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| <div class="section" id="pyspark-pandas-dataframe-squeeze"> |
| <h1>pyspark.pandas.DataFrame.squeeze<a class="headerlink" href="#pyspark-pandas-dataframe-squeeze" title="Permalink to this headline">¶</a></h1> |
| <dl class="py method"> |
| <dt id="pyspark.pandas.DataFrame.squeeze"> |
| <code class="sig-prename descclassname">DataFrame.</code><code class="sig-name descname">squeeze</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">axis</span><span class="p">:</span> <span class="n">Union[int, str, None]</span> <span class="o">=</span> <span class="default_value">None</span></em><span class="sig-paren">)</span> → Union[int, float, bool, str, bytes, decimal.Decimal, datetime.date, datetime.datetime, None, DataFrame, Series]<a class="headerlink" href="#pyspark.pandas.DataFrame.squeeze" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Squeeze 1 dimensional axis objects into scalars.</p> |
| <p>Series or DataFrames with a single element are squeezed to a scalar. |
| DataFrames with a single column or a single row are squeezed to a |
| Series. Otherwise the object is unchanged.</p> |
| <p>This method is most useful when you don’t know if your |
| object is a Series or DataFrame, but you do know it has just a single |
| column. In that case you can safely call <cite>squeeze</cite> to ensure you have a |
| Series.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><dl class="simple"> |
| <dt><strong>axis: {0 or ‘index’, 1 or ‘columns’, None}, default None</strong></dt><dd><p>A specific axis to squeeze. By default, all length-1 axes are |
| squeezed.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt>DataFrame, Series, or scalar</dt><dd><p>The projection after squeezing <cite>axis</cite> or all the axes.</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.Series.iloc.html#pyspark.pandas.Series.iloc" title="pyspark.pandas.Series.iloc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Series.iloc</span></code></a></dt><dd><p>Integer-location based indexing for selecting scalars.</p> |
| </dd> |
| <dt><a class="reference internal" href="pyspark.pandas.DataFrame.iloc.html#pyspark.pandas.DataFrame.iloc" title="pyspark.pandas.DataFrame.iloc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrame.iloc</span></code></a></dt><dd><p>Integer-location based indexing for selecting Series.</p> |
| </dd> |
| <dt><a class="reference internal" href="pyspark.pandas.Series.to_frame.html#pyspark.pandas.Series.to_frame" title="pyspark.pandas.Series.to_frame"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Series.to_frame</span></code></a></dt><dd><p>Inverse of DataFrame.squeeze for a single-column DataFrame.</p> |
| </dd> |
| </dl> |
| </div> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">primes</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">])</span> |
| </pre></div> |
| </div> |
| <p>Slicing might produce a Series with a single value:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">even_primes</span> <span class="o">=</span> <span class="n">primes</span><span class="p">[</span><span class="n">primes</span> <span class="o">%</span> <span class="mi">2</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span> |
| <span class="gp">>>> </span><span class="n">even_primes</span> |
| <span class="go">0 2</span> |
| <span class="go">dtype: int64</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">even_primes</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span> |
| <span class="go">2</span> |
| </pre></div> |
| </div> |
| <p>Squeezing objects with more than one value in every axis does nothing:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">odd_primes</span> <span class="o">=</span> <span class="n">primes</span><span class="p">[</span><span class="n">primes</span> <span class="o">%</span> <span class="mi">2</span> <span class="o">==</span> <span class="mi">1</span><span class="p">]</span> |
| <span class="gp">>>> </span><span class="n">odd_primes</span> |
| <span class="go">1 3</span> |
| <span class="go">2 5</span> |
| <span class="go">3 7</span> |
| <span class="go">dtype: int64</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">odd_primes</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span> |
| <span class="go">1 3</span> |
| <span class="go">2 5</span> |
| <span class="go">3 7</span> |
| <span class="go">dtype: int64</span> |
| </pre></div> |
| </div> |
| <p>Squeezing is even more effective when used with DataFrames.</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </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="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]],</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">'a'</span><span class="p">,</span> <span class="s1">'b'</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">df</span> |
| <span class="go"> a b</span> |
| <span class="go">0 1 2</span> |
| <span class="go">1 3 4</span> |
| </pre></div> |
| </div> |
| <p>Slicing a single column will produce a DataFrame with the columns |
| having only one value:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df_a</span> <span class="o">=</span> <span class="n">df</span><span class="p">[[</span><span class="s1">'a'</span><span class="p">]]</span> |
| <span class="gp">>>> </span><span class="n">df_a</span> |
| <span class="go"> a</span> |
| <span class="go">0 1</span> |
| <span class="go">1 3</span> |
| </pre></div> |
| </div> |
| <p>The columns can be squeezed down, resulting in a Series:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df_a</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="s1">'columns'</span><span class="p">)</span> |
| <span class="go">0 1</span> |
| <span class="go">1 3</span> |
| <span class="go">Name: a, dtype: int64</span> |
| </pre></div> |
| </div> |
| <p>Slicing a single row from a single column will produce a single |
| scalar DataFrame:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df_1a</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[[</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="s1">'a'</span><span class="p">]]</span> |
| <span class="gp">>>> </span><span class="n">df_1a</span> |
| <span class="go"> a</span> |
| <span class="go">1 3</span> |
| </pre></div> |
| </div> |
| <p>Squeezing the rows produces a single scalar Series:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df_1a</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="s1">'rows'</span><span class="p">)</span> |
| <span class="go">a 3</span> |
| <span class="go">Name: 1, dtype: int64</span> |
| </pre></div> |
| </div> |
| <p>Squeezing all axes will project directly into a scalar:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">df_1a</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span> |
| <span class="go">3</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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