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DOC: Improving docstring of take method #16948

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67 changes: 63 additions & 4 deletions pandas/core/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -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()
Expand Down