# xarray.DataArray.item

#### DataArray.item(\*args)[[source]](https://github.com/pydata/xarray/blob/main/xarray/computation/ops.py#L129-L130)

Copy an element of an array to a standard Python scalar and return it.

* **Parameters:**
  **\*args** (`Arguments (variable number` and `type)`) –
  * none: in this case, the method only works for arrays
    with one element (a.size == 1), which element is
    copied into a standard Python scalar object and returned.
  * int_type: this argument is interpreted as a flat index into
    the array, specifying which element to copy and return.
  * tuple of int_types: functions as does a single int_type argument,
    except that the argument is interpreted as an nd-index into the
    array.
* **Returns:**
  **z** (`Standard Python scalar object`) – A copy of the specified element of the array as a suitable
  Python scalar

### Notes

When the data type of a is longdouble or clongdouble, item() returns
a scalar array object because there is no available Python scalar that
would not lose information. Void arrays return a buffer object for item(),
unless fields are defined, in which case a tuple is returned.

item is very similar to a[args], except, instead of an array scalar,
a standard Python scalar is returned. This can be useful for speeding up
access to elements of the array and doing arithmetic on elements of the
array using Python’s optimized math.

### Examples

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```pycon
>>> import numpy as np
>>> np.random.seed(123)
>>> x = np.random.randint(9, size=(3, 3))
>>> x
array([[2, 2, 6],
       [1, 3, 6],
       [1, 0, 1]])
>>> x.item(3)
1
>>> x.item(7)
0
>>> x.item((0, 1))
2
>>> x.item((2, 2))
1
```

For an array with object dtype, elements are returned as-is.

```pycon
>>> a = np.array([np.int64(1)], dtype=np.object_)
>>> a.item() #return np.int64
np.int64(1)
```

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