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1. Repaso
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2. Consultas SQL
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Select
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Where
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Full Join
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Union
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Update
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Delete
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<div class="section" id="clase-14-continuacion-con-los-datos">
<h1>Clase 14: continuación con los datos<a class="headerlink" href="#clase-14-continuacion-con-los-datos" title="Permalink to this headline">¶</a></h1>
<p>En esta clase vamos a continuar con el uso de <code class="docutils literal notranslate"><span class="pre">pandas</span></code>. Veremos:</p>
<ol class="simple">
<li><p>Consultas SQL</p>
<ul class="simple">
<li><p>Qué es?</p></li>
<li><p>Select</p></li>
<li><p>Where</p></li>
<li><p>Join</p></li>
<li><p>Union</p></li>
<li><p>Update</p></li>
<li><p>Delete</p></li>
</ul>
</li>
<li><p>Ejercicios</p></li>
</ol>
<div class="section" id="repaso">
<h2>1. Repaso<a class="headerlink" href="#repaso" title="Permalink to this headline">¶</a></h2>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
</pre></div>
</div>
</div>
</div>
<p>Para el ejemplo de esta clase vamos a usar una pequeña base llamada <code class="docutils literal notranslate"><span class="pre">tips</span></code> que tiene a disposición la librería <code class="docutils literal notranslate"><span class="pre">pandas</span></code>.</p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Podemos llamar la librería con el siguiente url</span>
<span class="n">url</span> <span class="o">=</span> <span class="p">(</span><span class="s2">"https://raw.github.com/pandas-dev"</span>
<span class="s2">"/pandas/master/pandas/tests/io/data/csv/tips.csv"</span><span class="p">)</span>
<span class="c1">#Creamos el DataFrame</span>
<span class="n">tips</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">url</span><span class="p">)</span>
<span class="c1">#Revisamos el contenido</span>
<span class="n">tips</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output text_html"><div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total_bill</th>
<th>tip</th>
<th>sex</th>
<th>smoker</th>
<th>day</th>
<th>time</th>
<th>size</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16.99</td>
<td>1.01</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>1</th>
<td>10.34</td>
<td>1.66</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>21.01</td>
<td>3.50</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>23.68</td>
<td>3.31</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>24.59</td>
<td>3.61</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>25.29</td>
<td>4.71</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>4</td>
</tr>
<tr>
<th>6</th>
<td>8.77</td>
<td>2.00</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>26.88</td>
<td>3.12</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>4</td>
</tr>
<tr>
<th>8</th>
<td>15.04</td>
<td>1.96</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>14.78</td>
<td>3.23</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
</tbody>
</table>
</div></div></div>
</div>
<p>Vamos a crear una función que nos permita visualizar información del DataFrame</p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Declaramos la función y el nombre del input</span>
<span class="k">def</span> <span class="nf">grafico1</span><span class="p">(</span><span class="n">DF</span><span class="p">):</span>
<span class="c1">#Definimos los datos a usar</span>
<span class="n">data1</span> <span class="o">=</span> <span class="n">DF</span><span class="p">[[</span><span class="s1">'total_bill'</span><span class="p">,</span> <span class="s1">'size'</span><span class="p">]]</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">'size'</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="n">data1</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">data1</span><span class="o">.</span><span class="n">total_bill</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">"Tamaño de la mesa"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">"Promedio de la cuenta"</span><span class="p">)</span>
<span class="c1">#Llamamos la función y le damos el input</span>
<span class="n">grafico1</span><span class="p">(</span><span class="n">tips</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<img alt="_images/Clase_13_14_b_6_0.png" src="_images/Clase_13_14_b_6_0.png" />
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Declaramos la función y el nombre del input</span>
<span class="k">def</span> <span class="nf">grafico2</span><span class="p">(</span><span class="n">DF</span><span class="p">):</span>
<span class="c1">#Definimos los datos</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">DF</span><span class="o">.</span><span class="n">total_bill</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">DF</span><span class="o">.</span><span class="n">tip</span>
<span class="c1">#Gráfico de puntos (scatter)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">"Total cuenta"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">"Propina"</span><span class="p">)</span>
<span class="c1">#Gráfico de línea</span>
<span class="n">m</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span> <span class="c1">#Sacar la pendiente y el intercepto de y(x)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">m</span><span class="o">*</span><span class="n">x</span> <span class="o">+</span> <span class="n">b</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">)</span>
<span class="c1">#Llamamos la función y le damos el input</span>
<span class="n">grafico2</span><span class="p">(</span><span class="n">tips</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<img alt="_images/Clase_13_14_b_7_0.png" src="_images/Clase_13_14_b_7_0.png" />
</div>
</div>
<p>Y si la función la queremos con dos input?</p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Declaramos la función y el nombre del input</span>
<span class="k">def</span> <span class="nf">grafico2</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
<span class="c1">#Gráfico de puntos (scatter)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">"Total cuenta"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">"Propina"</span><span class="p">)</span>
<span class="c1">#Gráfico de línea</span>
<span class="n">m</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span> <span class="c1">#Sacar la pendiente y el intercepto de y(x)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">m</span><span class="o">*</span><span class="n">x</span> <span class="o">+</span> <span class="n">b</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">)</span>
<span class="c1">#Creamos las variables que vamos a usar como input</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">tips</span><span class="o">.</span><span class="n">total_bill</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">tips</span><span class="o">.</span><span class="n">tip</span>
<span class="c1">#Hacemos el gráfico</span>
<span class="n">grafico2</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<img alt="_images/Clase_13_14_b_9_0.png" src="_images/Clase_13_14_b_9_0.png" />
</div>
</div>
<p>Si queremos guardar la diferencia entre las filas de una variable del set de datos, podemos por ejemplo usar un <code class="docutils literal notranslate"><span class="pre">for</span></code></p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Definimos la variable a utilizar</span>
<span class="n">var</span> <span class="o">=</span> <span class="n">tips</span><span class="o">.</span><span class="n">total_bill</span>
<span class="c1">#Creamos la lista donde vamos a guardar los datos</span>
<span class="n">lista</span> <span class="o">=</span> <span class="p">[]</span>
<span class="c1">#Realizamos el lopp: desde el segundo valor hasta el último (1, n)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">var</span><span class="p">)):</span>
<span class="n">lista</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">-</span><span class="n">var</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="c1">#Sacamos la diferencia</span>
<span class="nb">print</span><span class="p">(</span><span class="n">var</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
<span class="nb">print</span><span class="p">(</span><span class="n">lista</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">10</span><span class="p">])</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0 16.99
1 10.34
2 21.01
3 23.68
4 24.59
5 25.29
6 8.77
7 26.88
8 15.04
9 14.78
Name: total_bill, dtype: float64
[-6.649999999999999, 10.670000000000002, 2.669999999999998, 0.9100000000000001, 0.6999999999999993, -16.52, 18.11, -11.84, -0.2599999999999998, -4.51]
</pre></div>
</div>
</div>
</div>
<p>Otra forma es usar la función <code class="docutils literal notranslate"><span class="pre">diff</span></code>. El siguiente link muestra en detalle cómo usar la función:
<a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.diff.html">https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.diff.html</a></p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#si queremos sacar la diferencia de una variable definimos el DataFrame.nombre_variable.diff()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">tips</span><span class="o">.</span><span class="n">total_bill</span><span class="o">.</span><span class="n">diff</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="c1">#Tambien podemos especificar los periodos para hacer la diferencia</span>
<span class="nb">print</span><span class="p">(</span><span class="n">tips</span><span class="o">.</span><span class="n">total_bill</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">periods</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
<span class="c1">#Podemos cambiar el sentido de la diferencia (ascendente o descendente)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">tips</span><span class="o">.</span><span class="n">total_bill</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">periods</span><span class="o">=-</span><span class="mi">3</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">())</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0 NaN
1 -6.65
2 10.67
3 2.67
4 0.91
Name: total_bill, dtype: float64
0 NaN
1 NaN
2 NaN
3 6.69
4 14.25
Name: total_bill, dtype: float64
0 -6.69
1 -14.25
2 -4.28
3 14.91
4 -2.29
Name: total_bill, dtype: float64
</pre></div>
</div>
</div>
</div>
</div>
<div class="section" id="consultas-sql">
<h2>2. Consultas SQL<a class="headerlink" href="#consultas-sql" title="Permalink to this headline">¶</a></h2>
<p>SQL (por su nombre en inglés) es un lenguaje de programación utilizado para trabajar con <code class="docutils literal notranslate"><span class="pre">bases</span> <span class="pre">relacionales</span></code>. Este lenguaje nos permite recuperar de forma simple información de bases de datos donde tenemos bases que pueden estar relacionadas mediante alguna variable. Por ejemplo:</p>
<div class="figure align-default">
<a class="reference internal image-reference" href="_images/base_relacional.png"><img alt="_images/base_relacional.png" src="_images/base_relacional.png" style="height: 400px;" /></a>
</div>
<p>Podemos tener información de diferentes fuentes, planillas de costos, ingresos, compras, etc. y buscar vincular esta información para hacer análisis, presentar información o realizar cálculos específico.</p>
<p>El objetivo de esta clase no es SQL, sino la forma de trabajar este lenguaje. En python podemos usar <code class="docutils literal notranslate"><span class="pre">pandas</span></code> para replicar el trabajo con bases de datos relacionales.</p>
<div class="section" id="select">
<h3>Select<a class="headerlink" href="#select" title="Permalink to this headline">¶</a></h3>
<p>El objetivo es seleccionar un set de información específico</p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Ponemos el DataFrame y las variables específicas que queremos</span>
<span class="c1">#Ojo que va "DataFrame[]" y dentro del paréntesis van las variables dentro de un "[]"</span>
<span class="n">tips</span><span class="p">[[</span><span class="s2">"total_bill"</span><span class="p">,</span> <span class="s2">"tip"</span><span class="p">,</span> <span class="s2">"smoker"</span><span class="p">,</span> <span class="s2">"time"</span><span class="p">]]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output text_html"><div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total_bill</th>
<th>tip</th>
<th>smoker</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16.99</td>
<td>1.01</td>
<td>No</td>
<td>Dinner</td>
</tr>
<tr>
<th>1</th>
<td>10.34</td>
<td>1.66</td>
<td>No</td>
<td>Dinner</td>
</tr>
<tr>
<th>2</th>
<td>21.01</td>
<td>3.50</td>
<td>No</td>
<td>Dinner</td>
</tr>
<tr>
<th>3</th>
<td>23.68</td>
<td>3.31</td>
<td>No</td>
<td>Dinner</td>
</tr>
<tr>
<th>4</th>
<td>24.59</td>
<td>3.61</td>
<td>No</td>
<td>Dinner</td>
</tr>
</tbody>
</table>
</div></div></div>
</div>
<p>Para agregar un nueva variable según un ratio podemos usar <code class="docutils literal notranslate"><span class="pre">DataFrame.assign()</span></code></p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">tips</span><span class="o">.</span><span class="n">assign</span><span class="p">(</span><span class="n">tip_rate</span><span class="o">=</span><span class="n">tips</span><span class="p">[</span><span class="s2">"tip"</span><span class="p">]</span> <span class="o">/</span> <span class="n">tips</span><span class="p">[</span><span class="s2">"total_bill"</span><span class="p">])</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output text_html"><div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total_bill</th>
<th>tip</th>
<th>sex</th>
<th>smoker</th>
<th>day</th>
<th>time</th>
<th>size</th>
<th>tip_rate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16.99</td>
<td>1.01</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
<td>0.059447</td>
</tr>
<tr>
<th>1</th>
<td>10.34</td>
<td>1.66</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
<td>0.160542</td>
</tr>
<tr>
<th>2</th>
<td>21.01</td>
<td>3.50</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
<td>0.166587</td>
</tr>
<tr>
<th>3</th>
<td>23.68</td>
<td>3.31</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
<td>0.139780</td>
</tr>
<tr>
<th>4</th>
<td>24.59</td>
<td>3.61</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>4</td>
<td>0.146808</td>
</tr>
</tbody>
</table>
</div></div></div>
</div>
</div>
<div class="section" id="where">
<h3>Where<a class="headerlink" href="#where" title="Permalink to this headline">¶</a></h3>
<p>Usamos este tipo de consulta para seleccionar una información en específico, por ejemplo cuando la variable <code class="docutils literal notranslate"><span class="pre">time</span></code> es igual a <code class="docutils literal notranslate"><span class="pre">Diner</span></code></p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#La sintaxis es DataFrame[DataFrame[Variable] == Condicion]</span>
<span class="c1">#En resumen le estamos diciendo DataFrame[Variable == Condicion], donde Variable=DataFrame[Variable]</span>
<span class="n">tips</span><span class="p">[</span><span class="n">tips</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"Dinner"</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
</div>
</div>
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<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>total_bill</th>
<th>tip</th>
<th>sex</th>
<th>smoker</th>
<th>day</th>
<th>time</th>
<th>size</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>16.99</td>
<td>1.01</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>1</th>
<td>10.34</td>
<td>1.66</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>21.01</td>
<td>3.50</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>23.68</td>
<td>3.31</td>
<td>Male</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>24.59</td>
<td>3.61</td>
<td>Female</td>
<td>No</td>
<td>Sun</td>
<td>Dinner</td>
<td>4</td>
</tr>
</tbody>
</table>
</div></div></div>
</div>
<p>Podemos ver si se cumple una condición como verdadero/falso y podemos usar la función <code class="docutils literal notranslate"><span class="pre">value_counts()</span></code> para ver cuántas veces se cumple o no</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1">#Creamos una variable que guarde si se cumple la condición</span>
<span class="n">variable_condicion</span> <span class="o">=</span> <span class="n">tips</span><span class="p">[</span><span class="s2">"time"</span><span class="p">]</span> <span class="o">==</span> <span class="s2">"Dinner"</span>
<span class="c1">#Evaluamos cuantas veces se cumple la condición con la función value_counts()</span>
<span class="n">variable_condicion</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
</pre></div>
</div>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>True 176
False 68
Name: time, dtype: int64
</pre></div>
</div>
</div>
</div>
<p>Luego, podemos revisar el DataFrame donde se cumpla la condición que establecimos previamente.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">tips</span><span class="p">[</span><span class="n">variable_condicion</span><span class="p">]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
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