# xarray.ufuncs.left_shift

### xarray.ufuncs.left_shift *= <xarray.ufuncs._binary_ufunc object>*

xarray specific variant of `numpy.left_shift()`. Handles xarray objects by dispatching to the appropriate function for the underlying array type.

Documentation from numpy:

Shift the bits of an integer to the left.

Bits are shifted to the left by appending x2 0s at the right of x1.
Since the internal representation of numbers is in binary format, this
operation is equivalent to multiplying x1 by `2**x2`.

* **Parameters:**
  * **x1** ([array_like](https://numpy.org/doc/stable/glossary.html#term-array_like) of `integer type`) – Input values.
  * **x2** ([array_like](https://numpy.org/doc/stable/glossary.html#term-array_like) of `integer type`) – Number of zeros to append to x1. Has to be non-negative.
    If `x1.shape != x2.shape`, they must be broadcastable to a common
    shape (which becomes the shape of the output).
  * **out** ([`ndarray`](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray), [`None`](https://docs.python.org/3/builtins/constants.html#None), or [`tuple`](https://docs.python.org/3/builtins/stdtypes.html#tuple) of [`ndarray`](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray) and [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – A location into which the result is stored. If provided, it must have
    a shape that the inputs broadcast to. If not provided or None,
    a freshly-allocated array is returned. A tuple (possible only as a
    keyword argument) must have length equal to the number of outputs.
  * **where** ([array_like](https://numpy.org/doc/stable/glossary.html#term-array_like), *optional*) – This condition is broadcast over the input. At locations where the
    condition is True, the out array will be set to the ufunc result.
    Elsewhere, the out array will retain its original value.
    Note that if an uninitialized out array is created via the default
    `out=None`, locations within it where the condition is False will
    remain uninitialized.
  * **\*\*kwargs** – For other keyword-only arguments, see the
    [ufunc docs](https://numpy.org/doc/stable/reference/ufuncs.html#ufuncs-kwargs).
* **Returns:**
  **out** ([array](https://numpy.org/doc/stable/glossary.html#term-array) of `integer type`) – Return x1 with bits shifted x2 times to the left.
  This is a scalar if both x1 and x2 are scalars.

#### SEE ALSO
[`right_shift`](xarray.ufuncs.right_shift.html.md#xarray.ufuncs.right_shift)
: Shift the bits of an integer to the right.

`binary_repr`
: Return the binary representation of the input number as a string.

### Examples

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```pycon
>>> import numpy as np
>>> np.binary_repr(5)
'101'
>>> np.left_shift(5, 2)
20
>>> np.binary_repr(20)
'10100'
```

```pycon
>>> np.left_shift(5, [1,2,3])
array([10, 20, 40])
```

Note that the dtype of the second argument may change the dtype of the
result and can lead to unexpected results in some cases (see
[Casting Rules](https://numpy.org/doc/stable/user/basics.ufuncs.html#ufuncs-casting)):

```pycon
>>> a = np.left_shift(np.uint8(255), np.int64(1))  # Expect 254
>>> print(a, type(a)) # Unexpected result due to upcasting
510 <class 'numpy.int64'>
>>> b = np.left_shift(np.uint8(255), np.uint8(1))
>>> print(b, type(b))
254 <class 'numpy.uint8'>
```

The `<<` operator can be used as a shorthand for `np.left_shift` on
ndarrays.

```pycon
>>> x1 = 5
>>> x2 = np.array([1, 2, 3])
>>> x1 << x2
array([10, 20, 40])
```

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