From 2448809c9b542b43454b2f3f5981573edec30c6f Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 10:52:01 -0500
Subject: [PATCH 01/25] docstring for clip

---
 pandas/core/generic.py | 64 +++++++++++++++++++++++-------------------
 1 file changed, 35 insertions(+), 29 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 9f2112729a503..70472aacbc45b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5618,36 +5618,42 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Examples
         --------
         >>> df
-                  0         1
-        0  0.335232 -1.256177
-        1 -1.367855  0.746646
-        2  0.027753 -1.176076
-        3  0.230930 -0.679613
-        4  1.261967  0.570967
-
-        >>> df.clip(-1.0, 0.5)
-                  0         1
-        0  0.335232 -1.000000
-        1 -1.000000  0.500000
-        2  0.027753 -1.000000
-        3  0.230930 -0.679613
-        4  0.500000  0.500000
-
-        >>> t
-        0   -0.3
-        1   -0.2
-        2   -0.1
-        3    0.0
-        4    0.1
-        dtype: float64
+            a   b   c
+        0   1   4   7
+        1   2   5   8
+        2   3   6   9001
+
+
+        >>> df.clip( lower = 1 , upper = 9 )
+            a   b   c
+        0   1   4   7
+        1   2   5   8
+        2   3   6   9
+
+        
+        You can clip each column with different thresholds by passing a Series to the lower/upper argument.
+
+        >>> df
+              A   B
+        foo  -19  1
+        bar   12 100
+        bizz -5  -5
+        
+        >>> df.clip( lower = pd.Series({'A': -10, 'B': 10}) , axis = 1 )
+
+              A   B
+        foo  -10 10
+        bar   12 100
+        bizz -5  10
+
+        Use the axis argument to clip by column or rows.
+
+        >>> df.clip( lower = pd.Series({'foo':-10,'bar':0, 'bizz':10}) , axis = 0 )
+             A   B
+        foo  -10 1
+        bar   12 100
+        bizz  10 10
 
-        >>> df.clip(t, t + 1, axis=0)
-                  0         1
-        0  0.335232 -0.300000
-        1 -0.200000  0.746646
-        2  0.027753 -0.100000
-        3  0.230930  0.000000
-        4  1.100000  0.570967
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From aaeb2dcfd35beb5a5b01caff8fece74797116845 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 10:56:09 -0500
Subject: [PATCH 02/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 70472aacbc45b..26ba8f57b6d6f 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5655,6 +5655,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         bizz  10 10
 
         """
+        
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")
 

From 62afcabf3bee4e813f73d106d0384e7c1e45dc72 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 12:19:31 -0500
Subject: [PATCH 03/25] Edit Docstring

---
 pandas/core/generic.py | 41 ++++++++++++++++++++++++++++++-----------
 1 file changed, 30 insertions(+), 11 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 26ba8f57b6d6f..0f75f0b0e89fc 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5601,6 +5601,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         """
         Trim values at input threshold(s).
 
+        Elements above the upper threshold will be changed to upper threshold.
+        Elements below the lower threshold will be changed to lower threshold.
+
         Parameters
         ----------
         lower : float or array_like, default None
@@ -5609,53 +5612,69 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Align object with lower and upper along the given axis.
         inplace : boolean, default False
             Whether to perform the operation in place on the data
-                .. versionadded:: 0.21.0
+                .. versionadded:: 0.21.0.
 
         Returns
         -------
         clipped : Series
 
+        Notes
+        -----
+        Clipping data is a method for dealing with dubious elements.
+        If some elements are too large or too small, clipping is one way to
+        transform the data into a reasonable range.
+
+        See Also
+        --------
+        pandas.DataFrame.clip_upper : Return copy of input with values
+            above given value(s) truncated.
+        pandas.DataFrame.clip_lower : Return copy of input with values
+            below given value(s) truncated.
+
         Examples
         --------
+        >>> df = pd.DataFrame({'a':[1, 2, 3], 'b':[4, 5, 6], 'c':[7, 8, 9001]})
         >>> df
             a   b   c
         0   1   4   7
         1   2   5   8
         2   3   6   9001
 
-
-        >>> df.clip( lower = 1 , upper = 9 )
+        >>> df.clip(lower = 1, upper = 9)
             a   b   c
         0   1   4   7
         1   2   5   8
         2   3   6   9
 
-        
-        You can clip each column with different thresholds by passing a Series to the lower/upper argument.
+        You can clip each column with different thresholds by passing
+        a Series to the lower/upper argument.
 
+        >>> some_data = {'A':[-19, 12, -5],'B':[1, 100, -5]}
+        >>> df = pd.DataFrame(data = some_data, index = ['foo', 'bar', 'bizz'])
         >>> df
               A   B
         foo  -19  1
         bar   12 100
         bizz -5  -5
-        
-        >>> df.clip( lower = pd.Series({'A': -10, 'B': 10}) , axis = 1 )
 
+        Use the axis argument to clip by column or rows.  Clip column A with
+        lower threshold of -10 and column B has lower threshold of 10.
+
+        >>> df.clip(lower = pd.Series({'A':-10, 'B':10}), axis = 1)
               A   B
         foo  -10 10
         bar   12 100
         bizz -5  10
 
-        Use the axis argument to clip by column or rows.
+        Clip the foo, bar, and bizz rows with lower thresholds -10, 0, and 10.
 
-        >>> df.clip( lower = pd.Series({'foo':-10,'bar':0, 'bizz':10}) , axis = 0 )
+        >>> row_thresh = pd.Series({'foo':-10, 'bar':0, 'bizz':10})
+        >>> df.clip(lower = row_thresh ,axis = 0)
              A   B
         foo  -10 1
         bar   12 100
         bizz  10 10
-
         """
-        
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")
 

From 33af7ce175d59cb43af3f051919f78b64b171284 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 12:37:30 -0500
Subject: [PATCH 04/25] docstrings clip

---
 pandas/core/generic.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 0f75f0b0e89fc..b6e5c6f2e83a4 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5616,7 +5616,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Returns
         -------
-        clipped : Series
+        clipped : DataFrame/Series
 
         Notes
         -----
@@ -5640,17 +5640,17 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         1   2   5   8
         2   3   6   9001
 
-        >>> df.clip(lower = 1, upper = 9)
+        >>> df.clip(lower=1, upper=9)
             a   b   c
         0   1   4   7
         1   2   5   8
         2   3   6   9
 
         You can clip each column with different thresholds by passing
-        a Series to the lower/upper argument.
+        a ``Series`` to the lower/upper argument.
 
         >>> some_data = {'A':[-19, 12, -5],'B':[1, 100, -5]}
-        >>> df = pd.DataFrame(data = some_data, index = ['foo', 'bar', 'bizz'])
+        >>> df = pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
         >>> df
               A   B
         foo  -19  1
@@ -5660,7 +5660,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Use the axis argument to clip by column or rows.  Clip column A with
         lower threshold of -10 and column B has lower threshold of 10.
 
-        >>> df.clip(lower = pd.Series({'A':-10, 'B':10}), axis = 1)
+        >>> df.clip(lower=pd.Series({'A':-10, 'B':10}), axis=1)
               A   B
         foo  -10 10
         bar   12 100
@@ -5668,8 +5668,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Clip the foo, bar, and bizz rows with lower thresholds -10, 0, and 10.
 
-        >>> row_thresh = pd.Series({'foo':-10, 'bar':0, 'bizz':10})
-        >>> df.clip(lower = row_thresh ,axis = 0)
+        >>> row_thresh=pd.Series({'foo':-10, 'bar':0, 'bizz':10})
+        >>> df.clip(lower=row_thresh, axis=0)
              A   B
         foo  -10 1
         bar   12 100

From cb8d7ab2c24bc01e44c88d11e5866eb91e4e54f8 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 13:08:43 -0500
Subject: [PATCH 05/25] clip docstring

Added winsoriztion example.
---
 pandas/core/generic.py | 18 +++++++++++++++---
 1 file changed, 15 insertions(+), 3 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index b6e5c6f2e83a4..06da176cb4195 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5633,7 +5633,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Examples
         --------
-        >>> df = pd.DataFrame({'a':[1, 2, 3], 'b':[4, 5, 6], 'c':[7, 8, 9001]})
+        >>> df=pd.DataFrame({'a':[1, 2, 3], 'b':[4, 5, 6], 'c':[7, 8, 9001]})
         >>> df
             a   b   c
         0   1   4   7
@@ -5646,11 +5646,11 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         1   2   5   8
         2   3   6   9
 
-        You can clip each column with different thresholds by passing
+        You can clip each column or row with different thresholds by passing
         a ``Series`` to the lower/upper argument.
 
         >>> some_data = {'A':[-19, 12, -5],'B':[1, 100, -5]}
-        >>> df = pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
+        >>> df=pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
         >>> df
               A   B
         foo  -19  1
@@ -5674,6 +5674,18 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         foo  -10 1
         bar   12 100
         bizz  10 10
+
+        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a way
+        of removing outliers from data.  Columns of a DataFrame can be
+        winsorized by using clip.
+
+        >>> import numpy as np
+        >>> x=np.random.normal(size=(1000,3))
+        >>> df=pd.DataFrame(x, columns=['a','b','c'])
+        >>> #Winsorize columns at 5% and 95%
+        >>> U=df.quantile(0.95)
+        >>> L=df.quantile(0.5)
+        >>> winsorized_df=df.clip(lower=L, upper=U, axis = 1)
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From e062a88e3f81c868664ce62cc59c3dcacb9d19a3 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 13:11:15 -0500
Subject: [PATCH 06/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 06da176cb4195..680b953e9d6a2 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5649,7 +5649,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         You can clip each column or row with different thresholds by passing
         a ``Series`` to the lower/upper argument.
 
-        >>> some_data = {'A':[-19, 12, -5],'B':[1, 100, -5]}
+        >>> some_data={'A':[-19, 12, -5],'B':[1, 100, -5]}
         >>> df=pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
         >>> df
               A   B

From 87f8b5b83d95cd5394c84e83cfee5d4cd31c7435 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 13:20:01 -0500
Subject: [PATCH 07/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 680b953e9d6a2..628eccb0d7009 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5617,6 +5617,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Returns
         -------
         clipped : DataFrame/Series
+            Elements above or below the upper and lower thresholds converted to
+            threshold values.
 
         Notes
         -----

From 1371a237c247983e1d3a8875d79dbb9677e9a69f Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 13:28:17 -0500
Subject: [PATCH 08/25] docstring for pandas.DataFrame.clip

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 628eccb0d7009..633732930ec79 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5607,7 +5607,11 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Parameters
         ----------
         lower : float or array_like, default None
+            Lower threshold for clipping.  Values smaller than upper will be
+            converted to lower.
         upper : float or array_like, default None
+            Upper threshold for clipping.  Values larger than upper will be
+            converted to upper.
         axis : int or string axis name, optional
             Align object with lower and upper along the given axis.
         inplace : boolean, default False

From 674ffb6adf80a0e2edcb50d77a609c8e57a45cf4 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 13:36:30 -0500
Subject: [PATCH 09/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 633732930ec79..17faa62725910 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5617,6 +5617,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         inplace : boolean, default False
             Whether to perform the operation in place on the data
                 .. versionadded:: 0.21.0.
+        args : dictionary of arguments arguments passed to pandas.compat.numpy
+        kwargs : dictionary of keyword arguments passed to pandas.compat.numpy
 
         Returns
         -------

From 495847d13a5f831e00336d7e33d9c542bbd8666f Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 15:49:30 -0500
Subject: [PATCH 10/25] docstring clip

---
 pandas/core/generic.py | 53 +++++++++++++++++++++---------------------
 1 file changed, 26 insertions(+), 27 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 17faa62725910..e41cc5820bc3b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5601,34 +5601,34 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         """
         Trim values at input threshold(s).
 
-        Elements above the upper threshold will be changed to upper threshold.
-        Elements below the lower threshold will be changed to lower threshold.
+        Elements above/below the upper'lower thresholds will be changed to
+        upper/lower thresholds.
 
         Parameters
         ----------
-        lower : float or array_like, default None
-            Lower threshold for clipping.  Values smaller than upper will be
-            converted to lower.
-        upper : float or array_like, default None
-            Upper threshold for clipping.  Values larger than upper will be
-            converted to upper.
-        axis : int or string axis name, optional
+        lower : float, array-like or None, default None
+            Lower threshold for clipping.  Values smaller than `lower` will be
+            converted to `lower`.
+        upper : float, array-like or None, default None
+            Upper threshold for clipping.  Values larger than `upper` will be
+            converted to `upper`.
+        axis : {0 or 'index', 1 or 'columns', None}, default None
             Align object with lower and upper along the given axis.
         inplace : boolean, default False
             Whether to perform the operation in place on the data
                 .. versionadded:: 0.21.0.
-        args : dictionary of arguments arguments passed to pandas.compat.numpy
-        kwargs : dictionary of keyword arguments passed to pandas.compat.numpy
+        *args : arguments passed to pandas.compat.numpy
+        **kwargs : keyword arguments passed to pandas.compat.numpy
 
         Returns
         -------
-        clipped : DataFrame/Series
+        clipped : `Series` or `DataFrame`.
             Elements above or below the upper and lower thresholds converted to
             threshold values.
 
         Notes
         -----
-        Clipping data is a method for dealing with dubious elements.
+        Clipping data is a method for dealing with out-of-range elements.
         If some elements are too large or too small, clipping is one way to
         transform the data into a reasonable range.
 
@@ -5638,10 +5638,12 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             above given value(s) truncated.
         pandas.DataFrame.clip_lower : Return copy of input with values
             below given value(s) truncated.
+        pandas.Series.clip : Trim values at input threshold(s).
 
         Examples
         --------
-        >>> df=pd.DataFrame({'a':[1, 2, 3], 'b':[4, 5, 6], 'c':[7, 8, 9001]})
+        >>> some_data = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9001]}
+        >>> df = pd.DataFrame(some_data)
         >>> df
             a   b   c
         0   1   4   7
@@ -5657,8 +5659,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         You can clip each column or row with different thresholds by passing
         a ``Series`` to the lower/upper argument.
 
-        >>> some_data={'A':[-19, 12, -5],'B':[1, 100, -5]}
-        >>> df=pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
+        >>> some_data = {'A': [-19, 12, -5], 'B': [1, 100, -5]}
+        >>> df = pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
         >>> df
               A   B
         foo  -19  1
@@ -5668,7 +5670,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Use the axis argument to clip by column or rows.  Clip column A with
         lower threshold of -10 and column B has lower threshold of 10.
 
-        >>> df.clip(lower=pd.Series({'A':-10, 'B':10}), axis=1)
+        >>> df.clip(lower=pd.Series({'A': -10, 'B': 10}), axis=1)
               A   B
         foo  -10 10
         bar   12 100
@@ -5676,7 +5678,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Clip the foo, bar, and bizz rows with lower thresholds -10, 0, and 10.
 
-        >>> row_thresh=pd.Series({'foo':-10, 'bar':0, 'bizz':10})
+        >>> row_thresh = pd.Series({'foo': -10, 'bar': 0, 'bizz': 10})
         >>> df.clip(lower=row_thresh, axis=0)
              A   B
         foo  -10 1
@@ -5685,15 +5687,12 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a way
         of removing outliers from data.  Columns of a DataFrame can be
-        winsorized by using clip.
-
-        >>> import numpy as np
-        >>> x=np.random.normal(size=(1000,3))
-        >>> df=pd.DataFrame(x, columns=['a','b','c'])
-        >>> #Winsorize columns at 5% and 95%
-        >>> U=df.quantile(0.95)
-        >>> L=df.quantile(0.5)
-        >>> winsorized_df=df.clip(lower=L, upper=U, axis = 1)
+        winsorized at 5th and 95th percentile by using clip.
+
+        >>> x = np.random.normal(size=(1000,3))
+        >>> U = df.quantile(0.95)
+        >>> L = df.quantile(0.5)
+        >>> winsorized_df = df.clip(lower=L, upper=U, axis = 1)
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From 89a7690048d9cdddba93fe82268a310e37240c29 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 15:52:30 -0500
Subject: [PATCH 11/25] docstring clip

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index e41cc5820bc3b..8197d71f1990b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5601,7 +5601,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         """
         Trim values at input threshold(s).
 
-        Elements above/below the upper'lower thresholds will be changed to
+        Elements above/below the upper/lower thresholds will be changed to
         upper/lower thresholds.
 
         Parameters

From 131c052b56588ca313d6c7e1b8c2bccf1416da86 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 17:16:40 -0500
Subject: [PATCH 12/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 8197d71f1990b..48dab1ed92961 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5692,7 +5692,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         >>> x = np.random.normal(size=(1000,3))
         >>> U = df.quantile(0.95)
         >>> L = df.quantile(0.5)
-        >>> winsorized_df = df.clip(lower=L, upper=U, axis = 1)
+        >>> winsorized_df = df.clip(lower=L, upper=U, axis=1)
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From 089e882d3594df756d49e428a8bba88f97ed95f2 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 17:40:39 -0500
Subject: [PATCH 13/25] docstring clip

Possible documentation for args and kwargs
---
 pandas/core/generic.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 48dab1ed92961..2bb1d9aac7e45 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5617,9 +5617,10 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         inplace : boolean, default False
             Whether to perform the operation in place on the data
                 .. versionadded:: 0.21.0.
-        *args : arguments passed to pandas.compat.numpy
-        **kwargs : keyword arguments passed to pandas.compat.numpy
-
+        *args : Additional keywords have no effect but might be accepted
+            for compatibility with numpy.
+        **kwargs :  Additional keywords have no effect but might be accepted
+            for compatibility with numpy.
         Returns
         -------
         clipped : `Series` or `DataFrame`.

From 1089460dc8562c247b697007c0c461dd444d56d7 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 23:26:50 -0500
Subject: [PATCH 14/25] clip docstring

---
 pandas/core/generic.py | 95 +++++++++++++++++-------------------------
 1 file changed, 39 insertions(+), 56 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 2bb1d9aac7e45..f703fc02f69be 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5619,81 +5619,64 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
                 .. versionadded:: 0.21.0.
         *args : Additional keywords have no effect but might be accepted
             for compatibility with numpy.
-        **kwargs :  Additional keywords have no effect but might be accepted
+        **kwargs : Additional keywords have no effect but might be accepted
             for compatibility with numpy.
+
         Returns
         -------
-        clipped : `Series` or `DataFrame`.
-            Elements above or below the upper and lower thresholds converted to
-            threshold values.
-
-        Notes
-        -----
-        Clipping data is a method for dealing with out-of-range elements.
-        If some elements are too large or too small, clipping is one way to
-        transform the data into a reasonable range.
+        `Series` or `DataFrame`.
+            DataFrame is returned with those values above/below the 
+            `upper`/`'lower` thresholds set to the threshold values.
 
         See Also
         --------
-        pandas.DataFrame.clip_upper : Return copy of input with values
-            above given value(s) truncated.
-        pandas.DataFrame.clip_lower : Return copy of input with values
-            below given value(s) truncated.
         pandas.Series.clip : Trim values at input threshold(s).
 
         Examples
         --------
         >>> some_data = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9001]}
-        >>> df = pd.DataFrame(some_data)
+        >>> df = pd.DataFrame(some_data, index = ['foo','bar','foobar'])
         >>> df
             a   b   c
-        0   1   4   7
-        1   2   5   8
-        2   3   6   9001
+        foo 1   4   7
+        bar 2   5   8
+        foobar  3   6   9001
 
         >>> df.clip(lower=1, upper=9)
             a   b   c
-        0   1   4   7
-        1   2   5   8
-        2   3   6   9
+        foo 1   4   7
+        bar 2   5   8
+        foobar  3   6   9
 
         You can clip each column or row with different thresholds by passing
-        a ``Series`` to the lower/upper argument.
+        a ``Series`` to the lower/upper argument. Use the axis argument to clip 
+        by column or rows.
 
-        >>> some_data = {'A': [-19, 12, -5], 'B': [1, 100, -5]}
-        >>> df = pd.DataFrame(data=some_data, index=['foo', 'bar', 'bizz'])
-        >>> df
-              A   B
-        foo  -19  1
-        bar   12 100
-        bizz -5  -5
-
-        Use the axis argument to clip by column or rows.  Clip column A with
-        lower threshold of -10 and column B has lower threshold of 10.
-
-        >>> df.clip(lower=pd.Series({'A': -10, 'B': 10}), axis=1)
-              A   B
-        foo  -10 10
-        bar   12 100
-        bizz -5  10
-
-        Clip the foo, bar, and bizz rows with lower thresholds -10, 0, and 10.
-
-        >>> row_thresh = pd.Series({'foo': -10, 'bar': 0, 'bizz': 10})
-        >>> df.clip(lower=row_thresh, axis=0)
-             A   B
-        foo  -10 1
-        bar   12 100
-        bizz  10 10
-
-        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a way
-        of removing outliers from data.  Columns of a DataFrame can be
-        winsorized at 5th and 95th percentile by using clip.
-
-        >>> x = np.random.normal(size=(1000,3))
-        >>> U = df.quantile(0.95)
-        >>> L = df.quantile(0.5)
-        >>> winsorized_df = df.clip(lower=L, upper=U, axis=1)
+        >>> col_thresh = pd.Series({'a':4, 'b':5, 'c':6})
+        >>> df.clip(lower=col_thresh, axis='columns')
+            a   b   c
+        foo 4   5   7
+        bar 4   5   8
+        foobar  4   6   9001
+
+        Clip the foo, bar, and foobar rows with lower thresholds 5, 7, and 10.
+
+        >>> row_thresh = pd.Series({'foo': 5, 'bar': 7, 'foobar': 10})
+        >>> df.clip(lower=row_thresh, axis='index')
+            a   b   c
+        foo 5   5   7
+        bar 7   7   8
+        foobar  10  10  9001
+
+        Clipping data is a method for dealing with out-of-range elements.
+        If some elements are too large or too small, clipping is one way to
+        transform the data into a reasonable range.
+        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a related
+        method, whereby the data are clipped at the 5th and 95th percentiles.
+
+        >>> lwr_thresh = df.quantile(0.05)
+        >>> upr_thresh = df.quantile(0.95)
+        >>> df_win = df.clip(lower=lwr_thresh, upper=upr_thresh, axis='columns')
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From 60c34db3386ff00ab41b52a8b2945cd664df034d Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 23:30:13 -0500
Subject: [PATCH 15/25] docstring clip

---
 pandas/core/generic.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index f703fc02f69be..346d47b409759 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5625,7 +5625,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Returns
         -------
         `Series` or `DataFrame`.
-            DataFrame is returned with those values above/below the 
+            DataFrame is returned with those values above/below the
             `upper`/`'lower` thresholds set to the threshold values.
 
         See Also
@@ -5649,7 +5649,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         foobar  3   6   9
 
         You can clip each column or row with different thresholds by passing
-        a ``Series`` to the lower/upper argument. Use the axis argument to clip 
+        a ``Series`` to the lower/upper argument. Use the axis argument to clip
         by column or rows.
 
         >>> col_thresh = pd.Series({'a':4, 'b':5, 'c':6})
@@ -5671,12 +5671,13 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Clipping data is a method for dealing with out-of-range elements.
         If some elements are too large or too small, clipping is one way to
         transform the data into a reasonable range.
-        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a related
-        method, whereby the data are clipped at the 5th and 95th percentiles.
+        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a
+        related method, whereby the data are clipped at
+        the 5th and 95th percentiles.
 
         >>> lwr_thresh = df.quantile(0.05)
         >>> upr_thresh = df.quantile(0.95)
-        >>> df_win = df.clip(lower=lwr_thresh, upper=upr_thresh, axis='columns')
+        >>> dfw = df.clip(lower=lwr_thresh, upper=upr_thresh, axis='columns')
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From 9aeda8e909ab7279a3fe4dbb395a782f3927ea6f Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 23:31:39 -0500
Subject: [PATCH 16/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 346d47b409759..b3ef20871a31c 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5613,7 +5613,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Upper threshold for clipping.  Values larger than `upper` will be
             converted to `upper`.
         axis : {0 or 'index', 1 or 'columns', None}, default None
-            Align object with lower and upper along the given axis.
+            Apply clip by index (i.e. by rows) or columns.
         inplace : boolean, default False
             Whether to perform the operation in place on the data
                 .. versionadded:: 0.21.0.

From 75eecd18229d75af60b5a8bbaf7f499c7cd168d5 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sat, 10 Mar 2018 23:39:01 -0500
Subject: [PATCH 17/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index b3ef20871a31c..c45117470ea42 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5635,7 +5635,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Examples
         --------
         >>> some_data = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9001]}
-        >>> df = pd.DataFrame(some_data, index = ['foo','bar','foobar'])
+        >>> df = pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
         >>> df
             a   b   c
         foo 1   4   7

From 504389fa617cacc6cad9724c20dedee8c4466f65 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 17:29:11 -0400
Subject: [PATCH 18/25] clip docstring

---
 pandas/core/generic.py | 73 ++++++++++++++++++++++--------------------
 1 file changed, 39 insertions(+), 34 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index c45117470ea42..74d0f7f106555 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5602,7 +5602,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         Trim values at input threshold(s).
 
         Elements above/below the upper/lower thresholds will be changed to
-        upper/lower thresholds.
+        upper/lower thresholds. Clipping data is a method for dealing with
+        out-of-range elements. If some elements are too large or too small,
+        clipping is one way to transform the data into a reasonable range.
 
         Parameters
         ----------
@@ -5617,67 +5619,70 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         inplace : boolean, default False
             Whether to perform the operation in place on the data
                 .. versionadded:: 0.21.0.
-        *args : Additional keywords have no effect but might be accepted
-            for compatibility with numpy.
-        **kwargs : Additional keywords have no effect but might be accepted
+        *args, **kwargs
+            Additional keywords have no effect but might be accepted
             for compatibility with numpy.
 
         Returns
         -------
         `Series` or `DataFrame`.
-            DataFrame is returned with those values above/below the
+            Original input with those values above/below the
             `upper`/`'lower` thresholds set to the threshold values.
 
         See Also
         --------
-        pandas.Series.clip : Trim values at input threshold(s).
+        Series.clip : Trim values at input threshold(s).
+        DataFrame.clip_upper : Return copy of input with values above given
+            value(s) truncated.
+        DataFrame.clip_lower : Return copy of the input with values below given
+            value(s) truncated.
 
         Examples
         --------
-        >>> some_data = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9001]}
-        >>> df = pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
+        >>> some_data = {'a': [-1, -2, -100], 'b': [1, 2, 100]}
+        >>> df=pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
         >>> df
-            a   b   c
-        foo 1   4   7
-        bar 2   5   8
-        foobar  3   6   9001
+            a   b
+        foo -1  1
+        bar -2  2
+        foobar  -100    100
 
-        >>> df.clip(lower=1, upper=9)
-            a   b   c
-        foo 1   4   7
-        bar 2   5   8
-        foobar  3   6   9
+        >>> df.clip(lower=-10, upper=10)
+            a   b
+        foo -1  1
+        bar -2  2
+        foobar  -10 10
 
         You can clip each column or row with different thresholds by passing
         a ``Series`` to the lower/upper argument. Use the axis argument to clip
         by column or rows.
 
-        >>> col_thresh = pd.Series({'a':4, 'b':5, 'c':6})
+        >>> col_thresh=pd.Series({'a':-5, 'b':5})
         >>> df.clip(lower=col_thresh, axis='columns')
-            a   b   c
-        foo 4   5   7
-        bar 4   5   8
-        foobar  4   6   9001
+            a   b
+        foo -1  5
+        bar -2  5
+        foobar  -5  100
 
         Clip the foo, bar, and foobar rows with lower thresholds 5, 7, and 10.
 
-        >>> row_thresh = pd.Series({'foo': 5, 'bar': 7, 'foobar': 10})
+        >>> row_thresh=pd.Series({'foo': 0, 'bar': 1, 'foobar': 10})
         >>> df.clip(lower=row_thresh, axis='index')
-            a   b   c
-        foo 5   5   7
-        bar 7   7   8
-        foobar  10  10  9001
-
-        Clipping data is a method for dealing with out-of-range elements.
-        If some elements are too large or too small, clipping is one way to
-        transform the data into a reasonable range.
+            a   b
+        foo 0   1
+        bar 1   2
+        foobar  10  100
+
         `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a
         related method, whereby the data are clipped at
         the 5th and 95th percentiles.
 
-        >>> lwr_thresh = df.quantile(0.05)
-        >>> upr_thresh = df.quantile(0.95)
-        >>> dfw = df.clip(lower=lwr_thresh, upper=upr_thresh, axis='columns')
+        >>> lower, upper = df.quantile(0.05), df.quantile(0.95)
+        >>> df.clip(lower=lower, upper=upper, axis='columns')
+            a   b
+        foo -1.1    1.1
+        bar -2.0    2.0
+        foobar  -90.2   90.2
         """
         if isinstance(self, ABCPanel):
             raise NotImplementedError("clip is not supported yet for panels")

From 694f9fbc48d9cc5e7e4768d72ceda29f0de56c87 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 17:32:12 -0400
Subject: [PATCH 19/25] clip docstring

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 74d0f7f106555..095067e706353 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5639,7 +5639,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Examples
         --------
-        >>> some_data = {'a': [-1, -2, -100], 'b': [1, 2, 100]}
+        >>> some_data={'a': [-1, -2, -100], 'b': [1, 2, 100]}
         >>> df=pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
         >>> df
             a   b

From af991cc6932efe158ef0776a846d8ef37b62724e Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 17:51:04 -0400
Subject: [PATCH 20/25] clip docstring

PEP8
---
 pandas/core/generic.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 095067e706353..2460e7a9a696c 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5639,8 +5639,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Examples
         --------
-        >>> some_data={'a': [-1, -2, -100], 'b': [1, 2, 100]}
-        >>> df=pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
+        >>> some_data = {'a': [-1, -2, -100], 'b': [1, 2, 100]}
+        >>> df = pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
         >>> df
             a   b
         foo -1  1
@@ -5657,7 +5657,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         a ``Series`` to the lower/upper argument. Use the axis argument to clip
         by column or rows.
 
-        >>> col_thresh=pd.Series({'a':-5, 'b':5})
+        >>> col_thresh = pd.Series({'a': -5, 'b': 5})
         >>> df.clip(lower=col_thresh, axis='columns')
             a   b
         foo -1  5
@@ -5666,7 +5666,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Clip the foo, bar, and foobar rows with lower thresholds 5, 7, and 10.
 
-        >>> row_thresh=pd.Series({'foo': 0, 'bar': 1, 'foobar': 10})
+        >>> row_thresh = pd.Series({'foo': 0, 'bar': 1, 'foobar': 10})
         >>> df.clip(lower=row_thresh, axis='index')
             a   b
         foo 0   1

From 141e8c92dbd83dabce655d3dbc96fc969d60cf3d Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 18:01:40 -0400
Subject: [PATCH 21/25] clip docstring

---
 pandas/core/generic.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 2460e7a9a696c..cd23e1183b161 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5631,11 +5631,18 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         See Also
         --------
+        DataFrame.clip : Trim values at input threshold(s).
         Series.clip : Trim values at input threshold(s).
-        DataFrame.clip_upper : Return copy of input with values above given
+        Series.clip_lower : Return copy of the input with values below given
+            value(s) truncated.
+        Series.clip_upper : Return copy of input with values above given
             value(s) truncated.
         DataFrame.clip_lower : Return copy of the input with values below given
             value(s) truncated.
+        DataFrame.clip_upper : Return copy of input with values above given
+            value(s) truncated.
+        DataFrame.quantile : Return values at the given quantile over requested
+            axis, a la numpy.percentile.
 
         Examples
         --------

From 383c56d0ee750ec4d9131e680785415a246aa70c Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 18:43:57 -0400
Subject: [PATCH 22/25] docstring clip

---
 pandas/core/generic.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index cd23e1183b161..f463c1e60f13d 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5646,8 +5646,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         Examples
         --------
-        >>> some_data = {'a': [-1, -2, -100], 'b': [1, 2, 100]}
-        >>> df = pd.DataFrame(some_data, index = ['foo', 'bar', 'foobar'])
+        >>> df = pd.DataFrame({'a': [-1, -2, -100],
+        ...                    'b': [1, 2, 100]},
+        ...                    index=['foo', 'bar', 'foobar'])
         >>> df
             a   b
         foo -1  1
@@ -5682,7 +5683,9 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a
         related method, whereby the data are clipped at
-        the 5th and 95th percentiles.
+        the 5th and 95th percentiles. The ``DataFrame.quantile`` method returns
+        a ``Series`` with column names as index and the quantiles as values.
+        Use ``axis='columns'`` to apply clipping to columns.
 
         >>> lower, upper = df.quantile(0.05), df.quantile(0.95)
         >>> df.clip(lower=lower, upper=upper, axis='columns')

From 3f1c7854ede5300def99e061373b46a78630b489 Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Sun, 11 Mar 2018 18:44:54 -0400
Subject: [PATCH 23/25] docstring clip

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index f463c1e60f13d..58fdddd51ed11 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5627,7 +5627,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         -------
         `Series` or `DataFrame`.
             Original input with those values above/below the
-            `upper`/`'lower` thresholds set to the threshold values.
+            `upper`/`lower` thresholds set to the threshold values.
 
         See Also
         --------

From 90d8268c8b0d1886bb955b5c20917c7000c25a6e Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Tue, 13 Mar 2018 11:14:21 -0400
Subject: [PATCH 24/25] docstring clip

---
 pandas/core/generic.py | 17 +++++++++++------
 1 file changed, 11 insertions(+), 6 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 58fdddd51ed11..aa41ebb779106 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5629,6 +5629,12 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Original input with those values above/below the
             `upper`/`lower` thresholds set to the threshold values.
 
+        Notes
+        -----
+
+        .. [1] Tukey, John W. "The future of data analysis." The annals of
+            mathematical statistics 33.1 (1962): 1-67.
+
         See Also
         --------
         DataFrame.clip : Trim values at input threshold(s).
@@ -5650,13 +5656,13 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         ...                    'b': [1, 2, 100]},
         ...                    index=['foo', 'bar', 'foobar'])
         >>> df
-            a   b
+             a  b
         foo -1  1
         bar -2  2
         foobar  -100    100
 
         >>> df.clip(lower=-10, upper=10)
-            a   b
+             a  b
         foo -1  1
         bar -2  2
         foobar  -10 10
@@ -5667,7 +5673,7 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
 
         >>> col_thresh = pd.Series({'a': -5, 'b': 5})
         >>> df.clip(lower=col_thresh, axis='columns')
-            a   b
+             a  b
         foo -1  5
         bar -2  5
         foobar  -5  100
@@ -5681,15 +5687,14 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
         bar 1   2
         foobar  10  100
 
-        `Winsorizing <https://en.wikipedia.org/wiki/Winsorizing>`__ is a
-        related method, whereby the data are clipped at
+        Winsorizing [1]_ is a related method, whereby the data are clipped at
         the 5th and 95th percentiles. The ``DataFrame.quantile`` method returns
         a ``Series`` with column names as index and the quantiles as values.
         Use ``axis='columns'`` to apply clipping to columns.
 
         >>> lower, upper = df.quantile(0.05), df.quantile(0.95)
         >>> df.clip(lower=lower, upper=upper, axis='columns')
-            a   b
+             a  b
         foo -1.1    1.1
         bar -2.0    2.0
         foobar  -90.2   90.2

From bd26d0f8efe2732774701865ae6b3e85a378ba8c Mon Sep 17 00:00:00 2001
From: Demetri Pananos <dpananos@gmail.com>
Date: Tue, 13 Mar 2018 11:28:53 -0400
Subject: [PATCH 25/25] docstring clip

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

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index aa41ebb779106..6b79ed8028d24 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -5629,9 +5629,8 @@ def clip(self, lower=None, upper=None, axis=None, inplace=False,
             Original input with those values above/below the
             `upper`/`lower` thresholds set to the threshold values.
 
-        Notes
+        References
         -----
-
         .. [1] Tukey, John W. "The future of data analysis." The annals of
             mathematical statistics 33.1 (1962): 1-67.