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Minor fixes
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@yashdave003
yashdave003 committed Feb 16, 2024
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127 changes: 124 additions & 3 deletions visualizations/images/visualizations.html → visualizations/visualizations.html
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<link href="visualizations_files/libs/bootstrap/bootstrap-icons.css" rel="stylesheet">
<link href="visualizations_files/libs/bootstrap/bootstrap.min.css" rel="stylesheet" id="quarto-bootstrap" data-mode="light">

<script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
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</head>

Expand All @@ -47,6 +76,8 @@ <h2 id="toc-title">Table of contents</h2>
<ul>
<li><a href="#my-legends-labels-dont-match-up-my-legend-isnt-displaying-properly" id="toc-my-legends-labels-dont-match-up-my-legend-isnt-displaying-properly" class="nav-link active" data-scroll-target="#my-legends-labels-dont-match-up-my-legend-isnt-displaying-properly">My legend’s labels don’t match up / my legend isn’t displaying properly</a></li>
<li><a href="#the-y-axis-of-my-histplot-shows-the-count-not-the-density" id="toc-the-y-axis-of-my-histplot-shows-the-count-not-the-density" class="nav-link" data-scroll-target="#the-y-axis-of-my-histplot-shows-the-count-not-the-density">The y-axis of my <code>histplot</code> shows the count, not the density</a></li>
<li><a href="#im-having-trouble-labeling-the-axestitle-of-my-graph" id="toc-im-having-trouble-labeling-the-axestitle-of-my-graph" class="nav-link" data-scroll-target="#im-having-trouble-labeling-the-axestitle-of-my-graph">I’m having trouble labeling the axes/title of my graph</a></li>
<li><a href="#my-sns.lineplot-has-an-unwanted-shaded-region-around-the-solid-lines." id="toc-my-sns.lineplot-has-an-unwanted-shaded-region-around-the-solid-lines." class="nav-link" data-scroll-target="#my-sns.lineplot-has-an-unwanted-shaded-region-around-the-solid-lines.">My <code>sns.lineplot</code> has an unwanted shaded region around the solid lines.</a></li>
</ul>
</nav>
</div>
Expand Down Expand Up @@ -75,19 +106,109 @@ <h1 class="title">Visualizations</h1>
<section id="my-legends-labels-dont-match-up-my-legend-isnt-displaying-properly" class="level3">
<h3 class="anchored" data-anchor-id="my-legends-labels-dont-match-up-my-legend-isnt-displaying-properly">My legend’s labels don’t match up / my legend isn’t displaying properly</h3>
<p>If you simply add <code>plt.legend()</code> after your plotting line of code, you should see a legend. When using seaborn, sometimes it will automatically populate the legend. However, if you’re plotting multiple lines or sets of points on a single plot, the labels in the legend may not correctly line up with what’s shown.</p>
<p>Make sure to pass in the <code>label</code> argument into the function call with the label you want associated with that individual plot. For example,</p>
<p>Make sure to pass in the <code>label=</code> argument into the plotting function with the label you want associated with that individual plot. For example,</p>
<pre><code>sns.histplot(means_arr, label = 'simulated values') # informative label name
plt.title('Simulated values')
plt.plot(original, 10, 'bo', label = 'original test statistic') # informative label name
plt.legend(loc = 'upper left') # can specify location of legend</code></pre>
<center>
<img src="example_label_plot.png" width="500">
<img src="images/example_label_plot.png" width="500">
</center>
<p><br></p>
</section>
<section id="the-y-axis-of-my-histplot-shows-the-count-not-the-density" class="level2">
<h2 class="anchored" data-anchor-id="the-y-axis-of-my-histplot-shows-the-count-not-the-density">The y-axis of my <code>histplot</code> shows the count, not the density</h2>
<p>Look into the <code>sns.histplot</code> <a href="https://seaborn.pydata.org/generated/seaborn.histplot.html">documentation</a> and see what arguments the <code>stat</code> parameter takes in. By default, <code>stat=count</code>, but if you wanted to normalize the distribution such that the total area is 1, you could consider <code>stat=density</code>.</p>
<p>Look into the <code>sns.histplot</code> <a href="https://seaborn.pydata.org/generated/seaborn.histplot.html">documentation</a> and see what arguments the <code>stat=</code> parameter takes in. By default, <code>stat=count</code>, and the number of elements in each histogram bin is the y axis. But if you wanted to normalize the distribution such that the total area is 1, consider passing <code>stat=density</code> into the plot function.</p>
</section>
<section id="im-having-trouble-labeling-the-axestitle-of-my-graph" class="level2">
<h2 class="anchored" data-anchor-id="im-having-trouble-labeling-the-axestitle-of-my-graph">I’m having trouble labeling the axes/title of my graph</h2>
<p>To label the axes and title of a graph, we use the following syntax:</p>
<pre><code>plt.xlabel(“x axis name”)
plt.ylabel(“y axis name”)
plt.title(“graph title”) </code></pre>
<p>Where <code>plt.xlabel</code>, <code>plt.ylabel</code>, and <code>plt.title</code> are matplotlib functions that we call.</p>
<p>However, we often see students use the following incorrect syntax to try and label their plot:</p>
<pre><code>plt.xlabel = “x name”
plt.ylabel = "y name”
plt.title = “graph title” </code></pre>
<p>Now, instead of <code>plt.xlabel</code>, <code>plt.ylabel</code>, and <code>plt.title</code> being functions, they are strings. Trying to call one of the labelling function using the correct syntax afterwards (ie.<code>plt.xlabel(“x name”)</code>) results in a <code>TypeError: str object is not callable</code>. If this happens to you, comb through your notebook and look for places when you used the incorrect syntax. After fixing it, <a href="https://ds100.org/debugging-guide/jupyter101/jupyter101.html#restarting-kernel">restart your kernel</a> and <a href="https://ds100.org/debugging-guide/jupyter101/jupyter101.html#running-cells">rerun your cells</a>.</p>
</section>
<section id="my-sns.lineplot-has-an-unwanted-shaded-region-around-the-solid-lines." class="level2">
<h2 class="anchored" data-anchor-id="my-sns.lineplot-has-an-unwanted-shaded-region-around-the-solid-lines.">My <code>sns.lineplot</code> has an unwanted shaded region around the solid lines.</h2>
<blockquote class="blockquote">
<p>Note: the following examples are taken from <code>sns.lineplot</code>’s <a href="https://seaborn.pydata.org/generated/seaborn.lineplot.html">documentation</a>.</p>
</blockquote>
<p><code>sns.lineplot</code> gives us a clean line when each x value has one y value. For example, the table</p>
<table class="table">
<thead>
<tr class="header">
<th>Year</th>
<th>May</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>1948</td>
<td>120</td>
</tr>
<tr class="even">
<td>1949</td>
<td>122</td>
</tr>
<tr class="odd">
<td>1950</td>
<td>123</td>
</tr>
</tbody>
</table>
<p><span class="math inline">\(\vdots\)</span></p>
<p>will result in the following clean plot because each year corresponds to a single “Number of Flights in May” value.</p>
<center>
<img src="images/normal_lineplot.png" width="500">
</center>
<p><br></p>
<p>When each x value has multiple y values, <code>sns.lineplot</code> will automatically plot a shaded region around the solid line, where the solid line is the mean of the y values for that x value and the shaded region is the 95% confidence interval (read more about confidence intervals in the <a href="https://inferentialthinking.com/chapters/13/3/Confidence_Intervals.html?highlight=confidence+intervals">Data 8 textbook</a>). For example, the table</p>
<table class="table">
<thead>
<tr class="header">
<th>Year</th>
<th>May</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>1948</td>
<td>115</td>
</tr>
<tr class="even">
<td>1948</td>
<td>120</td>
</tr>
<tr class="odd">
<td>1948</td>
<td>125</td>
</tr>
<tr class="even">
<td>1949</td>
<td>118</td>
</tr>
<tr class="odd">
<td>1949</td>
<td>122</td>
</tr>
<tr class="even">
<td>1949</td>
<td>126</td>
</tr>
</tbody>
</table>
<p><span class="math inline">\(\vdots\)</span></p>
<p>will plot a lineplot with a shaded region representing the 95% confidence interval.</p>
<center>
<img src="images/shaded_lineplot.png" width="500">
</center>
<p><br></p>
<p>If you do not want the shaded region, aggregate the data such that there is only one y-value for a given x-value; then, make the plot.</p>
</section>

</main>
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12 changes: 6 additions & 6 deletions visualizations/visualizations.md
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Expand Up @@ -20,7 +20,7 @@ Visualizations are how data scientists use to communicate their insights to the

If you simply add `plt.legend()` after your plotting line of code, you should see a legend. When using seaborn, sometimes it will automatically populate the legend. However, if you’re plotting multiple lines or sets of points on a single plot, the labels in the legend may not correctly line up with what’s shown.

Make sure to pass in the `label=` argument into the plotting function with the label you want associated with that individual plot. For example,
Make sure to pass in the `label` argument into the plotting function with the label you want associated with that individual plot. For example,

```
sns.histplot(means_arr, label = 'simulated values') # informative label name
Expand All @@ -33,7 +33,7 @@ plt.legend(loc = 'upper left') # can specify location of legend

## The y-axis of my `histplot` shows the count, not the density

Look into the `sns.histplot` [documentation](https://seaborn.pydata.org/generated/seaborn.histplot.html) and see what arguments the `stat=` parameter takes in. By default, `stat=count`, and the number of elements in each histogram bin is the y axis. But if you wanted to normalize the distribution such that the total area is 1, consider passing `stat=density` into the plot function.
Look into the `sns.histplot` [documentation](https://seaborn.pydata.org/generated/seaborn.histplot.html) and see what arguments the `stat` parameter takes in. By default, `stat=count`, and the number of elements in each histogram bin is the y axis. But if you wanted to normalize the distribution such that the total area is 1, consider passing `stat=density` into the plot function.

## I’m having trouble labeling the axes/title of my graph
To label the axes and title of a graph, we use the following syntax:
Expand All @@ -49,16 +49,16 @@ Where `plt.xlabel`, `plt.ylabel`, and `plt.title` are matplotlib functions that
However, we often see students use the following incorrect syntax to try and label their plot:

```
plt.xlabel = “x name”
plt.ylabel = "y name”
plt.title = “graph title”
plt.xlabel = "x name"
plt.ylabel = "y name"
plt.title = "graph title"
```
Now, instead of `plt.xlabel`, `plt.ylabel`, and `plt.title` being functions, they are strings. Trying to call one of the labelling function using the correct syntax afterwards (ie.` plt.xlabel(“x name”)`) results in a `TypeError: str object is not callable`. If this happens to you, comb through your notebook and look for places when you used the incorrect syntax. After fixing it, [restart your kernel](https://ds100.org/debugging-guide/jupyter101/jupyter101.html#restarting-kernel) and [rerun your cells](https://ds100.org/debugging-guide/jupyter101/jupyter101.html#running-cells).

## My `sns.lineplot` has an unwanted shaded region around the solid lines.
>Note: the following examples are taken from `sns.lineplot`'s [documentation](https://seaborn.pydata.org/generated/seaborn.lineplot.html).
`sns.lineplot` gives us a clean line when each x value has one y value. For example, the table
`sns.lineplot` gives us a clean line when each `x` value has one `y` value. For example, the table

| Year | May |
| --- | --- |
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