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| <div class="section" id="groupby"> |
| <span id="api-groupby"></span><h1>GroupBy<a class="headerlink" href="#groupby" title="Permalink to this headline">¶</a></h1> |
| <p>GroupBy objects are returned by groupby calls: <a class="reference internal" href="api/pyspark.pandas.DataFrame.groupby.html#pyspark.pandas.DataFrame.groupby" title="pyspark.pandas.DataFrame.groupby"><code class="xref py py-func docutils literal notranslate"><span class="pre">DataFrame.groupby()</span></code></a>, <a class="reference internal" href="api/pyspark.pandas.Series.groupby.html#pyspark.pandas.Series.groupby" title="pyspark.pandas.Series.groupby"><code class="xref py py-func docutils literal notranslate"><span class="pre">Series.groupby()</span></code></a>, etc.</p> |
| <div class="section" id="indexing-iteration"> |
| <h2>Indexing, iteration<a class="headerlink" href="#indexing-iteration" title="Permalink to this headline">¶</a></h2> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.get_group.html#pyspark.pandas.groupby.GroupBy.get_group" title="pyspark.pandas.groupby.GroupBy.get_group"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.get_group</span></code></a>(name)</p></td> |
| <td><p>Construct DataFrame from group with provided name.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <div class="section" id="function-application"> |
| <h2>Function application<a class="headerlink" href="#function-application" title="Permalink to this headline">¶</a></h2> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.apply.html#pyspark.pandas.groupby.GroupBy.apply" title="pyspark.pandas.groupby.GroupBy.apply"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.apply</span></code></a>(func, *args, **kwargs)</p></td> |
| <td><p>Apply function <cite>func</cite> group-wise and combine the results together.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.transform.html#pyspark.pandas.groupby.GroupBy.transform" title="pyspark.pandas.groupby.GroupBy.transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.transform</span></code></a>(func, *args, **kwargs)</p></td> |
| <td><p>Apply function column-by-column to the GroupBy object.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p>The following methods are available only for <cite>DataFrameGroupBy</cite> objects.</p> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.DataFrameGroupBy.agg.html#pyspark.pandas.groupby.DataFrameGroupBy.agg" title="pyspark.pandas.groupby.DataFrameGroupBy.agg"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrameGroupBy.agg</span></code></a>([func_or_funcs])</p></td> |
| <td><p>Aggregate using one or more operations over the specified axis.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.DataFrameGroupBy.aggregate.html#pyspark.pandas.groupby.DataFrameGroupBy.aggregate" title="pyspark.pandas.groupby.DataFrameGroupBy.aggregate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrameGroupBy.aggregate</span></code></a>([func_or_funcs])</p></td> |
| <td><p>Aggregate using one or more operations over the specified axis.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <div class="section" id="computations-descriptive-stats"> |
| <h2>Computations / Descriptive Stats<a class="headerlink" href="#computations-descriptive-stats" title="Permalink to this headline">¶</a></h2> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.all.html#pyspark.pandas.groupby.GroupBy.all" title="pyspark.pandas.groupby.GroupBy.all"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.all</span></code></a>([skipna])</p></td> |
| <td><p>Returns True if all values in the group are truthful, else False.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.any.html#pyspark.pandas.groupby.GroupBy.any" title="pyspark.pandas.groupby.GroupBy.any"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.any</span></code></a>()</p></td> |
| <td><p>Returns True if any value in the group is truthful, else False.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.count.html#pyspark.pandas.groupby.GroupBy.count" title="pyspark.pandas.groupby.GroupBy.count"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.count</span></code></a>()</p></td> |
| <td><p>Compute count of group, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.cumcount.html#pyspark.pandas.groupby.GroupBy.cumcount" title="pyspark.pandas.groupby.GroupBy.cumcount"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.cumcount</span></code></a>([ascending])</p></td> |
| <td><p>Number each item in each group from 0 to the length of that group - 1.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.cummax.html#pyspark.pandas.groupby.GroupBy.cummax" title="pyspark.pandas.groupby.GroupBy.cummax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.cummax</span></code></a>()</p></td> |
| <td><p>Cumulative max for each group.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.cummin.html#pyspark.pandas.groupby.GroupBy.cummin" title="pyspark.pandas.groupby.GroupBy.cummin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.cummin</span></code></a>()</p></td> |
| <td><p>Cumulative min for each group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.cumprod.html#pyspark.pandas.groupby.GroupBy.cumprod" title="pyspark.pandas.groupby.GroupBy.cumprod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.cumprod</span></code></a>()</p></td> |
| <td><p>Cumulative product for each group.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.cumsum.html#pyspark.pandas.groupby.GroupBy.cumsum" title="pyspark.pandas.groupby.GroupBy.cumsum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.cumsum</span></code></a>()</p></td> |
| <td><p>Cumulative sum for each group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.ewm.html#pyspark.pandas.groupby.GroupBy.ewm" title="pyspark.pandas.groupby.GroupBy.ewm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.ewm</span></code></a>([com, span, halflife, alpha, …])</p></td> |
| <td><p>Return an ewm grouper, providing ewm functionality per group.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.filter.html#pyspark.pandas.groupby.GroupBy.filter" title="pyspark.pandas.groupby.GroupBy.filter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.filter</span></code></a>(func)</p></td> |
| <td><p>Return a copy of a DataFrame excluding elements from groups that do not satisfy the boolean criterion specified by func.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.first.html#pyspark.pandas.groupby.GroupBy.first" title="pyspark.pandas.groupby.GroupBy.first"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.first</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute first of group values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.last.html#pyspark.pandas.groupby.GroupBy.last" title="pyspark.pandas.groupby.GroupBy.last"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.last</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute last of group values.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.mad.html#pyspark.pandas.groupby.GroupBy.mad" title="pyspark.pandas.groupby.GroupBy.mad"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.mad</span></code></a>()</p></td> |
| <td><p>Compute mean absolute deviation of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.max.html#pyspark.pandas.groupby.GroupBy.max" title="pyspark.pandas.groupby.GroupBy.max"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.max</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute max of group values.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.mean.html#pyspark.pandas.groupby.GroupBy.mean" title="pyspark.pandas.groupby.GroupBy.mean"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.mean</span></code></a>([numeric_only])</p></td> |
| <td><p>Compute mean of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.median.html#pyspark.pandas.groupby.GroupBy.median" title="pyspark.pandas.groupby.GroupBy.median"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.median</span></code></a>([numeric_only, accuracy])</p></td> |
| <td><p>Compute median of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.min.html#pyspark.pandas.groupby.GroupBy.min" title="pyspark.pandas.groupby.GroupBy.min"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.min</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute min of group values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.nth.html#pyspark.pandas.groupby.GroupBy.nth" title="pyspark.pandas.groupby.GroupBy.nth"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.nth</span></code></a>(n)</p></td> |
| <td><p>Take the nth row from each group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.prod.html#pyspark.pandas.groupby.GroupBy.prod" title="pyspark.pandas.groupby.GroupBy.prod"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.prod</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute prod of groups.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.rank.html#pyspark.pandas.groupby.GroupBy.rank" title="pyspark.pandas.groupby.GroupBy.rank"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.rank</span></code></a>([method, ascending])</p></td> |
| <td><p>Provide the rank of values within each group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.sem.html#pyspark.pandas.groupby.GroupBy.sem" title="pyspark.pandas.groupby.GroupBy.sem"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.sem</span></code></a>([ddof])</p></td> |
| <td><p>Compute standard error of the mean of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.std.html#pyspark.pandas.groupby.GroupBy.std" title="pyspark.pandas.groupby.GroupBy.std"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.std</span></code></a>([ddof])</p></td> |
| <td><p>Compute standard deviation of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.sum.html#pyspark.pandas.groupby.GroupBy.sum" title="pyspark.pandas.groupby.GroupBy.sum"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.sum</span></code></a>([numeric_only, min_count])</p></td> |
| <td><p>Compute sum of group values</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.var.html#pyspark.pandas.groupby.GroupBy.var" title="pyspark.pandas.groupby.GroupBy.var"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.var</span></code></a>([ddof])</p></td> |
| <td><p>Compute variance of groups, excluding missing values.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.nunique.html#pyspark.pandas.groupby.GroupBy.nunique" title="pyspark.pandas.groupby.GroupBy.nunique"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.nunique</span></code></a>([dropna])</p></td> |
| <td><p>Return DataFrame with number of distinct observations per group for each column.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.quantile.html#pyspark.pandas.groupby.GroupBy.quantile" title="pyspark.pandas.groupby.GroupBy.quantile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.quantile</span></code></a>([q, accuracy])</p></td> |
| <td><p>Return group values at the given quantile.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.size.html#pyspark.pandas.groupby.GroupBy.size" title="pyspark.pandas.groupby.GroupBy.size"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.size</span></code></a>()</p></td> |
| <td><p>Compute group sizes.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.diff.html#pyspark.pandas.groupby.GroupBy.diff" title="pyspark.pandas.groupby.GroupBy.diff"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.diff</span></code></a>([periods])</p></td> |
| <td><p>First discrete difference of element.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.idxmax.html#pyspark.pandas.groupby.GroupBy.idxmax" title="pyspark.pandas.groupby.GroupBy.idxmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.idxmax</span></code></a>([skipna])</p></td> |
| <td><p>Return index of first occurrence of maximum over requested axis in group.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.idxmin.html#pyspark.pandas.groupby.GroupBy.idxmin" title="pyspark.pandas.groupby.GroupBy.idxmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.idxmin</span></code></a>([skipna])</p></td> |
| <td><p>Return index of first occurrence of minimum over requested axis in group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.fillna.html#pyspark.pandas.groupby.GroupBy.fillna" title="pyspark.pandas.groupby.GroupBy.fillna"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.fillna</span></code></a>([value, method, axis, …])</p></td> |
| <td><p>Fill NA/NaN values in group.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.bfill.html#pyspark.pandas.groupby.GroupBy.bfill" title="pyspark.pandas.groupby.GroupBy.bfill"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.bfill</span></code></a>([limit])</p></td> |
| <td><p>Synonym for <cite>DataFrame.fillna()</cite> with <code class="docutils literal notranslate"><span class="pre">method=`bfill`</span></code>.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.ffill.html#pyspark.pandas.groupby.GroupBy.ffill" title="pyspark.pandas.groupby.GroupBy.ffill"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.ffill</span></code></a>([limit])</p></td> |
| <td><p>Synonym for <cite>DataFrame.fillna()</cite> with <code class="docutils literal notranslate"><span class="pre">method=`ffill`</span></code>.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.head.html#pyspark.pandas.groupby.GroupBy.head" title="pyspark.pandas.groupby.GroupBy.head"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.head</span></code></a>([n])</p></td> |
| <td><p>Return first n rows of each group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.backfill.html#pyspark.pandas.groupby.GroupBy.backfill" title="pyspark.pandas.groupby.GroupBy.backfill"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.backfill</span></code></a>([limit])</p></td> |
| <td><p>Alias for bfill.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.shift.html#pyspark.pandas.groupby.GroupBy.shift" title="pyspark.pandas.groupby.GroupBy.shift"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.shift</span></code></a>([periods, fill_value])</p></td> |
| <td><p>Shift each group by periods observations.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.GroupBy.tail.html#pyspark.pandas.groupby.GroupBy.tail" title="pyspark.pandas.groupby.GroupBy.tail"><code class="xref py py-obj docutils literal notranslate"><span class="pre">GroupBy.tail</span></code></a>([n])</p></td> |
| <td><p>Return last n rows of each group.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p>The following methods are available only for <cite>DataFrameGroupBy</cite> objects.</p> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.DataFrameGroupBy.describe.html#pyspark.pandas.groupby.DataFrameGroupBy.describe" title="pyspark.pandas.groupby.DataFrameGroupBy.describe"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrameGroupBy.describe</span></code></a>()</p></td> |
| <td><p>Generate descriptive statistics that summarize the central tendency, dispersion and shape of a dataset’s distribution, excluding <code class="docutils literal notranslate"><span class="pre">NaN</span></code> values.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| <p>The following methods are available only for <cite>SeriesGroupBy</cite> objects.</p> |
| <table class="longtable table autosummary"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.SeriesGroupBy.nsmallest.html#pyspark.pandas.groupby.SeriesGroupBy.nsmallest" title="pyspark.pandas.groupby.SeriesGroupBy.nsmallest"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SeriesGroupBy.nsmallest</span></code></a>([n])</p></td> |
| <td><p>Return the smallest <cite>n</cite> elements.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.SeriesGroupBy.nlargest.html#pyspark.pandas.groupby.SeriesGroupBy.nlargest" title="pyspark.pandas.groupby.SeriesGroupBy.nlargest"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SeriesGroupBy.nlargest</span></code></a>([n])</p></td> |
| <td><p>Return the first n rows ordered by columns in descending order in group.</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.SeriesGroupBy.value_counts.html#pyspark.pandas.groupby.SeriesGroupBy.value_counts" title="pyspark.pandas.groupby.SeriesGroupBy.value_counts"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SeriesGroupBy.value_counts</span></code></a>([sort, …])</p></td> |
| <td><p>Compute group sizes.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="api/pyspark.pandas.groupby.SeriesGroupBy.unique.html#pyspark.pandas.groupby.SeriesGroupBy.unique" title="pyspark.pandas.groupby.SeriesGroupBy.unique"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SeriesGroupBy.unique</span></code></a>()</p></td> |
| <td><p>Return unique values in group.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| </div> |
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