):
         return (styler.format({'N': '{:,}', 'X': '{:.1%}'})
@@ -282,8 +277,7 @@ See the :ref:`Merge, join, and concatenate
 
 
    left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
-                        'B': ['B0', 'B1', 'B2']},
-                         index=index_left)
+                        'B': ['B0', 'B1', 'B2']}, index=index_left)
 
 
    index_right = pd.MultiIndex.from_tuples([('K0', 'Y0'), ('K1', 'Y1'),
@@ -292,11 +286,9 @@ See the :ref:`Merge, join, and concatenate
 
 
    right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
-                         'D': ['D0', 'D1', 'D2', 'D3']},
-                        index=index_right)
+                         'D': ['D0', 'D1', 'D2', 'D3']}, index=index_right)
 
-
-    left.join(right)
+   left.join(right)
 
 For earlier versions this can be done using the following.
 
@@ -441,26 +433,26 @@ Previous Behavior on Windows:
 
 .. code-block:: ipython
 
-    In [1]: data = pd.DataFrame({
-    ...:     "string_with_lf": ["a\nbc"],
-    ...:     "string_with_crlf": ["a\r\nbc"]
-    ...: })
+    In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+       ...:                      "string_with_crlf": ["a\r\nbc"]})
 
-    In [2]: # When passing file PATH to to_csv, line_terminator does not work, and csv is saved with '\r\n'.
-    ...: # Also, this converts all '\n's in the data to '\r\n'.
-    ...: data.to_csv("test.csv", index=False, line_terminator='\n')
+    In [2]: # When passing file PATH to to_csv,
+       ...: # line_terminator does not work, and csv is saved with '\r\n'.
+       ...: # Also, this converts all '\n's in the data to '\r\n'.
+       ...: data.to_csv("test.csv", index=False, line_terminator='\n')
 
     In [3]: with open("test.csv", mode='rb') as f:
-    ...:     print(f.read())
-    b'string_with_lf,string_with_crlf\r\n"a\r\nbc","a\r\r\nbc"\r\n'
+       ...:     print(f.read())
+    Out[3]: b'string_with_lf,string_with_crlf\r\n"a\r\nbc","a\r\r\nbc"\r\n'
 
-    In [4]: # When passing file OBJECT with newline option to to_csv, line_terminator works.
-    ...: with open("test2.csv", mode='w', newline='\n') as f:
-    ...:     data.to_csv(f, index=False, line_terminator='\n')
+    In [4]: # When passing file OBJECT with newline option to
+       ...: # to_csv, line_terminator works.
+       ...: with open("test2.csv", mode='w', newline='\n') as f:
+       ...:     data.to_csv(f, index=False, line_terminator='\n')
 
     In [5]: with open("test2.csv", mode='rb') as f:
-    ...:     print(f.read())
-    b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
+       ...:     print(f.read())
+    Out[5]: b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
 
 
 New Behavior on Windows:
@@ -471,16 +463,14 @@ New Behavior on Windows:
 
   .. code-block:: ipython
 
-    In [1]: data = pd.DataFrame({
-    ...:     "string_with_lf": ["a\nbc"],
-    ...:     "string_with_crlf": ["a\r\nbc"]
-    ...: })
+    In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+       ...:                      "string_with_crlf": ["a\r\nbc"]})
 
     In [2]: data.to_csv("test.csv", index=False, line_terminator='\n')
 
     In [3]: with open("test.csv", mode='rb') as f:
-    ...:     print(f.read())
-    b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
+       ...:     print(f.read())
+    Out[3]: b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
 
 
 - On Windows, the value of ``os.linesep`` is ``'\r\n'``,
@@ -489,16 +479,14 @@ New Behavior on Windows:
 
   .. code-block:: ipython
 
-    In [1]: data = pd.DataFrame({
-    ...: "string_with_lf": ["a\nbc"],
-    ...: "string_with_crlf": ["a\r\nbc"]
-    ...: })
+    In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+       ...:                      "string_with_crlf": ["a\r\nbc"]})
 
     In [2]: data.to_csv("test.csv", index=False)
 
     In [3]: with open("test.csv", mode='rb') as f:
-    ...:     print(f.read())
-    b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
+       ...:     print(f.read())
+    Out[3]: b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
 
 
 - For files objects, specifying ``newline`` is not sufficient to set the line terminator.
@@ -506,17 +494,15 @@ New Behavior on Windows:
 
   .. code-block:: ipython
 
-    In [1]: data = pd.DataFrame({
-    ...: "string_with_lf": ["a\nbc"],
-    ...: "string_with_crlf": ["a\r\nbc"]
-    ...: })
+    In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+       ...:                      "string_with_crlf": ["a\r\nbc"]})
 
     In [2]: with open("test2.csv", mode='w', newline='\n') as f:
-    ...:     data.to_csv(f, index=False)
+       ...:     data.to_csv(f, index=False)
 
     In [3]: with open("test2.csv", mode='rb') as f:
-    ...:     print(f.read())
-    b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
+       ...:     print(f.read())
+    Out[3]: b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
 
 .. _whatsnew_0240.api.timezone_offset_parsing:
 
@@ -563,7 +549,8 @@ Parsing datetime strings with different UTC offsets will now create an Index of
 
 .. ipython:: python
 
-    idx = pd.to_datetime(["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30"])
+    idx = pd.to_datetime(["2015-11-18 15:30:00+05:30",
+                          "2015-11-18 16:30:00+06:30"])
     idx
     idx[0]
     idx[1]
@@ -573,7 +560,8 @@ that the dates have been converted to UTC
 
 .. ipython:: python
 
-    pd.to_datetime(["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30"], utc=True)
+    pd.to_datetime(["2015-11-18 15:30:00+05:30",
+                    "2015-11-18 16:30:00+06:30"], utc=True)
 
 .. _whatsnew_0240.api_breaking.calendarday:
 
@@ -675,6 +663,7 @@ changes were made:
 - ``SparseDataFrame.combine`` and ``DataFrame.combine_first`` no longer supports combining a sparse column with a dense column while preserving the sparse subtype. The result will be an object-dtype SparseArray.
 - Setting :attr:`SparseArray.fill_value` to a fill value with a different dtype is now allowed.
 - ``DataFrame[column]`` is now a :class:`Series` with sparse values, rather than a :class:`SparseSeries`, when slicing a single column with sparse values (:issue:`23559`).
+- The result of :meth:`Series.where` is now a ``Series`` with sparse values, like with other extension arrays (:issue:`24077`)
 
 Some new warnings are issued for operations that require or are likely to materialize a large dense array:
 
@@ -844,7 +833,7 @@ Previous Behavior:
    In [4]: df = pd.DataFrame(arr)
 
    In [5]: df == arr[[0], :]
-      ...: # comparison previously broadcast where arithmetic would raise
+       ...: # comparison previously broadcast where arithmetic would raise
    Out[5]:
           0      1
    0   True   True
@@ -855,8 +844,8 @@ Previous Behavior:
    ValueError: Unable to coerce to DataFrame, shape must be (3, 2): given (1, 2)
 
    In [7]: df == (1, 2)
-      ...: # length matches number of columns;
-      ...: # comparison previously raised where arithmetic would broadcast
+       ...: # length matches number of columns;
+       ...: # comparison previously raised where arithmetic would broadcast
    ...
    ValueError: Invalid broadcasting comparison [(1, 2)] with block values
    In [8]: df + (1, 2)
@@ -867,8 +856,8 @@ Previous Behavior:
    2  5  7
 
    In [9]: df == (1, 2, 3)
-      ...: # length matches number of rows
-      ...: # comparison previously broadcast where arithmetic would raise
+       ...:  # length matches number of rows
+       ...:  # comparison previously broadcast where arithmetic would raise
    Out[9]:
           0      1
    0  False   True
@@ -1031,7 +1020,8 @@ Current Behavior:
 
 .. code-block:: ipython
 
-    In [3]: df = pd.DataFrame({'a': [1, 2, 2, 2, 2], 'b': [3, 3, 4, 4, 4],
+    In [3]: df = pd.DataFrame({'a': [1, 2, 2, 2, 2],
+       ...:                    'b': [3, 3, 4, 4, 4],
        ...:                    'c': [1, 1, np.nan, 1, 1]})
     In [4]: pd.crosstab(df.a, df.b, normalize='columns')
 
@@ -1113,6 +1103,9 @@ Deprecations
 - :func:`pandas.types.is_datetimetz` is deprecated in favor of `pandas.types.is_datetime64tz` (:issue:`23917`)
 - Creating a :class:`TimedeltaIndex` or :class:`DatetimeIndex` by passing range arguments `start`, `end`, and `periods` is deprecated in favor of :func:`timedelta_range` and :func:`date_range` (:issue:`23919`)
 - Passing a string alias like ``'datetime64[ns, UTC]'`` as the `unit` parameter to :class:`DatetimeTZDtype` is deprecated. Use :class:`DatetimeTZDtype.construct_from_string` instead (:issue:`23990`).
+- In :meth:`Series.where` with Categorical data, providing an ``other`` that is not present in the categories is deprecated. Convert the categorical to a different dtype or add the ``other`` to the categories first (:issue:`24077`).
+- :meth:`Series.clip_lower`, :meth:`Series.clip_upper`, :meth:`DataFrame.clip_lower` and :meth:`DataFrame.clip_upper` are deprecated and will be removed in a future version. Use ``Series.clip(lower=threshold)``, ``Series.clip(upper=threshold)`` and the equivalent ``DataFrame`` methods (:issue:`24203`)
+
 
 .. _whatsnew_0240.deprecations.datetimelike_int_ops:
 
@@ -1209,6 +1202,7 @@ Performance Improvements
 - Improved performance of :func:`Series.describe` in case of numeric dtpyes (:issue:`21274`)
 - Improved performance of :func:`pandas.core.groupby.GroupBy.rank` when dealing with tied rankings (:issue:`21237`)
 - Improved performance of :func:`DataFrame.set_index` with columns consisting of :class:`Period` objects (:issue:`21582`, :issue:`21606`)
+- Improved performance of :meth:`Series.at` and :meth:`Index.get_value` for Extension Arrays values (e.g. :class:`Categorical`) (:issue:`24204`)
 - Improved performance of membership checks in :class:`Categorical` and :class:`CategoricalIndex`
   (i.e. ``x in cat``-style checks are much faster). :meth:`CategoricalIndex.contains`
   is likewise much faster (:issue:`21369`, :issue:`21508`)
@@ -1223,6 +1217,7 @@ Performance Improvements
 - Improved performance of :meth:`DatetimeIndex.tz_localize` and various ``DatetimeIndex`` attributes with dateutil UTC timezone (:issue:`23772`)
 - Fixed a performance regression on Windows with Python 3.7 of :func:`pd.read_csv` (:issue:`23516`)
 - Improved performance of :class:`Categorical` constructor for `Series` objects (:issue:`23814`)
+- Improved performance of :meth:`~DataFrame.where` for Categorical data (:issue:`24077`)
 
 .. _whatsnew_0240.docs:
 
@@ -1249,6 +1244,7 @@ Categorical
 - In meth:`Series.unstack`, specifying a ``fill_value`` not present in the categories now raises a ``TypeError`` rather than ignoring the ``fill_value`` (:issue:`23284`)
 - Bug when resampling :meth:`Dataframe.resample()` and aggregating on categorical data, the categorical dtype was getting lost. (:issue:`23227`)
 - Bug in many methods of the ``.str``-accessor, which always failed on calling the ``CategoricalIndex.str`` constructor (:issue:`23555`, :issue:`23556`)
+- Bug in :meth:`Series.where` losing the categorical dtype for categorical data (:issue:`24077`)
 
 Datetimelike
 ^^^^^^^^^^^^
@@ -1285,6 +1281,8 @@ Datetimelike
 - Bug in :class:`DatetimeIndex` where calling ``np.array(dtindex, dtype=object)`` would incorrectly return an array of ``long`` objects (:issue:`23524`)
 - Bug in :class:`Index` where passing a timezone-aware :class:`DatetimeIndex` and `dtype=object` would incorrectly raise a ``ValueError`` (:issue:`23524`)
 - Bug in :class:`Index` where calling ``np.array(dtindex, dtype=object)`` on a timezone-naive :class:`DatetimeIndex` would return an array of ``datetime`` objects instead of :class:`Timestamp` objects, potentially losing nanosecond portions of the timestamps (:issue:`23524`)
+- Bug in :class:`Categorical.__setitem__` not allowing setting with another ``Categorical`` when both are undordered and have the same categories, but in a different order (:issue:`24142`)
+- Bug in :func:`date_range` where using dates with millisecond resolution or higher could return incorrect values or the wrong number of values in the index (:issue:`24110`)
 
 Timedelta
 ^^^^^^^^^
@@ -1355,6 +1353,7 @@ Numeric
 - :meth:`Series.agg` can now handle numpy NaN-aware methods like :func:`numpy.nansum` (:issue:`19629`)
 - Bug in :meth:`Series.rank` and :meth:`DataFrame.rank` when ``pct=True`` and more than 2:sup:`24` rows are present resulted in percentages greater than 1.0 (:issue:`18271`)
 - Calls such as :meth:`DataFrame.round` with a non-unique :meth:`CategoricalIndex` now return expected data. Previously, data would be improperly duplicated (:issue:`21809`).
+- Added ``log10`` to the list of supported functions in :meth:`DataFrame.eval` (:issue:`24139`)
 
 Strings
 ^^^^^^^
diff --git a/pandas/_libs/tslibs/timestamps.pyx b/pandas/_libs/tslibs/timestamps.pyx
index b4862a5f3b02f..472ac0ee6d45c 100644
--- a/pandas/_libs/tslibs/timestamps.pyx
+++ b/pandas/_libs/tslibs/timestamps.pyx
@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-import enum
 import warnings
 
 from cpython cimport (PyObject_RichCompareBool, PyObject_RichCompare,
@@ -71,8 +70,7 @@ cdef inline object create_timestamp_from_ts(int64_t value,
     return ts_base
 
 
-@enum.unique
-class RoundTo(enum.Enum):
+class RoundTo(object):
     """
     enumeration defining the available rounding modes
 
@@ -105,11 +103,25 @@ class RoundTo(enum.Enum):
     .. [6] "Round half to even"
            https://en.wikipedia.org/wiki/Rounding#Round_half_to_even
     """
-    MINUS_INFTY = 0
-    PLUS_INFTY = 1
-    NEAREST_HALF_EVEN = 2
-    NEAREST_HALF_PLUS_INFTY = 3
-    NEAREST_HALF_MINUS_INFTY = 4
+    @property
+    def MINUS_INFTY(self):
+        return 0
+
+    @property
+    def PLUS_INFTY(self):
+        return 1
+
+    @property
+    def NEAREST_HALF_EVEN(self):
+        return 2
+
+    @property
+    def NEAREST_HALF_PLUS_INFTY(self):
+        return 3
+
+    @property
+    def NEAREST_HALF_MINUS_INFTY(self):
+        return 4
 
 
 cdef inline _npdivmod(x1, x2):
@@ -152,20 +164,17 @@ def round_nsint64(values, mode, freq):
     :obj:`ndarray`
     """
 
-    if not isinstance(mode, RoundTo):
-        raise ValueError('mode should be a RoundTo member')
-
     unit = to_offset(freq).nanos
 
-    if mode is RoundTo.MINUS_INFTY:
+    if mode == RoundTo.MINUS_INFTY:
         return _floor_int64(values, unit)
-    elif mode is RoundTo.PLUS_INFTY:
+    elif mode == RoundTo.PLUS_INFTY:
         return _ceil_int64(values, unit)
-    elif mode is RoundTo.NEAREST_HALF_MINUS_INFTY:
+    elif mode == RoundTo.NEAREST_HALF_MINUS_INFTY:
         return _rounddown_int64(values, unit)
-    elif mode is RoundTo.NEAREST_HALF_PLUS_INFTY:
+    elif mode == RoundTo.NEAREST_HALF_PLUS_INFTY:
         return _roundup_int64(values, unit)
-    elif mode is RoundTo.NEAREST_HALF_EVEN:
+    elif mode == RoundTo.NEAREST_HALF_EVEN:
         # for odd unit there is no need of a tie break
         if unit % 2:
             return _rounddown_int64(values, unit)
@@ -179,8 +188,8 @@ def round_nsint64(values, mode, freq):
 
     # if/elif above should catch all rounding modes defined in enum 'RoundTo':
     # if flow of control arrives here, it is a bug
-    raise AssertionError("round_nsint64 called with an unrecognized "
-                         "rounding mode")
+    raise ValueError("round_nsint64 called with an unrecognized "
+                     "rounding mode")
 
 
 # This is PITA. Because we inherit from datetime, which has very specific
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index 15abffa9a5d23..cf145064fd7b1 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -220,6 +220,8 @@ def __setitem__(self, key, value):
         #   example, a string like '2018-01-01' is coerced to a datetime
         #   when setting on a datetime64ns array. In general, if the
         #   __init__ method coerces that value, then so should __setitem__
+        # Note, also, that Series/DataFrame.where internally use __setitem__
+        # on a copy of the data.
         raise NotImplementedError(_not_implemented_message.format(
             type(self), '__setitem__')
         )
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index b2c580ac435db..101d03cd55d40 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -2078,11 +2078,21 @@ def __setitem__(self, key, value):
             `Categorical` does not have the same categories
         """
 
+        if isinstance(value, (ABCIndexClass, ABCSeries)):
+            value = value.array
+
         # require identical categories set
         if isinstance(value, Categorical):
-            if not value.categories.equals(self.categories):
+            if not is_dtype_equal(self, value):
                 raise ValueError("Cannot set a Categorical with another, "
                                  "without identical categories")
+            if not self.categories.equals(value.categories):
+                new_codes = _recode_for_categories(
+                    value.codes, value.categories, self.categories
+                )
+                value = Categorical.from_codes(new_codes,
+                                               categories=self.categories,
+                                               ordered=self.ordered)
 
         rvalue = value if is_list_like(value) else [value]
 
diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 9e8116bd15611..4849ee1e3e665 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -82,7 +82,7 @@ def f(self):
         return result
 
     f.__name__ = name
-    f.__doc__ = "{}".format(docstring)
+    f.__doc__ = "\n{}\n".format(docstring)
     return property(f)
 
 
@@ -307,7 +307,12 @@ def _generate_range(cls, start, end, periods, freq, tz=None,
                     end = end.tz_localize(tz).asm8
         else:
             # Create a linearly spaced date_range in local time
-            arr = np.linspace(start.value, end.value, periods)
+            # Nanosecond-granularity timestamps aren't always correctly
+            # representable with doubles, so we limit the range that we
+            # pass to np.linspace as much as possible
+            arr = np.linspace(
+                0, end.value - start.value,
+                periods, dtype='int64') + start.value
             index = cls._simple_new(
                 arr.astype('M8[ns]', copy=False), freq=None, tz=tz
             )
@@ -1065,9 +1070,9 @@ def date(self):
 
         return tslib.ints_to_pydatetime(timestamps, box="date")
 
-    year = _field_accessor('year', 'Y', " The year of the datetime.")
+    year = _field_accessor('year', 'Y', "The year of the datetime.")
     month = _field_accessor('month', 'M',
-                            " The month as January=1, December=12. ")
+                            "The month as January=1, December=12. ")
     day = _field_accessor('day', 'D', "The days of the datetime.")
     hour = _field_accessor('hour', 'h', "The hours of the datetime.")
     minute = _field_accessor('minute', 'm', "The minutes of the datetime.")
diff --git a/pandas/core/arrays/sparse.py b/pandas/core/arrays/sparse.py
index 0bd899149d940..9e1d2efc21b81 100644
--- a/pandas/core/arrays/sparse.py
+++ b/pandas/core/arrays/sparse.py
@@ -706,6 +706,8 @@ def __array__(self, dtype=None, copy=True):
 
     def __setitem__(self, key, value):
         # I suppose we could allow setting of non-fill_value elements.
+        # TODO(SparseArray.__setitem__): remove special cases in
+        # ExtensionBlock.where
         msg = "SparseArray does not support item assignment via setitem"
         raise TypeError(msg)
 
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index 9e9f124352229..cbdb3525d5e88 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -23,7 +23,7 @@
 
 _unary_math_ops = ('sin', 'cos', 'exp', 'log', 'expm1', 'log1p',
                    'sqrt', 'sinh', 'cosh', 'tanh', 'arcsin', 'arccos',
-                   'arctan', 'arccosh', 'arcsinh', 'arctanh', 'abs')
+                   'arctan', 'arccosh', 'arcsinh', 'arctanh', 'abs', 'log10')
 _binary_math_ops = ('arctan2',)
 _mathops = _unary_math_ops + _binary_math_ops
 
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index e52a0b60c610e..11d1333851794 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -7206,11 +7206,6 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Same type as calling object with the values outside the
             clip boundaries replaced
 
-        See Also
-        --------
-        clip_lower : Clip values below specified threshold(s).
-        clip_upper : Clip values above specified threshold(s).
-
         Examples
         --------
         >>> data = {'col_0': [9, -3, 0, -1, 5], 'col_1': [-2, -7, 6, 8, -5]}
@@ -7283,11 +7278,13 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         result = self
         if lower is not None:
-            result = result.clip_lower(lower, axis, inplace=inplace)
+            result = result._clip_with_one_bound(lower, method=self.ge,
+                                                 axis=axis, inplace=inplace)
         if upper is not None:
             if inplace:
                 result = self
-            result = result.clip_upper(upper, axis, inplace=inplace)
+            result = result._clip_with_one_bound(upper, method=self.le,
+                                                 axis=axis, inplace=inplace)
 
         return result
 
@@ -7295,6 +7292,9 @@ def clip_upper(self, threshold, axis=None, inplace=False):
         """
         Trim values above a given threshold.
 
+        .. deprecated:: 0.24.0
+            Use clip(upper=threshold) instead.
+
         Elements above the `threshold` will be changed to match the
         `threshold` value(s). Threshold can be a single value or an array,
         in the latter case it performs the truncation element-wise.
@@ -7321,18 +7321,15 @@ def clip_upper(self, threshold, axis=None, inplace=False):
 
         Returns
         -------
-        clipped
+        Series or DataFrame
             Original data with values trimmed.
 
         See Also
         --------
-        DataFrame.clip : General purpose method to trim DataFrame values to
-            given threshold(s).
-        DataFrame.clip_lower : Trim DataFrame values below given
-            threshold(s).
         Series.clip : General purpose method to trim Series values to given
             threshold(s).
-        Series.clip_lower : Trim Series values below given threshold(s).
+        DataFrame.clip : General purpose method to trim DataFrame values to
+            given threshold(s).
 
         Examples
         --------
@@ -7365,6 +7362,9 @@ def clip_upper(self, threshold, axis=None, inplace=False):
         4    1
         dtype: int64
         """
+        warnings.warn('clip_upper(threshold) is deprecated, '
+                      'use clip(upper=threshold) instead',
+                      FutureWarning, stacklevel=2)
         return self._clip_with_one_bound(threshold, method=self.le,
                                          axis=axis, inplace=inplace)
 
@@ -7372,6 +7372,9 @@ def clip_lower(self, threshold, axis=None, inplace=False):
         """
         Trim values below a given threshold.
 
+        .. deprecated:: 0.24.0
+            Use clip(lower=threshold) instead.
+
         Elements below the `threshold` will be changed to match the
         `threshold` value(s). Threshold can be a single value or an array,
         in the latter case it performs the truncation element-wise.
@@ -7399,18 +7402,15 @@ def clip_lower(self, threshold, axis=None, inplace=False):
 
         Returns
         -------
-        clipped
+        Series or DataFrame
             Original data with values trimmed.
 
         See Also
         --------
-        DataFrame.clip : General purpose method to trim DataFrame values to
-            given threshold(s).
-        DataFrame.clip_upper : Trim DataFrame values above given
-            threshold(s).
         Series.clip : General purpose method to trim Series values to given
             threshold(s).
-        Series.clip_upper : Trim Series values above given threshold(s).
+        DataFrame.clip : General purpose method to trim DataFrame values to
+            given threshold(s).
 
         Examples
         --------
@@ -7478,6 +7478,9 @@ def clip_lower(self, threshold, axis=None, inplace=False):
         1  4  5
         2  5  6
         """
+        warnings.warn('clip_lower(threshold) is deprecated, '
+                      'use clip(lower=threshold) instead',
+                      FutureWarning, stacklevel=2)
         return self._clip_with_one_bound(threshold, method=self.ge,
                                          axis=axis, inplace=inplace)
 
@@ -9896,11 +9899,11 @@ def _add_numeric_operations(cls):
         axis_descr, name, name2 = _doc_parms(cls)
 
         cls.any = _make_logical_function(
-            cls, 'any', name, name2, axis_descr,
-            _any_desc, nanops.nanany, _any_examples, _any_see_also)
+            cls, 'any', name, name2, axis_descr, _any_desc, nanops.nanany,
+            _any_examples, _any_see_also, empty_value=False)
         cls.all = _make_logical_function(
-            cls, 'all', name, name2, axis_descr, _all_doc,
-            nanops.nanall, _all_examples, _all_see_also)
+            cls, 'all', name, name2, axis_descr, _all_desc, nanops.nanall,
+            _all_examples, _all_see_also, empty_value=True)
 
         @Substitution(outname='mad',
                       desc="Return the mean absolute deviation of the values "
@@ -10221,12 +10224,14 @@ def _doc_parms(cls):
       original index.
     * None : reduce all axes, return a scalar.
 
-bool_only : boolean, default None
+bool_only : bool, default None
     Include only boolean columns. If None, will attempt to use everything,
     then use only boolean data. Not implemented for Series.
-skipna : boolean, default True
-    Exclude NA/null values. If an entire row/column is NA, the result
-    will be NA.
+skipna : bool, default True
+    Exclude NA/null values. If the entire row/column is NA and skipna is
+    True, then the result will be %(empty_value)s, as for an empty row/column.
+    If skipna is False, then NA are treated as True, because these are not
+    equal to zero.
 level : int or level name, default None
     If the axis is a MultiIndex (hierarchical), count along a
     particular level, collapsing into a %(name1)s.
@@ -10236,28 +10241,37 @@ def _doc_parms(cls):
 
 Returns
 -------
-%(outname)s : %(name1)s or %(name2)s (if level specified)
+%(name1)s or %(name2)s
+    If level is specified, then, %(name2)s is returned; otherwise, %(name1)s
+    is returned.
 
 %(see_also)s
 %(examples)s"""
 
-_all_doc = """\
+_all_desc = """\
 Return whether all elements are True, potentially over an axis.
 
-Returns True if all elements within a series or along a Dataframe
-axis are non-zero, not-empty or not-False."""
+Returns True unless there at least one element within a series or
+along a Dataframe axis that is False or equivalent (e.g. zero or
+empty)."""
 
 _all_examples = """\
 Examples
 --------
-Series
+**Series**
 
 >>> pd.Series([True, True]).all()
 True
 >>> pd.Series([True, False]).all()
 False
+>>> pd.Series([]).all()
+True
+>>> pd.Series([np.nan]).all()
+True
+>>> pd.Series([np.nan]).all(skipna=False)
+True
 
-DataFrames
+**DataFrames**
 
 Create a dataframe from a dictionary.
 
@@ -10599,10 +10613,11 @@ def _doc_parms(cls):
 """
 
 _any_desc = """\
-Return whether any element is True over requested axis.
+Return whether any element is True, potentially over an axis.
 
-Unlike :meth:`DataFrame.all`, this performs an *or* operation. If any of the
-values along the specified axis is True, this will return True."""
+Returns False unless there at least one element within a series or
+along a Dataframe axis that is True or equivalent (e.g. non-zero or
+non-empty)."""
 
 _any_examples = """\
 Examples
@@ -10612,8 +10627,16 @@ def _doc_parms(cls):
 For Series input, the output is a scalar indicating whether any element
 is True.
 
+>>> pd.Series([False, False]).any()
+False
 >>> pd.Series([True, False]).any()
 True
+>>> pd.Series([]).any()
+False
+>>> pd.Series([np.nan]).any()
+False
+>>> pd.Series([np.nan]).any(skipna=False)
+True
 
 **DataFrame**
 
@@ -10899,9 +10922,10 @@ def cum_func(self, axis=None, skipna=True, *args, **kwargs):
 
 
 def _make_logical_function(cls, name, name1, name2, axis_descr, desc, f,
-                           examples, see_also):
+                           examples, see_also, empty_value):
     @Substitution(outname=name, desc=desc, name1=name1, name2=name2,
-                  axis_descr=axis_descr, examples=examples, see_also=see_also)
+                  axis_descr=axis_descr, examples=examples, see_also=see_also,
+                  empty_value=empty_value)
     @Appender(_bool_doc)
     def logical_func(self, axis=0, bool_only=None, skipna=True, level=None,
                      **kwargs):
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index fc5f6758f9e06..811d66c74ed15 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -4281,7 +4281,8 @@ def get_value(self, series, key):
 
         # if we have something that is Index-like, then
         # use this, e.g. DatetimeIndex
-        s = getattr(series, '_values', None)
+        # Things like `Series._get_value` (via .at) pass the EA directly here.
+        s = getattr(series, '_values', series)
         if isinstance(s, (ExtensionArray, Index)) and is_scalar(key):
             # GH 20882, 21257
             # Unify Index and ExtensionArray treatment
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 9ce4949992f4c..f1a05ec607b59 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -501,10 +501,13 @@ def _can_reindex(self, indexer):
 
     @Appender(_index_shared_docs['where'])
     def where(self, cond, other=None):
+        # TODO: Investigate an alternative implementation with
+        # 1. copy the underyling Categorical
+        # 2. setitem with `cond` and `other`
+        # 3. Rebuild CategoricalIndex.
         if other is None:
             other = self._na_value
         values = np.where(cond, self.values, other)
-
         cat = Categorical(values, dtype=self.dtype)
         return self._shallow_copy(cat, **self._get_attributes_dict())
 
diff --git a/pandas/core/internals/blocks.py b/pandas/core/internals/blocks.py
index d37da14ab5d2c..1383ce09bc2d0 100644
--- a/pandas/core/internals/blocks.py
+++ b/pandas/core/internals/blocks.py
@@ -28,7 +28,8 @@
 from pandas.core.dtypes.dtypes import (
     CategoricalDtype, DatetimeTZDtype, ExtensionDtype, PandasExtensionDtype)
 from pandas.core.dtypes.generic import (
-    ABCDatetimeIndex, ABCExtensionArray, ABCIndexClass, ABCSeries)
+    ABCDataFrame, ABCDatetimeIndex, ABCExtensionArray, ABCIndexClass,
+    ABCSeries)
 from pandas.core.dtypes.missing import (
     _isna_compat, array_equivalent, is_null_datelike_scalar, isna, notna)
 
@@ -1886,7 +1887,6 @@ def take_nd(self, indexer, axis=0, new_mgr_locs=None, fill_tuple=None):
         new_values = self.values.take(indexer, fill_value=fill_value,
                                       allow_fill=True)
 
-        # if we are a 1-dim object, then always place at 0
         if self.ndim == 1 and new_mgr_locs is None:
             new_mgr_locs = [0]
         else:
@@ -1967,6 +1967,57 @@ def shift(self, periods, axis=0):
                                            placement=self.mgr_locs,
                                            ndim=self.ndim)]
 
+    def where(self, other, cond, align=True, errors='raise',
+              try_cast=False, axis=0, transpose=False):
+        # Extract the underlying arrays.
+        if isinstance(other, (ABCIndexClass, ABCSeries)):
+            other = other.array
+
+        elif isinstance(other, ABCDataFrame):
+            # ExtensionArrays are 1-D, so if we get here then
+            # `other` should be a DataFrame with a single column.
+            assert other.shape[1] == 1
+            other = other.iloc[:, 0].array
+
+        if isinstance(cond, ABCDataFrame):
+            assert cond.shape[1] == 1
+            cond = cond.iloc[:, 0].array
+
+        elif isinstance(cond, (ABCIndexClass, ABCSeries)):
+            cond = cond.array
+
+        if lib.is_scalar(other) and isna(other):
+            # The default `other` for Series / Frame is np.nan
+            # we want to replace that with the correct NA value
+            # for the type
+            other = self.dtype.na_value
+
+        if is_sparse(self.values):
+            # TODO(SparseArray.__setitem__): remove this if condition
+            # We need to re-infer the type of the data after doing the
+            # where, for cases where the subtypes don't match
+            dtype = None
+        else:
+            dtype = self.dtype
+
+        try:
+            result = self.values.copy()
+            icond = ~cond
+            if lib.is_scalar(other):
+                result[icond] = other
+            else:
+                result[icond] = other[icond]
+        except (NotImplementedError, TypeError):
+            # NotImplementedError for class not implementing `__setitem__`
+            # TypeError for SparseArray, which implements just to raise
+            # a TypeError
+            result = self._holder._from_sequence(
+                np.where(cond, self.values, other),
+                dtype=dtype,
+            )
+
+        return self.make_block_same_class(result, placement=self.mgr_locs)
+
     @property
     def _ftype(self):
         return getattr(self.values, '_pandas_ftype', Block._ftype)
@@ -2658,6 +2709,33 @@ def concat_same_type(self, to_concat, placement=None):
             values, placement=placement or slice(0, len(values), 1),
             ndim=self.ndim)
 
+    def where(self, other, cond, align=True, errors='raise',
+              try_cast=False, axis=0, transpose=False):
+        # TODO(CategoricalBlock.where):
+        # This can all be deleted in favor of ExtensionBlock.where once
+        # we enforce the deprecation.
+        object_msg = (
+            "Implicitly converting categorical to object-dtype ndarray. "
+            "One or more of the values in 'other' are not present in this "
+            "categorical's categories. A future version of pandas will raise "
+            "a ValueError when 'other' contains different categories.\n\n"
+            "To preserve the current behavior, add the new categories to "
+            "the categorical before calling 'where', or convert the "
+            "categorical to a different dtype."
+        )
+        try:
+            # Attempt to do preserve categorical dtype.
+            result = super(CategoricalBlock, self).where(
+                other, cond, align, errors, try_cast, axis, transpose
+            )
+        except (TypeError, ValueError):
+            warnings.warn(object_msg, FutureWarning, stacklevel=6)
+            result = self.astype(object).where(other, cond, align=align,
+                                               errors=errors,
+                                               try_cast=try_cast,
+                                               axis=axis, transpose=transpose)
+        return result
+
 
 class DatetimeBlock(DatetimeLikeBlockMixin, Block):
     __slots__ = ()
diff --git a/pandas/tests/arrays/categorical/test_indexing.py b/pandas/tests/arrays/categorical/test_indexing.py
index 8df5728f7d895..4ba934f44a0ac 100644
--- a/pandas/tests/arrays/categorical/test_indexing.py
+++ b/pandas/tests/arrays/categorical/test_indexing.py
@@ -3,6 +3,7 @@
 import numpy as np
 import pytest
 
+import pandas as pd
 from pandas import Categorical, CategoricalIndex, Index, PeriodIndex, Series
 import pandas.core.common as com
 from pandas.tests.arrays.categorical.common import TestCategorical
@@ -43,6 +44,45 @@ def test_setitem(self):
 
         tm.assert_categorical_equal(c, expected)
 
+    @pytest.mark.parametrize('other', [
+        pd.Categorical(['b', 'a']),
+        pd.Categorical(['b', 'a'], categories=['b', 'a']),
+    ])
+    def test_setitem_same_but_unordered(self, other):
+        # GH-24142
+        target = pd.Categorical(['a', 'b'], categories=['a', 'b'])
+        mask = np.array([True, False])
+        target[mask] = other[mask]
+        expected = pd.Categorical(['b', 'b'], categories=['a', 'b'])
+        tm.assert_categorical_equal(target, expected)
+
+    @pytest.mark.parametrize('other', [
+        pd.Categorical(['b', 'a'], categories=['b', 'a', 'c']),
+        pd.Categorical(['b', 'a'], categories=['a', 'b', 'c']),
+        pd.Categorical(['a', 'a'], categories=['a']),
+        pd.Categorical(['b', 'b'], categories=['b']),
+    ])
+    def test_setitem_different_unordered_raises(self, other):
+        # GH-24142
+        target = pd.Categorical(['a', 'b'], categories=['a', 'b'])
+        mask = np.array([True, False])
+        with pytest.raises(ValueError):
+            target[mask] = other[mask]
+
+    @pytest.mark.parametrize('other', [
+        pd.Categorical(['b', 'a']),
+        pd.Categorical(['b', 'a'], categories=['b', 'a'], ordered=True),
+        pd.Categorical(['b', 'a'], categories=['a', 'b', 'c'], ordered=True),
+    ])
+    def test_setitem_same_ordered_rasies(self, other):
+        # Gh-24142
+        target = pd.Categorical(['a', 'b'], categories=['a', 'b'],
+                                ordered=True)
+        mask = np.array([True, False])
+
+        with pytest.raises(ValueError):
+            target[mask] = other[mask]
+
 
 class TestCategoricalIndexing(object):
 
@@ -122,6 +162,60 @@ def test_get_indexer_non_unique(self, idx_values, key_values, key_class):
             tm.assert_numpy_array_equal(expected, result)
             tm.assert_numpy_array_equal(exp_miss, res_miss)
 
+    def test_where_unobserved_nan(self):
+        ser = pd.Series(pd.Categorical(['a', 'b']))
+        result = ser.where([True, False])
+        expected = pd.Series(pd.Categorical(['a', None],
+                                            categories=['a', 'b']))
+        tm.assert_series_equal(result, expected)
+
+        # all NA
+        ser = pd.Series(pd.Categorical(['a', 'b']))
+        result = ser.where([False, False])
+        expected = pd.Series(pd.Categorical([None, None],
+                                            categories=['a', 'b']))
+        tm.assert_series_equal(result, expected)
+
+    def test_where_unobserved_categories(self):
+        ser = pd.Series(
+            Categorical(['a', 'b', 'c'], categories=['d', 'c', 'b', 'a'])
+        )
+        result = ser.where([True, True, False], other='b')
+        expected = pd.Series(
+            Categorical(['a', 'b', 'b'], categories=ser.cat.categories)
+        )
+        tm.assert_series_equal(result, expected)
+
+    def test_where_other_categorical(self):
+        ser = pd.Series(
+            Categorical(['a', 'b', 'c'], categories=['d', 'c', 'b', 'a'])
+        )
+        other = Categorical(['b', 'c', 'a'], categories=['a', 'c', 'b', 'd'])
+        result = ser.where([True, False, True], other)
+        expected = pd.Series(Categorical(['a', 'c', 'c'], dtype=ser.dtype))
+        tm.assert_series_equal(result, expected)
+
+    def test_where_warns(self):
+        ser = pd.Series(Categorical(['a', 'b', 'c']))
+        with tm.assert_produces_warning(FutureWarning):
+            result = ser.where([True, False, True], 'd')
+
+        expected = pd.Series(np.array(['a', 'd', 'c'], dtype='object'))
+        tm.assert_series_equal(result, expected)
+
+    def test_where_ordered_differs_rasies(self):
+        ser = pd.Series(
+            Categorical(['a', 'b', 'c'], categories=['d', 'c', 'b', 'a'],
+                        ordered=True)
+        )
+        other = Categorical(['b', 'c', 'a'], categories=['a', 'c', 'b', 'd'],
+                            ordered=True)
+        with tm.assert_produces_warning(FutureWarning):
+            result = ser.where([True, False, True], other)
+
+        expected = pd.Series(np.array(['a', 'c', 'c'], dtype=object))
+        tm.assert_series_equal(result, expected)
+
 
 @pytest.mark.parametrize("index", [True, False])
 def test_mask_with_boolean(index):
@@ -145,3 +239,30 @@ def test_mask_with_boolean_raises(index):
 
     with pytest.raises(ValueError, match='NA / NaN'):
         s[idx]
+
+
+@pytest.fixture
+def non_coercible_categorical(monkeypatch):
+    """
+    Monkeypatch Categorical.__array__ to ensure no implicit conversion.
+
+    Raises
+    ------
+    ValueError
+        When Categorical.__array__ is called.
+    """
+    # TODO(Categorical): identify other places where this may be
+    # useful and move to a conftest.py
+    def array(self, dtype=None):
+        raise ValueError("I cannot be converted.")
+
+    with monkeypatch.context() as m:
+        m.setattr(Categorical, "__array__", array)
+        yield
+
+
+def test_series_at(non_coercible_categorical):
+    arr = Categorical(['a', 'b', 'c'])
+    ser = Series(arr)
+    result = ser.at[0]
+    assert result == 'a'
diff --git a/pandas/tests/arrays/interval/test_interval.py b/pandas/tests/arrays/interval/test_interval.py
index a04579dbbb6b1..9604010571294 100644
--- a/pandas/tests/arrays/interval/test_interval.py
+++ b/pandas/tests/arrays/interval/test_interval.py
@@ -2,7 +2,8 @@
 import numpy as np
 import pytest
 
-from pandas import Index, IntervalIndex, date_range, timedelta_range
+import pandas as pd
+from pandas import Index, Interval, IntervalIndex, date_range, timedelta_range
 from pandas.core.arrays import IntervalArray
 import pandas.util.testing as tm
 
@@ -50,6 +51,17 @@ def test_set_closed(self, closed, new_closed):
         expected = IntervalArray.from_breaks(range(10), closed=new_closed)
         tm.assert_extension_array_equal(result, expected)
 
+    @pytest.mark.parametrize('other', [
+        Interval(0, 1, closed='right'),
+        IntervalArray.from_breaks([1, 2, 3, 4], closed='right'),
+    ])
+    def test_where_raises(self, other):
+        ser = pd.Series(IntervalArray.from_breaks([1, 2, 3, 4],
+                                                  closed='left'))
+        match = "'value.closed' is 'right', expected 'left'."
+        with pytest.raises(ValueError, match=match):
+            ser.where([True, False, True], other=other)
+
 
 class TestSetitem(object):
 
diff --git a/pandas/tests/arrays/sparse/test_array.py b/pandas/tests/arrays/sparse/test_array.py
index b8cef92f6a6d4..7d8cc34ae1462 100644
--- a/pandas/tests/arrays/sparse/test_array.py
+++ b/pandas/tests/arrays/sparse/test_array.py
@@ -357,10 +357,10 @@ def setitem():
         def setslice():
             self.arr[1:5] = 2
 
-        with pytest.raises(TypeError, match="item assignment"):
+        with pytest.raises(TypeError, match="assignment via setitem"):
             setitem()
 
-        with pytest.raises(TypeError, match="item assignment"):
+        with pytest.raises(TypeError, match="assignment via setitem"):
             setslice()
 
     def test_constructor_from_too_large_array(self):
diff --git a/pandas/tests/arrays/test_period.py b/pandas/tests/arrays/test_period.py
index bf139bb0ce616..4425cc8eb1139 100644
--- a/pandas/tests/arrays/test_period.py
+++ b/pandas/tests/arrays/test_period.py
@@ -197,6 +197,21 @@ def test_sub_period():
         arr - other
 
 
+# ----------------------------------------------------------------------------
+# Methods
+
+@pytest.mark.parametrize('other', [
+    pd.Period('2000', freq='H'),
+    period_array(['2000', '2001', '2000'], freq='H')
+])
+def test_where_different_freq_raises(other):
+    ser = pd.Series(period_array(['2000', '2001', '2002'], freq='D'))
+    cond = np.array([True, False, True])
+    with pytest.raises(IncompatibleFrequency,
+                       match="Input has different freq=H"):
+        ser.where(cond, other)
+
+
 # ----------------------------------------------------------------------------
 # Printing
 
diff --git a/pandas/tests/extension/base/methods.py b/pandas/tests/extension/base/methods.py
index 677963078176d..4a409a84f3db4 100644
--- a/pandas/tests/extension/base/methods.py
+++ b/pandas/tests/extension/base/methods.py
@@ -164,7 +164,6 @@ def test_combine_add(self, data_repeated):
             orig_data1._from_sequence([a + val for a in list(orig_data1)]))
         self.assert_series_equal(result, expected)
 
-    @pytest.mark.xfail(reason="GH-24147", strict=True)
     def test_combine_first(self, data):
         # https://github.com/pandas-dev/pandas/issues/24147
         a = pd.Series(data[:3])
@@ -231,3 +230,37 @@ def test_hash_pandas_object_works(self, data, as_frame):
         a = pd.util.hash_pandas_object(data)
         b = pd.util.hash_pandas_object(data)
         self.assert_equal(a, b)
+
+    @pytest.mark.parametrize("as_frame", [True, False])
+    def test_where_series(self, data, na_value, as_frame):
+        assert data[0] != data[1]
+        cls = type(data)
+        a, b = data[:2]
+
+        ser = pd.Series(cls._from_sequence([a, a, b, b], dtype=data.dtype))
+        cond = np.array([True, True, False, False])
+
+        if as_frame:
+            ser = ser.to_frame(name='a')
+            cond = cond.reshape(-1, 1)
+
+        result = ser.where(cond)
+        expected = pd.Series(cls._from_sequence([a, a, na_value, na_value],
+                                                dtype=data.dtype))
+
+        if as_frame:
+            expected = expected.to_frame(name='a')
+        self.assert_equal(result, expected)
+
+        # array other
+        cond = np.array([True, False, True, True])
+        other = cls._from_sequence([a, b, a, b], dtype=data.dtype)
+        if as_frame:
+            other = pd.DataFrame({"a": other})
+            cond = pd.DataFrame({"a": cond})
+        result = ser.where(cond, other)
+        expected = pd.Series(cls._from_sequence([a, b, b, b],
+                                                dtype=data.dtype))
+        if as_frame:
+            expected = expected.to_frame(name='a')
+        self.assert_equal(result, expected)
diff --git a/pandas/tests/extension/conftest.py b/pandas/tests/extension/conftest.py
index 7758bd01840ae..5349dd919f2a2 100644
--- a/pandas/tests/extension/conftest.py
+++ b/pandas/tests/extension/conftest.py
@@ -11,7 +11,11 @@ def dtype():
 
 @pytest.fixture
 def data():
-    """Length-100 array for this type."""
+    """Length-100 array for this type.
+
+    * data[0] and data[1] should both be non missing
+    * data[0] and data[1] should not gbe equal
+    """
     raise NotImplementedError
 
 
diff --git a/pandas/tests/extension/json/test_json.py b/pandas/tests/extension/json/test_json.py
index a941b562fe1ec..a35997b07fd83 100644
--- a/pandas/tests/extension/json/test_json.py
+++ b/pandas/tests/extension/json/test_json.py
@@ -217,10 +217,21 @@ def test_combine_le(self, data_repeated):
     def test_combine_add(self, data_repeated):
         pass
 
+    @pytest.mark.skip(reason="combine for JSONArray not supported")
+    def test_combine_first(self, data):
+        pass
+
     @unhashable
     def test_hash_pandas_object_works(self, data, kind):
         super().test_hash_pandas_object_works(data, kind)
 
+    @pytest.mark.skip(reason="broadcasting error")
+    def test_where_series(self, data, na_value):
+        # Fails with
+        # *** ValueError: operands could not be broadcast together
+        # with shapes (4,) (4,) (0,)
+        super().test_where_series(data, na_value)
+
 
 class TestCasting(BaseJSON, base.BaseCastingTests):
     @pytest.mark.skip(reason="failing on np.array(self, dtype=str)")
diff --git a/pandas/tests/extension/test_categorical.py b/pandas/tests/extension/test_categorical.py
index 5b873b337880e..6106bc3d58620 100644
--- a/pandas/tests/extension/test_categorical.py
+++ b/pandas/tests/extension/test_categorical.py
@@ -25,7 +25,14 @@
 
 
 def make_data():
-    return np.random.choice(list(string.ascii_letters), size=100)
+    while True:
+        values = np.random.choice(list(string.ascii_letters), size=100)
+        # ensure we meet the requirements
+        # 1. first two not null
+        # 2. first and second are different
+        if values[0] != values[1]:
+            break
+    return values
 
 
 @pytest.fixture
@@ -35,7 +42,11 @@ def dtype():
 
 @pytest.fixture
 def data():
-    """Length-100 PeriodArray for semantics test."""
+    """Length-100 array for this type.
+
+    * data[0] and data[1] should both be non missing
+    * data[0] and data[1] should not gbe equal
+    """
     return Categorical(make_data())
 
 
diff --git a/pandas/tests/extension/test_sparse.py b/pandas/tests/extension/test_sparse.py
index 891e5f4dd9a95..ea849a78cda12 100644
--- a/pandas/tests/extension/test_sparse.py
+++ b/pandas/tests/extension/test_sparse.py
@@ -13,6 +13,8 @@ def make_data(fill_value):
         data = np.random.uniform(size=100)
     else:
         data = np.random.randint(1, 100, size=100)
+        if data[0] == data[1]:
+            data[0] += 1
 
     data[2::3] = fill_value
     return data
@@ -255,6 +257,35 @@ def test_fillna_copy_series(self, data_missing):
     def test_fillna_length_mismatch(self, data_missing):
         pass
 
+    def test_where_series(self, data, na_value):
+        assert data[0] != data[1]
+        cls = type(data)
+        a, b = data[:2]
+
+        ser = pd.Series(cls._from_sequence([a, a, b, b], dtype=data.dtype))
+
+        cond = np.array([True, True, False, False])
+        result = ser.where(cond)
+
+        new_dtype = SparseDtype('float', 0.0)
+        expected = pd.Series(cls._from_sequence([a, a, na_value, na_value],
+                                                dtype=new_dtype))
+        self.assert_series_equal(result, expected)
+
+        other = cls._from_sequence([a, b, a, b], dtype=data.dtype)
+        cond = np.array([True, False, True, True])
+        result = ser.where(cond, other)
+        expected = pd.Series(cls._from_sequence([a, b, b, b],
+                                                dtype=data.dtype))
+        self.assert_series_equal(result, expected)
+
+    def test_combine_first(self, data):
+        if data.dtype.subtype == 'int':
+            # Right now this is upcasted to float, just like combine_first
+            # for Series[int]
+            pytest.skip("TODO(SparseArray.__setitem__ will preserve dtype.")
+        super(TestMethods, self).test_combine_first(data)
+
 
 class TestCasting(BaseSparseTests, base.BaseCastingTests):
     pass
diff --git a/pandas/tests/frame/test_analytics.py b/pandas/tests/frame/test_analytics.py
index 6c30f3fb02fb0..88262220015c7 100644
--- a/pandas/tests/frame/test_analytics.py
+++ b/pandas/tests/frame/test_analytics.py
@@ -1841,10 +1841,12 @@ def test_clip(self, float_frame):
         median = float_frame.median().median()
         original = float_frame.copy()
 
-        capped = float_frame.clip_upper(median)
+        with tm.assert_produces_warning(FutureWarning):
+            capped = float_frame.clip_upper(median)
         assert not (capped.values > median).any()
 
-        floored = float_frame.clip_lower(median)
+        with tm.assert_produces_warning(FutureWarning):
+            floored = float_frame.clip_lower(median)
         assert not (floored.values < median).any()
 
         double = float_frame.clip(upper=median, lower=median)
@@ -1858,11 +1860,13 @@ def test_inplace_clip(self, float_frame):
         median = float_frame.median().median()
         frame_copy = float_frame.copy()
 
-        frame_copy.clip_upper(median, inplace=True)
+        with tm.assert_produces_warning(FutureWarning):
+            frame_copy.clip_upper(median, inplace=True)
         assert not (frame_copy.values > median).any()
         frame_copy = float_frame.copy()
 
-        frame_copy.clip_lower(median, inplace=True)
+        with tm.assert_produces_warning(FutureWarning):
+            frame_copy.clip_lower(median, inplace=True)
         assert not (frame_copy.values < median).any()
         frame_copy = float_frame.copy()
 
@@ -2263,7 +2267,8 @@ def test_series_broadcasting(self):
         s_nan = Series([np.nan, np.nan, 1])
 
         with tm.assert_produces_warning(None):
-            df_nan.clip_lower(s, axis=0)
+            with tm.assert_produces_warning(FutureWarning):
+                df_nan.clip_lower(s, axis=0)
             for op in ['lt', 'le', 'gt', 'ge', 'eq', 'ne']:
                 getattr(df, op)(s_nan, axis=0)
 
diff --git a/pandas/tests/indexes/datetimes/test_date_range.py b/pandas/tests/indexes/datetimes/test_date_range.py
index 54a04ab6f80fd..11cefec4f34cf 100644
--- a/pandas/tests/indexes/datetimes/test_date_range.py
+++ b/pandas/tests/indexes/datetimes/test_date_range.py
@@ -769,3 +769,14 @@ def test_all_custom_freq(self, freq):
         msg = 'invalid custom frequency string: {freq}'
         with pytest.raises(ValueError, match=msg.format(freq=bad_freq)):
             bdate_range(START, END, freq=bad_freq)
+
+    @pytest.mark.parametrize('start_end', [
+        ('2018-01-01T00:00:01.000Z', '2018-01-03T00:00:01.000Z'),
+        ('2018-01-01T00:00:00.010Z', '2018-01-03T00:00:00.010Z'),
+        ('2001-01-01T00:00:00.010Z', '2001-01-03T00:00:00.010Z')])
+    def test_range_with_millisecond_resolution(self, start_end):
+        # https://github.com/pandas-dev/pandas/issues/24110
+        start, end = start_end
+        result = pd.date_range(start=start, end=end, periods=2, closed='left')
+        expected = DatetimeIndex([start])
+        tm.assert_index_equal(result, expected)
diff --git a/pandas/tests/indexing/multiindex/test_getitem.py b/pandas/tests/indexing/multiindex/test_getitem.py
index 00b30bab37441..1013bb3e90149 100644
--- a/pandas/tests/indexing/multiindex/test_getitem.py
+++ b/pandas/tests/indexing/multiindex/test_getitem.py
@@ -1,5 +1,3 @@
-from warnings import catch_warnings, simplefilter
-
 import numpy as np
 import pytest
 
@@ -11,335 +9,339 @@
 from pandas.util import testing as tm
 
 
-@pytest.mark.filterwarnings("ignore:\\n.ix:DeprecationWarning")
-class TestMultiIndexGetItem(object):
-
-    def test_series_getitem_multiindex(self):
-
-        # GH 6018
-        # series regression getitem with a multi-index
-
-        s = Series([1, 2, 3])
-        s.index = MultiIndex.from_tuples([(0, 0), (1, 1), (2, 1)])
-
-        result = s[:, 0]
-        expected = Series([1], index=[0])
-        tm.assert_series_equal(result, expected)
-
-        result = s.loc[:, 1]
-        expected = Series([2, 3], index=[1, 2])
-        tm.assert_series_equal(result, expected)
-
-        # xs
-        result = s.xs(0, level=0)
-        expected = Series([1], index=[0])
-        tm.assert_series_equal(result, expected)
-
-        result = s.xs(1, level=1)
-        expected = Series([2, 3], index=[1, 2])
-        tm.assert_series_equal(result, expected)
-
-        # GH6258
-        dt = list(date_range('20130903', periods=3))
-        idx = MultiIndex.from_product([list('AB'), dt])
-        s = Series([1, 3, 4, 1, 3, 4], index=idx)
+@pytest.mark.parametrize('access_method', [lambda s, x: s[:, x],
+                                           lambda s, x: s.loc[:, x],
+                                           lambda s, x: s.xs(x, level=1)])
+@pytest.mark.parametrize('level1_value, expected', [
+    (0, Series([1], index=[0])),
+    (1, Series([2, 3], index=[1, 2]))
+])
+def test_series_getitem_multiindex(access_method, level1_value, expected):
+
+    # GH 6018
+    # series regression getitem with a multi-index
+
+    s = Series([1, 2, 3])
+    s.index = MultiIndex.from_tuples([(0, 0), (1, 1), (2, 1)])
+    result = access_method(s, level1_value)
+    tm.assert_series_equal(result, expected)
+
+
+def test_series_getitem_multiindex_xs():
+    # GH6258
+    dt = list(date_range('20130903', periods=3))
+    idx = MultiIndex.from_product([list('AB'), dt])
+    s = Series([1, 3, 4, 1, 3, 4], index=idx)
+
+    result = s.xs('20130903', level=1)
+    expected = Series([1, 1], index=list('AB'))
+    tm.assert_series_equal(result, expected)
+
+
+def test_series_getitem_multiindex_xs_by_label():
+    # GH5684
+    idx = MultiIndex.from_tuples([('a', 'one'), ('a', 'two'), ('b', 'one'),
+                                  ('b', 'two')])
+    s = Series([1, 2, 3, 4], index=idx)
+    s.index.set_names(['L1', 'L2'], inplace=True)
+    result = s.xs('one', level='L2')
+    expected = Series([1, 3], index=['a', 'b'])
+    expected.index.set_names(['L1'], inplace=True)
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('level0_value', ['D', 'A'])
+def test_getitem_duplicates_multiindex(level0_value):
+    # GH 5725 the 'A' happens to be a valid Timestamp so the doesn't raise
+    # the appropriate error, only in PY3 of course!
+
+    index = MultiIndex(levels=[[level0_value, 'B', 'C'],
+                               [0, 26, 27, 37, 57, 67, 75, 82]],
+                       codes=[[0, 0, 0, 1, 2, 2, 2, 2, 2, 2],
+                              [1, 3, 4, 6, 0, 2, 2, 3, 5, 7]],
+                       names=['tag', 'day'])
+    arr = np.random.randn(len(index), 1)
+    df = DataFrame(arr, index=index, columns=['val'])
+
+    # confirm indexing on missing value raises KeyError
+    if level0_value != 'A':
+        msg = "'A'"
+        with pytest.raises(KeyError, match=msg):
+            df.val['A']
 
-        result = s.xs('20130903', level=1)
-        expected = Series([1, 1], index=list('AB'))
-        tm.assert_series_equal(result, expected)
+    msg = "'X'"
+    with pytest.raises(KeyError, match=msg):
+        df.val['X']
+
+    result = df.val[level0_value]
+    expected = Series(arr.ravel()[0:3], name='val', index=Index(
+        [26, 37, 57], name='day'))
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize('indexer, is_level1, expected_error', [
+    ([], False, None),  # empty ok
+    (['A'], False, None),
+    (['A', 'D'], False, None),
+    (['D'], False, r"\['D'\] not in index"),  # not any values found
+    (pd.IndexSlice[:, ['foo']], True, None),
+    (pd.IndexSlice[:, ['foo', 'bah']], True, None)
+])
+def test_getitem_duplicates_multiindex_missing_indexers(indexer, is_level1,
+                                                        expected_error):
+    # GH 7866
+    # multi-index slicing with missing indexers
+    idx = MultiIndex.from_product([['A', 'B', 'C'],
+                                   ['foo', 'bar', 'baz']],
+                                  names=['one', 'two'])
+    s = Series(np.arange(9, dtype='int64'), index=idx).sort_index()
+
+    if indexer == []:
+        expected = s.iloc[[]]
+    elif is_level1:
+        expected = Series([0, 3, 6], index=MultiIndex.from_product(
+            [['A', 'B', 'C'], ['foo']], names=['one', 'two'])).sort_index()
+    else:
+        exp_idx = MultiIndex.from_product([['A'], ['foo', 'bar', 'baz']],
+                                          names=['one', 'two'])
+        expected = Series(np.arange(3, dtype='int64'),
+                          index=exp_idx).sort_index()
 
-        # GH5684
-        idx = MultiIndex.from_tuples([('a', 'one'), ('a', 'two'), ('b', 'one'),
-                                      ('b', 'two')])
-        s = Series([1, 2, 3, 4], index=idx)
-        s.index.set_names(['L1', 'L2'], inplace=True)
-        result = s.xs('one', level='L2')
-        expected = Series([1, 3], index=['a', 'b'])
-        expected.index.set_names(['L1'], inplace=True)
+    if expected_error is not None:
+        with pytest.raises(KeyError, match=expected_error):
+            s.loc[indexer]
+    else:
+        result = s.loc[indexer]
         tm.assert_series_equal(result, expected)
 
-    def test_getitem_duplicates_multiindex(self):
-        # GH 5725 the 'A' happens to be a valid Timestamp so the doesn't raise
-        # the appropriate error, only in PY3 of course!
-
-        index = MultiIndex(levels=[['D', 'B', 'C'],
-                                   [0, 26, 27, 37, 57, 67, 75, 82]],
-                           codes=[[0, 0, 0, 1, 2, 2, 2, 2, 2, 2],
-                                  [1, 3, 4, 6, 0, 2, 2, 3, 5, 7]],
-                           names=['tag', 'day'])
-        arr = np.random.randn(len(index), 1)
-        df = DataFrame(arr, index=index, columns=['val'])
-        result = df.val['D']
-        expected = Series(arr.ravel()[0:3], name='val', index=Index(
-            [26, 37, 57], name='day'))
-        tm.assert_series_equal(result, expected)
 
-        def f():
-            df.val['A']
+@pytest.mark.parametrize('columns_indexer', [
+    ([], slice(None)),
+    (['foo'], [])
+])
+def test_getitem_duplicates_multiindex_empty_indexer(columns_indexer):
+    # GH 8737
+    # empty indexer
+    multi_index = MultiIndex.from_product((['foo', 'bar', 'baz'],
+                                           ['alpha', 'beta']))
+    df = DataFrame(np.random.randn(5, 6), index=range(5), columns=multi_index)
+    df = df.sort_index(level=0, axis=1)
+
+    expected = DataFrame(index=range(5), columns=multi_index.reindex([])[0])
+    result = df.loc[:, columns_indexer]
+    tm.assert_frame_equal(result, expected)
+
+
+def test_getitem_duplicates_multiindex_non_scalar_type_object():
+    # regression from < 0.14.0
+    # GH 7914
+    df = DataFrame([[np.mean, np.median], ['mean', 'median']],
+                   columns=MultiIndex.from_tuples([('functs', 'mean'),
+                                                   ('functs', 'median')]),
+                   index=['function', 'name'])
+    result = df.loc['function', ('functs', 'mean')]
+    expected = np.mean
+    assert result == expected
+
+
+def test_getitem_simple(multiindex_dataframe_random_data):
+    frame = multiindex_dataframe_random_data
+    df = frame.T
+
+    col = df['foo', 'one']
+    tm.assert_almost_equal(col.values, df.values[:, 0])
+    msg = r"\('foo', 'four'\)"
+    with pytest.raises(KeyError, match=msg):
+        df[('foo', 'four')]
+    msg = "'foobar'"
+    with pytest.raises(KeyError, match=msg):
+        df['foobar']
 
-        pytest.raises(KeyError, f)
 
-        def f():
-            df.val['X']
-
-        pytest.raises(KeyError, f)
+@pytest.mark.filterwarnings("ignore:\\n.ix:DeprecationWarning")
+def test_series_getitem(multiindex_year_month_day_dataframe_random_data):
+    ymd = multiindex_year_month_day_dataframe_random_data
+    s = ymd['A']
 
-        # A is treated as a special Timestamp
-        index = MultiIndex(levels=[['A', 'B', 'C'],
-                                   [0, 26, 27, 37, 57, 67, 75, 82]],
-                           codes=[[0, 0, 0, 1, 2, 2, 2, 2, 2, 2],
-                                  [1, 3, 4, 6, 0, 2, 2, 3, 5, 7]],
-                           names=['tag', 'day'])
-        df = DataFrame(arr, index=index, columns=['val'])
-        result = df.val['A']
-        expected = Series(arr.ravel()[0:3], name='val', index=Index(
-            [26, 37, 57], name='day'))
-        tm.assert_series_equal(result, expected)
+    result = s[2000, 3]
 
-        def f():
-            df.val['X']
+    # TODO(wesm): unused?
+    # result2 = s.loc[2000, 3]
 
-        pytest.raises(KeyError, f)
+    expected = s.reindex(s.index[42:65])
+    expected.index = expected.index.droplevel(0).droplevel(0)
+    tm.assert_series_equal(result, expected)
 
-        # GH 7866
-        # multi-index slicing with missing indexers
-        idx = MultiIndex.from_product([['A', 'B', 'C'],
-                                       ['foo', 'bar', 'baz']],
-                                      names=['one', 'two'])
-        s = Series(np.arange(9, dtype='int64'), index=idx).sort_index()
+    result = s[2000, 3, 10]
+    expected = s[49]
+    assert result == expected
 
-        exp_idx = MultiIndex.from_product([['A'], ['foo', 'bar', 'baz']],
-                                          names=['one', 'two'])
-        expected = Series(np.arange(3, dtype='int64'),
-                          index=exp_idx).sort_index()
+    # fancy
+    expected = s.reindex(s.index[49:51])
+    result = s.loc[[(2000, 3, 10), (2000, 3, 13)]]
+    tm.assert_series_equal(result, expected)
 
-        result = s.loc[['A']]
-        tm.assert_series_equal(result, expected)
-        result = s.loc[['A', 'D']]
-        tm.assert_series_equal(result, expected)
+    result = s.ix[[(2000, 3, 10), (2000, 3, 13)]]
+    tm.assert_series_equal(result, expected)
 
-        # not any values found
-        pytest.raises(KeyError, lambda: s.loc[['D']])
+    # key error
+    msg = "356"
+    with pytest.raises(KeyError, match=msg):
+        s.__getitem__((2000, 3, 4))
 
-        # empty ok
-        result = s.loc[[]]
-        expected = s.iloc[[]]
-        tm.assert_series_equal(result, expected)
 
-        idx = pd.IndexSlice
-        expected = Series([0, 3, 6], index=MultiIndex.from_product(
-            [['A', 'B', 'C'], ['foo']], names=['one', 'two'])).sort_index()
+def test_series_getitem_corner(
+        multiindex_year_month_day_dataframe_random_data):
+    ymd = multiindex_year_month_day_dataframe_random_data
+    s = ymd['A']
 
-        result = s.loc[idx[:, ['foo']]]
-        tm.assert_series_equal(result, expected)
-        result = s.loc[idx[:, ['foo', 'bah']]]
-        tm.assert_series_equal(result, expected)
+    # don't segfault, GH #495
+    # out of bounds access
+    msg = "index out of bounds"
+    with pytest.raises(IndexError, match=msg):
+        s.__getitem__(len(ymd))
 
-        # GH 8737
-        # empty indexer
-        multi_index = MultiIndex.from_product((['foo', 'bar', 'baz'],
-                                               ['alpha', 'beta']))
-        df = DataFrame(
-            np.random.randn(5, 6), index=range(5), columns=multi_index)
-        df = df.sort_index(level=0, axis=1)
-
-        expected = DataFrame(index=range(5),
-                             columns=multi_index.reindex([])[0])
-        result1 = df.loc[:, ([], slice(None))]
-        result2 = df.loc[:, (['foo'], [])]
-        tm.assert_frame_equal(result1, expected)
-        tm.assert_frame_equal(result2, expected)
-
-        # regression from < 0.14.0
-        # GH 7914
-        df = DataFrame([[np.mean, np.median], ['mean', 'median']],
-                       columns=MultiIndex.from_tuples([('functs', 'mean'),
-                                                       ('functs', 'median')]),
-                       index=['function', 'name'])
-        result = df.loc['function', ('functs', 'mean')]
-        assert result == np.mean
-
-    def test_getitem_simple(self, multiindex_dataframe_random_data):
-        frame = multiindex_dataframe_random_data
-        df = frame.T
-
-        col = df['foo', 'one']
-        tm.assert_almost_equal(col.values, df.values[:, 0])
-        with pytest.raises(KeyError):
-            df[('foo', 'four')]
-        with pytest.raises(KeyError):
-            df['foobar']
-
-    def test_series_getitem(
-            self, multiindex_year_month_day_dataframe_random_data):
-        ymd = multiindex_year_month_day_dataframe_random_data
-        s = ymd['A']
-
-        result = s[2000, 3]
-
-        # TODO(wesm): unused?
-        # result2 = s.loc[2000, 3]
-
-        expected = s.reindex(s.index[42:65])
-        expected.index = expected.index.droplevel(0).droplevel(0)
-        tm.assert_series_equal(result, expected)
+    # generator
+    result = s[(x > 0 for x in s)]
+    expected = s[s > 0]
+    tm.assert_series_equal(result, expected)
 
-        result = s[2000, 3, 10]
-        expected = s[49]
-        assert result == expected
 
-        # fancy
-        expected = s.reindex(s.index[49:51])
-        result = s.loc[[(2000, 3, 10), (2000, 3, 13)]]
-        tm.assert_series_equal(result, expected)
+def test_frame_getitem_multicolumn_empty_level():
+    f = DataFrame({'a': ['1', '2', '3'], 'b': ['2', '3', '4']})
+    f.columns = [['level1 item1', 'level1 item2'], ['', 'level2 item2'],
+                 ['level3 item1', 'level3 item2']]
 
-        with catch_warnings(record=True):
-            simplefilter("ignore", DeprecationWarning)
-            result = s.ix[[(2000, 3, 10), (2000, 3, 13)]]
-        tm.assert_series_equal(result, expected)
+    result = f['level1 item1']
+    expected = DataFrame([['1'], ['2'], ['3']], index=f.index,
+                         columns=['level3 item1'])
+    tm.assert_frame_equal(result, expected)
 
-        # key error
-        pytest.raises(KeyError, s.__getitem__, (2000, 3, 4))
 
-    def test_series_getitem_corner(
-            self, multiindex_year_month_day_dataframe_random_data):
-        ymd = multiindex_year_month_day_dataframe_random_data
-        s = ymd['A']
+@pytest.mark.filterwarnings("ignore:\\n.ix:DeprecationWarning")
+def test_getitem_tuple_plus_slice():
+    # GH #671
+    df = DataFrame({'a': lrange(10),
+                    'b': lrange(10),
+                    'c': np.random.randn(10),
+                    'd': np.random.randn(10)})
 
-        # don't segfault, GH #495
-        # out of bounds access
-        pytest.raises(IndexError, s.__getitem__, len(ymd))
+    idf = df.set_index(['a', 'b'])
 
-        # generator
-        result = s[(x > 0 for x in s)]
-        expected = s[s > 0]
-        tm.assert_series_equal(result, expected)
+    result = idf.loc[(0, 0), :]
+    expected = idf.loc[0, 0]
+    expected2 = idf.xs((0, 0))
+    expected3 = idf.ix[0, 0]
 
-    def test_frame_getitem_multicolumn_empty_level(self):
-        f = DataFrame({'a': ['1', '2', '3'], 'b': ['2', '3', '4']})
-        f.columns = [['level1 item1', 'level1 item2'], ['', 'level2 item2'],
-                     ['level3 item1', 'level3 item2']]
+    tm.assert_series_equal(result, expected)
+    tm.assert_series_equal(result, expected2)
+    tm.assert_series_equal(result, expected3)
 
-        result = f['level1 item1']
-        expected = DataFrame([['1'], ['2'], ['3']], index=f.index,
-                             columns=['level3 item1'])
-        tm.assert_frame_equal(result, expected)
 
-    def test_getitem_tuple_plus_slice(self):
-        # GH #671
-        df = DataFrame({'a': lrange(10),
-                        'b': lrange(10),
-                        'c': np.random.randn(10),
-                        'd': np.random.randn(10)})
+def test_getitem_toplevel(multiindex_dataframe_random_data):
+    frame = multiindex_dataframe_random_data
+    df = frame.T
 
-        idf = df.set_index(['a', 'b'])
+    result = df['foo']
+    expected = df.reindex(columns=df.columns[:3])
+    expected.columns = expected.columns.droplevel(0)
+    tm.assert_frame_equal(result, expected)
 
-        result = idf.loc[(0, 0), :]
-        expected = idf.loc[0, 0]
-        expected2 = idf.xs((0, 0))
-        with catch_warnings(record=True):
-            simplefilter("ignore", DeprecationWarning)
-            expected3 = idf.ix[0, 0]
+    result = df['bar']
+    result2 = df.loc[:, 'bar']
 
-        tm.assert_series_equal(result, expected)
-        tm.assert_series_equal(result, expected2)
-        tm.assert_series_equal(result, expected3)
+    expected = df.reindex(columns=df.columns[3:5])
+    expected.columns = expected.columns.droplevel(0)
+    tm.assert_frame_equal(result, expected)
+    tm.assert_frame_equal(result, result2)
 
-    def test_getitem_toplevel(self, multiindex_dataframe_random_data):
-        frame = multiindex_dataframe_random_data
-        df = frame.T
 
-        result = df['foo']
-        expected = df.reindex(columns=df.columns[:3])
-        expected.columns = expected.columns.droplevel(0)
-        tm.assert_frame_equal(result, expected)
+def test_getitem_int(multiindex_dataframe_random_data):
+    levels = [[0, 1], [0, 1, 2]]
+    codes = [[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]]
+    index = MultiIndex(levels=levels, codes=codes)
 
-        result = df['bar']
-        result2 = df.loc[:, 'bar']
+    frame = DataFrame(np.random.randn(6, 2), index=index)
 
-        expected = df.reindex(columns=df.columns[3:5])
-        expected.columns = expected.columns.droplevel(0)
-        tm.assert_frame_equal(result, expected)
-        tm.assert_frame_equal(result, result2)
+    result = frame.loc[1]
+    expected = frame[-3:]
+    expected.index = expected.index.droplevel(0)
+    tm.assert_frame_equal(result, expected)
 
-    def test_getitem_int(self, multiindex_dataframe_random_data):
-        levels = [[0, 1], [0, 1, 2]]
-        codes = [[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]]
-        index = MultiIndex(levels=levels, codes=codes)
+    # raises exception
+    msg = "3"
+    with pytest.raises(KeyError, match=msg):
+        frame.loc.__getitem__(3)
 
-        frame = DataFrame(np.random.randn(6, 2), index=index)
+    # however this will work
+    frame = multiindex_dataframe_random_data
+    result = frame.iloc[2]
+    expected = frame.xs(frame.index[2])
+    tm.assert_series_equal(result, expected)
 
-        result = frame.loc[1]
-        expected = frame[-3:]
-        expected.index = expected.index.droplevel(0)
-        tm.assert_frame_equal(result, expected)
 
-        # raises exception
-        pytest.raises(KeyError, frame.loc.__getitem__, 3)
+def test_frame_getitem_view(multiindex_dataframe_random_data):
+    frame = multiindex_dataframe_random_data
+    df = frame.T.copy()
 
-        # however this will work
-        frame = multiindex_dataframe_random_data
-        result = frame.iloc[2]
-        expected = frame.xs(frame.index[2])
-        tm.assert_series_equal(result, expected)
+    # this works because we are modifying the underlying array
+    # really a no-no
+    df['foo'].values[:] = 0
+    assert (df['foo'].values == 0).all()
 
-    def test_frame_getitem_view(self, multiindex_dataframe_random_data):
-        frame = multiindex_dataframe_random_data
-        df = frame.T.copy()
+    # but not if it's mixed-type
+    df['foo', 'four'] = 'foo'
+    df = df.sort_index(level=0, axis=1)
 
-        # this works because we are modifying the underlying array
-        # really a no-no
-        df['foo'].values[:] = 0
-        assert (df['foo'].values == 0).all()
+    # this will work, but will raise/warn as its chained assignment
+    def f():
+        df['foo']['one'] = 2
+        return df
 
-        # but not if it's mixed-type
-        df['foo', 'four'] = 'foo'
-        df = df.sort_index(level=0, axis=1)
+    msg = "A value is trying to be set on a copy of a slice from a DataFrame"
+    with pytest.raises(com.SettingWithCopyError, match=msg):
+        df['foo']['one'] = 2
 
-        # this will work, but will raise/warn as its chained assignment
-        def f():
-            df['foo']['one'] = 2
-            return df
+    try:
+        df = f()
+    except ValueError:
+        pass
+    assert (df['foo', 'one'] == 0).all()
 
-        pytest.raises(com.SettingWithCopyError, f)
 
-        try:
-            df = f()
-        except ValueError:
-            pass
-        assert (df['foo', 'one'] == 0).all()
+def test_getitem_lowerdim_corner(multiindex_dataframe_random_data):
+    frame = multiindex_dataframe_random_data
+    msg = "11"
+    with pytest.raises(KeyError, match=msg):
+        frame.loc.__getitem__((('bar', 'three'), 'B'))
 
-    def test_getitem_lowerdim_corner(self, multiindex_dataframe_random_data):
-        frame = multiindex_dataframe_random_data
-        pytest.raises(KeyError, frame.loc.__getitem__,
-                      (('bar', 'three'), 'B'))
+    # in theory should be inserting in a sorted space????
+    frame.loc[('bar', 'three'), 'B'] = 0
+    assert frame.sort_index().loc[('bar', 'three'), 'B'] == 0
 
-        # in theory should be inserting in a sorted space????
-        frame.loc[('bar', 'three'), 'B'] = 0
-        assert frame.sort_index().loc[('bar', 'three'), 'B'] == 0
 
-    @pytest.mark.parametrize('unicode_strings', [True, False])
-    def test_mixed_depth_get(self, unicode_strings):
-        # If unicode_strings is True, the column labels in dataframe
-        # construction will use unicode strings in Python 2 (pull request
-        # #17099).
+@pytest.mark.parametrize('unicode_strings', [True, False])
+def test_mixed_depth_get(unicode_strings):
+    # If unicode_strings is True, the column labels in dataframe
+    # construction will use unicode strings in Python 2 (pull request
+    # #17099).
 
-        arrays = [['a', 'top', 'top', 'routine1', 'routine1', 'routine2'],
-                  ['', 'OD', 'OD', 'result1', 'result2', 'result1'],
-                  ['', 'wx', 'wy', '', '', '']]
+    arrays = [['a', 'top', 'top', 'routine1', 'routine1', 'routine2'],
+              ['', 'OD', 'OD', 'result1', 'result2', 'result1'],
+              ['', 'wx', 'wy', '', '', '']]
 
-        if unicode_strings:
-            arrays = [[u(s) for s in arr] for arr in arrays]
+    if unicode_strings:
+        arrays = [[u(s) for s in arr] for arr in arrays]
 
-        tuples = sorted(zip(*arrays))
-        index = MultiIndex.from_tuples(tuples)
-        df = DataFrame(np.random.randn(4, 6), columns=index)
+    tuples = sorted(zip(*arrays))
+    index = MultiIndex.from_tuples(tuples)
+    df = DataFrame(np.random.randn(4, 6), columns=index)
 
-        result = df['a']
-        expected = df['a', '', ''].rename('a')
-        tm.assert_series_equal(result, expected)
+    result = df['a']
+    expected = df['a', '', ''].rename('a')
+    tm.assert_series_equal(result, expected)
 
-        result = df['routine1', 'result1']
-        expected = df['routine1', 'result1', '']
-        expected = expected.rename(('routine1', 'result1'))
-        tm.assert_series_equal(result, expected)
+    result = df['routine1', 'result1']
+    expected = df['routine1', 'result1', '']
+    expected = expected.rename(('routine1', 'result1'))
+    tm.assert_series_equal(result, expected)
diff --git a/pandas/tests/series/test_analytics.py b/pandas/tests/series/test_analytics.py
index a9c8e855cd324..81d60aba44b0f 100644
--- a/pandas/tests/series/test_analytics.py
+++ b/pandas/tests/series/test_analytics.py
@@ -924,8 +924,10 @@ def test_matmul(self):
     def test_clip(self, datetime_series):
         val = datetime_series.median()
 
-        assert datetime_series.clip_lower(val).min() == val
-        assert datetime_series.clip_upper(val).max() == val
+        with tm.assert_produces_warning(FutureWarning):
+            assert datetime_series.clip_lower(val).min() == val
+        with tm.assert_produces_warning(FutureWarning):
+            assert datetime_series.clip_upper(val).max() == val
 
         assert datetime_series.clip(lower=val).min() == val
         assert datetime_series.clip(upper=val).max() == val
@@ -943,8 +945,10 @@ def test_clip_types_and_nulls(self):
 
         for s in sers:
             thresh = s[2]
-            lower = s.clip_lower(thresh)
-            upper = s.clip_upper(thresh)
+            with tm.assert_produces_warning(FutureWarning):
+                lower = s.clip_lower(thresh)
+            with tm.assert_produces_warning(FutureWarning):
+                upper = s.clip_upper(thresh)
             assert lower[notna(lower)].min() == thresh
             assert upper[notna(upper)].max() == thresh
             assert list(isna(s)) == list(isna(lower))
@@ -971,8 +975,12 @@ def test_clip_against_series(self):
         s = Series([1.0, 1.0, 4.0])
         threshold = Series([1.0, 2.0, 3.0])
 
-        assert_series_equal(s.clip_lower(threshold), Series([1.0, 2.0, 4.0]))
-        assert_series_equal(s.clip_upper(threshold), Series([1.0, 1.0, 3.0]))
+        with tm.assert_produces_warning(FutureWarning):
+            assert_series_equal(s.clip_lower(threshold),
+                                Series([1.0, 2.0, 4.0]))
+        with tm.assert_produces_warning(FutureWarning):
+            assert_series_equal(s.clip_upper(threshold),
+                                Series([1.0, 1.0, 3.0]))
 
         lower = Series([1.0, 2.0, 3.0])
         upper = Series([1.5, 2.5, 3.5])
diff --git a/scripts/validate_docstrings.py b/scripts/validate_docstrings.py
index 0f553cc4f2fe8..ecb02071c5bb6 100755
--- a/scripts/validate_docstrings.py
+++ b/scripts/validate_docstrings.py
@@ -174,6 +174,7 @@ def get_api_items(api_doc_fd):
         The name of the subsection in the API page where the object item is
         located.
     """
+    current_module = 'pandas'
     previous_line = current_section = current_subsection = ''
     position = None
     for line in api_doc_fd:
diff --git a/setup.cfg b/setup.cfg
index bfffe56e088eb..30b4d13bd0a66 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -32,10 +32,18 @@ exclude =
 
 [flake8-rst]
 bootstrap =
-    import pandas as pd
     import numpy as np
+    import pandas as pd
+    np  # avoiding error when importing again numpy or pandas
+    pd  # (in some cases we want to do it to show users)
 ignore = E402,  # module level import not at top of file
          W503,  # line break before binary operator
+         # Classes/functions in different blocks can generate those errors
+         E302,  # expected 2 blank lines, found 0
+         E305,  # expected 2 blank lines after class or function definition, found 0
+         # We use semicolon at the end to avoid displaying plot objects
+         E703,  # statement ends with a semicolon
+
 exclude =
     doc/source/whatsnew/v0.7.0.rst
     doc/source/whatsnew/v0.7.3.rst
@@ -63,31 +71,16 @@ exclude =
     doc/source/whatsnew/v0.19.0.rst
     doc/source/whatsnew/v0.20.0.rst
     doc/source/whatsnew/v0.21.0.rst
-    doc/source/whatsnew/v0.22.0.rst
-    doc/source/whatsnew/v0.23.0.rst
     doc/source/whatsnew/v0.23.1.rst
     doc/source/whatsnew/v0.23.2.rst
-    doc/source/whatsnew/v0.24.0.rst
-    doc/source/10min.rst
-    doc/source/advanced.rst
     doc/source/basics.rst
-    doc/source/categorical.rst
     doc/source/contributing_docstring.rst
-    doc/source/contributing.rst
-    doc/source/dsintro.rst
     doc/source/enhancingperf.rst
-    doc/source/extending.rst
     doc/source/groupby.rst
     doc/source/indexing.rst
-    doc/source/merging.rst
     doc/source/missing_data.rst
     doc/source/options.rst
     doc/source/release.rst
-    doc/source/comparison_with_sas.rst
-    doc/source/comparison_with_sql.rst
-    doc/source/comparison_with_stata.rst
-    doc/source/reshaping.rst
-    doc/source/visualization.rst
 
 
 [yapf]
diff --git a/tmp.xlsx b/tmp.xlsx
deleted file mode 100644
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