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DOC: Address reviewer comments
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pandas/core/generic.py

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@@ -2063,57 +2063,73 @@ def __delitem__(self, key):
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def take(self, indices, axis=0, convert=True, is_copy=True, **kwargs):
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"""
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Return an object formed from the elements in the given indices along an
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axis
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Return the elements in the given *positional* indices along an axis.
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This means that we are not indexing according to actual values in
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the index attribute of the object. We are indexing according to the
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actual position of the element in the object's array of values.
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Parameters
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----------
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indices : list / array of ints
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indices : array-like
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An array of ints indicating which positions to take.
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axis : int, default 0
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convert : translate neg to pos indices (default)
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is_copy : mark the returned frame as a copy
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The axis on which to select elements. "0" means that we are
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selecting rows, "1" means that we are selecting columns, etc.
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convert : bool, default True
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Whether to convert negative indices to positive ones.
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is_copy : bool, default True
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Whether to return a copy of the original object or not.
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Examples
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--------
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>>> import numpy as np
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>>> import pandas as pd
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>>> df = pd.DataFrame([('falcon', 'bird', 389.0),
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('parrot', 'bird', 24.0),
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('lion', 'mammal', 80.5),
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('monkey', 'mammal', np.nan)],
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columns=('name', 'class', 'max_speed'))
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columns=('name', 'class', 'max_speed'),
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index=[0, 3, 2, 1])
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>>> df
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name class max_speed
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0 falcon bird 389.0
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1 parrot bird 24.0
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3 parrot bird 24.0
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2 lion mammal 80.5
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3 monkey mammal NaN
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1 monkey mammal NaN
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Take elements at indices 0 and 3 along the axis 0 (default)
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Take elements at positions 0 and 3 along the axis 0 (default).
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Note how the actual indices selected (0 and 1) do not correspond to
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our selected indices 0 and 3. That's because we are selecting the 0th
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and 3rd rows, not rows whose indices equal 0 and 3.
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>>> df.take([0, 3])
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0 falcon bird 389.0
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3 monkey mammal NaN
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1 monkey mammal NaN
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Take elements at indices 1 and 2 along the axis 1
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>>> df.take([1, 2], axis=1)
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class max_speed
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0 bird 389.0
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1 bird 24.0
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3 bird 24.0
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2 mammal 80.5
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3 mammal NaN
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1 mammal NaN
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Also, we may take elements using negative integers for pos indices
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We may take elements using negative integers for positive indices.
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>>> df.take([-1, -2])
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name class max_speed
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3 monkey mammal NaN
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1 monkey mammal NaN
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2 lion mammal 80.5
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Returns
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-------
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taken : type of caller
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An array-like containing the elements taken from the object.
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See Also
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--------
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ndarray.take
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"""
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nv.validate_take(tuple(), kwargs)
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self._consolidate_inplace()

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