Doc updates · TomAugspurger/pandas@9a6c7d4 (original) (raw)

`@@ -1464,18 +1464,17 @@ def take(arr, indices, allow_fill=False, fill_value=None):

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` allow_fill : bool, default False

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`` How to handle negative values in indices.

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`` -

False: negative values in indices indicate positional indicies

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`` +

False: negative values in indices indicate positional indices

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`` from the right (the default). This is similar to :func:numpy.take.

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`` * True: negative values in indices indicate

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`` missing values. These values are set to fill_value. Any other

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``` other negative values raise a ValueError.


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``

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` fill_value : any, optional

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``

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Fill value to use for NA-indicies when `allow_fill` is True.

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``

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Fill value to use for NA-indices when `allow_fill` is True.

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```  This may be ``None``, in which case the default NA value for

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`` -

the type is used. For ndarrays, :attr:numpy.nan is used. For

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ExtensionArrays, a different value may be used.

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 the type (``self.dtype.na_value``) is used.

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` Returns

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` -------

`@@ -1506,7 +1505,7 @@ def take(arr, indices, allow_fill=False, fill_value=None):

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` >>> from pandas.api.extensions import take

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``` With the default allow_fill=False, negative numbers indicate

```

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positional indicies from the right.

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positional indices from the right.

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` >>> take(np.array([10, 20, 30]), [0, 0, -1])

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` array([10, 10, 30])

`@@ -1525,8 +1524,7 @@ def take(arr, indices, allow_fill=False, fill_value=None):

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`if not is_array_like(arr):

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`arr = np.asarray(arr)

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Do we require int64 or intp here?

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indices = np.asarray(indices, dtype='int')

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indices = np.asarray(indices, dtype=np.intp)

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`if allow_fill:

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`# Pandas style, -1 means NA

`@@ -1552,7 +1550,7 @@ def take_nd(arr, indexer, axis=0, out=None, fill_value=np.nan, mask_info=None,

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` Input array.

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` indexer : ndarray

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` 1-D array of indices to take, subarrays corresponding to -1 value

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indicies are filed with fill_value

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indices are filed with fill_value

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` axis : int, default 0

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` Axis to take from

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` out : ndarray or None, default None