From d0d28fec180ee61de17921fe5068ecde95adae8a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?agust=C3=ADn=20m=C3=A9ndez?= <matagus@gmail.com>
Date: Mon, 21 Aug 2017 10:27:24 +0200
Subject: [PATCH] DOC: Improving docstring of take method (#16948)

---
 pandas/core/generic.py | 67 +++++++++++++++++++++++++++++++++++++++---
 1 file changed, 63 insertions(+), 4 deletions(-)

diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index d9d75c870b20c..c83b1073afc8e 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -2063,18 +2063,77 @@ def __delitem__(self, key):
 
     def take(self, indices, axis=0, convert=True, is_copy=True, **kwargs):
         """
-        Analogous to ndarray.take
+        Return the elements in the given *positional* indices along an axis.
+
+        This means that we are not indexing according to actual values in
+        the index attribute of the object. We are indexing according to the
+        actual position of the element in the object.
 
         Parameters
         ----------
-        indices : list / array of ints
+        indices : array-like
+            An array of ints indicating which positions to take.
         axis : int, default 0
-        convert : translate neg to pos indices (default)
-        is_copy : mark the returned frame as a copy
+            The axis on which to select elements. "0" means that we are
+            selecting rows, "1" means that we are selecting columns, etc.
+        convert : bool, default True
+            Whether to convert negative indices to positive ones, just as with
+            indexing into Python lists. For example, if `-1` was passed in,
+            this index would be converted ``n - 1``.
+        is_copy : bool, default True
+            Whether to return a copy of the original object or not.
+
+        Examples
+        --------
+        >>> df = pd.DataFrame([('falcon', 'bird',    389.0),
+                               ('parrot', 'bird',     24.0),
+                               ('lion',   'mammal',   80.5),
+                               ('monkey', 'mammal', np.nan)],
+                              columns=('name', 'class', 'max_speed'),
+                              index=[0, 2, 3, 1])
+        >>> df
+             name   class  max_speed
+        0  falcon    bird      389.0
+        2  parrot    bird       24.0
+        3    lion  mammal       80.5
+        1  monkey  mammal        NaN
+
+        Take elements at positions 0 and 3 along the axis 0 (default).
+
+        Note how the actual indices selected (0 and 1) do not correspond to
+        our selected indices 0 and 3. That's because we are selecting the 0th
+        and 3rd rows, not rows whose indices equal 0 and 3.
+
+        >>> df.take([0, 3])
+        0  falcon    bird      389.0
+        1  monkey  mammal        NaN
+
+        Take elements at indices 1 and 2 along the axis 1 (column selection).
+
+        >>> df.take([1, 2], axis=1)
+            class  max_speed
+        0    bird      389.0
+        2    bird       24.0
+        3  mammal       80.5
+        1  mammal        NaN
+
+        We may take elements using negative integers for positive indices,
+        starting from the end of the object, just like with Python lists.
+
+        >>> df.take([-1, -2])
+             name   class  max_speed
+        1  monkey  mammal        NaN
+        3    lion  mammal       80.5
 
         Returns
         -------
         taken : type of caller
+            An array-like containing the elements taken from the object.
+
+        See Also
+        --------
+        numpy.ndarray.take
+        numpy.take
         """
         nv.validate_take(tuple(), kwargs)
         self._consolidate_inplace()