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<section id="pyspark-pandas-dataframe-reset-index">
<h1>pyspark.pandas.DataFrame.reset_index<a class="headerlink" href="#pyspark-pandas-dataframe-reset-index" title="Permalink to this headline">#</a></h1>
<dl class="py method">
<dt class="sig sig-object py" id="pyspark.pandas.DataFrame.reset_index">
<span class="sig-prename descclassname"><span class="pre">DataFrame.</span></span><span class="sig-name descname"><span class="pre">reset_index</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">level</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="n"><span class="pre">drop</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inplace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col_level</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">col_fill</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/pyspark/pandas/frame.html#DataFrame.reset_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyspark.pandas.DataFrame.reset_index" title="Permalink to this definition">#</a></dt>
<dd><p>Reset the index, or a level of it.</p>
<p>For DataFrame with multi-level index, return new DataFrame with labeling information in
the columns under the index names, defaulting to ‘level_0’, ‘level_1’, etc. if any are None.
For a standard index, the index name will be used (if set), otherwise a default ‘index’ or
‘level_0’ (if ‘index’ is already taken) will be used.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>level</strong><span class="classifier">int, str, tuple, or list, default None</span></dt><dd><p>Only remove the given levels from the index. Removes all levels by
default.</p>
</dd>
<dt><strong>drop</strong><span class="classifier">bool, default False</span></dt><dd><p>Do not try to insert index into dataframe columns. This reset
the index to the default integer index.</p>
</dd>
<dt><strong>inplace</strong><span class="classifier">bool, default False</span></dt><dd><p>Modify the DataFrame in place (do not create a new object).</p>
</dd>
<dt><strong>col_level</strong><span class="classifier">int or str, default 0</span></dt><dd><p>If the columns have multiple levels, determines which level the
labels are inserted into. By default it is inserted into the first
level.</p>
</dd>
<dt><strong>col_fill</strong><span class="classifier">object, default ‘’</span></dt><dd><p>If the columns have multiple levels, determines how the other
levels are named. If None then the index name is repeated.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt>DataFrame</dt><dd><p>DataFrame with the new index.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="pyspark.pandas.DataFrame.set_index.html#pyspark.pandas.DataFrame.set_index" title="pyspark.pandas.DataFrame.set_index"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrame.set_index</span></code></a></dt><dd><p>Opposite of reset_index.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">([(</span><span class="s1">&#39;bird&#39;</span><span class="p">,</span> <span class="mf">389.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;bird&#39;</span><span class="p">,</span> <span class="mf">24.0</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;mammal&#39;</span><span class="p">,</span> <span class="mf">80.5</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;mammal&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;falcon&#39;</span><span class="p">,</span> <span class="s1">&#39;parrot&#39;</span><span class="p">,</span> <span class="s1">&#39;lion&#39;</span><span class="p">,</span> <span class="s1">&#39;monkey&#39;</span><span class="p">],</span>
<span class="gp">... </span> <span class="n">columns</span><span class="o">=</span><span class="p">(</span><span class="s1">&#39;class&#39;</span><span class="p">,</span> <span class="s1">&#39;max_speed&#39;</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span>
<span class="go"> class max_speed</span>
<span class="go">falcon bird 389.0</span>
<span class="go">parrot bird 24.0</span>
<span class="go">lion mammal 80.5</span>
<span class="go">monkey mammal NaN</span>
</pre></div>
</div>
<p>When we reset the index, the old index is added as a column. Unlike pandas, pandas-on-Spark
does not automatically add a sequential index. The following 0, 1, 2, 3 are only
there when we display the DataFrame.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
<span class="go"> index class max_speed</span>
<span class="go">0 falcon bird 389.0</span>
<span class="go">1 parrot bird 24.0</span>
<span class="go">2 lion mammal 80.5</span>
<span class="go">3 monkey mammal NaN</span>
</pre></div>
</div>
<p>We can use the <cite>drop</cite> parameter to avoid the old index being added as
a column:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="go"> class max_speed</span>
<span class="go">0 bird 389.0</span>
<span class="go">1 bird 24.0</span>
<span class="go">2 mammal 80.5</span>
<span class="go">3 mammal NaN</span>
</pre></div>
</div>
<p>You can also use <cite>reset_index</cite> with <cite>MultiIndex</cite>.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">index</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_tuples</span><span class="p">([(</span><span class="s1">&#39;bird&#39;</span><span class="p">,</span> <span class="s1">&#39;falcon&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;bird&#39;</span><span class="p">,</span> <span class="s1">&#39;parrot&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;mammal&#39;</span><span class="p">,</span> <span class="s1">&#39;lion&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;mammal&#39;</span><span class="p">,</span> <span class="s1">&#39;monkey&#39;</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">names</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;class&#39;</span><span class="p">,</span> <span class="s1">&#39;name&#39;</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">MultiIndex</span><span class="o">.</span><span class="n">from_tuples</span><span class="p">([(</span><span class="s1">&#39;speed&#39;</span><span class="p">,</span> <span class="s1">&#39;max&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="s1">&#39;species&#39;</span><span class="p">,</span> <span class="s1">&#39;type&#39;</span><span class="p">)])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">([(</span><span class="mf">389.0</span><span class="p">,</span> <span class="s1">&#39;fly&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span> <span class="mf">24.0</span><span class="p">,</span> <span class="s1">&#39;fly&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span> <span class="mf">80.5</span><span class="p">,</span> <span class="s1">&#39;run&#39;</span><span class="p">),</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">&#39;jump&#39;</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">index</span><span class="o">=</span><span class="n">index</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">columns</span><span class="o">=</span><span class="n">columns</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span>
<span class="go"> speed species</span>
<span class="go"> max type</span>
<span class="go">class name</span>
<span class="go">bird falcon 389.0 fly</span>
<span class="go"> parrot 24.0 fly</span>
<span class="go">mammal lion 80.5 run</span>
<span class="go"> monkey NaN jump</span>
</pre></div>
</div>
<p>If the index has multiple levels, we can reset a subset of them:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="s1">&#39;class&#39;</span><span class="p">)</span>
<span class="go"> class speed species</span>
<span class="go"> max type</span>
<span class="go">name</span>
<span class="go">falcon bird 389.0 fly</span>
<span class="go">parrot bird 24.0 fly</span>
<span class="go">lion mammal 80.5 run</span>
<span class="go">monkey mammal NaN jump</span>
</pre></div>
</div>
<p>If we are not dropping the index, by default, it is placed in the top
level. We can place it in another level:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="s1">&#39;class&#39;</span><span class="p">,</span> <span class="n">col_level</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="go"> speed species</span>
<span class="go"> class max type</span>
<span class="go">name</span>
<span class="go">falcon bird 389.0 fly</span>
<span class="go">parrot bird 24.0 fly</span>
<span class="go">lion mammal 80.5 run</span>
<span class="go">monkey mammal NaN jump</span>
</pre></div>
</div>
<p>When the index is inserted under another level, we can specify under
which one with the parameter <cite>col_fill</cite>:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="s1">&#39;class&#39;</span><span class="p">,</span> <span class="n">col_level</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">col_fill</span><span class="o">=</span><span class="s1">&#39;species&#39;</span><span class="p">)</span>
<span class="go"> species speed species</span>
<span class="go"> class max type</span>
<span class="go">name</span>
<span class="go">falcon bird 389.0 fly</span>
<span class="go">parrot bird 24.0 fly</span>
<span class="go">lion mammal 80.5 run</span>
<span class="go">monkey mammal NaN jump</span>
</pre></div>
</div>
<p>If we specify a nonexistent level for <cite>col_fill</cite>, it is created:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">(</span><span class="n">level</span><span class="o">=</span><span class="s1">&#39;class&#39;</span><span class="p">,</span> <span class="n">col_level</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">col_fill</span><span class="o">=</span><span class="s1">&#39;genus&#39;</span><span class="p">)</span>
<span class="go"> genus speed species</span>
<span class="go"> class max type</span>
<span class="go">name</span>
<span class="go">falcon bird 389.0 fly</span>
<span class="go">parrot bird 24.0 fly</span>
<span class="go">lion mammal 80.5 run</span>
<span class="go">monkey mammal NaN jump</span>
</pre></div>
</div>
</dd></dl>
</section>
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