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| <div class="section" id="pyarrow-recordbatch"> |
| <h1>pyarrow.RecordBatch<a class="headerlink" href="#pyarrow-recordbatch" title="Permalink to this headline">¶</a></h1> |
| <dl class="py class"> |
| <dt id="pyarrow.RecordBatch"> |
| <em class="property">class </em><code class="sig-prename descclassname">pyarrow.</code><code class="sig-name descname">RecordBatch</code><a class="headerlink" href="#pyarrow.RecordBatch" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">pyarrow.lib._PandasConvertible</span></code></p> |
| <p>Batch of rows of columns of equal length</p> |
| <div class="admonition warning"> |
| <p class="admonition-title">Warning</p> |
| <p>Do not call this class’s constructor directly, use one of the |
| <code class="docutils literal notranslate"><span class="pre">RecordBatch.from_*</span></code> functions instead.</p> |
| </div> |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.__init__"> |
| <code class="sig-name descname">__init__</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">*</span><span class="n">args</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.__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 class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.__init__" title="pyarrow.RecordBatch.__init__"><code class="xref py py-obj docutils literal notranslate"><span class="pre">__init__</span></code></a>(*args, **kwargs)</p></td> |
| <td><p>Initialize self.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.column" title="pyarrow.RecordBatch.column"><code class="xref py py-obj docutils literal notranslate"><span class="pre">column</span></code></a>(self, i)</p></td> |
| <td><p>Select single column from record batch</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.equals" title="pyarrow.RecordBatch.equals"><code class="xref py py-obj docutils literal notranslate"><span class="pre">equals</span></code></a>(self, other, bool check_metadata=False)</p></td> |
| <td><p>Check if contents of two record batches are equal.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.filter" title="pyarrow.RecordBatch.filter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">filter</span></code></a>(self, Array mask[, …])</p></td> |
| <td><p>Select record from a record batch.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.from_arrays" title="pyarrow.RecordBatch.from_arrays"><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_arrays</span></code></a>(list arrays[, names, schema, …])</p></td> |
| <td><p>Construct a RecordBatch from multiple pyarrow.Arrays</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.from_pandas" title="pyarrow.RecordBatch.from_pandas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_pandas</span></code></a>(type cls, df, Schema schema=None)</p></td> |
| <td><p>Convert pandas.DataFrame to an Arrow RecordBatch</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.from_struct_array" title="pyarrow.RecordBatch.from_struct_array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">from_struct_array</span></code></a>(StructArray struct_array)</p></td> |
| <td><p>Construct a RecordBatch from a StructArray.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.replace_schema_metadata" title="pyarrow.RecordBatch.replace_schema_metadata"><code class="xref py py-obj docutils literal notranslate"><span class="pre">replace_schema_metadata</span></code></a>(self[, metadata])</p></td> |
| <td><p>EXPERIMENTAL: Create shallow copy of record batch by replacing schema key-value metadata with the indicated new metadata (which may be None, which deletes any existing metadata</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.serialize" title="pyarrow.RecordBatch.serialize"><code class="xref py py-obj docutils literal notranslate"><span class="pre">serialize</span></code></a>(self[, memory_pool])</p></td> |
| <td><p>Write RecordBatch to Buffer as encapsulated IPC message.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.slice" title="pyarrow.RecordBatch.slice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">slice</span></code></a>(self[, offset, length])</p></td> |
| <td><p>Compute zero-copy slice of this RecordBatch</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.take" title="pyarrow.RecordBatch.take"><code class="xref py py-obj docutils literal notranslate"><span class="pre">take</span></code></a>(self, indices)</p></td> |
| <td><p>Select records from an RecordBatch.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.to_pandas" title="pyarrow.RecordBatch.to_pandas"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_pandas</span></code></a>(self[, memory_pool, categories, …])</p></td> |
| <td><p>Convert to a pandas-compatible NumPy array or DataFrame, as appropriate</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.to_pydict" title="pyarrow.RecordBatch.to_pydict"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_pydict</span></code></a>(self)</p></td> |
| <td><p>Convert the RecordBatch to a dict or OrderedDict.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.to_string" title="pyarrow.RecordBatch.to_string"><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_string</span></code></a>(self[, show_metadata])</p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.validate" title="pyarrow.RecordBatch.validate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">validate</span></code></a>(self, *[, full])</p></td> |
| <td><p>Perform validation checks.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Attributes</p> |
| <table class="longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.columns" title="pyarrow.RecordBatch.columns"><code class="xref py py-obj docutils literal notranslate"><span class="pre">columns</span></code></a></p></td> |
| <td><p>List of all columns in numerical order</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.nbytes" title="pyarrow.RecordBatch.nbytes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">nbytes</span></code></a></p></td> |
| <td><p>Total number of bytes consumed by the elements of the record batch.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.num_columns" title="pyarrow.RecordBatch.num_columns"><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_columns</span></code></a></p></td> |
| <td><p>Number of columns</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.num_rows" title="pyarrow.RecordBatch.num_rows"><code class="xref py py-obj docutils literal notranslate"><span class="pre">num_rows</span></code></a></p></td> |
| <td><p>Number of rows</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#pyarrow.RecordBatch.schema" title="pyarrow.RecordBatch.schema"><code class="xref py py-obj docutils literal notranslate"><span class="pre">schema</span></code></a></p></td> |
| <td><p>Schema of the RecordBatch and its columns</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.column"> |
| <code class="sig-name descname">column</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">i</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.column" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Select single column from record batch</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><strong>column</strong> (<em>pyarrow.Array</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.RecordBatch.columns"> |
| <code class="sig-name descname">columns</code><a class="headerlink" href="#pyarrow.RecordBatch.columns" title="Permalink to this definition">¶</a></dt> |
| <dd><p>List of all columns in numerical order</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><em>list of pa.Array</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.equals"> |
| <code class="sig-name descname">equals</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">other</em>, <em class="sig-param">bool check_metadata=False</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.equals" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Check if contents of two record batches are equal.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>other</strong> (<a class="reference internal" href="#pyarrow.RecordBatch" title="pyarrow.RecordBatch"><em>pyarrow.RecordBatch</em></a>) – RecordBatch to compare against.</p></li> |
| <li><p><strong>check_metadata</strong> (<em>bool</em><em>, </em><em>default False</em>) – Whether schema metadata equality should be checked as well.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>are_equal</strong> (<em>bool</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.filter"> |
| <code class="sig-name descname">filter</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">Array mask</em>, <em class="sig-param">null_selection_behavior=u'drop'</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.filter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Select record from a record batch. See pyarrow.compute.filter for full |
| usage.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.from_arrays"> |
| <em class="property">static </em><code class="sig-name descname">from_arrays</code><span class="sig-paren">(</span><em class="sig-param">list arrays</em>, <em class="sig-param">names=None</em>, <em class="sig-param">schema=None</em>, <em class="sig-param">metadata=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.from_arrays" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Construct a RecordBatch from multiple pyarrow.Arrays</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>arrays</strong> (<em>list of pyarrow.Array</em>) – One for each field in RecordBatch</p></li> |
| <li><p><strong>names</strong> (<em>list of str</em><em>, </em><em>optional</em>) – Names for the batch fields. If not passed, schema must be passed</p></li> |
| <li><p><strong>schema</strong> (<a class="reference internal" href="pyarrow.Schema.html#pyarrow.Schema" title="pyarrow.Schema"><em>Schema</em></a><em>, </em><em>default None</em>) – Schema for the created batch. If not passed, names must be passed</p></li> |
| <li><p><strong>metadata</strong> (<em>dict</em><em> or </em><em>Mapping</em><em>, </em><em>default None</em>) – Optional metadata for the schema (if inferred).</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.RecordBatch</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.from_pandas"> |
| <code class="sig-name descname">from_pandas</code><span class="sig-paren">(</span><em class="sig-param">type cls</em>, <em class="sig-param">df</em>, <em class="sig-param">Schema schema=None</em>, <em class="sig-param">preserve_index=None</em>, <em class="sig-param">nthreads=None</em>, <em class="sig-param">columns=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.from_pandas" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert pandas.DataFrame to an Arrow RecordBatch</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>df</strong> (<em>pandas.DataFrame</em>) – </p></li> |
| <li><p><strong>schema</strong> (<a class="reference internal" href="pyarrow.Schema.html#pyarrow.Schema" title="pyarrow.Schema"><em>pyarrow.Schema</em></a><em>, </em><em>optional</em>) – The expected schema of the RecordBatch. This can be used to |
| indicate the type of columns if we cannot infer it automatically. |
| If passed, the output will have exactly this schema. Columns |
| specified in the schema that are not found in the DataFrame columns |
| or its index will raise an error. Additional columns or index |
| levels in the DataFrame which are not specified in the schema will |
| be ignored.</p></li> |
| <li><p><strong>preserve_index</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to store the index as an additional column in the resulting |
| <code class="docutils literal notranslate"><span class="pre">RecordBatch</span></code>. The default of None will store the index as a |
| column, except for RangeIndex which is stored as metadata only. Use |
| <code class="docutils literal notranslate"><span class="pre">preserve_index=True</span></code> to force it to be stored as a column.</p></li> |
| <li><p><strong>nthreads</strong> (<em>int</em><em>, </em><em>default None</em><em> (</em><em>may use up to system CPU count threads</em><em>)</em>) – If greater than 1, convert columns to Arrow in parallel using |
| indicated number of threads</p></li> |
| <li><p><strong>columns</strong> (<em>list</em><em>, </em><em>optional</em>) – List of column to be converted. If None, use all columns.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.RecordBatch</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.from_struct_array"> |
| <em class="property">static </em><code class="sig-name descname">from_struct_array</code><span class="sig-paren">(</span><em class="sig-param">StructArray struct_array</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.from_struct_array" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Construct a RecordBatch from a StructArray.</p> |
| <p>Each field in the StructArray will become a column in the resulting |
| <code class="docutils literal notranslate"><span class="pre">RecordBatch</span></code>.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>struct_array</strong> (<a class="reference internal" href="pyarrow.StructArray.html#pyarrow.StructArray" title="pyarrow.StructArray"><em>StructArray</em></a>) – Array to construct the record batch from.</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pyarrow.RecordBatch</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.RecordBatch.nbytes"> |
| <code class="sig-name descname">nbytes</code><a class="headerlink" href="#pyarrow.RecordBatch.nbytes" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Total number of bytes consumed by the elements of the record batch.</p> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.RecordBatch.num_columns"> |
| <code class="sig-name descname">num_columns</code><a class="headerlink" href="#pyarrow.RecordBatch.num_columns" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of columns</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><em>int</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.RecordBatch.num_rows"> |
| <code class="sig-name descname">num_rows</code><a class="headerlink" href="#pyarrow.RecordBatch.num_rows" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Number of rows</p> |
| <p>Due to the definition of a RecordBatch, all columns have the same |
| number of rows.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><em>int</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.replace_schema_metadata"> |
| <code class="sig-name descname">replace_schema_metadata</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">metadata</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.replace_schema_metadata" title="Permalink to this definition">¶</a></dt> |
| <dd><p>EXPERIMENTAL: Create shallow copy of record batch by replacing schema |
| key-value metadata with the indicated new metadata (which may be None, |
| which deletes any existing metadata</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>metadata</strong> (<em>dict</em><em>, </em><em>default None</em>) – </p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>shallow_copy</strong> (<em>RecordBatch</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py attribute"> |
| <dt id="pyarrow.RecordBatch.schema"> |
| <code class="sig-name descname">schema</code><a class="headerlink" href="#pyarrow.RecordBatch.schema" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Schema of the RecordBatch and its columns</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><em>pyarrow.Schema</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.serialize"> |
| <code class="sig-name descname">serialize</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">memory_pool</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.serialize" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Write RecordBatch to Buffer as encapsulated IPC message.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>default None</em>) – Uses default memory pool if not specified</p> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>serialized</strong> (<em>Buffer</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.slice"> |
| <code class="sig-name descname">slice</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">offset</span><span class="o">=</span><span class="default_value">0</span></em>, <em class="sig-param"><span class="n">length</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.slice" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Compute zero-copy slice of this RecordBatch</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>offset</strong> (<em>int</em><em>, </em><em>default 0</em>) – Offset from start of record batch to slice</p></li> |
| <li><p><strong>length</strong> (<em>int</em><em>, </em><em>default None</em>) – Length of slice (default is until end of batch starting from |
| offset)</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><strong>sliced</strong> (<em>RecordBatch</em>)</p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.take"> |
| <code class="sig-name descname">take</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">indices</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.take" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Select records from an RecordBatch. See pyarrow.compute.take for full |
| usage.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.to_pandas"> |
| <code class="sig-name descname">to_pandas</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">memory_pool=None</em>, <em class="sig-param">categories=None</em>, <em class="sig-param">bool strings_to_categorical=False</em>, <em class="sig-param">bool zero_copy_only=False</em>, <em class="sig-param">bool integer_object_nulls=False</em>, <em class="sig-param">bool date_as_object=True</em>, <em class="sig-param">bool timestamp_as_object=False</em>, <em class="sig-param">bool use_threads=True</em>, <em class="sig-param">bool deduplicate_objects=True</em>, <em class="sig-param">bool ignore_metadata=False</em>, <em class="sig-param">bool safe=True</em>, <em class="sig-param">bool split_blocks=False</em>, <em class="sig-param">bool self_destruct=False</em>, <em class="sig-param">types_mapper=None</em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.to_pandas" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert to a pandas-compatible NumPy array or DataFrame, as appropriate</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>memory_pool</strong> (<a class="reference internal" href="pyarrow.MemoryPool.html#pyarrow.MemoryPool" title="pyarrow.MemoryPool"><em>MemoryPool</em></a><em>, </em><em>default None</em>) – Arrow MemoryPool to use for allocations. Uses the default memory |
| pool is not passed.</p></li> |
| <li><p><strong>strings_to_categorical</strong> (<em>bool</em><em>, </em><em>default False</em>) – Encode string (UTF8) and binary types to pandas.Categorical.</p></li> |
| <li><p><strong>categories</strong> (<em>list</em><em>, </em><em>default empty</em>) – List of fields that should be returned as pandas.Categorical. Only |
| applies to table-like data structures.</p></li> |
| <li><p><strong>zero_copy_only</strong> (<em>bool</em><em>, </em><em>default False</em>) – Raise an ArrowException if this function call would require copying |
| the underlying data.</p></li> |
| <li><p><strong>integer_object_nulls</strong> (<em>bool</em><em>, </em><em>default False</em>) – Cast integers with nulls to objects</p></li> |
| <li><p><strong>date_as_object</strong> (<em>bool</em><em>, </em><em>default True</em>) – Cast dates to objects. If False, convert to datetime64[ns] dtype.</p></li> |
| <li><p><strong>timestamp_as_object</strong> (<em>bool</em><em>, </em><em>default False</em>) – Cast non-nanosecond timestamps (np.datetime64) to objects. This is |
| useful if you have timestamps that don’t fit in the normal date |
| range of nanosecond timestamps (1678 CE-2262 CE). |
| If False, all timestamps are converted to datetime64[ns] dtype.</p></li> |
| <li><p><strong>use_threads</strong> (<em>bool</em><em>, </em><em>default True</em>) – Whether to parallelize the conversion using multiple threads.</p></li> |
| <li><p><strong>deduplicate_objects</strong> (<em>bool</em><em>, </em><em>default False</em>) – Do not create multiple copies Python objects when created, to save |
| on memory use. Conversion will be slower.</p></li> |
| <li><p><strong>ignore_metadata</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True, do not use the ‘pandas’ metadata to reconstruct the |
| DataFrame index, if present</p></li> |
| <li><p><strong>safe</strong> (<em>bool</em><em>, </em><em>default True</em>) – For certain data types, a cast is needed in order to store the |
| data in a pandas DataFrame or Series (e.g. timestamps are always |
| stored as nanoseconds in pandas). This option controls whether it |
| is a safe cast or not.</p></li> |
| <li><p><strong>split_blocks</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True, generate one internal “block” for each column when |
| creating a pandas.DataFrame from a RecordBatch or Table. While this |
| can temporarily reduce memory note that various pandas operations |
| can trigger “consolidation” which may balloon memory use.</p></li> |
| <li><p><strong>self_destruct</strong> (<em>bool</em><em>, </em><em>default False</em>) – EXPERIMENTAL: If True, attempt to deallocate the originating Arrow |
| memory while converting the Arrow object to pandas. If you use the |
| object after calling to_pandas with this option it will crash your |
| program.</p></li> |
| <li><p><strong>types_mapper</strong> (<em>function</em><em>, </em><em>default None</em>) – A function mapping a pyarrow DataType to a pandas ExtensionDtype. |
| This can be used to override the default pandas type for conversion |
| of built-in pyarrow types or in absence of pandas_metadata in the |
| Table schema. The function receives a pyarrow DataType and is |
| expected to return a pandas ExtensionDtype or <code class="docutils literal notranslate"><span class="pre">None</span></code> if the |
| default conversion should be used for that type. If you have |
| a dictionary mapping, you can pass <code class="docutils literal notranslate"><span class="pre">dict.get</span></code> as function.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><p><em>pandas.Series or pandas.DataFrame depending on type of object</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.to_pydict"> |
| <code class="sig-name descname">to_pydict</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.to_pydict" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Convert the RecordBatch to a dict or OrderedDict.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Returns</dt> |
| <dd class="field-odd"><p><em>dict</em></p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.to_string"> |
| <code class="sig-name descname">to_string</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="n">show_metadata</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.to_string" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt id="pyarrow.RecordBatch.validate"> |
| <code class="sig-name descname">validate</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">self</span></em>, <em class="sig-param"><span class="o">*</span></em>, <em class="sig-param"><span class="n">full</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="headerlink" href="#pyarrow.RecordBatch.validate" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Perform validation checks. An exception is raised if validation fails.</p> |
| <p>By default only cheap validation checks are run. Pass <cite>full=True</cite> |
| for thorough validation checks (potentially O(n)).</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>full</strong> (<em>bool</em><em>, </em><em>default False</em>) – If True, run expensive checks, otherwise cheap checks only.</p> |
| </dd> |
| <dt class="field-even">Raises</dt> |
| <dd class="field-even"><p><strong>ArrowInvalid</strong> – </p> |
| </dd> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
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