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| <div class="section" id="pyarrow-array"> |
| <h1>pyarrow.array<a class="headerlink" href="#pyarrow-array" title="Permalink to this headline">¶</a></h1> |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="pyarrow.array"> |
| <span class="sig-prename descclassname"><span class="pre">pyarrow.</span></span><span class="sig-name descname"><span class="pre">array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">type=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">from_pandas=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bool</span> <span class="pre">safe=True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">MemoryPool</span> <span class="pre">memory_pool=None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.array" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Create pyarrow.Array instance from a Python object.</p> |
| <dl class="field-list"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl> |
| <dt><strong>obj</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/glossary.html#term-sequence" title="(in Python v3.10)"><span>sequence</span></a>, <a class="reference external" href="https://docs.python.org/3/glossary.html#term-iterable" title="(in Python v3.10)"><span>iterable</span></a>, <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.22)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray</span></code></a> or <a class="reference external" href="https://pandas.pydata.org/docs/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v1.4.0)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pandas.Series</span></code></a></span></dt><dd><p>If both type and size are specified may be a single use iterable. If |
| not strongly-typed, Arrow type will be inferred for resulting array.</p> |
| </dd> |
| <dt><strong>type</strong><span class="classifier"><a class="reference internal" href="pyarrow.DataType.html#pyarrow.DataType" title="pyarrow.DataType"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.DataType</span></code></a></span></dt><dd><p>Explicit type to attempt to coerce to, otherwise will be inferred from |
| the data.</p> |
| </dd> |
| <dt><strong>mask</strong><span class="classifier"><a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.22)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.10)"><span class="xref std std-ref">bool</span></a>], optional</span></dt><dd><p>Indicate which values are null (True) or not null (False).</p> |
| </dd> |
| <dt><strong>size</strong><span class="classifier"><a class="reference internal" href="pyarrow.int64.html#pyarrow.int64" title="pyarrow.int64"><code class="xref py py-obj docutils literal notranslate"><span class="pre">int64</span></code></a>, optional</span></dt><dd><p>Size of the elements. If the input is larger than size bail at this |
| length. For iterators, if size is larger than the input iterator this |
| will be treated as a “max size”, but will involve an initial allocation |
| of size followed by a resize to the actual size (so if you know the |
| exact size specifying it correctly will give you better performance).</p> |
| </dd> |
| <dt><strong>from_pandas</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.10)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.10)"><code class="docutils literal notranslate"><span class="pre">None</span></code></a></span></dt><dd><p>Use pandas’s semantics for inferring nulls from values in |
| ndarray-like data. If passed, the mask tasks precedence, but |
| if a value is unmasked (not-null), but still null according to |
| pandas semantics, then it is null. Defaults to False if not |
| passed explicitly by user, or True if a pandas object is |
| passed in.</p> |
| </dd> |
| <dt><strong>safe</strong><span class="classifier"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bltin-boolean-values" title="(in Python v3.10)"><span class="xref std std-ref">bool</span></a>, default <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.10)"><code class="docutils literal notranslate"><span class="pre">True</span></code></a></span></dt><dd><p>Check for overflows or other unsafe conversions.</p> |
| </dd> |
| <dt><strong>memory_pool</strong><span class="classifier"><a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.MemoryPool</span></code></a>, optional</span></dt><dd><p>If not passed, will allocate memory from the currently-set default |
| memory pool.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><dl> |
| <dt><strong>array</strong><span class="classifier"><a class="reference internal" href="pyarrow.Array.html#pyarrow.Array" title="pyarrow.Array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.Array</span></code></a> or <a class="reference internal" href="pyarrow.ChunkedArray.html#pyarrow.ChunkedArray" title="pyarrow.ChunkedArray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyarrow.ChunkedArray</span></code></a></span></dt><dd><p>A ChunkedArray instead of an Array is returned if:</p> |
| <ul class="simple"> |
| <li><p>the object data overflowed binary storage.</p></li> |
| <li><p>the object’s <code class="docutils literal notranslate"><span class="pre">__arrow_array__</span></code> protocol method returned a chunked |
| array.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| </dd> |
| </dl> |
| <p class="rubric">Notes</p> |
| <p>Timezone will be preserved in the returned array for timezone-aware data, |
| else no timezone will be returned for naive timestamps. |
| Internally, UTC values are stored for timezone-aware data with the |
| timezone set in the data type.</p> |
| <p>Pandas’s DateOffsets and dateutil.relativedelta.relativedelta are by |
| default converted as MonthDayNanoIntervalArray. relativedelta leapdays |
| are ignored as are all absolute fields on both objects. datetime.timedelta |
| can also be converted to MonthDayNanoIntervalArray but this requires |
| passing MonthDayNanoIntervalType explicitly.</p> |
| <p>Converting to dictionary array will promote to a wider integer type for |
| indices if the number of distinct values cannot be represented, even if |
| the index type was explicitly set. This means that if there are more than |
| 127 values the returned dictionary array’s index type will be at least |
| pa.int16() even if pa.int8() was passed to the function. Note that an |
| explicit index type will not be demoted even if it is wider than required.</p> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span> |
| <span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span> |
| <span class="gp">>>> </span><span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">]))</span> |
| <span class="go"><pyarrow.lib.Int64Array object at 0x7f674e4c0e10></span> |
| <span class="go">[</span> |
| <span class="go"> 1,</span> |
| <span class="go"> 2</span> |
| <span class="go">]</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="s2">"a"</span><span class="p">,</span> <span class="s2">"b"</span><span class="p">,</span> <span class="s2">"a"</span><span class="p">],</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">dictionary</span><span class="p">(</span><span class="n">pa</span><span class="o">.</span><span class="n">int8</span><span class="p">(),</span> <span class="n">pa</span><span class="o">.</span><span class="n">string</span><span class="p">()))</span> |
| <span class="go"><pyarrow.lib.DictionaryArray object at 0x7feb288d9040></span> |
| <span class="go">-- dictionary:</span> |
| <span class="go">[</span> |
| <span class="go"> "a",</span> |
| <span class="go"> "b"</span> |
| <span class="go">]</span> |
| <span class="go">-- indices:</span> |
| <span class="go">[</span> |
| <span class="go"> 0,</span> |
| <span class="go"> 1,</span> |
| <span class="go"> 0</span> |
| <span class="go">]</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> |
| <span class="gp">>>> </span><span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">]),</span> <span class="n">mask</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">))</span> |
| <span class="go"><pyarrow.lib.Int64Array object at 0x7f9019e11208></span> |
| <span class="go">[</span> |
| <span class="go"> 1,</span> |
| <span class="go"> null</span> |
| <span class="go">]</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">arr</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1024</span><span class="p">),</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">dictionary</span><span class="p">(</span><span class="n">pa</span><span class="o">.</span><span class="n">int8</span><span class="p">(),</span> <span class="n">pa</span><span class="o">.</span><span class="n">int64</span><span class="p">()))</span> |
| <span class="gp">>>> </span><span class="n">arr</span><span class="o">.</span><span class="n">type</span><span class="o">.</span><span class="n">index_type</span> |
| <span class="go">DataType(int16)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| |
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