From 5bedd60caeb3ebc4278587db3627b6631690cf47 Mon Sep 17 00:00:00 2001
From: alphaCTzo7G <alphaCTzo7G@users.noreply.github.com>
Date: Fri, 6 Jul 2018 09:15:55 -0700
Subject: [PATCH 1/4] Changed import statements in examples in DOCs

---
 pandas/core/series.py        |  2 +-
 pandas/core/sparse/series.py | 19 ++++++++++---------
 pandas/io/pytables.py        |  6 +++---
 pandas/io/sas/sas_xport.py   |  4 ++--
 pandas/plotting/_core.py     |  6 +++---
 pandas/plotting/_misc.py     | 12 ++++++------
 pandas/tseries/holiday.py    |  6 +++---
 7 files changed, 28 insertions(+), 27 deletions(-)

diff --git a/pandas/core/series.py b/pandas/core/series.py
index 93c1f866cad17..a04a281666e69 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -3048,7 +3048,7 @@ def _gotitem(self, key, ndim, subset=None):
     Examples
     --------
 
-    >>> s = Series(np.random.randn(10))
+    >>> s = pd.Series(np.random.randn(10))
 
     >>> s.agg('min')
     -1.3018049988556679
diff --git a/pandas/core/sparse/series.py b/pandas/core/sparse/series.py
index 09d958059d355..afc3d40ef2306 100644
--- a/pandas/core/sparse/series.py
+++ b/pandas/core/sparse/series.py
@@ -736,15 +736,16 @@ def to_coo(self, row_levels=(0, ), column_levels=(1, ), sort_labels=False):
 
         Examples
         --------
-        >>> from numpy import nan
-        >>> s = Series([3.0, nan, 1.0, 3.0, nan, nan])
-        >>> s.index = MultiIndex.from_tuples([(1, 2, 'a', 0),
-                                              (1, 2, 'a', 1),
-                                              (1, 1, 'b', 0),
-                                              (1, 1, 'b', 1),
-                                              (2, 1, 'b', 0),
-                                              (2, 1, 'b', 1)],
-                                              names=['A', 'B', 'C', 'D'])
+        >>> import numpy as np
+        >>> import pandas as pd
+        >>> s = pd.Series([3.0, np.nan, 1.0, 3.0, np.nan, np.nan])
+        >>> s.index = pd.MultiIndex.from_tuples([(1, 2, 'a', 0),
+                                                (1, 2, 'a', 1),
+                                                (1, 1, 'b', 0),
+                                                (1, 1, 'b', 1),
+                                                (2, 1, 'b', 0),
+                                                (2, 1, 'b', 1)],
+                                                names=['A', 'B', 'C', 'D'])
         >>> ss = s.to_sparse()
         >>> A, rows, columns = ss.to_coo(row_levels=['A', 'B'],
                                          column_levels=['C', 'D'],
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index f93ad425b2c6a..cfdb5d082aed8 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -454,9 +454,9 @@ class HDFStore(StringMixin):
 
     Examples
     --------
-    >>> from pandas import DataFrame
-    >>> from numpy.random import randn
-    >>> bar = DataFrame(randn(10, 4))
+    >>> import numpy as np
+    >>> import pandas as pd
+    >>> bar = pd.DataFrame(np.random.randn(10, 4))
     >>> store = HDFStore('test.h5')
     >>> store['foo'] = bar   # write to HDF5
     >>> bar = store['foo']   # retrieve
diff --git a/pandas/io/sas/sas_xport.py b/pandas/io/sas/sas_xport.py
index 7994517b9f303..cb01b7a652157 100644
--- a/pandas/io/sas/sas_xport.py
+++ b/pandas/io/sas/sas_xport.py
@@ -68,11 +68,11 @@
 --------
 Read a SAS Xport file:
 
->>> df = pandas.read_sas('filename.XPT')
+>>> df = pd.read_sas('filename.XPT')
 
 Read a Xport file in 10,000 line chunks:
 
->>> itr = pandas.read_sas('filename.XPT', chunksize=10000)
+>>> itr = pd.read_sas('filename.XPT', chunksize=10000)
 >>> for chunk in itr:
 >>>     do_something(chunk)
 
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 0fb1f2b23faac..4b7d42bfb4574 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2609,14 +2609,14 @@ def boxplot_frame_groupby(grouped, subplots=True, column=None, fontsize=None,
 
     Examples
     --------
-    >>> import pandas
+    >>> import pandas as pd
     >>> import numpy as np
     >>> import itertools
     >>>
     >>> tuples = [t for t in itertools.product(range(1000), range(4))]
-    >>> index = pandas.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
+    >>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
     >>> data = np.random.randn(len(index),4)
-    >>> df = pandas.DataFrame(data, columns=list('ABCD'), index=index)
+    >>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
     >>>
     >>> grouped = df.groupby(level='lvl1')
     >>> boxplot_frame_groupby(grouped)
diff --git a/pandas/plotting/_misc.py b/pandas/plotting/_misc.py
index 150c9274d4e5c..4013d2acadb58 100644
--- a/pandas/plotting/_misc.py
+++ b/pandas/plotting/_misc.py
@@ -407,6 +407,7 @@ def bootstrap_plot(series, fig=None, size=50, samples=500, **kwds):
             :context: close-figs
 
             >>> import numpy as np
+            >>> import pandas as pd
             >>> s = pd.Series(np.random.uniform(size=100))
             >>> fig = pd.plotting.bootstrap_plot(s)
     """
@@ -498,13 +499,12 @@ def parallel_coordinates(frame, class_column, cols=None, ax=None, color=None,
 
     Examples
     --------
-    >>> from pandas import read_csv
-    >>> from pandas.tools.plotting import parallel_coordinates
+    >>> import pandas as pd
     >>> from matplotlib import pyplot as plt
-    >>> df = read_csv('https://raw.github.com/pandas-dev/pandas/master'
-                      '/pandas/tests/data/iris.csv')
-    >>> parallel_coordinates(df, 'Name', color=('#556270',
-                             '#4ECDC4', '#C7F464'))
+    >>> df = pd.read_csv('https://raw.github.com/pandas-dev/pandas/master'
+                        '/pandas/tests/data/iris.csv')
+    >>> pd.plotting.parallel_coordinates(df, 'Name',
+                                        color=('#556270', '#4ECDC4', '#C7F464'))
     >>> plt.show()
     """
     if axvlines_kwds is None:
diff --git a/pandas/tseries/holiday.py b/pandas/tseries/holiday.py
index 4e874eac9e6c6..633f2a2518962 100644
--- a/pandas/tseries/holiday.py
+++ b/pandas/tseries/holiday.py
@@ -142,13 +142,13 @@ class from pandas.tseries.offsets
 
         Examples
         --------
+        >>> import pandas as pd
         >>> from pandas.tseries.holiday import Holiday, nearest_workday
-        >>> from pandas import DateOffset
         >>> from dateutil.relativedelta import MO
         >>> USMemorialDay = Holiday('MemorialDay', month=5, day=24,
-                                    offset=DateOffset(weekday=MO(1)))
+                                    offset=pd.DateOffset(weekday=MO(1)))
         >>> USLaborDay = Holiday('Labor Day', month=9, day=1,
-                            offset=DateOffset(weekday=MO(1)))
+                                offset=pd.DateOffset(weekday=MO(1)))
         >>> July3rd = Holiday('July 3rd', month=7, day=3,)
         >>> NewYears = Holiday('New Years Day', month=1,  day=1,
                                observance=nearest_workday),

From f3ee814706a71e548ce3ecb4e9db6424c7917bcc Mon Sep 17 00:00:00 2001
From: alphaCTzo7G <alphaCTzo7G@users.noreply.github.com>
Date: Sat, 7 Jul 2018 11:16:42 -0700
Subject: [PATCH 2/4] Remove `import numpy as np` and `import pandas as pd`
 statements

---
 pandas/core/frame.py           | 1 -
 pandas/core/generic.py         | 1 -
 pandas/core/groupby/groupby.py | 2 --
 pandas/core/panel.py           | 1 -
 pandas/core/reshape/melt.py    | 3 ---
 pandas/core/reshape/reshape.py | 2 --
 pandas/core/series.py          | 6 ------
 pandas/core/sparse/series.py   | 2 --
 pandas/core/tools/numeric.py   | 1 -
 pandas/io/pytables.py          | 2 --
 pandas/io/stata.py             | 4 ----
 pandas/plotting/_core.py       | 3 ---
 pandas/plotting/_misc.py       | 3 ---
 pandas/tseries/holiday.py      | 1 -
 14 files changed, 32 deletions(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 7b5f310315485..d192b32b26bdb 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -5643,7 +5643,6 @@ def unstack(self, level=-1, fill_value=None):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> df = pd.DataFrame({'A': {0: 'a', 1: 'b', 2: 'c'},
     ...                    'B': {0: 1, 1: 3, 2: 5},
     ...                    'C': {0: 2, 1: 4, 2: 6}})
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 818dd1b408518..251bdcf76355a 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -4824,7 +4824,6 @@ def ftypes(self):
 
         Examples
         --------
-        >>> import numpy as np
         >>> arr = np.random.RandomState(0).randn(100, 4)
         >>> arr[arr < .8] = np.nan
         >>> pd.DataFrame(arr).ftypes
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index c69d7f43de8ea..e973608507a29 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -3704,7 +3704,6 @@ def filter(self, func, dropna=True, *args, **kwargs):  # noqa
 
         Examples
         --------
-        >>> import pandas as pd
         >>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
         ...                           'foo', 'bar'],
         ...                    'B' : [1, 2, 3, 4, 5, 6],
@@ -4538,7 +4537,6 @@ def filter(self, func, dropna=True, *args, **kwargs):  # noqa
 
         Examples
         --------
-        >>> import pandas as pd
         >>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
         ...                           'foo', 'bar'],
         ...                    'B' : [1, 2, 3, 4, 5, 6],
diff --git a/pandas/core/panel.py b/pandas/core/panel.py
index e012819812f6b..9f08fabef8cc7 100644
--- a/pandas/core/panel.py
+++ b/pandas/core/panel.py
@@ -89,7 +89,6 @@ def panel_index(time, panels, names=None):
 
     or
 
-    >>> import numpy as np
     >>> years = np.repeat(range(1960,1963), 3)
     >>> panels = np.tile(['A', 'B', 'C'], 3)
     >>> panel_idx = panel_index(years, panels)
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index b3e3c52f6e363..f4b96c8f1ca49 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -103,7 +103,6 @@ def lreshape(data, groups, dropna=True, label=None):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> data = pd.DataFrame({'hr1': [514, 573], 'hr2': [545, 526],
     ...                      'team': ['Red Sox', 'Yankees'],
     ...                      'year1': [2007, 2007], 'year2': [2008, 2008]})
@@ -217,8 +216,6 @@ def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
 
     Examples
     --------
-    >>> import pandas as pd
-    >>> import numpy as np
     >>> np.random.seed(123)
     >>> df = pd.DataFrame({"A1970" : {0 : "a", 1 : "b", 2 : "c"},
     ...                    "A1980" : {0 : "d", 1 : "e", 2 : "f"},
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index 3d9e84954a63b..089634fb8e315 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -58,7 +58,6 @@ class _Unstacker(object):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> index = pd.MultiIndex.from_tuples([('one', 'a'), ('one', 'b'),
     ...                                    ('two', 'a'), ('two', 'b')])
     >>> s = pd.Series(np.arange(1, 5, dtype=np.int64), index=index)
@@ -771,7 +770,6 @@ def get_dummies(data, prefix=None, prefix_sep='_', dummy_na=False,
 
     Examples
     --------
-    >>> import pandas as pd
     >>> s = pd.Series(list('abca'))
 
     >>> pd.get_dummies(s)
diff --git a/pandas/core/series.py b/pandas/core/series.py
index a04a281666e69..10a08dc5e0cde 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -2749,8 +2749,6 @@ def nlargest(self, n=5, keep='first'):
 
         Examples
         --------
-        >>> import pandas as pd
-        >>> import numpy as np
         >>> s = pd.Series(np.random.randn(10**6))
         >>> s.nlargest(10)  # only sorts up to the N requested
         219921    4.644710
@@ -2796,8 +2794,6 @@ def nsmallest(self, n=5, keep='first'):
 
         Examples
         --------
-        >>> import pandas as pd
-        >>> import numpy as np
         >>> s = pd.Series(np.random.randn(10**6))
         >>> s.nsmallest(10)  # only sorts up to the N requested
         288532   -4.954580
@@ -3127,8 +3123,6 @@ def apply(self, func, convert_dtype=True, args=(), **kwds):
 
         Create a series with typical summer temperatures for each city.
 
-        >>> import pandas as pd
-        >>> import numpy as np
         >>> series = pd.Series([20, 21, 12], index=['London',
         ... 'New York','Helsinki'])
         >>> series
diff --git a/pandas/core/sparse/series.py b/pandas/core/sparse/series.py
index afc3d40ef2306..f6428568a6383 100644
--- a/pandas/core/sparse/series.py
+++ b/pandas/core/sparse/series.py
@@ -736,8 +736,6 @@ def to_coo(self, row_levels=(0, ), column_levels=(1, ), sort_labels=False):
 
         Examples
         --------
-        >>> import numpy as np
-        >>> import pandas as pd
         >>> s = pd.Series([3.0, np.nan, 1.0, 3.0, np.nan, np.nan])
         >>> s.index = pd.MultiIndex.from_tuples([(1, 2, 'a', 0),
                                                 (1, 2, 'a', 1),
diff --git a/pandas/core/tools/numeric.py b/pandas/core/tools/numeric.py
index ebe135dfb184c..f1d13ccf36cf6 100644
--- a/pandas/core/tools/numeric.py
+++ b/pandas/core/tools/numeric.py
@@ -58,7 +58,6 @@ def to_numeric(arg, errors='raise', downcast=None):
     --------
     Take separate series and convert to numeric, coercing when told to
 
-    >>> import pandas as pd
     >>> s = pd.Series(['1.0', '2', -3])
     >>> pd.to_numeric(s)
     0    1.0
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index cfdb5d082aed8..374114d2b014b 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -454,8 +454,6 @@ class HDFStore(StringMixin):
 
     Examples
     --------
-    >>> import numpy as np
-    >>> import pandas as pd
     >>> bar = pd.DataFrame(np.random.randn(10, 4))
     >>> store = HDFStore('test.h5')
     >>> store['foo'] = bar   # write to HDF5
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index b2a5bec2a4837..c3af5d214317a 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -102,7 +102,6 @@
 --------
 Read a Stata dta file:
 
->>> import pandas as pd
 >>> df = pd.read_stata('filename.dta')
 
 Read a Stata dta file in 10,000 line chunks:
@@ -216,7 +215,6 @@ def _stata_elapsed_date_to_datetime_vec(dates, fmt):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> dates = pd.Series([52])
     >>> _stata_elapsed_date_to_datetime_vec(dates , "%tw")
     0   1961-01-01
@@ -1946,7 +1944,6 @@ class StataWriter(StataParser):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> data = pd.DataFrame([[1.0, 1]], columns=['a', 'b'])
     >>> writer = StataWriter('./data_file.dta', data)
     >>> writer.write_file()
@@ -2709,7 +2706,6 @@ class StataWriter117(StataWriter):
 
     Examples
     --------
-    >>> import pandas as pd
     >>> from pandas.io.stata import StataWriter117
     >>> data = pd.DataFrame([[1.0, 1, 'a']], columns=['a', 'b', 'c'])
     >>> writer = StataWriter117('./data_file.dta', data)
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index 4b7d42bfb4574..842da838b4b83 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -2609,10 +2609,7 @@ def boxplot_frame_groupby(grouped, subplots=True, column=None, fontsize=None,
 
     Examples
     --------
-    >>> import pandas as pd
-    >>> import numpy as np
     >>> import itertools
-    >>>
     >>> tuples = [t for t in itertools.product(range(1000), range(4))]
     >>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
     >>> data = np.random.randn(len(index),4)
diff --git a/pandas/plotting/_misc.py b/pandas/plotting/_misc.py
index 4013d2acadb58..84e545a3ca2f2 100644
--- a/pandas/plotting/_misc.py
+++ b/pandas/plotting/_misc.py
@@ -406,8 +406,6 @@ def bootstrap_plot(series, fig=None, size=50, samples=500, **kwds):
     .. plot::
             :context: close-figs
 
-            >>> import numpy as np
-            >>> import pandas as pd
             >>> s = pd.Series(np.random.uniform(size=100))
             >>> fig = pd.plotting.bootstrap_plot(s)
     """
@@ -499,7 +497,6 @@ def parallel_coordinates(frame, class_column, cols=None, ax=None, color=None,
 
     Examples
     --------
-    >>> import pandas as pd
     >>> from matplotlib import pyplot as plt
     >>> df = pd.read_csv('https://raw.github.com/pandas-dev/pandas/master'
                         '/pandas/tests/data/iris.csv')
diff --git a/pandas/tseries/holiday.py b/pandas/tseries/holiday.py
index 633f2a2518962..33dcf6d64b302 100644
--- a/pandas/tseries/holiday.py
+++ b/pandas/tseries/holiday.py
@@ -142,7 +142,6 @@ class from pandas.tseries.offsets
 
         Examples
         --------
-        >>> import pandas as pd
         >>> from pandas.tseries.holiday import Holiday, nearest_workday
         >>> from dateutil.relativedelta import MO
         >>> USMemorialDay = Holiday('MemorialDay', month=5, day=24,

From bc25a86396ec027ca4359e1933ad00c2b372df8f Mon Sep 17 00:00:00 2001
From: alphaCTzo7G <alphaCTzo7G@users.noreply.github.com>
Date: Sat, 7 Jul 2018 11:33:04 -0700
Subject: [PATCH 3/4] Corrects reference to DataStructures in example code

---
 pandas/core/algorithms.py         |  8 ++++----
 pandas/core/arrays/categorical.py |  4 ++--
 pandas/core/dtypes/dtypes.py      |  2 +-
 pandas/core/frame.py              |  8 +++-----
 pandas/core/groupby/groupby.py    |  8 ++++----
 pandas/core/indexes/base.py       | 10 +++++-----
 pandas/core/indexes/category.py   |  2 +-
 pandas/core/indexes/multi.py      | 12 ++++++------
 pandas/core/indexes/period.py     |  4 ++--
 pandas/core/resample.py           |  5 ++---
 pandas/core/series.py             |  6 +++---
 pandas/core/sparse/series.py      |  2 +-
 pandas/core/strings.py            | 10 +++++-----
 pandas/core/window.py             |  4 ++--
 pandas/io/pytables.py             |  2 +-
 pandas/plotting/_misc.py          |  2 +-
 16 files changed, 43 insertions(+), 46 deletions(-)

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index c4e4f5471c4be..7f63481ac61ba 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -306,7 +306,7 @@ def unique(values):
     >>> pd.unique(pd.Series([2] + [1] * 5))
     array([2, 1])
 
-    >>> pd.unique(Series([pd.Timestamp('20160101'),
+    >>> pd.unique(pd.Series([pd.Timestamp('20160101'),
     ...                   pd.Timestamp('20160101')]))
     array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')
 
@@ -326,18 +326,18 @@ def unique(values):
     An unordered Categorical will return categories in the
     order of appearance.
 
-    >>> pd.unique(Series(pd.Categorical(list('baabc'))))
+    >>> pd.unique(pd.Series(pd.Categorical(list('baabc'))))
     [b, a, c]
     Categories (3, object): [b, a, c]
 
-    >>> pd.unique(Series(pd.Categorical(list('baabc'),
+    >>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
     ...                                 categories=list('abc'))))
     [b, a, c]
     Categories (3, object): [b, a, c]
 
     An ordered Categorical preserves the category ordering.
 
-    >>> pd.unique(Series(pd.Categorical(list('baabc'),
+    >>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
     ...                                 categories=list('abc'),
     ...                                 ordered=True)))
     [b, a, c]
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 0252b5b52ae94..caaebe352ecac 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -675,7 +675,7 @@ def _set_categories(self, categories, fastpath=False):
 
         Examples
         --------
-        >>> c = Categorical(['a', 'b'])
+        >>> c = pd.Categorical(['a', 'b'])
         >>> c
         [a, b]
         Categories (2, object): [a, b]
@@ -950,7 +950,7 @@ def rename_categories(self, new_categories, inplace=False):
 
         Examples
         --------
-        >>> c = Categorical(['a', 'a', 'b'])
+        >>> c = pd.Categorical(['a', 'a', 'b'])
         >>> c.rename_categories([0, 1])
         [0, 0, 1]
         Categories (2, int64): [0, 1]
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index de837efc235a0..4f7e9136022a5 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -171,7 +171,7 @@ class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
 
     Examples
     --------
-    >>> t = CategoricalDtype(categories=['b', 'a'], ordered=True)
+    >>> t = pd.CategoricalDtype(categories=['b', 'a'], ordered=True)
     >>> pd.Series(['a', 'b', 'a', 'c'], dtype=t)
     0      a
     1      b
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index d192b32b26bdb..bad9cb0084f82 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -2841,9 +2841,7 @@ def query(self, expr, inplace=False, **kwargs):
 
         Examples
         --------
-        >>> from numpy.random import randn
-        >>> from pandas import DataFrame
-        >>> df = pd.DataFrame(randn(10, 2), columns=list('ab'))
+        >>> df = pd.DataFrame(np.random.randn(10, 2), columns=list('ab'))
         >>> df.query('a > b')
         >>> df[df.a > df.b]  # same result as the previous expression
         """
@@ -4902,8 +4900,8 @@ def combine(self, other, func, fill_value=None, overwrite=True):
 
         Examples
         --------
-        >>> df1 = DataFrame({'A': [0, 0], 'B': [4, 4]})
-        >>> df2 = DataFrame({'A': [1, 1], 'B': [3, 3]})
+        >>> df1 = pd.DataFrame({'A': [0, 0], 'B': [4, 4]})
+        >>> df2 = pd.DataFrame({'A': [1, 1], 'B': [3, 3]})
         >>> df1.combine(df2, lambda s1, s2: s1 if s1.sum() < s2.sum() else s2)
            A  B
         0  0  3
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index e973608507a29..81b52680f7fd2 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -1824,7 +1824,7 @@ def cumcount(self, ascending=True):
 
         Essentially this is equivalent to
 
-        >>> self.apply(lambda x: Series(np.arange(len(x)), x.index))
+        >>> self.apply(lambda x: pd.Series(np.arange(len(x)), x.index))
 
         Parameters
         ----------
@@ -2094,7 +2094,7 @@ def head(self, n=5):
         Examples
         --------
 
-        >>> df = DataFrame([[1, 2], [1, 4], [5, 6]],
+        >>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]],
                            columns=['A', 'B'])
         >>> df.groupby('A', as_index=False).head(1)
            A  B
@@ -2121,7 +2121,7 @@ def tail(self, n=5):
         Examples
         --------
 
-        >>> df = DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
+        >>> df = pd.DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
                            columns=['A', 'B'])
         >>> df.groupby('A').tail(1)
            A  B
@@ -3430,7 +3430,7 @@ def _selection_name(self):
     Examples
     --------
 
-    >>> s = Series([1, 2, 3, 4])
+    >>> s = pd.Series([1, 2, 3, 4])
 
     >>> s
     0    1
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index ba60d10099948..a55d4256edfe6 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1272,11 +1272,11 @@ def set_names(self, names, level=None, inplace=False):
 
         Examples
         --------
-        >>> Index([1, 2, 3, 4]).set_names('foo')
+        >>> pd.Index([1, 2, 3, 4]).set_names('foo')
         Int64Index([1, 2, 3, 4], dtype='int64', name='foo')
-        >>> Index([1, 2, 3, 4]).set_names(['foo'])
+        >>> pd.Index([1, 2, 3, 4]).set_names(['foo'])
         Int64Index([1, 2, 3, 4], dtype='int64', name='foo')
-        >>> idx = MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
+        >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
                                           (2, u'one'), (2, u'two')],
                                           names=['foo', 'bar'])
         >>> idx.set_names(['baz', 'quz'])
@@ -2844,8 +2844,8 @@ def symmetric_difference(self, other, result_name=None):
 
         Examples
         --------
-        >>> idx1 = Index([1, 2, 3, 4])
-        >>> idx2 = Index([2, 3, 4, 5])
+        >>> idx1 = pd.Index([1, 2, 3, 4])
+        >>> idx2 = pd.Index([2, 3, 4, 5])
         >>> idx1.symmetric_difference(idx2)
         Int64Index([1, 5], dtype='int64')
 
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 8472d5fd49bd9..7c63b3c667c01 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -425,7 +425,7 @@ def get_loc(self, key, method=None):
         >>> monotonic_index.get_loc('b')
         slice(1, 3, None)
 
-        >>> non_monotonic_index = p.dCategoricalIndex(list('abcb'))
+        >>> non_monotonic_index = pd.CategoricalIndex(list('abcb'))
         >>> non_monotonic_index.get_loc('b')
         array([False,  True, False,  True], dtype=bool)
         """
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index ab1a5783a4045..281af5b57ba2d 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -345,7 +345,7 @@ def set_levels(self, levels, level=None, inplace=False,
 
         Examples
         --------
-        >>> idx = MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
+        >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
                                           (2, u'one'), (2, u'two')],
                                           names=['foo', 'bar'])
         >>> idx.set_levels([['a','b'], [1,2]])
@@ -441,7 +441,7 @@ def set_labels(self, labels, level=None, inplace=False,
 
         Examples
         --------
-        >>> idx = MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
+        >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
                                           (2, u'one'), (2, u'two')],
                                           names=['foo', 'bar'])
         >>> idx.set_labels([[1,0,1,0], [0,0,1,1]])
@@ -1191,7 +1191,7 @@ def to_hierarchical(self, n_repeat, n_shuffle=1):
 
         Examples
         --------
-        >>> idx = MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
+        >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
                                           (2, u'one'), (2, u'two')])
         >>> idx.to_hierarchical(3)
         MultiIndex(levels=[[1, 2], [u'one', u'two']],
@@ -1254,7 +1254,7 @@ def from_arrays(cls, arrays, sortorder=None, names=None):
         Examples
         --------
         >>> arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']]
-        >>> MultiIndex.from_arrays(arrays, names=('number', 'color'))
+        >>> pd.MultiIndex.from_arrays(arrays, names=('number', 'color'))
 
         See Also
         --------
@@ -1303,7 +1303,7 @@ def from_tuples(cls, tuples, sortorder=None, names=None):
         --------
         >>> tuples = [(1, u'red'), (1, u'blue'),
                       (2, u'red'), (2, u'blue')]
-        >>> MultiIndex.from_tuples(tuples, names=('number', 'color'))
+        >>> pd.MultiIndex.from_tuples(tuples, names=('number', 'color'))
 
         See Also
         --------
@@ -1356,7 +1356,7 @@ def from_product(cls, iterables, sortorder=None, names=None):
         --------
         >>> numbers = [0, 1, 2]
         >>> colors = [u'green', u'purple']
-        >>> MultiIndex.from_product([numbers, colors],
+        >>> pd.MultiIndex.from_product([numbers, colors],
                                      names=['number', 'color'])
         MultiIndex(levels=[[0, 1, 2], [u'green', u'purple']],
                    labels=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
diff --git a/pandas/core/indexes/period.py b/pandas/core/indexes/period.py
index 143cb8cd3ff6e..768f1334307b5 100644
--- a/pandas/core/indexes/period.py
+++ b/pandas/core/indexes/period.py
@@ -190,9 +190,9 @@ class PeriodIndex(PeriodArrayMixin, DatelikeOps, DatetimeIndexOpsMixin,
 
     Examples
     --------
-    >>> idx = PeriodIndex(year=year_arr, quarter=q_arr)
+    >>> idx = pd.PeriodIndex(year=year_arr, quarter=q_arr)
 
-    >>> idx2 = PeriodIndex(start='2000', end='2010', freq='A')
+    >>> idx2 = pd.PeriodIndex(start='2000', end='2010', freq='A')
 
     See Also
     ---------
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 0b0fcacc1bc48..5c3135fe14b51 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -188,9 +188,8 @@ def pipe(self, func, *args, **kwargs):
 
     Examples
     --------
-    >>> s = Series([1,2,3,4,5],
-                    index=pd.date_range('20130101',
-                                        periods=5,freq='s'))
+    >>> s = pd.Series([1,2,3,4,5],
+                      index=pd.date_range('20130101', periods=5,freq='s'))
     2013-01-01 00:00:00    1
     2013-01-01 00:00:01    2
     2013-01-01 00:00:02    3
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 10a08dc5e0cde..a5c140019bf54 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -1868,7 +1868,7 @@ def quantile(self, q=0.5, interpolation='linear'):
 
         Examples
         --------
-        >>> s = Series([1, 2, 3, 4])
+        >>> s = pd.Series([1, 2, 3, 4])
         >>> s.quantile(.5)
         2.5
         >>> s.quantile([.25, .5, .75])
@@ -2229,8 +2229,8 @@ def combine(self, other, func, fill_value=None):
 
         Examples
         --------
-        >>> s1 = Series([1, 2])
-        >>> s2 = Series([0, 3])
+        >>> s1 = pd.Series([1, 2])
+        >>> s2 = pd.Series([0, 3])
         >>> s1.combine(s2, lambda x1, x2: x1 if x1 < x2 else x2)
         0    0
         1    2
diff --git a/pandas/core/sparse/series.py b/pandas/core/sparse/series.py
index f6428568a6383..fb337d71fcf8d 100644
--- a/pandas/core/sparse/series.py
+++ b/pandas/core/sparse/series.py
@@ -795,7 +795,7 @@ def from_coo(cls, A, dense_index=False):
         matrix([[ 0.,  0.,  1.,  2.],
                 [ 3.,  0.,  0.,  0.],
                 [ 0.,  0.,  0.,  0.]])
-        >>> ss = SparseSeries.from_coo(A)
+        >>> ss = pd.SparseSeries.from_coo(A)
         >>> ss
         0  2    1
            3    2
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index b27cfdfe3f1bd..f39bf7bc2eda8 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -875,7 +875,7 @@ def str_extract(arr, pat, flags=0, expand=True):
     A pattern with two groups will return a DataFrame with two columns.
     Non-matches will be NaN.
 
-    >>> s = Series(['a1', 'b2', 'c3'])
+    >>> s = pd.Series(['a1', 'b2', 'c3'])
     >>> s.str.extract(r'([ab])(\d)')
          0    1
     0    a    1
@@ -959,7 +959,7 @@ def str_extractall(arr, pat, flags=0):
     A pattern with one group will return a DataFrame with one column.
     Indices with no matches will not appear in the result.
 
-    >>> s = Series(["a1a2", "b1", "c1"], index=["A", "B", "C"])
+    >>> s = pd.Series(["a1a2", "b1", "c1"], index=["A", "B", "C"])
     >>> s.str.extractall(r"[ab](\d)")
              0
       match
@@ -1051,13 +1051,13 @@ def str_get_dummies(arr, sep='|'):
 
     Examples
     --------
-    >>> Series(['a|b', 'a', 'a|c']).str.get_dummies()
+    >>> pd.Series(['a|b', 'a', 'a|c']).str.get_dummies()
        a  b  c
     0  1  1  0
     1  1  0  0
     2  1  0  1
 
-    >>> Series(['a|b', np.nan, 'a|c']).str.get_dummies()
+    >>> pd.Series(['a|b', np.nan, 'a|c']).str.get_dummies()
        a  b  c
     0  1  1  0
     1  0  0  0
@@ -2362,7 +2362,7 @@ def rsplit(self, pat=None, n=-1, expand=False):
     Examples
     --------
 
-    >>> s = Series(['A_B_C', 'D_E_F', 'X'])
+    >>> s = pd.Series(['A_B_C', 'D_E_F', 'X'])
     0    A_B_C
     1    D_E_F
     2        X
diff --git a/pandas/core/window.py b/pandas/core/window.py
index f089e402261db..3e337d1196413 100644
--- a/pandas/core/window.py
+++ b/pandas/core/window.py
@@ -1732,7 +1732,7 @@ class Expanding(_Rolling_and_Expanding):
     Examples
     --------
 
-    >>> df = DataFrame({'B': [0, 1, 2, np.nan, 4]})
+    >>> df = pd.DataFrame({'B': [0, 1, 2, np.nan, 4]})
          B
     0  0.0
     1  1.0
@@ -2017,7 +2017,7 @@ class EWM(_Rolling):
     Examples
     --------
 
-    >>> df = DataFrame({'B': [0, 1, 2, np.nan, 4]})
+    >>> df = pd.DataFrame({'B': [0, 1, 2, np.nan, 4]})
          B
     0  0.0
     1  1.0
diff --git a/pandas/io/pytables.py b/pandas/io/pytables.py
index 374114d2b014b..6b5714bcadba1 100644
--- a/pandas/io/pytables.py
+++ b/pandas/io/pytables.py
@@ -455,7 +455,7 @@ class HDFStore(StringMixin):
     Examples
     --------
     >>> bar = pd.DataFrame(np.random.randn(10, 4))
-    >>> store = HDFStore('test.h5')
+    >>> store = pd.HDFStore('test.h5')
     >>> store['foo'] = bar   # write to HDF5
     >>> bar = store['foo']   # retrieve
     >>> store.close()
diff --git a/pandas/plotting/_misc.py b/pandas/plotting/_misc.py
index 84e545a3ca2f2..47858d7651ce0 100644
--- a/pandas/plotting/_misc.py
+++ b/pandas/plotting/_misc.py
@@ -49,7 +49,7 @@ def scatter_matrix(frame, alpha=0.5, figsize=None, ax=None, grid=False,
 
     Examples
     --------
-    >>> df = DataFrame(np.random.randn(1000, 4), columns=['A','B','C','D'])
+    >>> df = pd.DataFrame(np.random.randn(1000, 4), columns=['A','B','C','D'])
     >>> scatter_matrix(df, alpha=0.2)
     """
 

From c27b5f45ee4be493bb76995d319a073026f6acf5 Mon Sep 17 00:00:00 2001
From: alphaCTzo7G <alphaCTzo7G@users.noreply.github.com>
Date: Sat, 7 Jul 2018 11:33:04 -0700
Subject: [PATCH 4/4] DOC: Corrects allignment of code in example code

---
 pandas/core/algorithms.py      |  8 ++++----
 pandas/core/groupby/groupby.py |  4 ++--
 pandas/core/indexes/base.py    |  4 ++--
 pandas/core/indexes/multi.py   | 12 ++++++------
 4 files changed, 14 insertions(+), 14 deletions(-)

diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index 7f63481ac61ba..6e49e8044ff25 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -307,7 +307,7 @@ def unique(values):
     array([2, 1])
 
     >>> pd.unique(pd.Series([pd.Timestamp('20160101'),
-    ...                   pd.Timestamp('20160101')]))
+    ...                     pd.Timestamp('20160101')]))
     array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')
 
     >>> pd.unique(pd.Series([pd.Timestamp('20160101', tz='US/Eastern'),
@@ -331,15 +331,15 @@ def unique(values):
     Categories (3, object): [b, a, c]
 
     >>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
-    ...                                 categories=list('abc'))))
+    ...                                    categories=list('abc'))))
     [b, a, c]
     Categories (3, object): [b, a, c]
 
     An ordered Categorical preserves the category ordering.
 
     >>> pd.unique(pd.Series(pd.Categorical(list('baabc'),
-    ...                                 categories=list('abc'),
-    ...                                 ordered=True)))
+    ...                                    categories=list('abc'),
+    ...                                    ordered=True)))
     [b, a, c]
     Categories (3, object): [a < b < c]
 
diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index ac7c51cec986b..e14a2e0b7a128 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2095,7 +2095,7 @@ def head(self, n=5):
         --------
 
         >>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]],
-                           columns=['A', 'B'])
+                              columns=['A', 'B'])
         >>> df.groupby('A', as_index=False).head(1)
            A  B
         0  1  2
@@ -2122,7 +2122,7 @@ def tail(self, n=5):
         --------
 
         >>> df = pd.DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
-                           columns=['A', 'B'])
+                              columns=['A', 'B'])
         >>> df.groupby('A').tail(1)
            A  B
         1  a  2
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 3767bc0a1f8ce..5025af9267d91 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1277,8 +1277,8 @@ def set_names(self, names, level=None, inplace=False):
         >>> pd.Index([1, 2, 3, 4]).set_names(['foo'])
         Int64Index([1, 2, 3, 4], dtype='int64', name='foo')
         >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
-                                          (2, u'one'), (2, u'two')],
-                                          names=['foo', 'bar'])
+                                            (2, u'one'), (2, u'two')],
+                                            names=['foo', 'bar'])
         >>> idx.set_names(['baz', 'quz'])
         MultiIndex(levels=[[1, 2], [u'one', u'two']],
                    labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index 4bb241a0e61f4..72569bbbab454 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -346,8 +346,8 @@ def set_levels(self, levels, level=None, inplace=False,
         Examples
         --------
         >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
-                                          (2, u'one'), (2, u'two')],
-                                          names=['foo', 'bar'])
+                                            (2, u'one'), (2, u'two')],
+                                            names=['foo', 'bar'])
         >>> idx.set_levels([['a','b'], [1,2]])
         MultiIndex(levels=[[u'a', u'b'], [1, 2]],
                    labels=[[0, 0, 1, 1], [0, 1, 0, 1]],
@@ -442,8 +442,8 @@ def set_labels(self, labels, level=None, inplace=False,
         Examples
         --------
         >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
-                                          (2, u'one'), (2, u'two')],
-                                          names=['foo', 'bar'])
+                                            (2, u'one'), (2, u'two')],
+                                            names=['foo', 'bar'])
         >>> idx.set_labels([[1,0,1,0], [0,0,1,1]])
         MultiIndex(levels=[[1, 2], [u'one', u'two']],
                    labels=[[1, 0, 1, 0], [0, 0, 1, 1]],
@@ -1192,7 +1192,7 @@ def to_hierarchical(self, n_repeat, n_shuffle=1):
         Examples
         --------
         >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
-                                          (2, u'one'), (2, u'two')])
+                                            (2, u'one'), (2, u'two')])
         >>> idx.to_hierarchical(3)
         MultiIndex(levels=[[1, 2], [u'one', u'two']],
                    labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
@@ -1357,7 +1357,7 @@ def from_product(cls, iterables, sortorder=None, names=None):
         >>> numbers = [0, 1, 2]
         >>> colors = [u'green', u'purple']
         >>> pd.MultiIndex.from_product([numbers, colors],
-                                     names=['number', 'color'])
+                                       names=['number', 'color'])
         MultiIndex(levels=[[0, 1, 2], [u'green', u'purple']],
                    labels=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
                    names=[u'number', u'color'])