@@ -2063,18 +2063,77 @@ def __delitem__(self, key):
20632063
20642064 def take (self , indices , axis = 0 , convert = True , is_copy = True , ** kwargs ):
20652065 """
2066- Analogous to ndarray.take
2066+ Return the elements in the given *positional* indices along an axis.
2067+
2068+ This means that we are not indexing according to actual values in
2069+ the index attribute of the object. We are indexing according to the
2070+ actual position of the element in the object.
20672071
20682072 Parameters
20692073 ----------
2070- indices : list / array of ints
2074+ indices : array-like
2075+ An array of ints indicating which positions to take.
20712076 axis : int, default 0
2072- convert : translate neg to pos indices (default)
2073- is_copy : mark the returned frame as a copy
2077+ The axis on which to select elements. "0" means that we are
2078+ selecting rows, "1" means that we are selecting columns, etc.
2079+ convert : bool, default True
2080+ Whether to convert negative indices to positive ones, just as with
2081+ indexing into Python lists. For example, if `-1` was passed in,
2082+ this index would be converted ``n - 1``.
2083+ is_copy : bool, default True
2084+ Whether to return a copy of the original object or not.
2085+
2086+ Examples
2087+ --------
2088+ >>> df = pd.DataFrame([('falcon', 'bird', 389.0),
2089+ ('parrot', 'bird', 24.0),
2090+ ('lion', 'mammal', 80.5),
2091+ ('monkey', 'mammal', np.nan)],
2092+ columns=('name', 'class', 'max_speed'),
2093+ index=[0, 2, 3, 1])
2094+ >>> df
2095+ name class max_speed
2096+ 0 falcon bird 389.0
2097+ 2 parrot bird 24.0
2098+ 3 lion mammal 80.5
2099+ 1 monkey mammal NaN
2100+
2101+ Take elements at positions 0 and 3 along the axis 0 (default).
2102+
2103+ Note how the actual indices selected (0 and 1) do not correspond to
2104+ our selected indices 0 and 3. That's because we are selecting the 0th
2105+ and 3rd rows, not rows whose indices equal 0 and 3.
2106+
2107+ >>> df.take([0, 3])
2108+ 0 falcon bird 389.0
2109+ 1 monkey mammal NaN
2110+
2111+ Take elements at indices 1 and 2 along the axis 1 (column selection).
2112+
2113+ >>> df.take([1, 2], axis=1)
2114+ class max_speed
2115+ 0 bird 389.0
2116+ 2 bird 24.0
2117+ 3 mammal 80.5
2118+ 1 mammal NaN
2119+
2120+ We may take elements using negative integers for positive indices,
2121+ starting from the end of the object, just like with Python lists.
2122+
2123+ >>> df.take([-1, -2])
2124+ name class max_speed
2125+ 1 monkey mammal NaN
2126+ 3 lion mammal 80.5
20742127
20752128 Returns
20762129 -------
20772130 taken : type of caller
2131+ An array-like containing the elements taken from the object.
2132+
2133+ See Also
2134+ --------
2135+ numpy.ndarray.take
2136+ numpy.take
20782137 """
20792138 nv .validate_take (tuple (), kwargs )
20802139 self ._consolidate_inplace ()
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