projects / ceph.git / blame
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1 | .. Licensed to the Apache Software Foundation (ASF) under one |
| 2 | .. or more contributor license agreements. See the NOTICE file | |
| 3 | .. distributed with this work for additional information | |
| 4 | .. regarding copyright ownership. The ASF licenses this file | |
| 5 | .. to you under the Apache License, Version 2.0 (the | |
| 6 | .. "License"); you may not use this file except in compliance | |
| 7 | .. with the License. You may obtain a copy of the License at | |
| 8 | ||
| 9 | .. http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | ||
| 11 | .. Unless required by applicable law or agreed to in writing, | |
| 12 | .. software distributed under the License is distributed on an | |
| 13 | .. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | |
| 14 | .. KIND, either express or implied. See the License for the | |
| 15 | .. specific language governing permissions and limitations | |
| 16 | .. under the License. | |
| 17 | ||
| 18 | .. _numpy_interop: | |
| 19 | ||
| 20 | NumPy Integration | |
| 21 | ================= | |
| 22 | ||
| 23 | PyArrow allows converting back and forth from | |
| 24 | `NumPy <https://www.numpy.org/>`_ arrays to Arrow :ref:`Arrays <data.array>`. | |
| 25 | ||
| 26 | NumPy to Arrow | |
| 27 | -------------- | |
| 28 | ||
| 29 | To convert a NumPy array to Arrow, one can simply call the :func:`pyarrow.array` | |
| 30 | factory function. | |
| 31 | ||
| 32 | .. code-block:: pycon | |
| 33 | ||
| 34 | >>> import numpy as np | |
| 35 | >>> import pyarrow as pa | |
| 36 | >>> data = np.arange(10, dtype='int16') | |
| 37 | >>> arr = pa.array(data) | |
| 38 | >>> arr | |
| 39 | <pyarrow.lib.Int16Array object at 0x7fb1d1e6ae58> | |
| 40 | [ | |
| 41 | 0, | |
| 42 | 1, | |
| 43 | 2, | |
| 44 | 3, | |
| 45 | 4, | |
| 46 | 5, | |
| 47 | 6, | |
| 48 | 7, | |
| 49 | 8, | |
| 50 | 9 | |
| 51 | ] | |
| 52 | ||
| 53 | Converting from NumPy supports a wide range of input dtypes, including | |
| 54 | structured dtypes or strings. | |
| 55 | ||
| 56 | Arrow to NumPy | |
| 57 | -------------- | |
| 58 | ||
| 59 | In the reverse direction, it is possible to produce a view of an Arrow Array | |
| 60 | for use with NumPy using the :meth:`~pyarrow.Array.to_numpy` method. | |
| 61 | This is limited to primitive types for which NumPy has the same physical | |
| 62 | representation as Arrow, and assuming the Arrow data has no nulls. | |
| 63 | ||
| 64 | .. code-block:: pycon | |
| 65 | ||
| 66 | >>> import numpy as np | |
| 67 | >>> import pyarrow as pa | |
| 68 | >>> arr = pa.array([4, 5, 6], type=pa.int32()) | |
| 69 | >>> view = arr.to_numpy() | |
| 70 | >>> view | |
| 71 | array([4, 5, 6], dtype=int32) | |
| 72 | ||
| 73 | For more complex data types, you have to use the :meth:`~pyarrow.Array.to_pandas` | |
| 74 | method (which will construct a Numpy array with Pandas semantics for, e.g., | |
| 75 | representation of null values). |