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From w...@apache.org
Subject [11/30] arrow-site git commit: Update Python and GLib API docs for 0.6.0
Date Wed, 16 Aug 2017 21:33:05 GMT
http://git-wip-us.apache.org/repos/asf/arrow-site/blob/4d4a3202/docs/python/generated/pyarrow.lib.Int32Array.html
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diff --git a/docs/python/generated/pyarrow.lib.Int32Array.html b/docs/python/generated/pyarrow.lib.Int32Array.html
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+      
+  <div class="section" id="pyarrow-lib-int32array">
+<h1>pyarrow.lib.Int32Array<a class="headerlink" href="#pyarrow-lib-int32array" title="Permalink to this headline">¶</a></h1>
+<dl class="class">
+<dt id="pyarrow.lib.Int32Array">
+<em class="property">class </em><code class="descclassname">pyarrow.lib.</code><code class="descname">Int32Array</code><a class="headerlink" href="#pyarrow.lib.Int32Array" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyarrow.lib.IntegerArray.html#pyarrow.lib.IntegerArray" title="pyarrow.lib.IntegerArray"><code class="xref py py-class docutils literal"><span class="pre">pyarrow.lib.IntegerArray</span></code></a></p>
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.__init__">
+<code class="descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.__init__" title="Permalink to this definition">¶</a></dt>
+<dd><p>Initialize self.  See help(type(self)) for accurate signature.</p>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.equals" title="pyarrow.lib.Int32Array.equals"><code class="xref py py-obj docutils literal"><span class="pre">equals</span></code></a>(self,&nbsp;Array&nbsp;other)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.from_pandas" title="pyarrow.lib.Int32Array.from_pandas"><code class="xref py py-obj docutils literal"><span class="pre">from_pandas</span></code></a>(obj[,&nbsp;mask,&nbsp;timestamps_to_ms])</td>
+<td>Convert pandas.Series to an Arrow Array.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.isnull" title="pyarrow.lib.Int32Array.isnull"><code class="xref py py-obj docutils literal"><span class="pre">isnull</span></code></a>(self)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.slice" title="pyarrow.lib.Int32Array.slice"><code class="xref py py-obj docutils literal"><span class="pre">slice</span></code></a>(self[,&nbsp;offset,&nbsp;length])</td>
+<td>Compute zero-copy slice of this array</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.to_pandas" title="pyarrow.lib.Int32Array.to_pandas"><code class="xref py py-obj docutils literal"><span class="pre">to_pandas</span></code></a>(self,&nbsp;...)</td>
+<td>Convert to an array object suitable for use in pandas</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.to_pylist" title="pyarrow.lib.Int32Array.to_pylist"><code class="xref py py-obj docutils literal"><span class="pre">to_pylist</span></code></a>(self)</td>
+<td>Convert to an list of native Python objects.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.validate" title="pyarrow.lib.Int32Array.validate"><code class="xref py py-obj docutils literal"><span class="pre">validate</span></code></a>(self)</td>
+<td>Perform any validation checks implemented by arrow::ValidateArray.</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.null_count" title="pyarrow.lib.Int32Array.null_count"><code class="xref py py-obj docutils literal"><span class="pre">null_count</span></code></a></td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int32Array.type" title="pyarrow.lib.Int32Array.type"><code class="xref py py-obj docutils literal"><span class="pre">type</span></code></a></td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.equals">
+<code class="descname">equals</code><span class="sig-paren">(</span><em>self</em>, <em>Array other</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.equals" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.from_pandas">
+<code class="descname">from_pandas</code><span class="sig-paren">(</span><em>obj</em>, <em>mask=None</em>, <em>DataType type=None</em>, <em>timestamps_to_ms=False</em>, <em>MemoryPool memory_pool=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.from_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert pandas.Series to an Arrow Array.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>series</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em>) &#8211; </li>
+<li><strong>mask</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em><em>, </em><em>optional</em>) &#8211; boolean mask if the object is null (True) or valid (False)</li>
+<li><strong>type</strong> (<em>pyarrow.DataType</em>) &#8211; Explicit type to attempt to coerce to</li>
+<li><strong>timestamps_to_ms</strong> (<em>bool</em><em>, </em><em>optional</em>) &#8211; Convert datetime columns to ms resolution. This is needed for
+compatibility with other functionality like Parquet I/O which
+only supports milliseconds.</li>
+<li><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>optional</em>) &#8211; Specific memory pool to use to allocate the resulting Arrow array.</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Notes</p>
+<p>Localized timestamps will currently be returned as UTC (pandas&#8217;s native
+representation).  Timezone-naive data will be implicitly interpreted as
+UTC.</p>
+<p class="rubric">Examples</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">&lt;pyarrow.array.Int64Array object at 0x7f674e4c0e10&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  2</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">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="gp">... </span><span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">))</span>
+<span class="go">&lt;pyarrow.array.Int64Array object at 0x7f9019e11208&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  NA</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple">
+<li><strong>array</strong> (<em>pyarrow.Array or pyarrow.ChunkedArray (if object data</em>)</li>
+<li><em>overflowed binary storage)</em></li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.isnull">
+<code class="descname">isnull</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.isnull" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int32Array.null_count">
+<code class="descname">null_count</code><a class="headerlink" href="#pyarrow.lib.Int32Array.null_count" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.slice">
+<code class="descname">slice</code><span class="sig-paren">(</span><em>self</em>, <em>offset=0</em>, <em>length=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.slice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute zero-copy slice of this array</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>offset</strong> (<em>int</em><em>, </em><em>default 0</em>) &#8211; Offset from start of array to slice</li>
+<li><strong>length</strong> (<em>int</em><em>, </em><em>default None</em>) &#8211; Length of slice (default is until end of Array starting from
+offset)</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><strong>sliced</strong> (<em>RecordBatch</em>)</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.to_pandas">
+<code class="descname">to_pandas</code><span class="sig-paren">(</span><em>self</em>, <em>bool strings_to_categorical=False</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.to_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an array object suitable for use in pandas</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>strings_to_categorical</strong> (<em>boolean</em><em>, </em><em>default False</em>) &#8211; Encode string (UTF8) and binary types to pandas.Categorical</td>
+</tr>
+</tbody>
+</table>
+<div class="admonition seealso">
+<p class="first admonition-title">See also</p>
+<p class="last"><code class="xref py py-meth docutils literal"><span class="pre">Column.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">Table.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">RecordBatch.to_pandas()</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.to_pylist">
+<code class="descname">to_pylist</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.to_pylist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an list of native Python objects.</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int32Array.type">
+<code class="descname">type</code><a class="headerlink" href="#pyarrow.lib.Int32Array.type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int32Array.validate">
+<code class="descname">validate</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int32Array.validate" title="Permalink to this definition">¶</a></dt>
+<dd><p>Perform any validation checks implemented by
+arrow::ValidateArray. Raises exception with error message if array does
+not validate</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal"><span class="pre">ArrowInvalid</span></code></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</dd></dl>
+
+</div>
+
+
+    </div>
+      
+  </div>
+</div>
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+  <div class="container">
+    <p class="pull-right">
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+        &copy; Copyright 2016-2017 Apache Software Foundation.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.5.5.<br/>
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+  </div>
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+  </body>
+</html>
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http://git-wip-us.apache.org/repos/asf/arrow-site/blob/4d4a3202/docs/python/generated/pyarrow.lib.Int64Array.html
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diff --git a/docs/python/generated/pyarrow.lib.Int64Array.html b/docs/python/generated/pyarrow.lib.Int64Array.html
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@@ -0,0 +1,364 @@
+<!DOCTYPE html>
+
+
+<html xmlns="http://www.w3.org/1999/xhtml">
+  <head>
+    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
+    
+    <title>pyarrow.lib.Int64Array &#8212; pyarrow  documentation</title>
+    
+    <link rel="stylesheet" href="../_static/bootstrap-sphinx.css" type="text/css" />
+    <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
+    
+    <script type="text/javascript">
+      var DOCUMENTATION_OPTIONS = {
+        URL_ROOT:    '../',
+        VERSION:     '',
+        COLLAPSE_INDEX: false,
+        FILE_SUFFIX: '.html',
+        HAS_SOURCE:  true,
+        SOURCELINK_SUFFIX: '.txt'
+      };
+    </script>
+    <script type="text/javascript" src="../_static/jquery.js"></script>
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+  <div class="section" id="pyarrow-lib-int64array">
+<h1>pyarrow.lib.Int64Array<a class="headerlink" href="#pyarrow-lib-int64array" title="Permalink to this headline">¶</a></h1>
+<dl class="class">
+<dt id="pyarrow.lib.Int64Array">
+<em class="property">class </em><code class="descclassname">pyarrow.lib.</code><code class="descname">Int64Array</code><a class="headerlink" href="#pyarrow.lib.Int64Array" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyarrow.lib.IntegerArray.html#pyarrow.lib.IntegerArray" title="pyarrow.lib.IntegerArray"><code class="xref py py-class docutils literal"><span class="pre">pyarrow.lib.IntegerArray</span></code></a></p>
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.__init__">
+<code class="descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.__init__" title="Permalink to this definition">¶</a></dt>
+<dd><p>Initialize self.  See help(type(self)) for accurate signature.</p>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.equals" title="pyarrow.lib.Int64Array.equals"><code class="xref py py-obj docutils literal"><span class="pre">equals</span></code></a>(self,&nbsp;Array&nbsp;other)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.from_pandas" title="pyarrow.lib.Int64Array.from_pandas"><code class="xref py py-obj docutils literal"><span class="pre">from_pandas</span></code></a>(obj[,&nbsp;mask,&nbsp;timestamps_to_ms])</td>
+<td>Convert pandas.Series to an Arrow Array.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.isnull" title="pyarrow.lib.Int64Array.isnull"><code class="xref py py-obj docutils literal"><span class="pre">isnull</span></code></a>(self)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.slice" title="pyarrow.lib.Int64Array.slice"><code class="xref py py-obj docutils literal"><span class="pre">slice</span></code></a>(self[,&nbsp;offset,&nbsp;length])</td>
+<td>Compute zero-copy slice of this array</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.to_pandas" title="pyarrow.lib.Int64Array.to_pandas"><code class="xref py py-obj docutils literal"><span class="pre">to_pandas</span></code></a>(self,&nbsp;...)</td>
+<td>Convert to an array object suitable for use in pandas</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.to_pylist" title="pyarrow.lib.Int64Array.to_pylist"><code class="xref py py-obj docutils literal"><span class="pre">to_pylist</span></code></a>(self)</td>
+<td>Convert to an list of native Python objects.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.validate" title="pyarrow.lib.Int64Array.validate"><code class="xref py py-obj docutils literal"><span class="pre">validate</span></code></a>(self)</td>
+<td>Perform any validation checks implemented by arrow::ValidateArray.</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.null_count" title="pyarrow.lib.Int64Array.null_count"><code class="xref py py-obj docutils literal"><span class="pre">null_count</span></code></a></td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int64Array.type" title="pyarrow.lib.Int64Array.type"><code class="xref py py-obj docutils literal"><span class="pre">type</span></code></a></td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.equals">
+<code class="descname">equals</code><span class="sig-paren">(</span><em>self</em>, <em>Array other</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.equals" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.from_pandas">
+<code class="descname">from_pandas</code><span class="sig-paren">(</span><em>obj</em>, <em>mask=None</em>, <em>DataType type=None</em>, <em>timestamps_to_ms=False</em>, <em>MemoryPool memory_pool=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.from_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert pandas.Series to an Arrow Array.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>series</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em>) &#8211; </li>
+<li><strong>mask</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em><em>, </em><em>optional</em>) &#8211; boolean mask if the object is null (True) or valid (False)</li>
+<li><strong>type</strong> (<em>pyarrow.DataType</em>) &#8211; Explicit type to attempt to coerce to</li>
+<li><strong>timestamps_to_ms</strong> (<em>bool</em><em>, </em><em>optional</em>) &#8211; Convert datetime columns to ms resolution. This is needed for
+compatibility with other functionality like Parquet I/O which
+only supports milliseconds.</li>
+<li><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>optional</em>) &#8211; Specific memory pool to use to allocate the resulting Arrow array.</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Notes</p>
+<p>Localized timestamps will currently be returned as UTC (pandas&#8217;s native
+representation).  Timezone-naive data will be implicitly interpreted as
+UTC.</p>
+<p class="rubric">Examples</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">&lt;pyarrow.array.Int64Array object at 0x7f674e4c0e10&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  2</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">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="gp">... </span><span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">))</span>
+<span class="go">&lt;pyarrow.array.Int64Array object at 0x7f9019e11208&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  NA</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple">
+<li><strong>array</strong> (<em>pyarrow.Array or pyarrow.ChunkedArray (if object data</em>)</li>
+<li><em>overflowed binary storage)</em></li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.isnull">
+<code class="descname">isnull</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.isnull" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int64Array.null_count">
+<code class="descname">null_count</code><a class="headerlink" href="#pyarrow.lib.Int64Array.null_count" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.slice">
+<code class="descname">slice</code><span class="sig-paren">(</span><em>self</em>, <em>offset=0</em>, <em>length=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.slice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute zero-copy slice of this array</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>offset</strong> (<em>int</em><em>, </em><em>default 0</em>) &#8211; Offset from start of array to slice</li>
+<li><strong>length</strong> (<em>int</em><em>, </em><em>default None</em>) &#8211; Length of slice (default is until end of Array starting from
+offset)</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><strong>sliced</strong> (<em>RecordBatch</em>)</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.to_pandas">
+<code class="descname">to_pandas</code><span class="sig-paren">(</span><em>self</em>, <em>bool strings_to_categorical=False</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.to_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an array object suitable for use in pandas</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>strings_to_categorical</strong> (<em>boolean</em><em>, </em><em>default False</em>) &#8211; Encode string (UTF8) and binary types to pandas.Categorical</td>
+</tr>
+</tbody>
+</table>
+<div class="admonition seealso">
+<p class="first admonition-title">See also</p>
+<p class="last"><code class="xref py py-meth docutils literal"><span class="pre">Column.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">Table.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">RecordBatch.to_pandas()</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.to_pylist">
+<code class="descname">to_pylist</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.to_pylist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an list of native Python objects.</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int64Array.type">
+<code class="descname">type</code><a class="headerlink" href="#pyarrow.lib.Int64Array.type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int64Array.validate">
+<code class="descname">validate</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int64Array.validate" title="Permalink to this definition">¶</a></dt>
+<dd><p>Perform any validation checks implemented by
+arrow::ValidateArray. Raises exception with error message if array does
+not validate</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal"><span class="pre">ArrowInvalid</span></code></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</dd></dl>
+
+</div>
+
+
+    </div>
+      
+  </div>
+</div>
+<footer class="footer">
+  <div class="container">
+    <p class="pull-right">
+      <a href="#">Back to top</a>
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+    </p>
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+        &copy; Copyright 2016-2017 Apache Software Foundation.<br/>
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+    </p>
+  </div>
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+  </body>
+</html>
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new file mode 100644
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+++ b/docs/python/generated/pyarrow.lib.Int8Array.html
@@ -0,0 +1,364 @@
+<!DOCTYPE html>
+
+
+<html xmlns="http://www.w3.org/1999/xhtml">
+  <head>
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+  <div class="section" id="pyarrow-lib-int8array">
+<h1>pyarrow.lib.Int8Array<a class="headerlink" href="#pyarrow-lib-int8array" title="Permalink to this headline">¶</a></h1>
+<dl class="class">
+<dt id="pyarrow.lib.Int8Array">
+<em class="property">class </em><code class="descclassname">pyarrow.lib.</code><code class="descname">Int8Array</code><a class="headerlink" href="#pyarrow.lib.Int8Array" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyarrow.lib.IntegerArray.html#pyarrow.lib.IntegerArray" title="pyarrow.lib.IntegerArray"><code class="xref py py-class docutils literal"><span class="pre">pyarrow.lib.IntegerArray</span></code></a></p>
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.__init__">
+<code class="descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.__init__" title="Permalink to this definition">¶</a></dt>
+<dd><p>Initialize self.  See help(type(self)) for accurate signature.</p>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.equals" title="pyarrow.lib.Int8Array.equals"><code class="xref py py-obj docutils literal"><span class="pre">equals</span></code></a>(self,&nbsp;Array&nbsp;other)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.from_pandas" title="pyarrow.lib.Int8Array.from_pandas"><code class="xref py py-obj docutils literal"><span class="pre">from_pandas</span></code></a>(obj[,&nbsp;mask,&nbsp;timestamps_to_ms])</td>
+<td>Convert pandas.Series to an Arrow Array.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.isnull" title="pyarrow.lib.Int8Array.isnull"><code class="xref py py-obj docutils literal"><span class="pre">isnull</span></code></a>(self)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.slice" title="pyarrow.lib.Int8Array.slice"><code class="xref py py-obj docutils literal"><span class="pre">slice</span></code></a>(self[,&nbsp;offset,&nbsp;length])</td>
+<td>Compute zero-copy slice of this array</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.to_pandas" title="pyarrow.lib.Int8Array.to_pandas"><code class="xref py py-obj docutils literal"><span class="pre">to_pandas</span></code></a>(self,&nbsp;...)</td>
+<td>Convert to an array object suitable for use in pandas</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.to_pylist" title="pyarrow.lib.Int8Array.to_pylist"><code class="xref py py-obj docutils literal"><span class="pre">to_pylist</span></code></a>(self)</td>
+<td>Convert to an list of native Python objects.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.validate" title="pyarrow.lib.Int8Array.validate"><code class="xref py py-obj docutils literal"><span class="pre">validate</span></code></a>(self)</td>
+<td>Perform any validation checks implemented by arrow::ValidateArray.</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.null_count" title="pyarrow.lib.Int8Array.null_count"><code class="xref py py-obj docutils literal"><span class="pre">null_count</span></code></a></td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.Int8Array.type" title="pyarrow.lib.Int8Array.type"><code class="xref py py-obj docutils literal"><span class="pre">type</span></code></a></td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.equals">
+<code class="descname">equals</code><span class="sig-paren">(</span><em>self</em>, <em>Array other</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.equals" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.from_pandas">
+<code class="descname">from_pandas</code><span class="sig-paren">(</span><em>obj</em>, <em>mask=None</em>, <em>DataType type=None</em>, <em>timestamps_to_ms=False</em>, <em>MemoryPool memory_pool=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.from_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert pandas.Series to an Arrow Array.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>series</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em>) &#8211; </li>
+<li><strong>mask</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em><em>, </em><em>optional</em>) &#8211; boolean mask if the object is null (True) or valid (False)</li>
+<li><strong>type</strong> (<em>pyarrow.DataType</em>) &#8211; Explicit type to attempt to coerce to</li>
+<li><strong>timestamps_to_ms</strong> (<em>bool</em><em>, </em><em>optional</em>) &#8211; Convert datetime columns to ms resolution. This is needed for
+compatibility with other functionality like Parquet I/O which
+only supports milliseconds.</li>
+<li><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>optional</em>) &#8211; Specific memory pool to use to allocate the resulting Arrow array.</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Notes</p>
+<p>Localized timestamps will currently be returned as UTC (pandas&#8217;s native
+representation).  Timezone-naive data will be implicitly interpreted as
+UTC.</p>
+<p class="rubric">Examples</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">&lt;pyarrow.array.Int64Array object at 0x7f674e4c0e10&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  2</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">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="gp">... </span><span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">))</span>
+<span class="go">&lt;pyarrow.array.Int64Array object at 0x7f9019e11208&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  NA</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple">
+<li><strong>array</strong> (<em>pyarrow.Array or pyarrow.ChunkedArray (if object data</em>)</li>
+<li><em>overflowed binary storage)</em></li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.isnull">
+<code class="descname">isnull</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.isnull" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int8Array.null_count">
+<code class="descname">null_count</code><a class="headerlink" href="#pyarrow.lib.Int8Array.null_count" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.slice">
+<code class="descname">slice</code><span class="sig-paren">(</span><em>self</em>, <em>offset=0</em>, <em>length=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.slice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute zero-copy slice of this array</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>offset</strong> (<em>int</em><em>, </em><em>default 0</em>) &#8211; Offset from start of array to slice</li>
+<li><strong>length</strong> (<em>int</em><em>, </em><em>default None</em>) &#8211; Length of slice (default is until end of Array starting from
+offset)</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><strong>sliced</strong> (<em>RecordBatch</em>)</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.to_pandas">
+<code class="descname">to_pandas</code><span class="sig-paren">(</span><em>self</em>, <em>bool strings_to_categorical=False</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.to_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an array object suitable for use in pandas</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>strings_to_categorical</strong> (<em>boolean</em><em>, </em><em>default False</em>) &#8211; Encode string (UTF8) and binary types to pandas.Categorical</td>
+</tr>
+</tbody>
+</table>
+<div class="admonition seealso">
+<p class="first admonition-title">See also</p>
+<p class="last"><code class="xref py py-meth docutils literal"><span class="pre">Column.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">Table.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">RecordBatch.to_pandas()</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.to_pylist">
+<code class="descname">to_pylist</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.to_pylist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an list of native Python objects.</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.Int8Array.type">
+<code class="descname">type</code><a class="headerlink" href="#pyarrow.lib.Int8Array.type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.Int8Array.validate">
+<code class="descname">validate</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.Int8Array.validate" title="Permalink to this definition">¶</a></dt>
+<dd><p>Perform any validation checks implemented by
+arrow::ValidateArray. Raises exception with error message if array does
+not validate</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal"><span class="pre">ArrowInvalid</span></code></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</dd></dl>
+
+</div>
+
+
+    </div>
+      
+  </div>
+</div>
+<footer class="footer">
+  <div class="container">
+    <p class="pull-right">
+      <a href="#">Back to top</a>
+      
+    </p>
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+        &copy; Copyright 2016-2017 Apache Software Foundation.<br/>
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+    </p>
+  </div>
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+  </body>
+</html>
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new file mode 100644
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+<!DOCTYPE html>
+
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+    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
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+  <ul class="dropdown-menu globaltoc"
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+<li class="toctree-l1"><a class="reference internal" href="../install.html">Install PyArrow</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../memory.html">Memory and IO Interfaces</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../ipc.html">IPC: Fast Streaming and Serialization</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../filesystems.html">File System Interfaces</a></li>
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+  <div class="section" id="pyarrow-lib-integerarray">
+<h1>pyarrow.lib.IntegerArray<a class="headerlink" href="#pyarrow-lib-integerarray" title="Permalink to this headline">¶</a></h1>
+<dl class="class">
+<dt id="pyarrow.lib.IntegerArray">
+<em class="property">class </em><code class="descclassname">pyarrow.lib.</code><code class="descname">IntegerArray</code><a class="headerlink" href="#pyarrow.lib.IntegerArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyarrow.lib.NumericArray.html#pyarrow.lib.NumericArray" title="pyarrow.lib.NumericArray"><code class="xref py py-class docutils literal"><span class="pre">pyarrow.lib.NumericArray</span></code></a></p>
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.__init__">
+<code class="descname">__init__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.__init__" title="Permalink to this definition">¶</a></dt>
+<dd><p>Initialize self.  See help(type(self)) for accurate signature.</p>
+</dd></dl>
+
+<p class="rubric">Methods</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.equals" title="pyarrow.lib.IntegerArray.equals"><code class="xref py py-obj docutils literal"><span class="pre">equals</span></code></a>(self,&nbsp;Array&nbsp;other)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.from_pandas" title="pyarrow.lib.IntegerArray.from_pandas"><code class="xref py py-obj docutils literal"><span class="pre">from_pandas</span></code></a>(obj[,&nbsp;mask,&nbsp;timestamps_to_ms])</td>
+<td>Convert pandas.Series to an Arrow Array.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.isnull" title="pyarrow.lib.IntegerArray.isnull"><code class="xref py py-obj docutils literal"><span class="pre">isnull</span></code></a>(self)</td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.slice" title="pyarrow.lib.IntegerArray.slice"><code class="xref py py-obj docutils literal"><span class="pre">slice</span></code></a>(self[,&nbsp;offset,&nbsp;length])</td>
+<td>Compute zero-copy slice of this array</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.to_pandas" title="pyarrow.lib.IntegerArray.to_pandas"><code class="xref py py-obj docutils literal"><span class="pre">to_pandas</span></code></a>(self,&nbsp;...)</td>
+<td>Convert to an array object suitable for use in pandas</td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.to_pylist" title="pyarrow.lib.IntegerArray.to_pylist"><code class="xref py py-obj docutils literal"><span class="pre">to_pylist</span></code></a>(self)</td>
+<td>Convert to an list of native Python objects.</td>
+</tr>
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.validate" title="pyarrow.lib.IntegerArray.validate"><code class="xref py py-obj docutils literal"><span class="pre">validate</span></code></a>(self)</td>
+<td>Perform any validation checks implemented by arrow::ValidateArray.</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Attributes</p>
+<table border="1" class="longtable docutils">
+<colgroup>
+<col width="10%" />
+<col width="90%" />
+</colgroup>
+<tbody valign="top">
+<tr class="row-odd"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.null_count" title="pyarrow.lib.IntegerArray.null_count"><code class="xref py py-obj docutils literal"><span class="pre">null_count</span></code></a></td>
+<td></td>
+</tr>
+<tr class="row-even"><td><a class="reference internal" href="#pyarrow.lib.IntegerArray.type" title="pyarrow.lib.IntegerArray.type"><code class="xref py py-obj docutils literal"><span class="pre">type</span></code></a></td>
+<td></td>
+</tr>
+</tbody>
+</table>
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.equals">
+<code class="descname">equals</code><span class="sig-paren">(</span><em>self</em>, <em>Array other</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.equals" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.from_pandas">
+<code class="descname">from_pandas</code><span class="sig-paren">(</span><em>obj</em>, <em>mask=None</em>, <em>DataType type=None</em>, <em>timestamps_to_ms=False</em>, <em>MemoryPool memory_pool=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.from_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert pandas.Series to an Arrow Array.</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
+<li><strong>series</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em>) &#8211; </li>
+<li><strong>mask</strong> (<em>pandas.Series</em><em> or </em><em>numpy.ndarray</em><em>, </em><em>optional</em>) &#8211; boolean mask if the object is null (True) or valid (False)</li>
+<li><strong>type</strong> (<em>pyarrow.DataType</em>) &#8211; Explicit type to attempt to coerce to</li>
+<li><strong>timestamps_to_ms</strong> (<em>bool</em><em>, </em><em>optional</em>) &#8211; Convert datetime columns to ms resolution. This is needed for
+compatibility with other functionality like Parquet I/O which
+only supports milliseconds.</li>
+<li><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>optional</em>) &#8211; Specific memory pool to use to allocate the resulting Arrow array.</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+<p class="rubric">Notes</p>
+<p>Localized timestamps will currently be returned as UTC (pandas&#8217;s native
+representation).  Timezone-naive data will be implicitly interpreted as
+UTC.</p>
+<p class="rubric">Examples</p>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="k">as</span> <span class="nn">pa</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">&lt;pyarrow.array.Int64Array object at 0x7f674e4c0e10&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  2</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">pa</span><span class="o">.</span><span class="n">Array</span><span class="o">.</span><span class="n">from_pandas</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">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="gp">... </span><span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">))</span>
+<span class="go">&lt;pyarrow.array.Int64Array object at 0x7f9019e11208&gt;</span>
+<span class="go">[</span>
+<span class="go">  1,</span>
+<span class="go">  NA</span>
+<span class="go">]</span>
+</pre></div>
+</div>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple">
+<li><strong>array</strong> (<em>pyarrow.Array or pyarrow.ChunkedArray (if object data</em>)</li>
+<li><em>overflowed binary storage)</em></li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.isnull">
+<code class="descname">isnull</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.isnull" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.IntegerArray.null_count">
+<code class="descname">null_count</code><a class="headerlink" href="#pyarrow.lib.IntegerArray.null_count" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.slice">
+<code class="descname">slice</code><span class="sig-paren">(</span><em>self</em>, <em>offset=0</em>, <em>length=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.slice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute zero-copy slice of this array</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
+<li><strong>offset</strong> (<em>int</em><em>, </em><em>default 0</em>) &#8211; Offset from start of array to slice</li>
+<li><strong>length</strong> (<em>int</em><em>, </em><em>default None</em>) &#8211; Length of slice (default is until end of Array starting from
+offset)</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><strong>sliced</strong> (<em>RecordBatch</em>)</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.to_pandas">
+<code class="descname">to_pandas</code><span class="sig-paren">(</span><em>self</em>, <em>bool strings_to_categorical=False</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.to_pandas" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an array object suitable for use in pandas</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>strings_to_categorical</strong> (<em>boolean</em><em>, </em><em>default False</em>) &#8211; Encode string (UTF8) and binary types to pandas.Categorical</td>
+</tr>
+</tbody>
+</table>
+<div class="admonition seealso">
+<p class="first admonition-title">See also</p>
+<p class="last"><code class="xref py py-meth docutils literal"><span class="pre">Column.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">Table.to_pandas()</span></code>, <code class="xref py py-meth docutils literal"><span class="pre">RecordBatch.to_pandas()</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.to_pylist">
+<code class="descname">to_pylist</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.to_pylist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert to an list of native Python objects.</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyarrow.lib.IntegerArray.type">
+<code class="descname">type</code><a class="headerlink" href="#pyarrow.lib.IntegerArray.type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyarrow.lib.IntegerArray.validate">
+<code class="descname">validate</code><span class="sig-paren">(</span><em>self</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.lib.IntegerArray.validate" title="Permalink to this definition">¶</a></dt>
+<dd><p>Perform any validation checks implemented by
+arrow::ValidateArray. Raises exception with error message if array does
+not validate</p>
+<table class="docutils field-list" frame="void" rules="none">
+<col class="field-name" />
+<col class="field-body" />
+<tbody valign="top">
+<tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal"><span class="pre">ArrowInvalid</span></code></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</dd></dl>
+
+</div>
+
+
+    </div>
+      
+  </div>
+</div>
+<footer class="footer">
+  <div class="container">
+    <p class="pull-right">
+      <a href="#">Back to top</a>
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+    </p>
+    <p>
+        &copy; Copyright 2016-2017 Apache Software Foundation.<br/>
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.5.5.<br/>
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