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| <li class="toctree-l4"><a class="reference internal" href="#apache_beam.dataframe.schemas.BatchRowsAsDataFrame"><code class="docutils literal notranslate"><span class="pre">BatchRowsAsDataFrame</span></code></a></li> |
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| <section id="module-apache_beam.dataframe.schemas"> |
| <span id="apache-beam-dataframe-schemas-module"></span><h1>apache_beam.dataframe.schemas module<a class="headerlink" href="#module-apache_beam.dataframe.schemas" title="Link to this heading"></a></h1> |
| <p>Utilities for relating schema-aware PCollections and DataFrame transforms.</p> |
| <p>The utilities here enforce the type mapping defined in |
| <a class="reference internal" href="apache_beam.typehints.pandas_type_compatibility.html#module-apache_beam.typehints.pandas_type_compatibility" title="apache_beam.typehints.pandas_type_compatibility"><code class="xref py py-mod docutils literal notranslate"><span class="pre">apache_beam.typehints.pandas_type_compatibility</span></code></a>.</p> |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.BatchRowsAsDataFrame"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">apache_beam.dataframe.schemas.</span></span><span class="sig-name descname"><span class="pre">BatchRowsAsDataFrame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">proxy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#BatchRowsAsDataFrame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.BatchRowsAsDataFrame" title="Link to this definition"></a></dt> |
| <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">PTransform</span></code></a></p> |
| <p>A transform that batches schema-aware PCollection elements into DataFrames</p> |
| <p>Batching parameters are inherited from |
| <a class="reference internal" href="apache_beam.transforms.util.html#apache_beam.transforms.util.BatchElements" title="apache_beam.transforms.util.BatchElements"><code class="xref py py-class docutils literal notranslate"><span class="pre">BatchElements</span></code></a>.</p> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.BatchRowsAsDataFrame.expand"> |
| <span class="sig-name descname"><span class="pre">expand</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pcoll</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#BatchRowsAsDataFrame.expand"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.BatchRowsAsDataFrame.expand" title="Link to this definition"></a></dt> |
| <dd></dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.generate_proxy"> |
| <span class="sig-prename descclassname"><span class="pre">apache_beam.dataframe.schemas.</span></span><span class="sig-name descname"><span class="pre">generate_proxy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">element_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#type" title="(in Python v3.13)"><span class="pre">type</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">DataFrame</span></span></span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#generate_proxy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.generate_proxy" title="Link to this definition"></a></dt> |
| <dd><p>Generate a proxy pandas object for the given PCollection element_type.</p> |
| <p>Currently only supports generating a DataFrame proxy from a schema-aware |
| PCollection or a Series proxy from a primitively typed PCollection.</p> |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.UnbatchPandas"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">apache_beam.dataframe.schemas.</span></span><span class="sig-name descname"><span class="pre">UnbatchPandas</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">proxy</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_indexes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#UnbatchPandas"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.UnbatchPandas" title="Link to this definition"></a></dt> |
| <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal notranslate"><span class="pre">PTransform</span></code></a></p> |
| <p>A transform that explodes a PCollection of DataFrame or Series. DataFrame |
| is converterd to a schema-aware PCollection, while Series is converted to its |
| underlying type.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters<span class="colon">:</span></dt> |
| <dd class="field-odd"><p><strong>include_indexes</strong> – (optional, default: False) When unbatching a DataFrame |
| if include_indexes=True, attempt to include index columns in the output |
| schema for expanded DataFrames. Raises an error if any of the index |
| levels are unnamed (name=None), or if any of the names are not unique |
| among all column and index names.</p> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.UnbatchPandas.expand"> |
| <span class="sig-name descname"><span class="pre">expand</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pcoll</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#UnbatchPandas.expand"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.UnbatchPandas.expand" title="Link to this definition"></a></dt> |
| <dd></dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py function"> |
| <dt class="sig sig-object py" id="apache_beam.dataframe.schemas.element_type_from_dataframe"> |
| <span class="sig-prename descclassname"><span class="pre">apache_beam.dataframe.schemas.</span></span><span class="sig-name descname"><span class="pre">element_type_from_dataframe</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">proxy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DataFrame</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_indexes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.13)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#type" title="(in Python v3.13)"><span class="pre">type</span></a></span></span><a class="reference internal" href="_modules/apache_beam/dataframe/schemas.html#element_type_from_dataframe"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#apache_beam.dataframe.schemas.element_type_from_dataframe" title="Link to this definition"></a></dt> |
| <dd><p>Generate an element_type for an element-wise PCollection from a proxy |
| pandas object. Currently only supports converting the element_type for |
| a schema-aware PCollection to a proxy DataFrame.</p> |
| <p>Currently only supports generating a DataFrame proxy from a schema-aware |
| PCollection.</p> |
| </dd></dl> |
| |
| </section> |
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