tag:blogger.com,1999:blog-78327700104208486872024-03-05T11:36:35.074+01:00Turning numbers into storiesThoughts about bringing data to life, using statistics, evolutionary computing and network science. The story of KDSS and me.Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.comBlogger5125tag:blogger.com,1999:blog-7832770010420848687.post-30535184950084841722016-04-28T18:00:00.000+02:002016-04-28T22:13:14.595+02:00Shades of Blue: Wie blau ist Österreich wirklich?<span style="text-align: justify;">Am 24. April 2016 hat die Bundespräsidentschaftswahl in Österreich für ein politisches Erdbeben gesorgt: das erste Mal in der Geschichte kam kein Kandidat von SPÖ oder ÖVP in die Stichwahl. Stattdessen wird diese nun zwischen dem FPÖ-Kandidaten Hofer und dem (mehr oder weniger, offiziell jedenfalls unabhängigen) Grünen Van der Bellen entschieden. Besonders schwer wog das Ergebnis auch deshalb, da Hofer einen deutlichen Vorsprung erzielen konnte: seine rund 35% standen Van der Bellens 21% gegenüber.</span><br />
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Schon bald geisterten Landkarten Österreichs durch das Internet<sup><a href="https://draft.blogger.com/blogger.g?blogID=7832770010420848687#fn1">1</a></sup>, die nahezu das ganze Bundesgebiet blau einfärbten. Wie das? Für jede Gemeinde wurde die Farbe anhand des stimmenstärksten Kandidaten entschieden: Blau wurden jene Gemeinden in denen Hofer führte, Grün jene von Van der Bellen. Ein paar andere Farbkleckse gab es auch noch für die übrigen Kandidaten. </div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgJ7hWvZ5tfMaHmnzvD9bbcIYLV9bfkA72FoMXUMKO1ZxW1nvOAm9Uwz88rjV_-lQtJvCkSIP_6Pakp_UARx_u0-emO3Q2ge-GDaAzOUKvFzqgiB5mmhf_8JQJ0z-cPL_s4NM2tq5vlgdyO/s1600/orig.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgJ7hWvZ5tfMaHmnzvD9bbcIYLV9bfkA72FoMXUMKO1ZxW1nvOAm9Uwz88rjV_-lQtJvCkSIP_6Pakp_UARx_u0-emO3Q2ge-GDaAzOUKvFzqgiB5mmhf_8JQJ0z-cPL_s4NM2tq5vlgdyO/s320/orig.jpg" width="320" /></a></div>
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Im Beispiel ist ersichtlich, dass sich -- abgesehen von ein paar grünen Inseln -- Österreich in ein blaues Meer verwandelt hatte. Dieser Form der Darstellung haften jedoch einige ziemlich deutliche Fehler inne:</div>
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<ol>
<li>Ignorieren der Briefwahlstimmen</li>
<li>Winner takes it all</li>
<li>Ignorieren der Wahlbeteiligung</li>
<li>Fläche ungleich Bevölkerungsdichte</li>
</ol>
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In Summe führen diese Darstellungsfehler dazu, dass vollkommen unberechtigt Österreich gleichmäßig blau eingefärbt wird und der Bevölkerung so eine Eindeutigkeit vorgegaukelt wird, die so einfach nicht stimmt. Freilich hat Hofer die erste Runde der Wahl gewonnen, aber deswegen ist Österreich noch lange nicht blau.</div>
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Wie blau ist Österreich nun wirklich?</h2>
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Im Folgenden eine Aufarbeitung und Behebung der eingangs angesprochenen Fehler der Originalkarte. Dargestellt werden die Ergebnisse von Hofer (blau) und Van der Bellen (orange)<sup><a href="https://draft.blogger.com/blogger.g?blogID=7832770010420848687#fn2">2</a></sup>. Orange wurde deshalb gewählt, da es zu Blau eine Komplementärfarbe ist -- im Gegensatz zu Grün. Zu den beiden Extremfarben wird Weiß gemischt werden, das die Unsicherheit des Ergebnisses aus unterschiedlichen Gründen darstellt. </div>
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Ignorieren der Briefwahlstimmen</h3>
<div>
Die Originalkarte stellt nur jene Stimmen dar, die in den Wahllokalen abgegeben wurden. Die Briefwahlstimmen -- es waren rund 640.000 Wahlkarten ausgegeben worden -- wurden nicht berücksichtigt. Zum einen deshalb, da diese am Wahlsonntag noch nicht gezählt worden waren. Zum anderen liegen diese auch nur auf Bezirks- nicht aber auf Gemeindeebene vor. Da aber BriefwählerInnen traditionell nicht blau wählen, ist dies eine erste Fehlerquelle.</div>
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Hier nun eine Karte Österreichs, die auch die Briefwahlstimmen berücksichtigt. Da diese eben nicht auf Gemeindeebene vorliegen, erfolgt die Darstellung grober auf Ebene des politischen Bezirks. Blau sind jene Bezirke in denen Hofer die absolut meisten Stimmen erzielen konnte, Orange jene in denen Van der Bellen obsiegte. Die Farbe Weiß für die Unsicherheit kommt hier noch nicht vor. </div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgUo0iqTHF9pxR0paaDQBVnHiPHPXxuEi5_1TeqSg0TL5OSy0zN7zd5Ni2965YeI8wqmarjN53CEhFjuzCKg6_nSCEjCotKwnGJAMrlyn4Y5ojC9gjjUFtZLP2OJwW0gOvGXMmc7K2u8J2i/s1600/winner.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgUo0iqTHF9pxR0paaDQBVnHiPHPXxuEi5_1TeqSg0TL5OSy0zN7zd5Ni2965YeI8wqmarjN53CEhFjuzCKg6_nSCEjCotKwnGJAMrlyn4Y5ojC9gjjUFtZLP2OJwW0gOvGXMmc7K2u8J2i/s320/winner.png" width="320" /></a></div>
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Winner takes it all</h3>
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Die in der Originalkarte gewählte Art der Darstellung schlägt eine Gemeinde immer dem Gewinner zu, unabhängig davon wie stark der Vorsprung tatsächlich ist. Dies, obwohl das österreichische Wahlrecht dafür überhaupt keine Basis bietet. Während andere Länder durchaus auch das Winner takes it all-Prinzip kennen, ist dies Österreich vollkommen fremd. Hierzulande wird strikt proportional gewählt, auch wenn das bei einer Bundespräsidentenwahl nur eine untergeordnete Rolle spielt. Dadurch entsteht jedoch der Eindruck, Gemeinden würden homogen wählen. Dem Fehlschluss der <a href="https://en.wikipedia.org/wiki/Ecological_fallacy" target="_blank">ecological fallacy</a> wird damit Tür und Tor geöffnet. Viel besser geeignet wäre eine Darstellung, die das Verhältnis der Stimmen zueinander berücksichtigt.</div>
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Um diesen Fehler zu beheben, wird das Verhältnis der Hofer und Van der Bellen-Stimmen zueinander dargestellt. Je blauer ein Bezirk, desto größer der Anteil der Stimmen für Hofer, je oranger, desto mehr haben für Van der Bellen votiert. Je heller die jeweilige Farbe ist, desto geringer ist die Deutlichkeit des Ergebnisses: die Farbe Weiß wird hinzugemischt. In weißen Bezirken liegen Hofer und Van der Bellen nahezu gleich auf.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhH_SRu96Vo63DHTkPPgyaVsjDy_cFybeA4e9EJOf8QX9pLdCyRNFn5uUrCCRvFNqgkX0SU0wt-_h_TyYvLpDnZift9mV7eNuKOIvok0iU9sfWGYXNjlwIKCmb7QwOcfw-S9A5eEpcb8oD_/s1600/relVDB.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhH_SRu96Vo63DHTkPPgyaVsjDy_cFybeA4e9EJOf8QX9pLdCyRNFn5uUrCCRvFNqgkX0SU0wt-_h_TyYvLpDnZift9mV7eNuKOIvok0iU9sfWGYXNjlwIKCmb7QwOcfw-S9A5eEpcb8oD_/s320/relVDB.png" width="320" /></a></div>
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Ignorieren der Wahlbeteiligung</h3>
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Ein weiteres Manko der Originalkarte ist das Ignorieren der Wahlbeteiligung. Wenn aus der Karte, wie oftmals nahegelegt, geschlossen werden soll, dass die Einstellung der Bevölkerung "blau" sei, so ist diese jedoch auch von essentieller Bedeutung. In der folgenden Darstellung wird daher das Verhältnis der Hofer und Van der Bellen-Stimmen noch mit der Wahlbeteiligung gewichtet. Je ausgeprägter die Farbe ist, desto höher lag auch die Wahlbeteiligung in dem Bezirk. Weiß wird nun zusätzlich die Farbe der NichtwählerInnen.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj9SyNBputvtwG6DKTvA6LwPtBz-KMGUJzmDH79WzmLJXiHmkezj-LI4bm06nOC7tnK-_wTUdmKRWat4XsxGmlcLPJtwe0LFDYgklCj4nqCC9UDhtLWheBid4GfKJ_R6vBBXh0nwjO5xgoI/s1600/relVDB2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj9SyNBputvtwG6DKTvA6LwPtBz-KMGUJzmDH79WzmLJXiHmkezj-LI4bm06nOC7tnK-_wTUdmKRWat4XsxGmlcLPJtwe0LFDYgklCj4nqCC9UDhtLWheBid4GfKJ_R6vBBXh0nwjO5xgoI/s320/relVDB2.png" width="320" /></a></div>
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Fläche ungleich Bevölkerungsdichte</h3>
<div class="" style="clear: both;">
Schließlich, und das ist ein Fehler der häufig bei Kartendarstellungen passiert, bekommen Flächen eine Bedeutung. Flächen haben in der Geographie und beispielsweise der Landwirtschaft durchaus Bedeutung: die Dichte der Bewaldung kann sinnvoll auf einer Fläche dargestellt werden. Für Wahlergebnisse eignet sich diese Darstellung aber nur bedingt. Jedenfalls muss die Bevölkerungsdichte berücksichtigt werden. Das Land ist ja nicht mehr blau, nur weil flächengroße aber bevölkerungsarme Bezirke blauer gewählt haben. Und da weite Teile Österreichs nur spärlich besiedelt sind, kommt diesem Faktor einige Bedeutung zu.</div>
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Zum Abschluss also eine Darstellung, die all diese Fehler bereinigt. Nach wie vor, je blauer ein Bezirk, desto deutlicher das Votum für Hofer. Je mehr Weiß in der Farbkodierung enthalten ist, desto geringer die Wahlbeteiligung und desto geringer die Bevölkerungsanzahl.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-RKdLDFYgKUU0GYQuIEsFOEDy1F60rghkoCTZR6YyGCUB65GAdI14MnIjDYQgvUGYx5vC-0JnPTqpuP0ZSelSgVL3vjzhAxtu4wwypm5P-thkwzcJpLENz4vzpU2VZWuQljXODvFLtL7_/s1600/relVDB3.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-RKdLDFYgKUU0GYQuIEsFOEDy1F60rghkoCTZR6YyGCUB65GAdI14MnIjDYQgvUGYx5vC-0JnPTqpuP0ZSelSgVL3vjzhAxtu4wwypm5P-thkwzcJpLENz4vzpU2VZWuQljXODvFLtL7_/s320/relVDB3.png" width="320" /></a></div>
Österreich ist also immer noch großteils blau, aber das Blau liegt in unterschiedlichsten Schattierungen vor, und es dominiert das Weiß der NichtwählerInnen und der bevölkerungsarmen Gebirgstäler. Gänzlich verschwunden ist auch das Artefakt der Vorarlberger GrünwählerInnen im Westen.<br />
<h3>
Update</h3>
Wie in den Kommentaren kritisch angemerkt, hatte sich ein kleiner Fehler eingeschlichen -- Bezirke die gänzlich von anderen umfasst sind, wie zB Graz von Graz-Umgebung umfasst wird, hat die Farbdarstellung nicht ganz gepasst. Das wurde jetzt korrigiert. Danke für die Hinweise.<br />
<h3>
Fußnoten</h3>
<span id="fn1">1</span>: Stellvertretend für die zahlreichen Darstellungen, wurde diese, ohne Quellenangabe, von Liza Ulitzka auf <a href="https://www.facebook.com/photo.php?fbid=10154841929378266&set=a.10150611997388266.489756.530478265&type=3" target="_blank">Facebook</a> geteilt. Eine weitere Darstellung, allerdings auf Bezirksebene findet sich im <a href="http://derstandard.at/2000035730248/Der-Niedergang-der-Grossparteien-in-einer-Grafik" target="_blank">Standard</a>. Bezugnehmend auf derartige Darstellungen verfasste auch Hans Rauscher im Standard einen <a href="http://derstandard.at/2000035726346/Die-blaue-Landkarte" target="_blank">Kommentar</a> dazu.<br />
<br />
<span id="fn2">2</span>: Zugrunde liegt der Betrachtung das <a href="http://www.bmi.gv.at/cms/BMI_wahlen/bundespraes/bpw_2016/FILES/vorlaeufiges_Gesamtergebnis_inkl_Briefwahlstimmen.xlsx" target="_blank">vorläufige amtliche Wahlergebnis</a>. Das Kartenmaterial wurde unter einer CC-BY-Lizenz von der <a href="https://www.data.gv.at/katalog/dataset/81f390f9-9b42-3a72-ad9b-e11a4dbebab0" target="_blank">Statistik Austria</a> zur Verfügung gestellt. <br />
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Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.com0tag:blogger.com,1999:blog-7832770010420848687.post-44916108871571618582015-11-26T23:36:00.002+01:002015-11-26T23:36:25.783+01:00Accessing APIs from R (and a little R programming)<!DOCTYPE html>
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Accessing APIs from R (and a little R programming)
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<h1 class="title">Working with APIs</h1>
<h4 class="author"><em>Christoph Waldhauser</em></h4>
<h4 class="date"><em>22/11/2015</em></h4>
</div>
<p>APIs are the driving force behind data mash-ups. It is APIs that allow machines to access data programmatically – that is automatically from within a program – to make use of API provided functionalities and data. Without APIs much of today’s Web 2.0, Apps and data applications would be outright impossible.</p>
<p>This post is about using APIs with R. As an example. we’ll use the EU’s <a href="http://eur-lex.europa.eu/en/">EurLex</a><a href="#fn1" class="footnoteRef" id="fnref1"><sup>1</sup></a> <a href="http://api.epdb.eu/">data base API</a> as provided by <a href="http://www.buhlrasmussen.eu/index.en.html">Buhl Rassmussen</a>. This API is a good example of the APIs you might find in the wild. Of course, there are the APIs of large vendors, like Google or Facebook, that are thought out and well documented. But then there is the vast majority of smaller APIs for special applications that often lack in structure or documentation. Nevertheless, these APIs often provide access to valuable ressources.</p>
<div id="background-on-apis" class="section level1">
<h1>Background on APIs</h1>
<p>API is short for Application Programming Interface. Basically, it means a way of accessing the functionality of a program from inside another program. So instead of performing an action using an interface that was made for humans, a point and click GUI for instance, an API allows a program to perform that action automatically. The power of this concept becomes only visible, when you imagine that you can mesh the calling of an API in the program with anything else that program might want to do. Some examples from data science:</p>
<ul>
<li>Retrieve data and produce a visualization from it that gets updated every time someone looks at it</li>
<li>Have tweets automatically translated and entities reported</li>
<li>Have additional nodes in a computer cluster launched as soon as tasks become cumbersome, to ensure fast data processing</li>
</ul>
<p>While an API can be any defined interface between two programs, today APIs usually refer to a special kind of APIs that are based on the WWW’s HyperText Transfer Protocol (HTTP) that is also used by web servers and browsers to exchange data. Indeed, one might consider browsing the web as using APIs: a program (the browser) uses a defined set of commands and conventions to retrieve data (the webpage) from a remote server (the website) and renders it locally in the browser (the thing you see).</p>
<p>All web-based <a href="#fn2" class="footnoteRef" id="fnref2"><sup>2</sup></a> APIs have always the same structure: they consist of a <code>URL</code> to a domain and a <code>path</code> to an endpoint. For instance: <code>http://example.com/api</code> where <code>http://example.com</code> is the <code>URL</code> and <code>/api</code> is the path to the endpoint.</p>
<p>Web-based APIs that are used for data science come usually in two flavors that are named after the HTTP verbs defined <a href="#fn3" class="footnoteRef" id="fnref3"><sup>3</sup></a>:</p>
<ul>
<li><code>GET</code> - sends a set of parameters, a <code>query</code> to an endpoint and then recieves an answer.</li>
<li><code>POST</code> - sends a data payload to an endpoint to be processed at the remote system, usually receiving only a success message as an answer.</li>
</ul>
<p>There are other verbs defined in <code>HTTP</code>, like <code>DELETE</code>, but they are less common in APIs. The by far largest group of APIs makes only use of the <code>GET</code> verb. Let’s look at that flavor in greater detail.</p>
<p>A canonical example would be an API that allows to retrieve data from some data base and the API’s <code>query</code> can be used to narrow down the selection. Let’s say an API provides access to newspaper articles. By specifying the parameter <code>year</code> the API returns not all articles, but only those that were written in a specific year. Let’s say we are only interested in articles written in 2014. The corresponding API call would, thus, look like: <code>http://example.com/api?year=2014</code>. We already know which part is the <code>URL</code> and which part is the <code>path</code> to the endpoint. What’s new is the query <code>year=2014</code>. Note that it’s separated from the <code>path</code> by a question mark. In this example, <code>year</code> is the name of the parameter, and <code>2014</code> is its value.</p>
<p>Upon receiving the API call, the remote system crafts an answer. The answer can be in any format. It could be a image file, or a movie, or text, or … In recent years, JSON has become the most common answer format by far. JSON is a simple text file that uses special characters and conventions to bring structure into its contents. You can find more info at the <a href="http://en.wikipedia.org/wiki/JSON">Wikipedia page on JSON</a>. For now it suffices to know that is a popular format to store data, that can potentially be nested and delivered together with metadata. And that R can process it quite easily.</p>
<p>The big problem with APIs is that they are always designed by humans. So APIs vary wildly in logical structure and the quality of documentation. This unfortunately means, that there is no simple catch-all solution for working with APIs and all programs will need to be custom tailored to the API used. This also means that using an API almost always requires programming to some degree.</p>
</div>
<div id="accessing-apis-from-r" class="section level1">
<h1>Accessing APIs from R</h1>
<p>In this example, we’ll use R to retrieve data from an API and process it. The API we’ll query provides data on EU legislative documents. More specifically, we are interested in which week day is most popular for EU energy legislative documents to go into force. Ok, perhaps that’s not a mind blowing research question, but one that will allow us to demonstrate the using of APIs and the required data processing quite nicely.</p>
<div id="required-packages" class="section level2">
<h2>Required packages</h2>
<p>There are many facilities in R that can be used to access APIs. The one package that I find most useful is Hadley<a href="#fn4" class="footnoteRef" id="fnref4"><sup>4</sup></a>’s <a href="https://cran.r-project.org/web/packages/httr/"><code>httr</code></a>. It allows for easy crafting of API calls and also handling the more intricate aspects of APIs like authentication.</p>
<p>Working with JSON data is facilitated a lot by the <a href="https://cran.r-project.org/web/packages/jsonlite/"><code>jsonlite</code></a> package. It does a good job translating JSON’s nested data structures into sensible R objects. Well, most of the time, anyway.</p>
<p>Since in this example we are going to work with dates, let’s use another of Hadley’s packages: <a href="https://cran.r-project.org/web/packages/lubridate/"><code>lubridate</code></a>. If you work with dates frequently, it’s a package that might be a valuable addition to your toolbox.</p>
<p>If you don’t yet have these packages installed, you can use this R code to obtain them:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">install.packages</span>(<span class="kw">c</span>(<span class="st">"httr"</span>, <span class="st">"jsonlite"</span>, <span class="st">"lubridate"</span>))</code></pre>
</div>
<div id="outline-of-the-example" class="section level2">
<h2>Outline of the example</h2>
<p>In this subsection I’ll outline the steps required to perform to find an answer to our question (which is the most popular day for having energy related documents turn into force?).</p>
<p>EurLex documents all bear a document classifier (directory code in EurLex parlance) that can be used to single out documents that relate to a specific topic. The EurLex classifiers are always four dot separated pairs of digits. For instance, the classifier <code>07.40.30.00</code> identifies documents that relate to air traffic safety. We will use the appropriate classifiers to retrieve the data on energy related documents.</p>
<p>So, these are the required steps we’ll need to take to get our answer:</p>
<ol style="list-style-type: decimal">
<li>Retrieve a list of all the valid classifiers</li>
<li>Extract from that answer only those classifiers that relate to energy, i.e. start with <code>12.</code>.<a href="#fn5" class="footnoteRef" id="fnref5"><sup>5</sup></a></li>
<li>Retrieve the documents’ meta data that are classified with one of the classifiers we’ve found to be relevant.</li>
<li>Work with the data we’ve retrieved to find out which weekday is most frequent.</li>
</ol>
<p>Steps (1) and (3) will involve calling the API and (2) and (4) are just local data processing chores.</p>
<p>Before doing anything else, we need to load the required packages:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(httr)
<span class="kw">library</span>(jsonlite)</code></pre>
<pre><code>##
## Attaching package: 'jsonlite'
##
## The following object is masked from 'package:utils':
##
## View</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(lubridate)</code></pre>
<p>One more thing before we get started: R has the “feature” of turning character strings automatically into factor variables. This is great, when doing actual statistical work. It is this magic that allows R to turn multinomial variables into dummy variables in regression models and produce nice cross tables. When working with APIs, however, this “feature” becomes a hinderance. Let’s just turn it off. Note: this call only affects the current session; when you restart R, all settings will be back to normal.</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">options</span>(<span class="dt">stringsAsFactors =</span> <span class="ot">FALSE</span>)</code></pre>
</div>
<div id="retrieving-valid-classifiers" class="section level2">
<h2>Retrieving valid classifiers</h2>
<p>Calling the <code>/eurlex/directory_code</code> endpoint directly, retrieves a list of all valid classifiers. Let’s obtain that list. First, we need set up the <code>URL</code> and <code>path</code> part of the API call. A query is not required at this point, as the API provides the answer directly.</p>
<pre class="sourceCode r"><code class="sourceCode r">url <-<span class="st"> "http://api.epdb.eu"</span>
path <-<span class="st"> "eurlex/directory_code"</span></code></pre>
<p>Executing an API call with the <code>GET</code> flavor is done using the <code>GET()</code> function.</p>
<pre class="sourceCode r"><code class="sourceCode r">raw.result <-<span class="st"> </span><span class="kw">GET</span>(<span class="dt">url =</span> url, <span class="dt">path =</span> path)</code></pre>
<p>Let’s explore what we’ve got back:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">names</span>(raw.result)</code></pre>
<pre><code>## [1] "url" "status_code" "headers" "all_headers" "cookies"
## [6] "content" "date" "times" "request" "handle"</code></pre>
<p>The result we got back from the API is a list of length 10. Of these, two parts are important:</p>
<ul>
<li><code>status_code</code> that tells us, if the call worked network-wise. For a list of possible status codes, see <a href="https://en.wikipedia.org/wiki/List_of_HTTP_status_codes" class="uri">https://en.wikipedia.org/wiki/List_of_HTTP_status_codes</a>.</li>
<li><code>content</code> the API’s answer in raw binary code, not text. Alas, the answer could also be an image or a sound file.</li>
</ul>
<p>If we examine the status code,</p>
<pre class="sourceCode r"><code class="sourceCode r">raw.result$status_code</code></pre>
<pre><code>## [1] 200</code></pre>
<p>we see that we’ve got <code>200</code>, which means, all worked out fine. Note that this status code only tells us, that the server recieved our request, not if it was valid for the API or found any data.</p>
<p>Let’s look at the actual answer or data payload we’ve got back. Let’s just look at the first few elements:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">head</span>(raw.result$content)</code></pre>
<pre><code>## [1] 7b 22 30 31 2e 30</code></pre>
<p>That’s useless, unless you speak Unicode. Let’s translate that into text.</p>
<pre class="sourceCode r"><code class="sourceCode r">this.raw.content <-<span class="st"> </span><span class="kw">rawToChar</span>(raw.result$content)</code></pre>
<p>Let’s see how large that is in terms of characters:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">nchar</span>(this.raw.content)</code></pre>
<pre><code>## [1] 121493</code></pre>
<p>That’s rather large. Let’s look at the first 100 characters:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">substr</span>(this.raw.content, <span class="dv">1</span>, <span class="dv">100</span>)</code></pre>
<pre><code>## [1] "{\"01.07.00.00\":{\"directory_code\":\"01.07.00.00\",\"url\":\"http:\\/\\/api.epdb.eu\\/eurlex\\/directory_code\\/"</code></pre>
<p>So the result is a single character string that contains a JSON file. Let’s tell R to parse it into something R can work with.</p>
<pre class="sourceCode r"><code class="sourceCode r">this.content <-<span class="st"> </span><span class="kw">fromJSON</span>(this.raw.content)</code></pre>
<p>What did R make out of it?</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">class</span>(this.content) <span class="co">#it's a list</span></code></pre>
<pre><code>## [1] "list"</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">length</span>(this.content) <span class="co">#it's a large list</span></code></pre>
<pre><code>## [1] 462</code></pre>
<pre class="sourceCode r"><code class="sourceCode r">this.content[[<span class="dv">1</span>]] <span class="co">#the first element</span></code></pre>
<pre><code>## $directory_code
## [1] "01.07.00.00"
##
## $url
## [1] "http://api.epdb.eu/eurlex/directory_code/?dc=01.07.00.00&key="
##
## $number_of_documents
## [1] "126"
##
## $list_of_acts_inforce_eurlex
## [1] "http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=0107*&repihm="</code></pre>
<pre class="sourceCode r"><code class="sourceCode r">this.content[[<span class="dv">2</span>]] <span class="co">#the second element</span></code></pre>
<pre><code>## $directory_code
## [1] "01.10.00.00"
##
## $url
## [1] "http://api.epdb.eu/eurlex/directory_code/?dc=01.10.00.00&key="
##
## $number_of_documents
## [1] "191"
##
## $list_of_acts_inforce_eurlex
## [1] "http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=011*&repihm="</code></pre>
<p>So, apparently R makes a list out of it, with one element per classifier. Each element has:</p>
<ul>
<li>the directory code document classifier</li>
<li>a URL where one can retrieve more details</li>
<li>the number of documents with that classifier</li>
<li>another URL with yet more details</li>
</ul>
<p>So, essentially, the result is a list of lists. Lists are not (always) very nice to work with, and lists of lists are usally despicable. Let’s turn it into a data frame:</p>
<pre class="sourceCode r"><code class="sourceCode r">this.content.df <-<span class="st"> </span><span class="kw">do.call</span>(<span class="dt">what =</span> <span class="st">"rbind"</span>,
<span class="dt">args =</span> <span class="kw">lapply</span>(this.content, as.data.frame))</code></pre>
<p>This call does a number of things. <code>lapply(this.content, as.data.frame)</code> turns each of the 462 list elements into mini single-row data frames. This is required, so that we then can combine (<code>rbind</code>) them all together into a single data frame.</p>
<p>In case you are interested in the gory details:</p>
<ol style="list-style-type: decimal">
<li>The function <code>rbind</code> takes any number of data frames as arguments, and turns them into a single data frame, by just stacking one on top of the next. So <code>C <- rbind(A, B)</code> will yield a data frame that has first the contents of <code>A</code> and then those of <code>B</code> stacked on top of each other.</li>
<li>The function <code>lapply</code> takes a list (the first argument) and applies the function that is the second argument (here: <code>as.data.frame</code>) to each of its elements. So, the call to <code>lapply</code> turns our list of lists into a list of single row data frames.</li>
<li>The function <code>do.call</code> is a true wonder girl. She uses its <code>args</code> argument as <strong>arguments</strong> to the function named at the <code>what</code> argument. So here, it executes <code>rbind</code> with all the elements (single row data frames, that we created in (2)) of our list of data frames. It is the same as typing:<br /> <code>rbind(OurDfList[[1]], OurDfList[[2]], OurDfList[[3]], ...)</code> where <code>...</code> would need to be replaced with all the other list items.</li>
</ol>
<p>What have we got now?</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">class</span>(this.content.df) <span class="co">#a single data frame</span></code></pre>
<pre><code>## [1] "data.frame"</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">dim</span>(this.content.df) <span class="co">#with 462 rows and 4 variables</span></code></pre>
<pre><code>## [1] 462 4</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">head</span>(this.content.df)</code></pre>
<pre><code>## directory_code
## 01.07.00.00 01.07.00.00
## 01.10.00.00 01.10.00.00
## 01.20.00.00 01.20.00.00
## 01.30.00.00 01.30.00.00
## 01.40.00.00 01.40.00.00
## 01.40.10.00 01.40.10.00
## url
## 01.07.00.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.07.00.00&key=
## 01.10.00.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.10.00.00&key=
## 01.20.00.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.20.00.00&key=
## 01.30.00.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.30.00.00&key=
## 01.40.00.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.40.00.00&key=
## 01.40.10.00 http://api.epdb.eu/eurlex/directory_code/?dc=01.40.10.00&key=
## number_of_documents
## 01.07.00.00 126
## 01.10.00.00 191
## 01.20.00.00 69
## 01.30.00.00 24
## 01.40.00.00 382
## 01.40.10.00 514
## list_of_acts_inforce_eurlex
## 01.07.00.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=0107*&repihm=
## 01.10.00.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=011*&repihm=
## 01.20.00.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=012*&repihm=
## 01.30.00.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=013*&repihm=
## 01.40.00.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=014*&repihm=
## 01.40.10.00 http://eur-lex.europa.eu/Result.do?RechType=RECH_repertoire&rep=01401*&repihm=</code></pre>
<p>That’s nice and we can work with it to extract all the classifiers of energy topics.</p>
</div>
<div id="extracting-energy-classifiers" class="section level2">
<h2>Extracting energy classifiers</h2>
<p>We’ve almost found the classifiers for energy topics. We just need to filter them out of all the other classifiers that are available. Remember, Energy classifiers start with <code>12.</code>. We can use that fact:</p>
<pre class="sourceCode r"><code class="sourceCode r">headClass <-<span class="st"> </span><span class="kw">substr</span>(<span class="dt">x =</span> this.content.df[, <span class="st">"directory_code"</span>],
<span class="dt">start =</span> <span class="dv">1</span>,
<span class="dt">stop =</span> <span class="dv">2</span>)</code></pre>
<p><code>headClass</code> is now just a character vector containing the first two characters of the <code>directory_code</code> for each of the 462 different classifiers.</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">length</span>(headClass)</code></pre>
<pre><code>## [1] 462</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">head</span>(headClass)</code></pre>
<pre><code>## [1] "01" "01" "01" "01" "01" "01"</code></pre>
<p>If these first two characters equal <code>12</code>, it’s an energy topic:</p>
<pre class="sourceCode r"><code class="sourceCode r">isEnergy <-<span class="st"> </span>headClass ==<span class="st"> "12"</span>
<span class="kw">table</span>(isEnergy) <span class="co"># 19 of the topic classifiers start with 12</span></code></pre>
<pre><code>## isEnergy
## FALSE TRUE
## 443 19</code></pre>
<p>Let’s use this logical vector to index our data frame:</p>
<pre class="sourceCode r"><code class="sourceCode r">relevant.df <-<span class="st"> </span>this.content.df[isEnergy, ]</code></pre>
<p>And let’s narrow that down to solely the document identifiers:</p>
<pre class="sourceCode r"><code class="sourceCode r">relevant.dc <-<span class="st"> </span>relevant.df[, <span class="st">"directory_code"</span>]</code></pre>
<p><code>relevant.dc</code> is now a character vector with all the directory codes that are relating to energy topics.</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">length</span>(relevant.dc)</code></pre>
<pre><code>## [1] 19</code></pre>
<pre class="sourceCode r"><code class="sourceCode r">relevant.dc</code></pre>
<pre><code>## [1] "12.07.00.00" "12.10.00.00" "12.10.10.00" "12.10.20.00" "12.20.10.00"
## [6] "12.20.20.00" "12.20.30.00" "12.20.40.00" "12.30.00.00" "12.40.00.00"
## [11] "12.40.10.00" "12.40.20.00" "12.40.30.00" "12.40.40.00" "12.40.50.00"
## [16] "12.50.10.00" "12.50.20.00" "12.50.30.00" "12.60.00.00"</code></pre>
<p>We’ve come a long way. We’ve retrieved all possible classifiers from the API, parsed the answer so that we can work with it, and, finally, extracted all those classifiers that are relating to energy topics.</p>
</div>
<div id="retrieving-energy-documents-meta-data" class="section level2">
<h2>Retrieving energy documents’ meta data</h2>
<p>In this step, we use the identified classifiers to retrieve all the documents’ meta data that relate to energy topics. We’ll use the API again. The base parts of the API call have not changed.</p>
<p>Now to the query: we cannot pass all the relevant classifiers in a single call. Rather, we need to create 19 queries, one for each identified classifier. There are many ways to do that. Let’s do it the pretty way with our own function:</p>
<pre class="sourceCode r"><code class="sourceCode r">makeQuery <-<span class="st"> </span>function(classifier) {
this.query <-<span class="st"> </span><span class="kw">list</span>(classifier)
<span class="kw">names</span>(this.query) <-<span class="st"> "dc"</span>
<span class="kw">return</span>(this.query)
}</code></pre>
<p>Remember, that a the query part of an API call is a named list. The name is the name of the API parameter, and it’s value is, well, it’s value. Our function, <code>makeQuery()</code> takes a single argument, <code>classifier</code> and turns it into a single element list and sets the name of that list’s single element to be <code>dc</code>. Let’s try it out with nonsense</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">makeQuery</span>(<span class="st">"foo"</span>)</code></pre>
<pre><code>## $dc
## [1] "foo"</code></pre>
<p>We discover, that the function indeed returns a list with a single element, that element is named <code>dc</code> and it’s value is the string we’ve specified.</p>
<p>Let’s apply our new function to all of our relevant classifiers from above to turn them into queries. Remember the <code>lapply</code> function we can use to apply a function to each element of a list:</p>
<pre class="sourceCode r"><code class="sourceCode r">queries <-<span class="st"> </span><span class="kw">lapply</span>(<span class="kw">as.list</span>(relevant.dc), makeQuery)</code></pre>
<p>Now we have a list (<code>queries</code>) that is composed of all the individual queries that result from our function. Now we are good to go to acutally execute the API calls.</p>
<p>It’s time now to execute the API calls we’ve created. Let’s start out with the first element of our query list.</p>
<pre class="sourceCode r"><code class="sourceCode r">this.raw.result <-<span class="st"> </span><span class="kw">GET</span>(<span class="dt">url =</span> url, <span class="dt">path =</span> path, <span class="dt">query =</span> queries[[<span class="dv">1</span>]])</code></pre>
<p>What did we get back?</p>
<pre class="sourceCode r"><code class="sourceCode r">this.result <-<span class="st"> </span><span class="kw">fromJSON</span>(<span class="kw">rawToChar</span>(this.raw.result$content))</code></pre>
<p>We’ve got back the meta data for all 11 documents that are classified with our first relevant classifier (<code>12.07.00.00</code>). For each document, we get:</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">names</span>(this.result[[<span class="dv">1</span>]])</code></pre>
<pre><code>## [1] "form" "title" "api_url"
## [4] "eurlex_perma_url" "doc_id" "date_document"
## [7] "of_effect" "end_validity" "oj_date"
## [10] "directory_codes" "legal_basis" "addressee"
## [13] "internal_ref" "additional_info" "text_url"
## [16] "prelex_relation" "relationships" "eurovoc_descriptors"
## [19] "subject_matter"</code></pre>
<p>Apparently, our call does work just fine. Executing the first query stored in <code>queries</code> results in 11 documents and their respective meta data.</p>
<p>Let’s execute the query for each element in <code>queries</code>. How to go about this? Why not use <code>lapply</code> to execute each of the queries in the list? We could do that, but let’s try another approach: a loop. A loop – loops – over a set of numbers, and at each iteration executes some code. Let’s try that:</p>
<p>First, we need something where we can store the results. For that, we create an empty list with just enough room to store each of the queries’ results:</p>
<pre class="sourceCode r"><code class="sourceCode r">all.results <-<span class="st"> </span><span class="kw">vector</span>(<span class="dt">mode =</span> <span class="st">"list"</span>,
<span class="dt">length =</span> <span class="kw">length</span>(relevant.dc))</code></pre>
<p>This made a new, empty list called <code>all.results</code>. It has as many empty slots as we have energy related classifiers.</p>
<pre class="sourceCode r"><code class="sourceCode r">for (i in <span class="dv">1</span>:<span class="kw">length</span>(all.results)) {
this.query <-<span class="st"> </span>queries[[i]]
this.raw.answer <-<span class="st"> </span><span class="kw">GET</span>(<span class="dt">url =</span> url, <span class="dt">path =</span> path, <span class="dt">query =</span> this.query)
this.answer <-<span class="st"> </span><span class="kw">fromJSON</span>(<span class="kw">rawToChar</span>(this.raw.answer$content))
all.results[[i]] <-<span class="st"> </span>this.answer
<span class="kw">message</span>(<span class="st">"."</span>, <span class="dt">appendLF =</span> <span class="ot">FALSE</span>)
<span class="kw">Sys.sleep</span>(<span class="dt">time =</span> <span class="dv">1</span>)
}</code></pre>
<p>This loop iterates over the numbers 1 to 19 (the number of relevant classifiers). At each iteration, it:</p>
<ul>
<li>loads the appropriate query (whos time has come)</li>
<li>executes the API call with that query</li>
<li>extracts the content of the response and converts it from JSON</li>
<li>writes the results to the empty list we had created beforehand</li>
<li>prints a dot, so we don’t get bored waiting</li>
<li>waits for a second (because we are polite and don’t want to bog down EU)</li>
</ul>
<p><code>all.results</code> is now no empty list no more. It is filled with the answers the API has produced as result to our 19 queries.</p>
<p>Now we have results. The next step is to beat these results into a shape we can actually use to find our corvetted answer. Of all the parts of the answer, we are interested in <code>form</code>, <code>date_document</code> and <code>of_effect</code>. Let’s create another function that returns just these parts as a data frame.</p>
<pre class="sourceCode r"><code class="sourceCode r">parseAnswer <-<span class="st"> </span>function(answer) {
this.form <-<span class="st"> </span>answer$form
this.date <-<span class="st"> </span>answer$date
this.effect <-<span class="st"> </span>answer$of_effect
result <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">form =</span> this.form,
<span class="dt">date =</span> this.date,
<span class="dt">effect =</span> this.effect)
<span class="kw">return</span>(result)
}</code></pre>
<p>Let’s try our function on one of the results. Remember, that the results we’ve retrieved is a list (19 elements, one for each classifier) of lists (one for each document; the numbers of documents varies from classifier to classifier).</p>
<pre><code>parseAnswer(all.results[[1]][[2]])</code></pre>
<p>This took from the first classifier (the <code>[[1]]</code>) the second document (the <code>[[2]]</code>). We see, it’s a data frame with one row and three columns.</p>
<p>Now to apply our function to all of our list of lists results, we need to go a little deeper and combine all the skills we’ve learned so far. We could use a loop to iterate over all the 19 classifiers first and then a second loop to iterate over all the documents in each classifier. But that’s rather verbose and cumbersome. Let’s use <code>lapply</code> instead:</p>
<pre class="sourceCode r"><code class="sourceCode r">parsedAnswers <-<span class="st"> </span><span class="kw">lapply</span>(all.results,
function(x) <span class="kw">do.call</span>(<span class="st">"rbind"</span>, <span class="kw">lapply</span>(x, parseAnswer)))</code></pre>
<p>What’s happening here? Let’s start from the inside out:</p>
<ol style="list-style-type: decimal">
<li>We apply our function, <code>parseAnswer</code> on each document in a classifier</li>
<li>Inside each classifier, we <code>rbind</code> the single line data frames together to form a single data.frame with one row per document.</li>
<li>We do this for each of the 19 classifiers in <code>all.results</code>.</li>
</ol>
<p>We get a back a list of data frames, each data frame having as many rows as there are documents in that classifier.</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">class</span>(parsedAnswers) <span class="co">#list</span></code></pre>
<pre><code>## [1] "list"</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">length</span>(parsedAnswers) <span class="co">#19</span></code></pre>
<pre><code>## [1] 19</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">sapply</span>(parsedAnswers, nrow) <span class="co">#11, 15, 107, ...</span></code></pre>
<pre><code>## [1] 11 15 107 110 172 41 16 22 55 42 16 60 62 143 84 18 11
## [18] 65 28</code></pre>
<p>Let’s combine these 19 data frames in a single one. How can we do that? Of course just like before using <code>do.call</code> and <code>rbind</code>.</p>
<pre class="sourceCode r"><code class="sourceCode r">finalResult <-<span class="st"> </span><span class="kw">do.call</span>(<span class="st">"rbind"</span>, parsedAnswers)
<span class="kw">class</span>(finalResult) <span class="co">#data.frame</span></code></pre>
<pre><code>## [1] "data.frame"</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">dim</span>(finalResult) <span class="co"># 1078 rows, 3 columns</span></code></pre>
<pre><code>## [1] 1078 3</code></pre>
<p>All the final results are now contained neatly in a single data frame. Note that the data frame’s row names are actually the document IDs. We can use them to retrieve the actual document’s meta data.</p>
</div>
<div id="working-with-dates" class="section level2">
<h2>Working with dates</h2>
<p>The data we’ve retrieved from the API is still all only characters. If we tell R that the date columns (<code>date</code> and <code>effect</code>) are actually dates, R can calculate with these dates.</p>
<p>First, we need to convert characters to dates. Let’s try this out with some arbitrary date.</p>
<pre class="sourceCode r"><code class="sourceCode r">date.character <-<span class="st"> "1981-05-02"</span>
date.POSIXct <-<span class="st"> </span><span class="kw">ymd</span>(date.character)
<span class="kw">class</span>(date.character) <span class="co">#character</span></code></pre>
<pre><code>## [1] "character"</code></pre>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">class</span>(date.POSIXct) <span class="co">#POSIXct</span></code></pre>
<pre><code>## [1] "POSIXct" "POSIXt"</code></pre>
<p>That worked just fine. Let’s do this for the date columns in our final results data frame:</p>
<pre class="sourceCode r"><code class="sourceCode r">finalResult$date <-<span class="st"> </span><span class="kw">ymd</span>(finalResult$date)
finalResult$effect <-<span class="st"> </span><span class="kw">ymd</span>(finalResult$effect)</code></pre>
<p>At last, we’ve retrieved all the data we need to answer our question and brought it into a format we can work with. Let’s answer our question, which day of the week is most popular for letting laws become effective:</p>
<pre class="sourceCode r"><code class="sourceCode r">finalResult$effectDay <-<span class="st"> </span><span class="kw">wday</span>(finalResult$effect, <span class="dt">label =</span> <span class="ot">TRUE</span>)
<span class="kw">table</span>(finalResult$effectDay) <span class="co">#Most documents went into effect on a Wednesday</span></code></pre>
<pre><code>##
## Sun Mon Tues Wed Thurs Fri Sat
## 31 160 132 172 145 384 54</code></pre>
<p>We see, that Wednesdays are the most popular ones.</p>
<p>This concludes this little tour de force of introducing working with APIs with R. We covered not only how to craft API calls, but also how to use R’s (list) programming features to deal with API answers and beat data into shape.</p>
</div>
</div>
<div class="footnotes">
<hr />
<ol>
<li id="fn1"><p>EurLex documents have been used in the past as text-book examples for statistical programming and machine learning. See for instance <a href="http://www.ke.tu-darmstadt.de/resources/eurlex">TU Darmstadt’s project</a>.<a href="#fnref1">↩</a></p></li>
<li id="fn2"><p>well, most anyway<a href="#fnref2">↩</a></p></li>
<li id="fn3"><p>Actually, it’s a little bit more complicated. <code>GET</code> and <code>POST</code> are methods an API might implement. Often, the same API will provide <code>GET</code> and <code>POST</code> methods side by side for different purposes. If taking the HTTP standard as the proverbial letter of the law, <code>GET</code> methods should not change anything on the remote system, i.e. only return data, while <code>POST</code> methods should change a state or a file on the remote system. In practice, <code>POST</code> methods are also used to provide data to the remote system that it can use to work with, e.g. a text that should be automatically translated.<a href="#fnref3">↩</a></p></li>
<li id="fn4"><p>Hadley Wickham is perhaps one of the most prolific R developers. He’s responsible for a great wealth of packages, among them the visualization package <a href="http://ggplot2.org/"><code>ggplot2</code></a> and the data munging facilities of <a href="https://cran.r-project.org/web/packages/dplyr/index.html"><code>dplyr</code></a>. Check out <a href="http://had.co.nz/">Hadley’s personal website</a> to get a glimpse on all the projects he’s involved with.<a href="#fnref4">↩</a></p></li>
<li id="fn5"><p>Finding out that <code>12.</code> is the document classifier that identifies energy related documents actually took quite some research. For easy access, <a href="http://sourceforge.net/projects/mulan/files/datasets/">Project Mulan</a> provides a list of all <a href="http://sourceforge.net/projects/mulan/files/datasets/eurlex-directory-codes.rar/download">EurLex directory codes</a>.<a href="#fnref5">↩</a></p></li>
</ol>
</div>
</div>
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Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.com4tag:blogger.com,1999:blog-7832770010420848687.post-74387838030147825582014-08-09T13:44:00.000+02:002014-08-09T13:44:51.859+02:00Visualizing Geo-Referenced Data With R<!DOCTYPE html>
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Visualizing Geo-Referenced Data With R
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<h1 class="title">Visualizing Geo-Referenced Data With R</h1>
<h4 class="author"><em>Christoph Waldhauser</em></h4>
<h4 class="date"><em>07/01/2014</em></h4>
<p>A key issue in data science is visualization to aid in the telling of stories and the exploration of patterns in data. In this blog post I’m going to look at producing maps that display data with R giving two examples. A large portion of the data of interest to social sciences is actually geo-referenced: election results of electoral districts in a country, worldwide country indicators, locations of conflict hot spots on a map. All these data are screaming for being visualized on maps. I will first outline the required steps for producing maps with geo-referenced data. Then I’ll walk through two examples for two different kinds of geo-referenced data.</p>
<h1>Steps</h1>
<p>Producing publication quality maps entails a number of steps:</p>
<ol style="list-style-type: decimal">
<li><p>Finding maps. While perhaps sounding trivial, it is not so easy to come up with public domain map data that can be used with R. What is required is a data frame that contains the corner points of any borders that should be printed on the map. These borders surround named areas. For example: provincial borders around provinces in a country. This can be produced easily from Shape files that are used with the popular (but proprietary and quite expensive) <a href="http://en.wikipedia.org/wiki/ArcGIS">ArcGIS</a> software package. The <code>maps</code> R package contains a number of maps for the US, Italy, France and New Zealand. It also provides a map of the World.</p></li>
<li><p>Finding geo-referenced data. If you came this far, then you probably already have some sort of geo-referenced data. Broadly speaking, these can fall into two categories:</p>
<ul>
<li><em>Areas</em> surrounded by borders in the region and identified by name</li>
<li><em>Points</em> identified by coordinates in degrees of longitude and latitude</li>
</ul></li>
<li><p>Drafting a plot to tell a story.</p></li>
<li><p>Implement the plot using (e.g.) <code>ggplot2</code>.</p></li>
</ol>
<h1>Area data example</h1>
<p>In these examples I’ll produce a number of different maps using R’s standard data sets. The first map will put key indicators of US States on a map. In the terms of the definition I sketched above, these are area data.</p>
<p>Some of R’s maps are organized in the <code>maps</code> R package. If you don’t have it installed yet, it’s only a quick <code>install.packages("maps")</code> away. After installing it, it is still necessary to load it:</p>
<pre class="r"><code>library(maps)</code></pre>
<p>As noted above, the <code>maps</code> package provides a number of maps at varying levels of details. However, these maps are stored in a binary format on disk. In order to turn them into a data frame that can be used for plotting, they need to be converted. This can be achieved by <code>ggplot</code>’s <code>map_data</code> function. Let’s first load the <code>ggplot</code> package, we will need it later for plotting the maps as well.</p>
<pre class="r"><code>library(ggplot2)</code></pre>
<p>The <code>map_data</code> function requires only the name of the map that should be converted, for the case at hand this is <code>"state"</code>. Conceptionally, the data frame is simply a number of points describing the corners, every corner, of a state. This means a set of points identified by longitude and latitude and and order describing the path that is the border around a state. This is accompanied by a group identifier. The group identifier binds together all those points that describe a single area. In most cases this identical with a state. However, if a state territory also encompasses islands, then these islands form their own respective group each. This explains why 50 states yield the 63 unique groups encoded within this data set. The <code>region</code> identifier finally provides the States’ names. This is the variable where we will later merge the geo-referenced data with. There is also another variable, <code>subregion</code>, that in this map is not used.</p>
<pre class="r"><code>us <- map_data("state")
head(us)</code></pre>
<table>
<caption>First six entries of the US State map data</caption>
<col width="9%"></col>
<col width="8%"></col>
<col width="11%"></col>
<col width="11%"></col>
<col width="12%"></col>
<col width="15%"></col>
<thead>
<tr class="header">
<th align="center">long</th>
<th align="center">lat</th>
<th align="center">group</th>
<th align="center">order</th>
<th align="center">region</th>
<th align="center">subregion</th>
</tr>
</thead>
<tbody>
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<td align="center">-87.46</td>
<td align="center">30.39</td>
<td align="center">1</td>
<td align="center">1</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
<tr class="even">
<td align="center">-87.48</td>
<td align="center">30.37</td>
<td align="center">1</td>
<td align="center">2</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
<tr class="odd">
<td align="center">-87.53</td>
<td align="center">30.37</td>
<td align="center">1</td>
<td align="center">3</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
<tr class="even">
<td align="center">-87.53</td>
<td align="center">30.33</td>
<td align="center">1</td>
<td align="center">4</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
<tr class="odd">
<td align="center">-87.57</td>
<td align="center">30.33</td>
<td align="center">1</td>
<td align="center">5</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
<tr class="even">
<td align="center">-87.59</td>
<td align="center">30.33</td>
<td align="center">1</td>
<td align="center">6</td>
<td align="center">alabama</td>
<td align="center"></td>
</tr>
</tbody>
</table>
<p>In a next step, let’s look at geo-referenced data. R comes with the <code>state</code> data set that contains a number of data frames with statistical data. The data frame of interest is <code>state.x77</code>. Let’s take a look at it:</p>
<pre class="r"><code>data(state)</code></pre>
<p>The data frame <code>state.x77</code> contains the following variables for each state: . For this map, let’s consider <code>Income</code>:</p>
<table>
<col width="9%"></col>
<col width="13%"></col>
<col width="12%"></col>
<col width="9%"></col>
<col width="13%"></col>
<col width="8%"></col>
<thead>
<tr class="header">
<th align="center">Min.</th>
<th align="center">1st Qu.</th>
<th align="center">Median</th>
<th align="center">Mean</th>
<th align="center">3rd Qu.</th>
<th align="center">Max.</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="center">3100</td>
<td align="center">3990</td>
<td align="center">4520</td>
<td align="center">4440</td>
<td align="center">4810</td>
<td align="center">6320</td>
</tr>
</tbody>
</table>
<p>After having identified a variable, we need to create a data set that merges the shape information from above with the variable of interest. The <code>merge</code> function can be used to this end. However, the map data only covers the continental US and therefore does not contain the states of Alaska and Hawaii. On the other hand, the state data set does not contain data for the District of Columbia. The respective entries from both data sets will therefore be lost in the merge operation.</p>
<pre class="r"><code>tmp <- data.frame(region=tolower(rownames(state.x77)),
Income=state.x77[,"Income"])
dta <- merge(x=us, y=tmp)
dta <- dta[order(dta$order),]</code></pre>
<p>Let’s start creating the map by setting up the aesthetics. Remember that in <code>ggplot2</code> aesthetics are used to map data to plot properties. Here, we state that the longitude goes on the x-axis and the latitude on the y-axis. Further, the <code>group</code> identifier separates the individual polygons.</p>
<pre class="r"><code>p1 <- ggplot(data=dta, aes(x=long, y=lat, group=group))</code></pre>
<p>The <code>ggplot2</code> geom we need for a map is a polygon. Basically, a polygon is a free shape object that is defined by a path along its borders; exactly what the map data provides. By adding the <code>geom_polygon</code> to the previously set up aesthetics, the map is plotted:</p>
<pre class="r"><code>p1 + geom_polygon(colour="white")</code></pre>
<p><img src="data:image/png;base64,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" title="plot of chunk simple-map-plot" alt="plot of chunk simple-map-plot" width="672" /></p>
<p>The <code>geom_polygon</code> has two interesting properties: <code>colour</code> to specify the color of the line depicting the border and <code>fill</code> to control the polygon’s fill color. It is <code>fill</code> that we will use to bring our data on the map. In order to add the area data to the plot, the <code>geom_polygon</code> needs to be beefed up with an aesthetics call to <code>fill</code> on it’s own.</p>
<pre class="r"><code>p1 + geom_polygon(colour="white", aes(fill=Income))</code></pre>
<p><img 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" title="plot of chunk data-map-plot" alt="plot of chunk data-map-plot" width="672" /></p>
<p>We can complete the plot using <code>ggplot2</code>’s usual annotation features:</p>
<pre class="r"><code>p1 + geom_polygon(colour="white", aes(fill=Income)) +
xlab("Longitude") +
ylab("Latitude") +
ggtitle("Per capita income distribution of US States, 1974")</code></pre>
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title="plot of chunk data-map-plot-complete" alt="plot of chunk data-map-plot-complete" width="672" /></p>
<h1>Point data example</h1>
<p>The second broad type of geo-referenced data are points of interest. Here we will plot the approximate locations of US nuclear power plants. The size of plotting marks will correspond with the power station’s licensed output.</p>
<p>First, the data needs to be retrieved. The <a href="http://www.nrc.gov/">US Nuclear Regulatory Commission</a> publishes among other things <a href="http://www.nrc.gov/reading-rm/doc-collections/nuregs/staff/sr1350/">annual reports</a> on all nuclear power plants. Their Appendix A contains some data of all the nuclear power stations in the US and is available as <a href="http://www.nrc.gov/reading-rm/doc-collections/nuregs/staff/sr1350/appa.xls">Excel file</a>.</p>
<p>There are multiple ways of working with Excel files in R, I find the <code>xlsx</code> package to be quite handy, so we’ll use that to read in the data into R. After reading it in, let’s clean up the data a little as well.</p>
<pre class="r"><code>library(xlsx)
nuclear.raw <- read.xlsx(file = "appa.xls", sheetIndex = 1, startRow = 2, header = TRUE)
nuclear <- nuclear.raw[,c(1, 4, 7, 11, 13, 15, 16, 18:23, 25:27)]
colnames(nuclear) <- c("Name", "Location", "Type", "Construction", "Operating",
"Expiring", "Output", paste0("Capacity", c(12:7,5:3)))</code></pre>
<p>Location in this data set is provided by city names and these cities relative locations to larger, better known population centers. We first need to extract the city names and then translate them into Longitude and Latitude. This can be done using the <code>zipcode</code> R package. Let’s extract the city names first.</p>
<pre class="r"><code>library(stringr)
citiesStates <- sapply(strsplit(as.character(nuclear$Location),
split = "(", fixed=TRUE), function(x) return(x[1]))
citiesStates <- t(sapply(strsplit(citiesStates, split=",", fixed=TRUE),
function(x) return(str_trim(x[1:2]))))
colnames(citiesStates) <- c("city", "state")
citiesStates[,"state"] <- toupper(citiesStates[,"state"])
nuclear <- data.frame(nuclear, citiesStates)</code></pre>
<p>This parsing works for most of the names provided by the NRC. Unfortunately, they are occasionally inconsistent. With a little bit more effort, even those cases could be mapped. As this post is more about visualization then regular expressions, let’s settle for the ones where the parsing worked out.</p>
<p>The <code>zipcode</code> package provides a database of zipcodes, city names and their geographic locations. We merge these locations to our <code>nuclear</code> data set, using <code>city</code> and <code>state</code> as key. Unfortunately, not all US nuclear power stations are contained within that database.</p>
<pre class="r"><code>data(zipcode, package="zipcode")
nuclear <- merge(nuclear,
zipcode[!duplicated(zipcode[,c("city", "state")]),-1],
all.x=TRUE)
nuclear <- nuclear[!is.na(nuclear[,"longitude"]),]</code></pre>
<p>Now that we’ve built our data set, let’s get about plotting. Basically, we just need to plot points at the correct locations. Let’s start out with an empty map:</p>
<pre class="r"><code>p2 <- p1 + geom_polygon(colour="white")
p2</code></pre>
<p><img 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" title="plot of chunk empty-location-plot" alt="plot of chunk empty-location-plot" width="672" /></p>
<p>We then add a layer of points to that map. The coordinates of the points come from the power stations’ locations. As the map polygons are defined using a <code>group</code> aesthetic, we need to add a constant group variable to the nuclear data as well. It won’t be used, but it needs to be present to appease <code>ggplot</code>.</p>
<pre class="r"><code>p2 + geom_point(data=data.frame(nuclear, group=NA),
aes(x=longitude, y=latitude), colour="red")</code></pre>
<p><img 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" title="plot of chunk basic-location-plot" alt="plot of chunk basic-location-plot" width="672" /></p>
<p>Finally, we can add the <code>Output</code> variable to the aesthetics call to map the power plant’s size to the size of the point on the map. To finalize the plot, we apply the usual beautifications:</p>
<pre class="r"><code>p2 + geom_point(data=data.frame(nuclear, group=NA),
aes(x=longitude, y=latitude, size=Output), colour="red") +
xlab("Longitude") + ylab("Latitude") + scale_size_continuous(name="Output (MWh)") +
ggtitle("Location of Commercial Nuclear Power Plants in the US")</code></pre>
<p><img 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title="plot of chunk final-location-plot" alt="plot of chunk final-location-plot" width="672" /></p>
<h1>Summary</h1>
<p>In this post, I’ve looked at producing attractive maps in R using <code>ggplot2</code>. Two kinds of geo-referenced data has been added to the maps: areas and points. Integrating both visualizations to create a story, e.g. the connection of nuclear power and income, is left as an exercise to the reader. Using even more granular data on say county level, could be used to tell story that nuclear power stations are never located in wealthy communities. Alas, the not-in-my-backyard attitude’s effectiveness is highly dependent on the wealth of their holders. As always, I’ll be excited to read any thoughts you might have on this in the comments.</p>
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Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.com2tag:blogger.com,1999:blog-7832770010420848687.post-72203603153154215122014-04-13T22:38:00.000+02:002014-04-13T22:38:43.161+02:00Survey: Computing Your Own Post-Stratification Weights in R<!DOCTYPE html>
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<h1 class="title">Survey Data: Computing Your Own Weights</h1>
<p>The second installment in my series on working with survey data in R explains how to compute your own post-stratification weights to use with survey data. For a more detailed overview on why you might need post-stratification weights, look at <a href="http://tophcito.blogspot.co.at/2014/04/social-science-goes-r-weighted-survey.html">my previous post on survey weights</a>.</p>
<p>Working with survey data has been a focal point of quantitative social sciences for most of the 20<sup>th</sup> century. The idea behind a survey is to take a sample of the general population and generalize the sample’s answers. For this, the sample needs to be representative, i.e. reflect the characteristics of the population it was drawn from. Broadly speaking, population characteristics are important because they define strata within the population that behave differently with respect to social science questions. For instance, workers tend to harbor different views than managers, and young people lead different lives than pensioners. Maintaining the population’s mix in the sample is key in coming up with generalizable findings.</p>
<p>What precisely a good characteristic for a population is, depends on the population, the questionnaire and the research interest. A lot of consideration needs to be put into selecting appropriate population characteristics for aligning it with the sample. Good starters, however, are the distributions of age and gender or employment status.</p>
<p>Post-stratification weights are actually a very important tool to generalize findings from a sample to a larger population. See for instance <a href="http://www.washingtonpost.com/blogs/monkey-cage/wp/2014/04/09/tracking-public-opinion-with-biased-polls/">Andrew Gelman’s piece in the Washington Post on the subject</a>.</p>
<h1>Computing your own weights</h1>
<p>When you conduct a survey yourself, you need to come up with weights. Already when sketching the questionnaire, one needs to know which characteristics will later be used to align sample and population. Each one of them needs to be covered by a question in the questionnaire. The idea behind post stratification is to make sure you have as many pensioners and as many workaholics in your data set, as there are in the general population, to extend the example from last time. For this to work, you need the number of workaholics and pensioners in the general population. We call these figures the marginal distributions. Again, which marginal distribution you need, depends on your data set and your research questions.</p>
<p>Once you have the marginal distributions, you can use <em>survey</em>’s <code>rake()</code> function to compute the weights. This is done by an algorithm called Iterative Proportional Fitting (IPF). See <a href="http://en.wikipedia.org/wiki/Iterative_proportional_fitting">Wikipedia’s entry on IPF</a> for all its gory details. For a easier description, let’s consider that this algorithm tries to find weights, so that the actual distributions in your data set, when weighted, match the specified marginal distributions of the general population as closely as possible. Sometimes, this can get a little out of hand, and weights become too large. In that case you need to trim the weights back to a reasonable amount. Having weights between 0.3 and 3 is a good rule of thumb.</p>
<p>There are three steps involved: (a) you need to make a survey design object out of your data, without any weights associated, (b) you need to rake this object, so that you now have weights, and optionally (c), if the weights become too small or too large, you need to trim them.</p>
<h1>Create unweighted survey design object</h1>
<p>Let’s use the small artificial data set from the previous post again. In order to have self-contained examples, let’s load the data set (again).</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">load</span>(<span class="kw">url</span>(<span class="st">"http://knutur.at/wsmt/R/RData/small.RData"</span>))</code></pre>
<p>This data set contains a weight variable, but for now let’s assume it had come without any. This would be the case, if e.g. you had conducted the survey yourself.</p>
<p>Now the first step is to create a survey design object without any weights. <em>survey</em>’s syntax here is quite straight forward. The <code>ids</code> argument is used to tell survey that the data came all from on single primary sampling unit. If we were to survey students nested in classes in schools, or institutions nested in countries, then our respondents would not all come from the same sampling unit. But since our data set <code>small</code> is to mimic a simple, run-of-the-mill survey, all respondents were chosen at random from the same list.</p>
<p>In order to create a survey object, let’s first load the survey package.</p>
<p>Then we create the unweighted survey object:</p>
<pre class="sourceCode r"><code class="sourceCode r">small.svy.unweighted <-<span class="st"> </span><span class="kw">svydesign</span>(<span class="dt">ids=</span>~<span class="dv">1</span>, <span class="dt">data=</span>small)</code></pre>
<pre><code>## Warning: No weights or probabilities supplied, assuming equal probability</code></pre>
<p>This just works as before, but now you don’t specify any weights. We still need to compute them (and R tells us that in a warning).</p>
<h1>Rake unweighted survey design</h1>
<p>To rake, you first need marginal distributions. Once you obtained them, you need to tell the rake function, which variables correspond with what distribution. R does everything else.</p>
<p>Specifying these relationships looks a little bit daunting at first, but is actually quite easy. <code>rake()</code> uses two arguments for this, <code>sample.margins</code> and <code>population.margins</code>. <code>Sample.margins</code> is a list of formulas, that tell R where to look for the variables you want to weight with. These formulas can be as simple as <code>~sex</code>. But they can also be more complicated, for instance <code>~sex+edu</code>, if you have population marginal distributions for education obtained separated for the two sexes.</p>
<p>The argument <code>population.margins</code> takes a list of just that, i.e. data frames specifying how often each level occurs in the population. You need one data frame for each of the formulas above.</p>
<p>Here, we want to compute weights based on the distribution of gender (variable <code>sex</code>) and education (<code>edu</code>). These variables have 2 and 3 levels, respectively. We are going to need the relative frequencies for each of these levels.<br />So let’s set up the population data frames:</p>
<pre class="sourceCode r"><code class="sourceCode r">sex.dist <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">sex =</span> <span class="kw">c</span>(<span class="st">"M"</span>, <span class="st">"F"</span>),
<span class="dt">Freq =</span> <span class="kw">nrow</span>(small) *<span class="st"> </span><span class="kw">c</span>(<span class="fl">0.45</span>, <span class="fl">0.55</span>))
edu.dist <-<span class="st"> </span><span class="kw">data.frame</span>(<span class="dt">edu =</span> <span class="kw">c</span>(<span class="st">"Lo"</span>, <span class="st">"Mid"</span>, <span class="st">"Hi"</span>),
<span class="dt">Freq =</span> <span class="kw">nrow</span>(small) *<span class="st"> </span><span class="kw">c</span>(<span class="fl">0.30</span>, <span class="fl">0.50</span>, <span class="fl">0.20</span>))</code></pre>
<p>Here, each data frame consists of two vectors: one describing the levels of the associated factor and the other the corresponding frequencies. Note that we multiply the theoretically known relative frequencies as we have obtained them from our reference population with the number of rows in the data set we compute the weights for, to obtain absolute frequencies.</p>
<p>In real life, we would not use fantasy distributions but frequencies others have obtained for our population. Where to obtain these frequencies from depends on the reference population. But if you are working with samples that should represent the general population, then checking with your national statistical offices might get you started.</p>
<p>Now it’s time to compute the weights by putting together the marginal distributions from before with our data.</p>
<pre class="sourceCode r"><code class="sourceCode r">small.svy.rake <-<span class="st"> </span><span class="kw">rake</span>(<span class="dt">design =</span> small.svy.unweighted,
<span class="dt">sample.margins =</span> <span class="kw">list</span>(~sex, ~edu),
<span class="dt">population.margins =</span> <span class="kw">list</span>(sex.dist, edu.dist))</code></pre>
<p>This creates a new survey design object, that now contains weights. The argument <code>sample.margins</code> contains a list of simple formulas, that tell R that the marginal distributions of interest to you are <code>sex</code> and <code>edu</code>. The argument <code>population.margins</code> then specifies the marginal distributions as they are to be found in the general population.</p>
<h1>Trim the weights</h1>
<p>As stated above, sometimes it is necessary to trim weights, if they have grown too large or too small. This will make your data fit less well the population marginal distributions, but inflating a few cases to too much weight, is rarely ever sensible: Perhaps that one person that now counts as 50 is somewhat deranged, or otherwise not representative. So it is best to keep an eye on your weights.</p>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">summary</span>(<span class="kw">weights</span>(small.svy.rake))</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.431 0.745 0.945 1.000 1.620 1.630</code></pre>
<p>These weights actually fit quite well, with none of them exceeding our rule of thumb bounds. If they were to be smaller than 0.3 or larger than 3, then we should trim the weights. <em>Survey</em> provides us with the handy <code>trimWeights()</code> function for this. This function takes three arguments: a survey design object, and a lower and upper bound for the weights. It works by setting weights below and above the limits to the limits’ values. The weight that is now “missing”, is divided equally among the cases that were not affected by the trimming operation. This can sometimes push cases above the limit. To prevent this, specify the option <code>strict=TRUE</code>.</p>
<pre class="sourceCode r"><code class="sourceCode r">small.svy.rake.trim <-<span class="st"> </span><span class="kw">trimWeights</span>(small.svy.rake, <span class="dt">lower=</span><span class="fl">0.3</span>, <span class="dt">upper=</span><span class="dv">3</span>,
<span class="dt">strict=</span><span class="ot">TRUE</span>) </code></pre>
<p>This would then create a new survey design object that now has its weights trimmed to fit into the interval <span class="math">\((0.3,3)\)</span>.</p>
<p>After this, we now have a survey design object with (trimmed) weights applied to it.</p>
<p>With that we conclude this little demonstration on how to compute your own sampling weights. While the main application is certainly with proper random samples, you can also use weights to get potentially biased surveys, like online surveys, to better fit the underlying population. But bear in mind that the only thing that weights can do, is ensure that your sample composition better mimics the general population’s characteristics. Weights will never help you if the process governing non-response is part of the puzzle you want to solve.</p>
<p>Perhaps noteworthy is also the relation between post-stratified random samples and quota samples. In a random sample, we define a population, draw from that population at random and then compute and apply weights to align the sample with the population. This weighting is necessary because some people originally sampled might be e.g. harder to reach than others, thereby biasing the sample. Once the post-stratification weights have been applied, the random sample is representative of the population it was drawn from. Statistics gives us a method to tell just how accurately the findings from the sample can be generalized.</p>
<p>Quota samples, on the other hand work differently. There, not only a population is being defined, but also how many persons of a certain strata are to be sampled. For instance, a quota sample might prescribe that there are 250 women and 200 men to be sampled, in a bid to generate a sample that is representative of the population in the first place. At a first look, this might make quota samples more attractive, as no post-stratification is required to ensure representativeness. There is a problem, however. And its quite a serious one: A quota sample might be representative of the population (if quotas actually do work, which they not always do). But a quota sample will never satisfy the strict randomness requirements that statistics require. Only if we are working with a random sample can we make inferences from the sample to the population. In quota samples, there is not sufficient randomness, as the interviewer selects the interviewees actively. Therefore, quota samples cannot be used to reason about the general population.</p>
<p>In the next post of this series we are going to dive deeper into the <code>survey</code> package and compute descriptive statistics for survey-weighted data. Again, if you have any thoughts on computing your own post-stratification weights, please do leave a comment.</p>
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Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.com0tag:blogger.com,1999:blog-7832770010420848687.post-87065128885977888092014-04-02T17:08:00.004+02:002014-04-02T17:08:58.414+02:00Social Science Goes R: Weighted Survey Data<!DOCTYPE html>
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<h1>Social Science Goes R: Weighted Survey Data</h1>
<p>To get this blog started, I'll be rolling out a series of posts relating to the use of survey data in R.
Most content comes from the <a href="http://ecpr.eu/">ECPR</a> <a href="http://ecpr.eu/Events/EventDetails.aspx?EventID=17">Winter School in Methods and Techniques</a> <a href="http://knutur.at/wsmt/">R course</a>, that I had the pleasure of teaching this February.
This post is going to be focused on some of the practical problems of sampling in social science contexts and on an introduction to the <code>survey</code> <a href="cran.r-project.org/package=survey">package</a> by <a href="http://r-survey.r-forge.r-project.org/survey/index.html">Thomas Lumley</a> and on how to set up data with predefined sampling weights.</p>
<p>In the next few weeks, I'll be covering more topics related to survey data, like computing your own weights for a survey, doing statistical analyses and visualizing survey data.
All posts will deal with R and <code>survey</code> and be example driven.
Enough of a prelude, let's get to the meat.</p>
<h2>Survey data</h2>
<p>Much of social science quantitative methods still rely on survey data.
Surveys are questionnaires that are distributed to interviewees in hopes of measuring their views on certain topics.
Instead of asking everyone – which is too costly, usually – only a subset, the sample, is being interviewed.
The findings from this subset are then generalized on the entire population, using statistical methods.
Most famously perhaps, surveys are used to predict the outcomes of elections.</p>
<p>For this generalization from sample to population to work, everyone in the population has to have the same chances of ending up in the sample.
We call this simple random sampling.
This is easy to achieve for small populations:
Let's say you want to estimate the age distribution of all students in a (large) class.
For small classes, you could simply ask everyone.
If you find a day where everyone is present, you can then simply pick people at random.
If your aim is as bad as mine, you can just throw things at people.
The person that catches it, is sampled.
This should make for a simple random sample.
Everyone had the same chance to be hit by my random shots.
If you don't like throwing things at people, you can throw things at a list of people instead.
This leads us to how simple random sampling is done in practice: taking a list of everyone in the population and selecting people at random from it.
Alternatively but to the same effect if (and only if unfortunately) everyone has a unique number, we can just randomly create numbers, until we have enough people in the sample.</p>
<p>Sampling from larger groups becomes more complex.
In theory we could use one of the simple random sampling approaches outlined above.
But for larger groups, there are usually no lists.
And even if there are complete and up-to-date lists, it might not guarantee that you can reach that person.
Or that the person on the list wants to even talk to you.</p>
<h2>Non response</h2>
<p>In social science, we generally group non-response into two broad categories: Item and unit non-response.
The former refers to certain questions not being answered by someone who was already sampled successfully.
This effectively boils down to missing values and is another topic that is generally ignored in social sciences.
There will be a series on missing value treatment later on.</p>
<p>Here, I want to focus on unit non-response.
That is, people not ending up in the sample, for various reasons.
One possibility is that they were not on the list from the example above.
If our list is made up of legal telephone numbers, but someone in the population does not have a telephone, than that person cannot end up in the sample.
Similarly, if we contact people by phone (and they indeed do have a phone), but they are too busy to participate in the survey, they won't end up in the sample either.</p>
<p>As long as this unit non-response is purely random, it is not a problem.
It is also not a problem, if it is not random but unconnected to the phenomenon we want to investigate.
For instance, if you investigate favorite colors, it is plausible to assume that people without phones or people that refuse to participate in the survey don't have systematically different color preferences.
Unfortunately, this is about the most realistic example for the independence of a social science investigative topic and sample inclusion.
Most questions in social science would be answered differently by those without phones and those that do not participate in surveys.</p>
<h2>Representativeness</h2>
<p>In order to be able to conclude from our sample to the entire population, that sample needs to be representative of the population.
Here representative means that traits that can be found in the population are also found in the sample.
And at the same proportions.
So if the population contains 54% women, so should the sample.
The odds that simple random sampling will produce a representative sample are very high.
Whether a sample is representative or not is also context dependent.
A sample that is representative for social sciences might not be representative in a medical context.</p>
<p>Because some people are very hard or even impossible to reach, the sample we end up with might not be representative.
It might be biased.
Typically, in a survey sample we end up with too many senior citizens, too many women and too few young people and too few workaholics.
Using that sample as is permits conclusions only from the sample to the typical survey participating population.
Usually, that population is not the one we are interested in.
Rather, we would like for our results to apply to the general public.</p>
<p>So, because not every one in the population has the same probability of being included in our sample, we don't end up with a simple random sample.
As it is not a simple random sample, we need to check if it is still representative.
And usually, it isn't.</p>
<h2>Post-stratification weights</h2>
<p>The solution to this dilemma is quite easy.
We assign everyone that did make it into the sample a weight \( w \).
So people that turn out too often in the sample receive a weight of less than 1.
And those that we were not able to reach enough of are upweighted with a weight larger than 1.
Respondents that belong to groups that have been sampled perfectly receive a weight of 1.
This solution is called post-stratification, because it computes weights based on group (or stratum) characteristics, like the distribution of age or gender proportions.</p>
<p>This method of course only works to correct minor biases.
If we did not manage to include a single person from a group, no weight can correct for that.
Even if we managed to sample only very few, the resulting large weights could be problematic.
If that three young men suddenly count for 100, the results might not be representative either.</p>
<p>In the next weeks we'll go into more detail here and discuss how these weights can be computed.
For now, we'll focus on data sets that come with weights supplied.
This is typical for large social science data sets, like the <a href="http://www.europeansocialsurvey.org/">European Social Survey</a>.</p>
<h2>Survey data in R</h2>
<p>In R, working with survey data that requires post-stratification weights is made possible by the <code>survey</code> package.
The <code>survey</code> package not only allows for adjusting the composition of a sample to the characteristics of the general population.
Most base packages would allow you to do that by specifying a <code>weights</code> argument.
The <code>survey</code> package goes further by correcting the design effect introduced by the application of post-stratification weights.</p>
<p>I've prepared a small data set to demonstrate the usage of <code>survey</code>.
You can find it under: <a href="http://knutur.at/wsmt/R/RData/small.RData">http://knutur.at/wsmt/R/RData/small.RData</a>.
It's basically just random data with some creative column names.</p>
<p>To start using this data set, we first need to load it into R and then attach the <code>survey</code> package.</p>
<pre><code class="r">load(url("http://knutur.at/wsmt/R/RData/small.RData"))
</code></pre>
<p>Let's look at the data briefly.</p>
<pre><code class="r">summary(small)
</code></pre>
<pre><code>## sex edu partDemo nJobsYear intell
## M:57 Lo :24 Min. :0.000 Min. :0.00 Min. :40.5
## F:43 Mid:42 1st Qu.:0.000 1st Qu.:1.00 1st Qu.:46.9
## Hi :34 Median :0.500 Median :2.00 Median :50.6
## Mean :0.735 Mean :2.25 Mean :50.0
## 3rd Qu.:1.000 3rd Qu.:3.00 3rd Qu.:52.6
## Max. :4.000 Max. :8.00 Max. :58.7
## NA's :2 NA's :1
## emo age weight
## Min. :-64.5 Min. :19.0 Min. :0.341
## 1st Qu.: 11.2 1st Qu.:27.0 1st Qu.:1.046
## Median : 79.4 Median :44.0 Median :1.707
## Mean : 54.2 Mean :41.7 Mean :1.716
## 3rd Qu.:100.3 3rd Qu.:54.0 3rd Qu.:2.436
## Max. :118.1 Max. :63.0 Max. :2.995
## NA's :1
</code></pre>
<p>There are a number of variables in this artificial data set.
The one of most interest now is perhaps the <code>weight</code> variable.
It contains the weight \( w \) per respondent. </p>
<p>Let's attach the survey package now:</p>
<pre><code class="r">library(survey)
</code></pre>
<pre><code>##
## Attaching package: 'survey'
##
## The following object is masked from 'package:graphics':
##
## dotchart
</code></pre>
<p>The message that the <code>dotchart</code> function from the <code>graphics</code> package is now being masked is not really dramatic.
It simply tells us that both packages provide a function by that name, and that after attaching <code>survey</code> the one from <code>survey</code> is going to be used.
If you were dependent on using <code>graphics</code>' <code>dotchart</code> function, you would need to be careful here.
But since we just demo the creation of weighted data sets, this message can simply be ignored.</p>
<p>Inside <code>survey</code>, there is the <code>svydesign</code> function that can be used to link a data frame with a weight.
This function takes many arguments, three are of importance at this point: <code>ids</code>, <code>data</code>, and <code>weights</code>. The latter two are easily explained as they specify the data frame we seek to apply weights on and the vector containing the weights.</p>
<p>The first argument, <code>ids</code> is a little bit more complex.
By default, <code>survey</code> assumes we use data generated in a multistage sampling procedure.
Then the <code>ids</code> argument would be used to specify which variables encode sampling cluster membership.
Clustered sampling is another quite frequent social science sampling method, but not one that is used (nor usable) for large general population surveys.
Therefore, we set <code>ids = ~ 1</code> to indicate that all respondents originated from the same cluster.</p>
<pre><code class="r">small.w <- svydesign(ids = ~1, data = small, weights = small$weight)
</code></pre>
<p>The resulting object is not a simple data frame anymore. Using <code>summary</code> on it produces different results:</p>
<pre><code class="r">summary(small.w)
</code></pre>
<pre><code>## Independent Sampling design (with replacement)
## svydesign(ids = ~1, data = small, weights = small$weight)
## Probabilities:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.334 0.410 0.586 0.801 0.956 2.930
## Data variables:
## [1] "sex" "edu" "partDemo" "nJobsYear" "intell"
## [6] "emo" "age" "weight"
</code></pre>
<p>To further use this object, we need to use <code>survey</code>'s own set of analytical functions. They will be the topics of the next few posts. As a little teaser, here is a comparison of the sex ratios in the unweighted and the weighted data frames:</p>
<pre><code class="r">prop.table(table(small$sex))
</code></pre>
<pre><code>##
## M F
## 0.57 0.43
</code></pre>
<pre><code class="r">prop.table(svytable(~sex, design = small.w))
</code></pre>
<pre><code>## sex
## M F
## 0.5857 0.4143
</code></pre>
<p>Not a dramatic change, but one that could prove decisive in the more complex analyses of the weeks to come.
This concludes the first entry in our series on survey data in R.
The next post in this series will deal with how we can compute post stratification survey weights in the first place.
If you have any thoughts on survey data in R or would like to see something specific covered, please leave a comment.</p>
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Christoph Waldhauserhttp://www.blogger.com/profile/06085140975734249128noreply@blogger.com3