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| <div class="section" id="pyspark-sql-functions-dense-rank"> |
| <h1>pyspark.sql.functions.dense_rank<a class="headerlink" href="#pyspark-sql-functions-dense-rank" title="Permalink to this headline">¶</a></h1> |
| <dl class="py function"> |
| <dt id="pyspark.sql.functions.dense_rank"> |
| <code class="sig-prename descclassname">pyspark.sql.functions.</code><code class="sig-name descname">dense_rank</code><span class="sig-paren">(</span><span class="sig-paren">)</span> → pyspark.sql.column.Column<a class="reference internal" href="../../../_modules/pyspark/sql/functions.html#dense_rank"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.sql.functions.dense_rank" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Window function: returns the rank of rows within a window partition, without any gaps.</p> |
| <p>The difference between rank and dense_rank is that dense_rank leaves no gaps in ranking |
| sequence when there are ties. That is, if you were ranking a competition using dense_rank |
| and had three people tie for second place, you would say that all three were in second |
| place and that the next person came in third. Rank would give me sequential numbers, making |
| the person that came in third place (after the ties) would register as coming in fifth.</p> |
| <p>This is equivalent to the DENSE_RANK function in SQL.</p> |
| <div class="versionadded"> |
| <p><span class="versionmodified added">New in version 1.6.</span></p> |
| </div> |
| </dd></dl> |
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