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.. _numpy_interop:

NumPy Integration

PyArrow allows converting back and forth from NumPy <https://www.numpy.org/>_ arrays to Arrow :ref:Arrays <data.array>.

NumPy to Arrow

To convert a NumPy array to Arrow, one can simply call the :func:pyarrow.array factory function.

.. code-block:: python

import numpy as np import pyarrow as pa data = np.arange(10, dtype='int16') arr = pa.array(data) arr <pyarrow.lib.Int16Array object at ...> [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]

Converting from NumPy supports a wide range of input dtypes, including structured dtypes or strings.

Arrow to NumPy

In the reverse direction, it is possible to produce a view of an Arrow Array for use with NumPy using the :meth:~pyarrow.Array.to_numpy method. This is limited to primitive types for which NumPy has the same physical representation as Arrow, and assuming the Arrow data has no nulls.

.. code-block:: python

import numpy as np import pyarrow as pa arr = pa.array([4, 5, 6], type=pa.int32()) view = arr.to_numpy() view array([4, 5, 6], dtype=int32)

For more complex data types, you have to use the :meth:~pyarrow.Array.to_pandas method (which will construct a Numpy array with Pandas semantics for, e.g., representation of null values).