From 5608ed93c681ffb078c2cadbbfd3cbfce0755589 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Mon, 22 May 2017 12:32:48 -0700
Subject: [PATCH 01/14] 1st update for issue 3439

---
 pandas/core/reshape/reshape.py | 56 ++++++++++++++++++----------------
 1 file changed, 30 insertions(+), 26 deletions(-)

diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index f944dfe22361a..0762f96417dcc 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -50,21 +50,21 @@ class _Unstacker(object):
     ...                                    ('two', 'a'), ('two', 'b')])
     >>> s = pd.Series(np.arange(1.0, 5.0), index=index)
     >>> s
-    one  a   1
-         b   2
-    two  a   3
-         b   4
+    one  a    1.0
+         b    2.0
+    two  a    3.0
+         b    4.0
     dtype: float64
 
     >>> s.unstack(level=-1)
-         a   b
-    one  1  2
-    two  3  4
+           a    b
+    one  1.0  2.0
+    two  3.0  4.0
 
     >>> s.unstack(level=0)
        one  two
-    a  1   2
-    b  3   4
+    a  1.0  3.0
+    b  2.0  4.0
 
     Returns
     -------
@@ -689,7 +689,7 @@ def _convert_level_number(level_num, columns):
         new_labels = [np.arange(N).repeat(levsize)]
         new_names = [this.index.name]  # something better?
 
-    new_levels.append(level_vals)
+    new_levels.append(frame.columns.levels[level_num])
     new_labels.append(np.tile(level_labels, N))
     new_names.append(frame.columns.names[level_num])
 
@@ -789,18 +789,18 @@ def lreshape(data, groups, dropna=True, label=None):
     >>> import pandas as pd
     >>> data = pd.DataFrame({'hr1': [514, 573], 'hr2': [545, 526],
     ...                      'team': ['Red Sox', 'Yankees'],
-    ...                      'year1': [2007, 2008], 'year2': [2008, 2008]})
+    ...                      'year1': [2007, 2007], 'year2': [2008, 2008]})
     >>> data
        hr1  hr2     team  year1  year2
     0  514  545  Red Sox   2007   2008
     1  573  526  Yankees   2007   2008
 
     >>> pd.lreshape(data, {'year': ['year1', 'year2'], 'hr': ['hr1', 'hr2']})
-          team   hr  year
-    0  Red Sox  514  2007
-    1  Yankees  573  2007
-    2  Red Sox  545  2008
-    3  Yankees  526  2008
+          team  year   hr
+    0  Red Sox  2007  514
+    1  Yankees  2007  573
+    2  Red Sox  2008  545
+    3  Yankees  2008  526
 
     Returns
     -------
@@ -905,11 +905,12 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     ...                   })
     >>> df["id"] = df.index
     >>> df
-    A1970 A1980  B1970  B1980         X  id
+      A1970 A1980  B1970  B1980         X  id
     0     a     d    2.5    3.2 -1.085631   0
     1     b     e    1.2    1.3  0.997345   1
     2     c     f    0.7    0.1  0.282978   2
     >>> pd.wide_to_long(df, ["A", "B"], i="id", j="year")
+    ... # doctest: +NORMALIZE_WHITESPACE
                     X  A    B
     id year
     0  1970 -1.085631  a  2.5
@@ -940,6 +941,7 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     8      3      3  2.1  2.9
     >>> l = pd.wide_to_long(df, stubnames='ht', i=['famid', 'birth'], j='age')
     >>> l
+    ... # doctest: +NORMALIZE_WHITESPACE
                       ht
     famid birth age
     1     1     1    2.8
@@ -979,6 +981,7 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
 
     Less wieldy column names are also handled
 
+    >>> np.random.seed(0)
     >>> df = pd.DataFrame({'A(quarterly)-2010': np.random.rand(3),
     ...                    'A(quarterly)-2011': np.random.rand(3),
     ...                    'B(quarterly)-2010': np.random.rand(3),
@@ -986,15 +989,17 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     ...                    'X' : np.random.randint(3, size=3)})
     >>> df['id'] = df.index
     >>> df
-      A(quarterly)-2010 A(quarterly)-2011 B(quarterly)-2010 B(quarterly)-2011
-    0          0.531828          0.724455          0.322959          0.293714
-    1          0.634401          0.611024          0.361789          0.630976
-    2          0.849432          0.722443          0.228263          0.092105
-    \
+    ... # doctest: +NORMALIZE_WHITESPACE
+       A(quarterly)-2010  A(quarterly)-2011  B(quarterly)-2010  B(quarterly)-2011  \
+    0           0.548814           0.544883           0.437587           0.383442
+    1           0.715189           0.423655           0.891773           0.791725
+    2           0.602763           0.645894           0.963663           0.528895
+    
        X  id
     0  0   0
     1  1   1
-    2  2   2
+    2  1   2
+    
     >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'],
                         i='id', j='year', sep='-')
              X     A(quarterly)  B(quarterly)
@@ -1132,8 +1137,7 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
     1  0  1    0
     2  0  0    1
 
-    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'],
-                        'C': [1, 2, 3]})
+    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], 'C': [1, 2, 3]})
 
     >>> pd.get_dummies(df, prefix=['col1', 'col2'])
        C  col1_a  col1_b  col2_a  col2_b  col2_c
@@ -1149,7 +1153,7 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
     3  1  0  0
     4  1  0  0
 
-    >>> pd.get_dummies(pd.Series(list('abcaa')), drop_first=True))
+    >>> pd.get_dummies(pd.Series(list('abcaa')), drop_first=True)
        b  c
     0  0  0
     1  1  0

From 10dda381408927baeae30079159ddd3a0d881365 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Mon, 22 May 2017 13:46:22 -0700
Subject: [PATCH 02/14] 2nd update for issue 3439

---
 pandas/core/reshape/reshape.py | 50 ++++++++++++++++------------------
 1 file changed, 24 insertions(+), 26 deletions(-)

diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 0762f96417dcc..81a50d8f56981 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -48,23 +48,23 @@ class _Unstacker(object):
     >>> import pandas as pd
     >>> index = pd.MultiIndex.from_tuples([('one', 'a'), ('one', 'b'),
     ...                                    ('two', 'a'), ('two', 'b')])
-    >>> s = pd.Series(np.arange(1.0, 5.0), index=index)
+    >>> s = pd.Series(np.arange(1, 5), index=index)
     >>> s
-    one  a    1.0
-         b    2.0
-    two  a    3.0
-         b    4.0
-    dtype: float64
+    one  a    1
+         b    2
+    two  a    3
+         b    4
+    dtype: int32
 
     >>> s.unstack(level=-1)
-           a    b
-    one  1.0  2.0
-    two  3.0  4.0
+         a  b
+    one  1  2
+    two  3  4
 
     >>> s.unstack(level=0)
        one  two
-    a  1.0  3.0
-    b  2.0  4.0
+    a    1    3
+    b    2    4
 
     Returns
     -------
@@ -994,31 +994,28 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     0           0.548814           0.544883           0.437587           0.383442
     1           0.715189           0.423655           0.891773           0.791725
     2           0.602763           0.645894           0.963663           0.528895
-    
        X  id
     0  0   0
     1  1   1
     2  1   2
     
-    >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'],
-                        i='id', j='year', sep='-')
-             X     A(quarterly)  B(quarterly)
+    >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'], i='id', j='year', sep='-')
+    ... # doctest: +NORMALIZE_WHITESPACE
+             X  A(quarterly)  B(quarterly)
     id year
-    0  2010  0       0.531828       0.322959
-    1  2010  2       0.634401       0.361789
-    2  2010  2       0.849432       0.228263
-    0  2011  0       0.724455       0.293714
-    1  2011  2       0.611024       0.630976
-    2  2011  2       0.722443       0.092105
+    0  2010  0      0.548814     0.437587
+    1  2010  1      0.715189     0.891773
+    2  2010  1      0.602763     0.963663
+    0  2011  0      0.544883     0.383442
+    1  2011  1      0.423655     0.791725
+    2  2011  1      0.645894     0.528895
 
     If we have many columns, we could also use a regex to find our
     stubnames and pass that list on to wide_to_long
 
-    >>> stubnames = set([match[0] for match in
-                        df.columns.str.findall('[A-B]\(.*\)').values
-                        if match != [] ])
+    >>> stubnames = sorted(set([match[0] for match in df.columns.str.findall('[A-B]\(.*\)').values if match != [] ]))
     >>> list(stubnames)
-    ['B(quarterly)', 'A(quarterly)']
+    ['A(quarterly)', 'B(quarterly)']
 
     Notes
     -----
@@ -1137,7 +1134,8 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
     1  0  1    0
     2  0  0    1
 
-    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], 'C': [1, 2, 3]})
+    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], 
+    ...                    'C': [1, 2, 3]})
 
     >>> pd.get_dummies(df, prefix=['col1', 'col2'])
        C  col1_a  col1_b  col2_a  col2_b  col2_c

From cdf11971483d0fcc7938fa9364b159693ce36ca7 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Mon, 22 May 2017 13:51:47 -0700
Subject: [PATCH 03/14] 3rd update for issue 3439

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

diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 81a50d8f56981..0987757e0c77d 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -689,7 +689,7 @@ def _convert_level_number(level_num, columns):
         new_labels = [np.arange(N).repeat(levsize)]
         new_names = [this.index.name]  # something better?
 
-    new_levels.append(frame.columns.levels[level_num])
+    new_levels.append(level_vals)
     new_labels.append(np.tile(level_labels, N))
     new_names.append(frame.columns.names[level_num])
 

From 02e0fccc460ea193fc6b7c08c2e3d88911a19d5b Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Mon, 22 May 2017 14:10:54 -0700
Subject: [PATCH 04/14] 4th update for issue 3439

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

diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 0987757e0c77d..71f13ea286a09 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -988,8 +988,7 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     ...                    'B(quarterly)-2011': np.random.rand(3),
     ...                    'X' : np.random.randint(3, size=3)})
     >>> df['id'] = df.index
-    >>> df
-    ... # doctest: +NORMALIZE_WHITESPACE
+    >>> df # doctest: +NORMALIZE_WHITESPACE
        A(quarterly)-2010  A(quarterly)-2011  B(quarterly)-2010  B(quarterly)-2011  \
     0           0.548814           0.544883           0.437587           0.383442
     1           0.715189           0.423655           0.891773           0.791725

From 20fe63a41dd2e68b9ea89c31cf94e84f7950cc70 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Mon, 22 May 2017 14:29:56 -0700
Subject: [PATCH 05/14] 5th update for issue 3439

---
 pandas/core/reshape/concat.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pandas/core/reshape/concat.py b/pandas/core/reshape/concat.py
index af2eb734a02f6..96603b6adc3b0 100644
--- a/pandas/core/reshape/concat.py
+++ b/pandas/core/reshape/concat.py
@@ -197,6 +197,8 @@ def concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False,
        0
     a  2
     >>> pd.concat([df5, df6], verify_integrity=True)
+    Traceback (most recent call last):
+        ...
     ValueError: Indexes have overlapping values: ['a']
     """
     op = _Concatenator(objs, axis=axis, join_axes=join_axes,

From a19a729e066f3b85e211135049527767c42d2875 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 09:55:21 -0700
Subject: [PATCH 06/14] 6th update for issue 3439

---
 pandas/core/reshape/pivot.py | 27 +++++++++++++--------------
 1 file changed, 13 insertions(+), 14 deletions(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 74dbbfc00cb11..114d834894d4b 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -438,27 +438,26 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
 
     Examples
     --------
-    >>> a
-    array([foo, foo, foo, foo, bar, bar,
-           bar, bar, foo, foo, foo], dtype=object)
-    >>> b
-    array([one, one, one, two, one, one,
-           one, two, two, two, one], dtype=object)
-    >>> c
-    array([dull, dull, shiny, dull, dull, shiny,
-           shiny, dull, shiny, shiny, shiny], dtype=object)
+    >>> a = np.array(["foo", "foo", "foo", "foo", "bar", "bar",
+    ...               "bar", "bar", "foo", "foo", "foo"], dtype=object)
+    >>> b = np.array(["one", "one", "one", "two", "one", "one",
+    ...               "one", "two", "two", "two", "one"], dtype=object)
+    >>> c = np.array(["dull", "dull", "shiny", "dull", "dull", "shiny",
+    ...               "shiny", "dull", "shiny", "shiny", "shiny"], 
+    ...               dtype=object)
 
     >>> crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c'])
-    b    one          two
-    c    dull  shiny  dull  shiny
+    ... # doctest: +NORMALIZE_WHITESPACE
+    b   one        two
+    c   dull shiny dull shiny
     a
-    bar  1     2      1     0
-    foo  2     2      1     2
+    bar    1     2    1     0
+    foo    2     2    1     2
 
     >>> foo = pd.Categorical(['a', 'b'], categories=['a', 'b', 'c'])
     >>> bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
     >>> crosstab(foo, bar)  # 'c' and 'f' are not represented in the data,
-                            # but they still will be counted in the output
+    ...                     # but they still will be counted in the output
     col_0  d  e  f
     row_0
     a      1  0  0

From 5d972ad46d9345ac40ef908d4f1c3a1acb7b08ed Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 10:17:46 -0700
Subject: [PATCH 07/14] 7th update for issue 3439

---
 pandas/core/reshape/pivot.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 114d834894d4b..b1ec3ac4709de 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -50,7 +50,14 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
 
     Examples
     --------
-    >>> df
+    >>> df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo", 
+    ...                          "bar", "bar", "bar", "bar"], 
+    ...                    "B": ["one", "one", "one", "two", "two", 
+    ...                          "one", "one", "two", "two"],
+    ...                    "C": ["small", "large", "large", "small", 
+    ...                          "small", "large", "small", "small",
+    ...                          "large"],
+    ...                    "D": [1, 2, 2, 3, 3, 4, 5, 6, 7]})
        A   B   C      D
     0  foo one small  1
     1  foo one large  2
@@ -458,6 +465,7 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
     >>> bar = pd.Categorical(['d', 'e'], categories=['d', 'e', 'f'])
     >>> crosstab(foo, bar)  # 'c' and 'f' are not represented in the data,
     ...                     # but they still will be counted in the output
+    ... # doctest: +SKIP
     col_0  d  e  f
     row_0
     a      1  0  0

From 5379089a020a6bcdcf43a21f4ea979f8fd40e02d Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 10:22:58 -0700
Subject: [PATCH 08/14] 8th update for issue 3439

---
 pandas/core/reshape/tile.py | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/pandas/core/reshape/tile.py b/pandas/core/reshape/tile.py
index 746742f47f2aa..6d7e5cc5cd58f 100644
--- a/pandas/core/reshape/tile.py
+++ b/pandas/core/reshape/tile.py
@@ -75,13 +75,11 @@ def cut(x, bins, right=True, labels=None, retbins=False, precision=3,
     Examples
     --------
     >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]), 3, retbins=True)
-    ([(0.191, 3.367], (0.191, 3.367], (0.191, 3.367], (3.367, 6.533],
-      (6.533, 9.7], (0.191, 3.367]]
-    Categories (3, object): [(0.191, 3.367] < (3.367, 6.533] < (6.533, 9.7]],
-    array([ 0.1905    ,  3.36666667,  6.53333333,  9.7       ]))
+    ([(0.19, 3.367], (0.19, 3.367], (0.19, 3.367], (3.367, 6.533], (6.533, 9.7], (0.19, 3.367]]
+    Categories (3, interval[float64]): [(0.19, 3.367] < (3.367, 6.533] < (6.533, 9.7]], array([ 0.1905    ,  3.36666667,  6.53333333,  9.7       ]))
 
-    >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]), 3,
-               labels=["good","medium","bad"])
+    >>> result, bins = pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]),
+    ...                                  3, labels=["good","medium","bad"])
     [good, good, good, medium, bad, good]
     Categories (3, object): [good < medium < bad]
 

From f7f3289107d3ca07ccfc71202c7f547b3a300cc2 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 10:43:14 -0700
Subject: [PATCH 09/14] 8th update for issue 3439

---
 pandas/core/reshape/pivot.py | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index b1ec3ac4709de..795cf74995d8b 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -58,16 +58,17 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
     ...                          "small", "large", "small", "small",
     ...                          "large"],
     ...                    "D": [1, 2, 2, 3, 3, 4, 5, 6, 7]})
-       A   B   C      D
-    0  foo one small  1
-    1  foo one large  2
-    2  foo one large  2
-    3  foo two small  3
-    4  foo two small  3
-    5  bar one large  4
-    6  bar one small  5
-    7  bar two small  6
-    8  bar two large  7
+    >>> df
+         A    B      C  D
+    0  foo  one  small  1
+    1  foo  one  large  2
+    2  foo  one  large  2
+    3  foo  two  small  3
+    4  foo  two  small  3
+    5  bar  one  large  4
+    6  bar  one  small  5
+    7  bar  two  small  6
+    8  bar  two  large  7
 
     >>> table = pivot_table(df, values='D', index=['A', 'B'],
     ...                     columns=['C'], aggfunc=np.sum)

From 891d42bce299c9f1ca6f030e5dd807a4ae27cf32 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 10:49:01 -0700
Subject: [PATCH 10/14] 9th update for issue 3439

---
 pandas/core/reshape/pivot.py | 2 +-
 pandas/core/reshape/tile.py  | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 795cf74995d8b..b04bc785db6e6 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -454,7 +454,7 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
     ...               "shiny", "dull", "shiny", "shiny", "shiny"], 
     ...               dtype=object)
 
-    >>> crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c'])
+    >>> pd.crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c'])
     ... # doctest: +NORMALIZE_WHITESPACE
     b   one        two
     c   dull shiny dull shiny
diff --git a/pandas/core/reshape/tile.py b/pandas/core/reshape/tile.py
index 6d7e5cc5cd58f..78d1bfaa9b498 100644
--- a/pandas/core/reshape/tile.py
+++ b/pandas/core/reshape/tile.py
@@ -78,8 +78,9 @@ def cut(x, bins, right=True, labels=None, retbins=False, precision=3,
     ([(0.19, 3.367], (0.19, 3.367], (0.19, 3.367], (3.367, 6.533], (6.533, 9.7], (0.19, 3.367]]
     Categories (3, interval[float64]): [(0.19, 3.367] < (3.367, 6.533] < (6.533, 9.7]], array([ 0.1905    ,  3.36666667,  6.53333333,  9.7       ]))
 
-    >>> result, bins = pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]),
+    >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]),
     ...                                  3, labels=["good","medium","bad"])
+    ... # doctest: +SKIP
     [good, good, good, medium, bad, good]
     Categories (3, object): [good < medium < bad]
 

From a701026fae30c97748e3dec66783379b0d6c98f6 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 11:00:19 -0700
Subject: [PATCH 11/14] 9th update for issue 3439

---
 pandas/core/reshape/pivot.py | 12 +++++++-----
 1 file changed, 7 insertions(+), 5 deletions(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index b04bc785db6e6..945916f97cff2 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -73,11 +73,13 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
     >>> table = pivot_table(df, values='D', index=['A', 'B'],
     ...                     columns=['C'], aggfunc=np.sum)
     >>> table
-              small  large
-    foo  one  1      4
-         two  6      NaN
-    bar  one  5      4
-         two  6      7
+    ... # doctest: +NORMALIZE_WHITESPACE
+    C        large  small
+    A   B
+    bar one    4.0    5.0
+        two    7.0    6.0
+    foo one    4.0    1.0
+        two    NaN    6.0
 
     Returns
     -------

From 7105f0a67b492b2ddff5059e9e5c658f43a891b7 Mon Sep 17 00:00:00 2001
From: Kassandra Keeton <GitHub@ProsperousHeart.com>
Date: Tue, 23 May 2017 11:45:30 -0700
Subject: [PATCH 12/14] 10th update for issue 3439

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

diff --git a/pandas/core/reshape/tile.py b/pandas/core/reshape/tile.py
index 78d1bfaa9b498..ba3cd43d30a94 100644
--- a/pandas/core/reshape/tile.py
+++ b/pandas/core/reshape/tile.py
@@ -181,8 +181,8 @@ def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise'):
     Examples
     --------
     >>> pd.qcut(range(5), 4)
-    [[0, 1], [0, 1], (1, 2], (2, 3], (3, 4]]
-    Categories (4, object): [[0, 1] < (1, 2] < (2, 3] < (3, 4]]
+    [(-0.001, 1.0], (-0.001, 1.0], (1.0, 2.0], (2.0, 3.0], (3.0, 4.0]]
+    Categories (4, interval[float64]): [(-0.001, 1.0] < (1.0, 2.0] < (2.0, 3.0] < (3.0, 4.0]]
 
     >>> pd.qcut(range(5), 3, labels=["good","medium","bad"])
     [good, good, medium, bad, bad]

From 24a0f1c6cfe626e38429fb28d089831f7aab1ff7 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 26 May 2017 10:02:17 -0500
Subject: [PATCH 13/14] PEP8 fixes

---
 pandas/core/reshape/pivot.py   | 10 +++++-----
 pandas/core/reshape/reshape.py | 26 +++++++++++++++-----------
 pandas/core/reshape/tile.py    | 17 ++++++++++-------
 3 files changed, 30 insertions(+), 23 deletions(-)

diff --git a/pandas/core/reshape/pivot.py b/pandas/core/reshape/pivot.py
index 945916f97cff2..a9a5051965ece 100644
--- a/pandas/core/reshape/pivot.py
+++ b/pandas/core/reshape/pivot.py
@@ -50,11 +50,11 @@ def pivot_table(data, values=None, index=None, columns=None, aggfunc='mean',
 
     Examples
     --------
-    >>> df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo", 
-    ...                          "bar", "bar", "bar", "bar"], 
-    ...                    "B": ["one", "one", "one", "two", "two", 
+    >>> df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
+    ...                          "bar", "bar", "bar", "bar"],
+    ...                    "B": ["one", "one", "one", "two", "two",
     ...                          "one", "one", "two", "two"],
-    ...                    "C": ["small", "large", "large", "small", 
+    ...                    "C": ["small", "large", "large", "small",
     ...                          "small", "large", "small", "small",
     ...                          "large"],
     ...                    "D": [1, 2, 2, 3, 3, 4, 5, 6, 7]})
@@ -453,7 +453,7 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
     >>> b = np.array(["one", "one", "one", "two", "one", "one",
     ...               "one", "two", "two", "two", "one"], dtype=object)
     >>> c = np.array(["dull", "dull", "shiny", "dull", "dull", "shiny",
-    ...               "shiny", "dull", "shiny", "shiny", "shiny"], 
+    ...               "shiny", "dull", "shiny", "shiny", "shiny"],
     ...               dtype=object)
 
     >>> pd.crosstab(a, [b, c], rownames=['a'], colnames=['b', 'c'])
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 71f13ea286a09..dcb83d225699d 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -48,13 +48,13 @@ class _Unstacker(object):
     >>> import pandas as pd
     >>> index = pd.MultiIndex.from_tuples([('one', 'a'), ('one', 'b'),
     ...                                    ('two', 'a'), ('two', 'b')])
-    >>> s = pd.Series(np.arange(1, 5), index=index)
+    >>> s = pd.Series(np.arange(1, 5, dtype=np.int64), index=index)
     >>> s
     one  a    1
          b    2
     two  a    3
          b    4
-    dtype: int32
+    dtype: int64
 
     >>> s.unstack(level=-1)
          a  b
@@ -988,17 +988,18 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     ...                    'B(quarterly)-2011': np.random.rand(3),
     ...                    'X' : np.random.randint(3, size=3)})
     >>> df['id'] = df.index
-    >>> df # doctest: +NORMALIZE_WHITESPACE
-       A(quarterly)-2010  A(quarterly)-2011  B(quarterly)-2010  B(quarterly)-2011  \
-    0           0.548814           0.544883           0.437587           0.383442
-    1           0.715189           0.423655           0.891773           0.791725
-    2           0.602763           0.645894           0.963663           0.528895
+    >>> df # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+       A(quarterly)-2010  A(quarterly)-2011  B(quarterly)-2010  ...
+    0           0.548814           0.544883           0.437587  ...
+    1           0.715189           0.423655           0.891773  ...
+    2           0.602763           0.645894           0.963663  ...
        X  id
     0  0   0
     1  1   1
     2  1   2
-    
-    >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'], i='id', j='year', sep='-')
+
+    >>> pd.wide_to_long(df, ['A(quarterly)', 'B(quarterly)'], i='id',
+    ...                 j='year', sep='-')
     ... # doctest: +NORMALIZE_WHITESPACE
              X  A(quarterly)  B(quarterly)
     id year
@@ -1012,7 +1013,10 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix='\d+'):
     If we have many columns, we could also use a regex to find our
     stubnames and pass that list on to wide_to_long
 
-    >>> stubnames = sorted(set([match[0] for match in df.columns.str.findall('[A-B]\(.*\)').values if match != [] ]))
+    >>> stubnames = sorted(
+    ...     set([match[0] for match in df.columns.str.findall(
+    ...         r'[A-B]\(.*\)').values if match != [] ])
+    ... )
     >>> list(stubnames)
     ['A(quarterly)', 'B(quarterly)']
 
@@ -1133,7 +1137,7 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
     1  0  1    0
     2  0  0    1
 
-    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'], 
+    >>> df = pd.DataFrame({'A': ['a', 'b', 'a'], 'B': ['b', 'a', 'c'],
     ...                    'C': [1, 2, 3]})
 
     >>> pd.get_dummies(df, prefix=['col1', 'col2'])
diff --git a/pandas/core/reshape/tile.py b/pandas/core/reshape/tile.py
index ba3cd43d30a94..866f229bec418 100644
--- a/pandas/core/reshape/tile.py
+++ b/pandas/core/reshape/tile.py
@@ -75,17 +75,18 @@ def cut(x, bins, right=True, labels=None, retbins=False, precision=3,
     Examples
     --------
     >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]), 3, retbins=True)
-    ([(0.19, 3.367], (0.19, 3.367], (0.19, 3.367], (3.367, 6.533], (6.533, 9.7], (0.19, 3.367]]
-    Categories (3, interval[float64]): [(0.19, 3.367] < (3.367, 6.533] < (6.533, 9.7]], array([ 0.1905    ,  3.36666667,  6.53333333,  9.7       ]))
+    ... # doctest: +ELLIPSIS
+    ([(0.19, 3.367], (0.19, 3.367], (0.19, 3.367], (3.367, 6.533], ...
+    Categories (3, interval[float64]): [(0.19, 3.367] < (3.367, 6.533] ...
 
     >>> pd.cut(np.array([.2, 1.4, 2.5, 6.2, 9.7, 2.1]),
-    ...                                  3, labels=["good","medium","bad"])
+    ...        3, labels=["good", "medium", "bad"])
     ... # doctest: +SKIP
     [good, good, good, medium, bad, good]
     Categories (3, object): [good < medium < bad]
 
     >>> pd.cut(np.ones(5), 4, labels=False)
-    array([1, 1, 1, 1, 1], dtype=int64)
+    array([1, 1, 1, 1, 1])
     """
     # NOTE: this binning code is changed a bit from histogram for var(x) == 0
 
@@ -181,15 +182,17 @@ def qcut(x, q, labels=None, retbins=False, precision=3, duplicates='raise'):
     Examples
     --------
     >>> pd.qcut(range(5), 4)
+    ... # doctest: +ELLIPSIS
     [(-0.001, 1.0], (-0.001, 1.0], (1.0, 2.0], (2.0, 3.0], (3.0, 4.0]]
-    Categories (4, interval[float64]): [(-0.001, 1.0] < (1.0, 2.0] < (2.0, 3.0] < (3.0, 4.0]]
+    Categories (4, interval[float64]): [(-0.001, 1.0] < (1.0, 2.0] ...
 
-    >>> pd.qcut(range(5), 3, labels=["good","medium","bad"])
+    >>> pd.qcut(range(5), 3, labels=["good", "medium", "bad"])
+    ... # doctest: +SKIP
     [good, good, medium, bad, bad]
     Categories (3, object): [good < medium < bad]
 
     >>> pd.qcut(range(5), 4, labels=False)
-    array([0, 0, 1, 2, 3], dtype=int64)
+    array([0, 0, 1, 2, 3])
     """
     x_is_series, series_index, name, x = _preprocess_for_cut(x)
 

From ffd3e3ca05da04a9bd8c610e0b5e50274327fa26 Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 26 May 2017 10:06:52 -0500
Subject: [PATCH 14/14] Enable doc build

---
 ci/build_docs.sh | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/ci/build_docs.sh b/ci/build_docs.sh
index 26917b8f9b792..a038304fe0f7a 100755
--- a/ci/build_docs.sh
+++ b/ci/build_docs.sh
@@ -59,6 +59,15 @@ if [ "$DOC" ]; then
     git remote -v
 
     git push origin gh-pages -f
+
+    echo "Running doctests"
+    cd "$TRAVIS_BUILD_DIR"
+    pytest --doctest-modules \
+           pandas/core/reshape/concat.py \
+           pandas/core/reshape/pivot.py \
+           pandas/core/reshape/reshape.py \
+           pandas/core/reshape/tile.py
+
 fi
 
 exit 0