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04_Relational_Data.html
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04_Relational_Data.html
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<!DOCTYPE html>
<html lang="en"><head>
<script src="04_Relational_Data_files/libs/clipboard/clipboard.min.js"></script>
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<meta name="generator" content="quarto-1.3.299">
<title>Relational Data</title>
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</head>
<body class="quarto-light">
<div class="reveal">
<div class="slides">
<section id="title-slide" class="quarto-title-block center">
<h1 class="title">Relational Data</h1>
<p class="subtitle">Fundamentals of Data Science for NHS using R</p>
<div class="quarto-title-authors">
</div>
</section>
<section id="todays-plan" class="slide level2">
<h2>Today’s Plan</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<ul>
<li>Introduction to relational data
<ul>
<li>Mutating joins</li>
<li>Filtering joins</li>
<li>Set operations</li>
</ul></li>
</ul>
</div>
</div>
</div>
</section>
<section>
<section id="lets-start-at-the-beginning" class="title-slide slide level1 center">
<h1>Let’s start at the beginning…</h1>
</section>
<section id="what-is-relational-data" class="slide level2">
<h2>What is relational data?</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<ul>
<li class="fragment"><p>Typically you have many tables of data, and you must combine them to answer the questions that you’re interested in.</p></li>
<li class="fragment"><p>Collectively, multiple tables of data are called relational data because it is the relations, not just the individual datasets, that are important.</p></li>
<li class="fragment"><p>Relations are always defined between a pair of tables.</p></li>
</ul>
</div>
</div>
</div>
</section>
<section id="verbs-that-work-with-pairs-of-tables" class="slide level2">
<h2>Verbs that work with pairs of tables</h2>
<div>
<ul>
<li class="fragment">There are three families of verbs designed to work with relational data:
<ul>
<li class="fragment"><code>Mutating joins</code>, which add new variables to one data frame from matching observations in another.</li>
<li class="fragment"><code>Filtering joins</code>, which filter observations from one data frame based on whether or not they match an observation in the other table.</li>
<li class="fragment"><code>Set operations</code>, which treat observations as if they were set elements.</li>
</ul></li>
</ul>
</div>
</section>
<section id="prerequisites" class="slide level2">
<h2>Prerequisites</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<ul>
<li>The most common place to find relational data is in a relational database management system.
<ul>
<li>If you’ve used a database before, you’ve almost certainly used SQL.</li>
</ul></li>
<li>We will explore relational data from <code>nycflights13</code> using the two-table verbs from <code>dplyr</code>.</li>
</ul>
</div>
</div>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(nycflights13)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="workshop-part-1-introduction-to-relational-data" class="slide level2">
<h2>Workshop Part 1: INTRODUCTION TO RELATIONAL DATA</h2>
<aside><div>
<p>Inspired from R for Data Science by Hadley Wickham and Garrett Grolemund. <a href="https://r4ds.had.co.nz/relational-data.html">https://r4ds.had.co.nz/relational-data.html</a></p>
</div></aside></section>
<section id="nycflights13" class="slide level2">
<h2><code>?nycflights13</code></h2>
<div>
<ul>
<li class="fragment"><code>nycflights13</code> contains four tibbles
<ul>
<li class="fragment"><code>airlines</code> lets you look up the full carrier name from its abbreviated <code>carrier</code> code</li>
<li class="fragment"><code>airports</code> gives information about each airport, identified by the <code>faa</code> airport code</li>
<li class="fragment"><code>planes</code> gives information about each plane, identified by its <code>tailnum</code></li>
<li class="fragment"><code>weather</code> gives the weather at each NYC airport for each hour</li>
</ul></li>
</ul>
</div>
</section>
<section id="exercise" class="slide level2">
<h2>EXERCISE</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>Examine the variables that exist across the 4 tibbles in <code>nycflights13</code> and draw a diagram depicting the relationships that exists between <code>flights</code> and the other tables.</p>
</div>
</div>
</div>
</section>
<section id="relationships-with-flights" class="slide level2">
<h2>Relationships with <code>flights</code></h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<ul>
<li class="fragment"><code>flights</code> connects to <code>planes</code> via a single variable, <code>tailnum</code></li>
<li class="fragment"><code>flights</code> connects to <code>airlines</code> through the <code>carrier</code> variable</li>
<li class="fragment"><code>flights</code> connects to <code>airports</code> in two ways: via the <code>origin</code> and <code>dest</code> variables</li>
<li class="fragment"><code>flights</code> connects to <code>weather</code> via <code>origin</code>, and <code>year</code>, <code>month</code>, <code>day</code> and <code>hour</code> variables</li>
</ul>
</div>
</div>
</div>
</section>
<section id="relationships-in-nycflights13" class="slide level2">
<h2>Relationships in <code>nycflights13</code></h2>
<img data-src="Img/relational-nycflights.png" class="r-stretch"></section>
<section id="questions" class="slide level2">
<h2>Questions</h2>
<div>
<ul>
<li class="fragment">What is the relationship between <code>weather</code> and <code>airports</code> and how should it appear in the diagram?</li>
<li class="fragment">Weather only contains information for the origin (NYC) airports. If it contained weather records for all airports in the USA, what additional relation would it define with flights?</li>
<li class="fragment">We know that some days of the year are “special”, and fewer people than usual fly on them. How might you represent that data as a data frame? How would it connect to the existing tables?</li>
</ul>
</div>
</section>
<section id="what-is-a-key" class="slide level2">
<h2>What is a <code>key</code>?</h2>
<div>
<ul>
<li class="fragment">A <code>key</code> is a variable (or set of variables) that uniquely identifies an observation.
<ul>
<li class="fragment">A <code>primary key</code> uniquely identifies an observation in its own table. For example, <code>planes$tailnum</code> is a primary key because it uniquely identifies each plane in the planes table.</li>
<li class="fragment">A <code>foreign key</code> uniquely identifies an observation in another table. For example, <code>flights$tailnum</code> is a foreign key because it appears in the flights table where it matches each flight to a unique plane.</li>
</ul></li>
</ul>
</div>
</section>
<section id="exercise-1" class="slide level2">
<h2>EXERCISE</h2>
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<p> </p>
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<ul>
<li>Identify the primary keys across the tables.</li>
<li>How can we check this?</li>
</ul>
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</div>
</div>
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<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>dataset <span class="sc">|></span> </span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">count</span>(var) <span class="sc">|></span> </span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(n <span class="sc">></span> <span class="dv">1</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="surrogate-key" class="slide level2">
<h2>Surrogate key</h2>
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<p> </p>
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<ul>
<li class="fragment">It is clear that <code>flights</code> does not have an explicit primary key.</li>
<li class="fragment">If a table lacks a primary key, it’s sometimes useful to add one with <code>mutate()</code> and <code>row_number()</code>.</li>
<li class="fragment">This is called a <code>surrogate</code> key and makes it easier to check back with the original data following manipulation.</li>
</ul>
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<section id="identifying-keys" class="slide level2">
<h2>Identifying keys</h2>
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<ul>
<li class="fragment">A primary key and the corresponding foreign key in another table form a <code>relation</code>.</li>
<li class="fragment">In simple cases, a single variable is sufficient to identify an observation (plane: tailnum).</li>
<li class="fragment">In other cases, multiple variables may be needed (weather: year, month, day, hour, origin).</li>
<li class="fragment">Relations are typically one-to-many. For example, each flight has one plane, but each plane has many flights.</li>
</ul>
</div>
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<section id="workshop-part-2-mutating-joins" class="slide level2">
<h2>Workshop Part 2: Mutating Joins</h2>
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<p>A mutating join allows you to combine variables from two tables. It first matches observations by their keys, then copies across variables from one table to the other.</p>
</div>
</div>
</div>
<aside><div>
<p>Like mutate(), the join functions add variables to the right of a table, so if you have a lot of variables already, the new variables won’t get printed out.</p>
</div></aside></section>
<section id="section" class="slide level2">
<h2></h2>
<img data-src="Img/dplyr_joins.png" class="r-stretch quarto-figure-center"></section>
<section id="understanding-joins" class="slide level2">
<h2>Understanding joins</h2>
<p>To help us understand joins, let’s create the following two tables.</p>
<img data-src="Img/join-setup.png" class="r-stretch quarto-figure-center"><p>The coloured column represents the “key” variable: these are used to match the rows between the tables.</p>
</section>
<section id="understanding-joins-1" class="slide level2">
<h2>Understanding joins</h2>
<p>In an actual join, matches will be indicated with dots. The number of dots = the number of matches = the number of rows in the output.</p>
<img data-src="Img/join-setup2.png" class="r-stretch quarto-figure-center"></section>
<section id="understanding-joins-2" class="slide level2">
<h2>Understanding joins</h2>
<p>In an actual join, matches will be indicated with dots. The number of dots = the number of matches = the number of rows in the output.</p>
<img data-src="Img/join-inner.png" class="r-stretch quarto-figure-center"></section>
<section id="inner_join" class="slide level2">
<h2><code>inner_join</code></h2>
<p>The simplest type of join is the inner join. An inner join matches pairs of observations whenever their keys are equal. We use <code>by</code> to tell dplyr which variable is the key.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>x <span class="sc">|></span> </span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">inner_join</span>(y, <span class="at">by =</span> <span class="st">"key"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<img data-src="Img/join-inner.png" class="r-stretch"></section>
<section id="outer_join" class="slide level2">
<h2><code>outer_join</code></h2>
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<p> </p>
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<p>An outer join keeps observations that appear in at least one of the tables. There are three types of outer joins:</p>
</div>
</div>
</div>
<div>
<ul>
<li class="fragment">A left join keeps all observations in x.</li>
<li class="fragment">A right join keeps all observations in y.</li>
<li class="fragment">A full join keeps all observations in x and y.</li>
</ul>
</div>
<aside><div>
<p>These joins work by adding an additional “virtual” observation to each table.</p>
</div></aside></section>
<section id="outer_join-1" class="slide level2">
<h2><code>outer_join</code></h2>
<img data-src="Img/join-outer.png" class="r-stretch quarto-figure-center"></section>
<section id="left_join" class="slide level2">
<h2><code>left_join()</code></h2>
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<p> </p>
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<p>Imagine you want to add the full airline name to the flights data. You can combine the airlines and flights data frames with <code>left_join()</code>.</p>
</div>
</div>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>flights <span class="sc">|></span> </span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">select</span>(<span class="sc">-</span>origin, <span class="sc">-</span>dest) <span class="sc">|></span> </span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">left_join</span>(airlines, <span class="at">by =</span> <span class="st">"carrier"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="exercise-2" class="slide level2">
<h2>EXERCISE</h2>
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<p> </p>
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<p>Explore the different outer join options across the tables.</p>
</div>
</div>
</div>
</section>
<section id="duplicate-keys" class="slide level2">
<h2>Duplicate keys</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
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<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>So far all the diagrams have assumed that the keys are unique. There are two possibilities when keys are not unique.</p>
</div>
</div>
</div>
<div>
<ul>
<li class="fragment">One table has duplicate keys</li>
<li class="fragment">Both tables have duplicate keys</li>
</ul>
</div>
</section>
<section id="one-table---duplicate-keys" class="slide level2">
<h2>One table - Duplicate keys</h2>
<p>This is useful when you want to add in additional information as there is typically a one-to-many relationship.</p>
<img data-src="Img/join-one-to-many.png" class="r-stretch quarto-figure-center"></section>
<section id="both-tables---duplicate-keys" class="slide level2">
<h2>Both tables - Duplicate keys</h2>
<p>When you join duplicated keys, you get all possible combinations.</p>
<img data-src="Img/join-many-to-many.png" class="r-stretch quarto-figure-center"></section>
<section id="natural-joins" class="slide level2">
<h2>Natural joins</h2>
<p>You can use other values for <code>by</code> to connect the tables in other ways:</p>
<div>
<ul>
<li class="fragment">The default, <code>by = NULL</code>, uses all variables that appear in both tables, the so called <code>natural</code> join.</li>
<li class="fragment">A character vector, <code>by = "x"</code>. This is like a natural join, but uses only some of the common variables.</li>
<li class="fragment">A named character vector: <code>by = c("a" = "b")</code>. This will match variable <code>a</code> in table <code>x</code> to variable <code>b</code> in table <code>y</code>. The variables from <code>x</code> will be used in the output.</li>
</ul>
</div>
</section>
<section id="workshop-part-3-filtering-joins" class="slide level2">
<h2>Workshop Part 3: Filtering Joins</h2>
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<p> </p>
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<p>Filtering joins match observations in the same way as mutating joins, but affect the observations, not the variables. There are two types:</p>
</div>
</div>
</div>
<div>
<ul>
<li class="fragment"><code>semi_join(x, y)</code> keeps all observations in <code>x</code> that have a match in <code>y</code>.</li>
<li class="fragment"><code>anti_join(x, y)</code> drops all observations in <code>x</code> that have a match in <code>y</code>.</li>
</ul>
</div>
</section>
<section id="filtering-joins" class="slide level2">
<h2>Filtering joins</h2>
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<div class="quarto-layout-row quarto-layout-valign-top">
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<p> </p>
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<p><code>Semi-joins</code> are useful for matching filtered summary tables back to the original rows. For example, imagine you’ve found the top ten most popular destinations.</p>
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</div>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>top_dest <span class="ot"><-</span> flights <span class="sc">|></span> </span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">count</span>(dest, <span class="at">sort =</span> <span class="cn">TRUE</span>) <span class="sc">|></span> </span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">head</span>(<span class="dv">10</span>)</span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a>top_dest</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="filtering-joins-1" class="slide level2">
<h2>Filtering joins</h2>
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<p> </p>
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<p>Now you want to find each flight that went to one of those destinations. You could construct a filter yourself.</p>
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</div>
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<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>flights <span class="sc">|></span> </span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(dest <span class="sc">%in%</span> top_dest<span class="sc">$</span>dest)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="semi-joins" class="slide level2">
<h2>Semi-joins</h2>
<div class="quarto-layout-panel">
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<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
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<p>Instead you can use a semi-join, which connects the two tables like a mutating join, but instead of adding new columns, only keeps the rows in x that have a match in y.</p>
</div>
</div>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>flights <span class="sc">|></span> </span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">semi_join</span>(top_dest)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="semi-joins-1" class="slide level2">
<h2>Semi-joins</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
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<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>Graphically, a semi-join looks like this:</p>
</div>
</div>
</div>
<img data-src="Img/join-semi.png" class="r-stretch quarto-figure-center"></section>
<section id="semi-joins-2" class="slide level2">
<h2>Semi-joins</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
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<p>Only the existence of a match is important; it doesn’t matter which observation is matched. This means that filtering joins never duplicate rows like mutating joins do.</p>
</div>
</div>
</div>
<img data-src="Img/join-semi-many.png" class="r-stretch quarto-figure-center"></section>
<section id="anti-joins" class="slide level2">
<h2>Anti-joins</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
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<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>The inverse of a semi-join is an anti-join. An anti-join keeps the rows that don’t have a match.</p>
</div>
</div>
</div>
<img data-src="Img/join-anti.png" class="r-stretch quarto-figure-center"></section>
<section id="anti-joins-1" class="slide level2">
<h2>Anti-joins</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
</div>
</div>
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<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>Anti-joins are useful for diagnosing join mismatches. For example, when connecting flights and planes, you might be interested to know that there are many flights that don’t have a match in planes.</p>
</div>
</div>
</div>
<div class="cell">
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>flights <span class="sc">|></span> </span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">anti_join</span>(planes, <span class="at">by =</span> <span class="st">"tailnum"</span>) <span class="sc">|></span> </span>
<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">count</span>(tailnum, <span class="at">sort =</span> <span class="cn">TRUE</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="set-operations" class="slide level2">
<h2>Set Operations</h2>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
<div class="quarto-figure-spacer quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p> </p>
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</div>
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<div class="quarto-layout-cell" style="flex-basis: 100.0%;justify-content: center;">
<p>The final type of two-table verb are the set operations. All these operations work with a complete row, comparing the values of every variable. These expect the x and y inputs to have the same variables:</p>
</div>
</div>
</div>
<div>
<ul>
<li class="fragment"><code>intersect(x, y):</code> return only observations in both <code>x</code> and <code>y</code>.</li>
<li class="fragment"><code>union(x, y):</code> return unique observations in <code>x</code> and <code>y</code>.</li>
<li class="fragment"><code>setdiff(x, y):</code> return observations in <code>x</code>, but not in <code>y</code>.</li>
</ul>
</div>
</section></section>
<section id="thank-you" class="title-slide slide level1 center">
<h1>Thank you!</h1>
</section>
<section id="in-the-next-episode" class="title-slide slide level1 center">
<h1>In the next episode</h1>
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<p>Data Visualisation!</p>
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<div class="quarto-figure quarto-figure-center">
<figure>
<p><img data-src="Img/ggplot2.png"></p>
</figure>
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<div class="footer footer-default">
<p><a href="https://filebb.github.io/NHS_intro_DS/">Fundamentals of Data Science for NHS using R</a> - Day 4</p>
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