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<body>
<h1 class="title toc-ignore">Visualising the History of
openSenseMap.org</h1>
<h4 class="author">Norwin Roosen</h4>
<h4 class="date">2023-03-08</h4>
<div id="TOC">
<ul>
<li><a href="#plot-count-of-boxes-by-time" id="toc-plot-count-of-boxes-by-time">Plot count of boxes by time</a>
<ul>
<li><a href="#and-exposure" id="toc-and-exposure">…and exposure</a></li>
<li><a href="#and-grouptag" id="toc-and-grouptag">…and grouptag</a></li>
</ul></li>
<li><a href="#plot-rate-of-growth-and-inactivity-per-week" id="toc-plot-rate-of-growth-and-inactivity-per-week">Plot rate of growth
and inactivity per week</a></li>
<li><a href="#plot-duration-of-boxes-being-active" id="toc-plot-duration-of-boxes-being-active">Plot duration of boxes
being active</a>
<ul>
<li><a href="#by-exposure" id="toc-by-exposure">…by exposure</a></li>
<li><a href="#by-grouptag" id="toc-by-grouptag">…by grouptag</a></li>
<li><a href="#by-year-of-registration" id="toc-by-year-of-registration">…by year of registration</a></li>
</ul></li>
<li><a href="#more-visualisations" id="toc-more-visualisations">More
Visualisations</a></li>
</ul>
</div>
<blockquote>
<p>This vignette serves as an example on data wrangling &amp;
visualization with <code>opensensmapr</code>, <code>dplyr</code> and
<code>ggplot2</code>.</p>
</blockquote>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># required packages:</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(opensensmapr) <span class="co"># data download</span></span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(dplyr) <span class="co"># data wrangling</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2) <span class="co"># plotting</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(lubridate) <span class="co"># date arithmetic</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(zoo) <span class="co"># rollmean()</span></span></code></pre></div>
<p>openSenseMap.org has grown quite a bit in the last years; it would be
interesting to see how we got to the current 11448 sensor stations,
split up by various attributes of the boxes.</p>
<p>While <code>opensensmapr</code> provides extensive methods of
filtering boxes by attributes on the server, we do the filtering within
R to save time and gain flexibility. So the first step is to retrieve
<em>all the boxes</em>:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># if you want to see results for a specific subset of boxes,</span></span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="co"># just specify a filter such as grouptag=&#39;ifgi&#39; here</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a><span class="co"># boxes = osem_boxes(cache = &#39;.&#39;)</span></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>boxes <span class="ot">=</span> <span class="fu">readRDS</span>(<span class="st">&#39;boxes_precomputed.rds&#39;</span>) <span class="co"># read precomputed file to save resources </span></span></code></pre></div>
<div id="plot-count-of-boxes-by-time" class="section level1 tabset">
<h1 class="tabset">Plot count of boxes by time</h1>
<p>By looking at the <code>createdAt</code> attribute of each box we
know the exact time a box was registered. With this approach we have no
information about boxes that were deleted in the meantime, but that’s
okay for now.</p>
<div id="and-exposure" class="section level2">
<h2>…and exposure</h2>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>exposure_counts <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(exposure) <span class="sc">%&gt;%</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">count =</span> <span class="fu">row_number</span>(createdAt))</span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a>exposure_colors <span class="ot">=</span> <span class="fu">c</span>(<span class="at">indoor =</span> <span class="st">&#39;red&#39;</span>, <span class="at">outdoor =</span> <span class="st">&#39;lightgreen&#39;</span>, <span class="at">mobile =</span> <span class="st">&#39;blue&#39;</span>, <span class="at">unknown =</span> <span class="st">&#39;darkgrey&#39;</span>)</span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(exposure_counts, <span class="fu">aes</span>(<span class="at">x =</span> createdAt, <span class="at">y =</span> count, <span class="at">colour =</span> exposure)) <span class="sc">+</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_line</span>() <span class="sc">+</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_colour_manual</span>(<span class="at">values =</span> exposure_colors) <span class="sc">+</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">xlab</span>(<span class="st">&#39;Registration Date&#39;</span>) <span class="sc">+</span> <span class="fu">ylab</span>(<span class="st">&#39;senseBox count&#39;</span>)</span></code></pre></div>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqAAAAHgCAMAAABNUi8GAAABEVBMVEUAAAAAADoAAGYAAP8AOmYAOpAAZrYzMzM6AAA6ADo6AGY6OgA6OmY6OpA6ZrY6kJA6kNtNTU1NTW5NTY5NbqtNjshmAABmADpmAGZmOgBmOpBmZmZmZrZmkJBmtrZmtv9uTU1uTW5uTY5ubo5ubqtuq+SOTU2OTW6OTY6Obk2ObquOyP+QOgCQOjqQOmaQZgCQkDqQkGaQtpCQ27aQ2/+Q7pCpqamrbk2rbm6rjk2ryKur5OSr5P+2ZgC2Zjq2Zma225C22/+2/7a2///Ijk3I///bkDrb25Db2//b/7bb///kq27k///r6+vy8vL/AAD/tmb/yI7/25D/27b/29v/5Kv//7b//8j//9v//+T///8ySIGqAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAZ2ElEQVR4nO2dC3vbRnaGJbuWZbXpionseHuT4/rWSu6uU9HqRdrdRhHbWnIlsaUp4f//kM4AIAmQAM8MgTlncPB9T2KYFPjm8OTV4EIOsJUgSMTZki4AQdYFgiJRB4IiUQeCIlEHgiJRB4IiUaeRoF+9s8FLgjB0FcL0btpyzisQVJYRDwSCunWBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKqTtdzOsWUMiEFSWEQ9kzhgOIWijxPe/VAVkxqjTE4JyMnQV0ua7qfcTgjIydBXS3rup3byna0gEgsoy4oFYxjo9ISgnQ1chbb2b9X5CUEaGrkJaejeEnxCUkaGrkHbeDeUnBGVk6CqkFQjpJwRlZOgqpA0I7ScEZWToKqQFyHCIz+LT97hB70IwdBXSHDLEl0Xy97hB80IwdBXSGDKEoLP3uEH3QjB0FdIQku1+QlC3LvAwdBXSDJIfHkFQty7wMHQV0lBQV0ZbznlljaCTV4MfLpNk+m5wcL28yOLfDFVeRFNII8iwq4JO358lVwfXD6dHydXzpLzI498NVV5EU0gTyPz8Z+cEnby5TqYfLs0/yeT10iJfxb8dqryIppAGkMX5+c4Jmo+gqafvz8oL8+OnJnxlImEyHEpXQGXNPmi2u3l3kCpZXuRr+P/Cqhq4oilkY0jx883OjaCTn86Sux8u60ZQG/+OqPIimkI2hJQ/fu+coPlgiX3QoAw5yPLsjs4Jmo+gD6dvs8P34iKPf1dUeRFNIZtAVr691DlBk7vB4PsznAcNy5CCrH67rnuC0vFuiy4voinEH1Lx7U8I6tYFHoauQrwhVd9OhqBuXeBh6CrEF1L57XkI6tYFHoauQvwgNRdngKBuXeBh6CrEC1J7aTD6vyIRCCrL4IbUX9sGgrp1gYehqxBnyLpLL0FQty7wMHQV4ghZe2UwCOrYBR6GrkKcIOv1hKCuXeBh6CrEAULpCUFdu8DD0FUICaH1hKCuXeBh6CqEgjjoCUFdu8DD0FUIAXHyE4I6doGHoasQStCWCmnLOa9AUFkGA8RtAIWgjl3gYegqhBC0rULacs4rEFSWERzicgDvWEhbznkFgsoyAkOc9YSgrl3gYegqpBbiricEde0CD0NXIXUQHz8hqGMXeBi6CqmBePkJQR27wMPQVUglxGP307GQtpzzCgSVZQSDeOoJQV27wMPQVUgFxNtPCOrYBR6GrkJWIf5+QlDHLvAwdBWyAtnATwjq2AUehq5CVgUNUkhbznkFgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKBILKMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICiRRoIikSb6exi7ByOoLAMjKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKBILKMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKBILKMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKBILKMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBE1gj6cDr4/ixJpu8GB9fLiywhusDD0FVITwX99Si5O7h+OD1Krp4n5UWeEF3gYegqpJ+CTj9czhaT15flRb5KiC7wMHQV0k9BJ2/+1W7iJ2+uk+n7s/LC/PipCV+ZiFd6cbfjyasja6fZylsly4t8lRC/pjwMXYX0dQStGDoXI6hNiC7wMHQV0k9Bp/+Yuoh90KAMCEpk/VG8GTAfTt9mh+/FRZ4QXeBh6Cqkp4JO3w1+uMR50LAMCEoEnyTJMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKBILKMiAoEQgqy4CgRCCoLAOCEoGgsgwISgSCyjIgKBEIKsuAoEQgqCwDghKBoLIMCEoEgsoyICgRCCrLgKBEIKgsA4ISgaCyDAhKpCjotxeHdnH76MLxxSG6wMPQVQgErUmILvAwdBXSD0FHW7PsuL44RBd4GLoKkRX0/nhry4xpo+0TM8Ttj5992tp68iV72po03jVKHSbjZyeJ/WO893uzdv4aL0HnI6h7QnSBh6GrEFFB74+NhiOj5PmO/We8a/XbSWb/ZmLuHs4F3d0pvMZPUO+E6AIPQ1chooKme4R2bBs/+3nvwrqYipg+bf4Y72UD5ULQw8JrPAVNR2PXsReCRlOIqKD5ruG+/dthLqJx79aOj/bBeb6lnwlql4vXeAmaDrw+CdEFHoauQmQFnW+pz62JK4LaR2bMKwvqtHVfERT7oPyM7gt6u32S/+XRL3ZDn27i9y7Sp2cnhIxZJUHnr/ET9P4YgnIzui/o/bEZDo1xdniz+5xLB0mpo8ZKc4BvHm9ngs5e4ymoxxlQCNoSo/uCpueTjGvnxjljZHqaaSdZnGa63Up/nB7g/N2PmaCz13gKavYVcJDEzFAgaDmZgO0Fp5lkGRCUCASVZUBQItjEyzLUCdp2VkfQbz86/wqE6AIPQ1ch/RI0uXU+ixqiCzwMXYX0TVDPk01IdNF9t+NzjKB8DIygRCoOktw/hgrRBR6GrkJEBf2f6jT0ch6cZpJlQFAiEFSWAUGJlAUduX5LL0uILvAwdBXSG0FH2RednQ0N0QUehq5C+iIoZnXyMyAoEQgqy4CgRLCJl2VAUCI4SJJlaBd0Nqkzi/ecDZxmkmZoF7QcCMoKiaaQiAU1I+j4u9/ZS4vYDyr/7LeH2RzPfKpnMv6L3xJHPCVB74/3veYeh+gCD0NXIcKC3qykLOjufvoNuXOzMKKeLx49+ZLOAXUX9Dyb7IRrM/ExNAhKjaD2eiN7F99eXthNvF18+/EkX5R3USlBcZqJn9EfQVMXzw/t4v7jSWEBQUNBoimkE4K2MILiPCg/oz+CVu+D+gmaTrLHeVBORo8EvT+uOIr3FNQzIbrAw9BVSMSCNg4ElWVAUCIQVJYBQYlAUFkGBCUCQWUZEJRI6fqg/+X54hBd4GHoKqQvguZnQO//CSfq2RgQlEj5Arb2Bje3uHgYIwOCEinvg6aXbsC3mRgZEJTI0kHSeNfjgyQIGitEq6D3x1s76WbeMSG6wMPQVUhfBP32Yju9xw32QfkYEJRISdC/yZZ/hKBsDAhKBCfqZRkQlAimHcsyICgRfGFZltFDQc/TeRuzSSA+gmLKBz+jt4Imyxd1qAkElWVoF/T+4yez03ib7jjm36U//2s7TT4fQfPn3ATFJp6foUHQxyspCHq8k4x3d+aTkuxspHQqUi6oeW609qNLHCTJMjQIun4EPUn/XUzkTDfx6fRjO9XTPLbPuwrqmRBd4GHoKqQbguZT4ZM/nBQEfUHdtQOCyjJ6JGhhBL0/ngm6dvRcEvTcbN3tTb3xbSZGRo8Ene+D7iSlfdD1dzZcCGr2Xe+Ptw7TK4hBUC5GnwRdHMWbjfriKH79fbnmgqaXbkzPMOFenYwM7YI2zlzQ9CRoJuj8xNTD6VGSTN8NDq6XFxC0JQYEbSLo1eAolfTq+dICgrbFgKANBJ38/T8cJdMPl8nk9WV5AUHbYkDQzQV9+Jd/N+Pl5M11Mn1/Vl6Ynz41aasIpOVw3o6bT9CtWXJBr97aDfrdQapkeZG/JsSvKQ9DVyG9GEFXYgbLhzUjKASNp5B+Cno1sHmLfdCgDAjqJehoa+twtDgNakfQh9O32eF7cQFB22JAUB9Bz5/894vDwl0+cB40OAOCeghqDuTtsTy+sMzIgKBEIKgsA4ISKX+j3m7i8Y16TgYEJYK7fMgyICgRfGFZltEvQfN5nD43PYagsgwISqQkaHqU5H79WggaKyQiQRc37Brv/WL/7nlX7uW7HY8eXayfBgpBW2VoEHS4koKgi1seFiZ5eNyVe+k0kz1Lj9NMjAwNgq4bQQs3jV1Mk/O5p+zKedB9CMrJ0C5o4bbbi5lyPnflLt2G5nj/dvvEbughKBdDu6CtjqD2CvU7dnYnBGVjaBc038m0kzrN4c0Gd+XGaSZZhnpB86P10dbWb15e3B8/uvC8KzcElWWoF7RpljfxhSkfdEJ0gYehq5C+CFr4JqhbQnSBh6GrkL4Iml/A1j0husDD0FVIXwT1+Yg0TYgu8DB0FdIXQT1O0WcJ0QUehq5C+iLobGo8DpL4GBCUCE4zyTIgKBEIKsuAoETWzounEqILPAxdhfRG0OV58VRCdIGHoauQvgiKacf8DAhKBILKMiAoEcyLl2VAUCKYFy/L6Jeg9n4fnsFpJlkGBCUCQWUZ2gWdzfX47nf2FsdG0PvjJ/+ZPci+rGy/ADJ+dpLczp9eIyjmxbMzNAj6eSWrgu6mUzuMoOf7Sf4gn+4x2k9GxsvR/uzpNYJiXjw7Q4OgLiNotrj/+Of78+dmE+a++/KHTzuLmZ9rBMW8eH5GzwQ9/s1ffSk+Z7z89vKXl3/a++XlhZOgmBfPzOiZoB9PzBa9PIIm53/7l/cfP+0ktKCYF8/P0C5oYb5xJmhhW57PPL7dyvZCaUExL56foV3QfL7xQlCz+FNuYn5Anh7Dzy8wtlZQ34ToAg9DVyExC9o0EFSWAUGJQFBZBgQlAkFlGRCUSCNBkUij8W7HmyTErykPQ1choiNo4EBQWQYEJQJBZRkQlAgElWVAUCIQVJYBQYlAUFkGBCUCQWUZEJQIBJVlQFAiEFSWAUGJQFBZBgQlAkFlGRCUCASVZUBQIhBUlgFBiUBQWQYEJQJBZRkQlAgElWVAUCIQVJYBQYlAUFkGBCUCQWUZEJQIBJVlQFAiEFSWAUGJQFBZBgQlAkFlGRCUCASVZUBQIhBUlgFBiUBQWQYEJQJBZRkQlAgElWVAUCIQVJYRpaA3NWtIBILKMiIU9OYGgjZKNF5EU0h7gt7U2vkVgnIydBXSoqBr15AIBJVlQFAiEFSWAUGJQFBZRlyCrtkB/QpBORm6CmlP0PVrSASCyjKiEnT9AApBGRm6CmlJUMJPCMrI0FVIW4JSa0gEgsoyYhH0Zu0p+vy/IhEIKsuIRFAjJ74skr5H/5cEYegqpKGg2eDZPUEnrwaDoySZvhscXC8vsni1IXuP/i8JwtBVSDNB80175wSdvj9LJj+dPZweJVfPk/Iij08bvjp2gYehq5CGgroWwiLkcuoFvbMe/no0/XCZTF5flhf5Kj5tcO0CD0NXIU0EnR8bdU5QGzOKTt5cry7Mj56a8JSIeMfjbsc34apoJWsFfTh9m9wdpEqWF/nP3X9P57+E/i8JwtBVSIMRdHFuqYMj6PTdW3OoVDOC2ji3YfEe/V8ShKGrkM0FLZz77J6gk1fmGD7BPmhQhpigNzdL5+Y7J2jmZ7qZTw/fi4s8fl106wIPQ1chvoJWfmzUOUGvBjZHOA8alMEq6M3KsOlVCIuQy8EnSbIMLkHpz9ohqFsXeBi6CqEEdfgiCAR17QIPQ1ch6wR1+ZqSYyFtOecVCCrLCCmos5uOhbTlnFcgqCwjmKA+bjoW0pZzXoGgsoxAgnrrCUFdu8DD0FVIS1M+yDUkAkFlGRCUCASVZUBQIhBUlgFBiUBQWQYEJQJBZRkQlAgElWVAUCIQVJYBQYlAUFkGBCUCQWUZEJQIBJVlQFAiEFSWAUGJQFBZBgQlAkFlGRCUCASVZUBQIhBUlgFBiUBQWQYEJQJBZRlBIEMImiVEF3gYugopQ4ye3vM9nAppyzmvQFBZRuuQoR0+IWiWEF3gYegqZAEZZlt3CJolRBd4GLoKmUGGs51PCJolRBd4GLoKySGLYyMImiVEF3gYugpJIcPCsTsEzRKiCzwMXYVYSOnUEgTNEqILPAxdhRhI+dQnBM0Sogs8DF2FlDbvNhA0S4gu8DBUFbKsJwSdJUQXeBiKCrF6LkMgaJYQXeBh6CkkHT0haHVCdIGHoaWQfOsOQasTogs8DCWFzHY+IWh1QnSBh6GjkPnBEQStTogu8DA0FFI4eIegSHQZrrmlcey3MPYIRlBZxoaQYfncJ0bQ6oToAg+j44Usn5mHoNUJ0QUeRqcLWZ1yBEGrE6ILPIzOFjIcrn6wCUHrEqILPIyOFlIlZxUEgmYJ0QUeRjcLqZ1ODEGrE6ILPIzuFVK9ba+BQNAsIbrAw+haIWvkrIJA0CwhusDD6FYhhJ4QtC4husDD6FAh6zbtdRAImiVEF3gYnSnEwc4KCATNEqILPIyOFOKmJwStS4gu8DC6UIjLtr0GAkGzhOgCD6MDhfhcQxGCVidEF3gY8RfidY1PCFqdEF3gYcReiPvWvRICQbOE6AIPI/JCfC+RDEGrE6ILPIyoC/EcPisgEDRLiC7wMGIuZIMrzLcn6GOT2jUkAkFlGauQTe6A0FDQx4us/a9IBILKMlYgrdyhw0nQJS2xiXfrAg8j2kI28tNd0MePa0dLCOrWBR5GpIX4Hx5VV1IvqDujYg2JQFBZRgmyoZ4QtC6u/fPpAg8jykI29hOC1sS1fz5d4GHEWMjmfjoISh+lQ1C3LvAwIiykgZ8rlTxeiT+jYg2JQFBZxhzSxM9VQVtgVKwhEQgqy5hBGvkJQWsSogs8jNgKaeYnBK1JiC7wMCIrpKGfELQmIbrAw4iqkE1Pz9dUcnNzA0GzhOgCDyOmQhrrWajkxgYj6CwhusDDiKeQ5sPn16yS3M00EDRLiC7wMKIppAU9b/IUnoKgWUJ0gYcRSyHDYTNIbiYOkqoTogs8jEgKqbiLoXsKoyYErU6ILvAwoiik8i6GRG4WWVMJBM0Sogs8jBgKqb6LYUVubqq1rK8EgmYJ0QUeRgSF5IdHdRDKybWVQNAsIbrAw5AvpO42m19nbjapBIJmCdEFHoZ4IZW32XQeMalKIGiWEF3gYUgXsnSbTfeN+WpWv/vp9PXPlSgRdPpucHA9exCiCzwM2UIWnx7ViVlpXXUaVVKIDkEfTo+Sq+ezRyG6wMMQK2SY361jPmaWIRsOgRB0lumHy2Ty+jJ/5P7uh0iW1EpiPGwq1+fPzRmVa0jEU9DJm+tk+v7M/O2pSc1KFf9fmpbplJuVsPxnvfM4JPzz588h8ezxFPTuYCaoTYhfUx6GrkKwiZ9nMYLahOgCD0NXIRB0nk33Qd27wMPQVQgEnefh9C2O4ttkxAPRISjOg7bMiAeiRNBSQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAhakxBd4GHoKgSC1iREF3gYugqBoDUJ0QUehq5CIGhNQnSBh6GrEAgaVepmmrAnmkIiqqT1QNDNE00hEVXSeiDo5ommkIgqaT0QdPNEU0hElbSeDgqK9CkQFIk6EBSJOhAUiToQFIk63RB08mowOCrMeU6vHWGe/OGSemXQQpbLEq8kX2hKJwS1F9uZ/HQ2v/bjnTXTPnnFLEa5kOWyxCvJF8ylhE0nBL2z//t/PZpdd+fX7//N/JleJuoD7xBaLmSpLPlK8gVvJYHTCUFtzOiwuHKZ9UFiBF0pZOmRcCWFhZp0RVB7UajFtR/TAUtk12+pkPIj6UoWCz3piKDTd2+L1360gtqdrTv2o6RyIUtlSVcyXyhKNwSdvLI7VoudPfunyMBVLmS5LOlKZgtN6YSged8X136UGkHLhayUJV2JQj+7IejVwOZo6Tzo3WDwPfMAWi5kpSzpSmZPakonBEX6GwiKRB0IikQdCIpEHQiKRB0IikSdHgt6f7yVZn/1R+NnJ/O//+9/LP3QPFH8+SpxZ2ltpEF6LWiq5nj3cN1aKy7WyLkg3h8/+eKyNuISCJqc76xby1/Q5NuLQ5e1EZdA0FRQu3F+dGHd2tr+ee/CajXeNVvrQ/vn/njv9+an6RP72RPm5/YlO9bAn80zhyXiyD6/WHtOR/wDQW+NXffHRqnRky/fXuwbRx9ZQdOhz2z+M1d38nFx9CiT99mJfYn9d7xrNuijTL+ZoLeWtFh7Rhd8r91NrwXNDpKMSbfZ6HmYLjOtxnvZkJcJatb5vy/Zo1zQdNVbO64ezjfkc0EfXRTXntGl3min02tB9+0YaZ0a5cfz6TA3zjbx59nheO6jfcGtWWV7Lmi66mykXRLU/myx9qj2bAFCpu+Cplv4+fa3KGi6QzrfottH2yfFEXSNoGavtrg2tu4N0ntBk3OzAb7dzo6159vt/NjbbJfngmbD4mIEtS+ZrVoW1G7Ni2vP6MgGgaD2CCg9dWk8Khwkpa6apbUtE9QOibvbsyfmB0krgs5g87XnTyD+gaBmFzE7EbR9kp1m+pQNi9k+pBlht3Yy/8xO6fY/G9/yJ+anmYqCLnY2C2vP6Yh/eixoXW6xyxhRIGgxdjucnrVEYgkELWW0/F0PRDgQFIk6EBSJOhAUiToQFIk6EBSJOhAUiToQFIk6/w90ZPg7gSjetwAAAABJRU5ErkJggg==" /><!-- --></p>
<p>Outdoor boxes are growing <em>fast</em>! We can also see the
introduction of <code>mobile</code> sensor “stations” in 2017. While
mobile boxes are still few, we can expect a quick rise in 2018 once the
new senseBox MCU with GPS support is released.</p>
<p>Let’s have a quick summary:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>exposure_counts <span class="sc">%&gt;%</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(</span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a> <span class="at">oldest =</span> <span class="fu">min</span>(createdAt),</span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a> <span class="at">newest =</span> <span class="fu">max</span>(createdAt),</span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> <span class="at">count =</span> <span class="fu">max</span>(count)</span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">%&gt;%</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">arrange</span>(<span class="fu">desc</span>(count))</span></code></pre></div>
<div class="kable-table">
<table>
<thead>
<tr class="header">
<th align="left">exposure</th>
<th align="left">oldest</th>
<th align="left">newest</th>
<th align="right">count</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="left">outdoor</td>
<td align="left">2016-08-09 19:34:42</td>
<td align="left">2023-02-28 09:47:17</td>
<td align="right">8417</td>
</tr>
<tr class="even">
<td align="left">indoor</td>
<td align="left">2018-05-10 20:14:44</td>
<td align="left">2023-02-27 09:53:33</td>
<td align="right">2364</td>
</tr>
<tr class="odd">
<td align="left">mobile</td>
<td align="left">2020-10-24 14:39:30</td>
<td align="left">2023-02-20 16:32:48</td>
<td align="right">590</td>
</tr>
<tr class="even">
<td align="left">unknown</td>
<td align="left">2022-03-01 07:04:31</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">19</td>
</tr>
</tbody>
</table>
</div>
</div>
<div id="and-grouptag" class="section level2">
<h2>…and grouptag</h2>
<p>We can try to find out where the increases in growth came from, by
analysing the box count by grouptag.</p>
<p>Caveats: Only a small subset of boxes has a grouptag, and we should
assume that these groups are actually bigger. Also, we can see that
grouptag naming is inconsistent (<code>Luftdaten</code>,
<code>luftdaten.info</code>, …)</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>grouptag_counts <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(grouptag) <span class="sc">%&gt;%</span></span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a> <span class="co"># only include grouptags with 8 or more members</span></span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="fu">length</span>(grouptag) <span class="sc">&gt;=</span> <span class="dv">8</span> <span class="sc">&amp;</span> <span class="sc">!</span><span class="fu">is.na</span>(grouptag)) <span class="sc">%&gt;%</span></span>
<span id="cb5-5"><a href="#cb5-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">count =</span> <span class="fu">row_number</span>(createdAt))</span>
<span id="cb5-6"><a href="#cb5-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb5-7"><a href="#cb5-7" aria-hidden="true" tabindex="-1"></a><span class="co"># helper for sorting the grouptags by boxcount</span></span>
<span id="cb5-8"><a href="#cb5-8" aria-hidden="true" tabindex="-1"></a>sortLvls <span class="ot">=</span> <span class="cf">function</span>(oldFactor, <span class="at">ascending =</span> <span class="cn">TRUE</span>) {</span>
<span id="cb5-9"><a href="#cb5-9" aria-hidden="true" tabindex="-1"></a> lvls <span class="ot">=</span> <span class="fu">table</span>(oldFactor) <span class="sc">%&gt;%</span> <span class="fu">sort</span>(., <span class="at">decreasing =</span> <span class="sc">!</span>ascending) <span class="sc">%&gt;%</span> <span class="fu">names</span>()</span>
<span id="cb5-10"><a href="#cb5-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">factor</span>(oldFactor, <span class="at">levels =</span> lvls)</span>
<span id="cb5-11"><a href="#cb5-11" aria-hidden="true" tabindex="-1"></a>}</span>
<span id="cb5-12"><a href="#cb5-12" aria-hidden="true" tabindex="-1"></a>grouptag_counts<span class="sc">$</span>grouptag <span class="ot">=</span> <span class="fu">sortLvls</span>(grouptag_counts<span class="sc">$</span>grouptag, <span class="at">ascending =</span> <span class="cn">FALSE</span>)</span>
<span id="cb5-13"><a href="#cb5-13" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb5-14"><a href="#cb5-14" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(grouptag_counts, <span class="fu">aes</span>(<span class="at">x =</span> createdAt, <span class="at">y =</span> count, <span class="at">colour =</span> grouptag)) <span class="sc">+</span></span>
<span id="cb5-15"><a href="#cb5-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_line</span>(<span class="fu">aes</span>(<span class="at">group =</span> grouptag)) <span class="sc">+</span></span>
<span id="cb5-16"><a href="#cb5-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">xlab</span>(<span class="st">&#39;Registration Date&#39;</span>) <span class="sc">+</span> <span class="fu">ylab</span>(<span class="st">&#39;senseBox count&#39;</span>)</span></code></pre></div>
<p><img 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xwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscHENQVCrZX2q7nsxfaTD3wpjuYlqlxH6K9lWXBuBAUYmGzNNkRzFTLZvq1s2VXj6oVeNqhYhaPvk5KqLBQtgkvcbksZP1KiD7kmipR0d3JdgOaYK2NBkvgrZm057iBAQF2fGQcjpiZhJUiXGe3aJq3GTnFNHWQthbZe2WomvslVDavsRPjo/RCap1gqA2rpzElyiR9a/7SU64zmLU2lwiJa73YB7/USQ6Pr3dvNCvWoXHWJRSRjp5Vh+CEjUFHPprH96QFnoXy5tRFwzqaOIkfWxLuCET+OcR1ElibP9aebnnzPzw8tPndwFBpxmOUn1qG2P1K7/Sj6D3z96qc1Orja2IQIkZr2rnf3yltT4TuOrudn83gndekTQghVbRsZKzkL194XHl1Lr7tfoPG/IvRWiXHdNDn9yQZmmRN6MuGB2KzYZES/y1GJjN/kw9JgJV4/4I6iyE7bBfUTmk+cDl3eYqIOhUI+h/ieCPlaZFYqc5EET6c1B1fWjOf1AbV84PUg876H880Trm5OWApAEpWMFHTUXHxhVX908sm6ucWvf++R0q3VIjqJUd+4o8EL5Cs8TyZk8XTCTTmZf4hp16FmNV4yBSgh50FsK+TkV1qOvktdor0lJPgGSfQov0n4OqiRaojSvnqAvXRet/DILb2YshaUAKjqBUdFy/tum3CI8rp9Y117lesT3ZsaWb0fiSZonlzZ4umEimswhqL/E6dz0vdiOoUfJZC2F/hCQjqD7C6S19fz/RSvw0QU2LtBLUuQTXhKCbF+ahHfEIiv7HChOIPfsRFIXDaHbri47V8AL90z6CwiH0I5V6xfZkx8EIis0Sy5s9XTCRTOeNoBAVVeN4iddKOm8O6qKRZ43oLt/4BN4udBcPLdJKUHQJJnd0l1+qUeHM1oMSX/KrIudSBIU0IAU6ojnRsarL39snqNUe07vyPgSFS/f2FA99ckOapUXeTHXBddCex7eEfiIU2j8TgmqJqbUQ9ghI7+K3en5w5r1vxKmjI9mn0CLtBEWXYDsx/SH9AKQvjNq4wrt4U6LdaC6o8xdD0oAUbL97ouPmKuAyjYTHUJQ6xMPHtz1j41eJziK6Bo0vaZYWeTPVBdcYOqUI7s7G3CMRS2ckqFFE74l+nCZvO/ljc8l/ZV5ekU+Oju5K0FZ72F+S5hVzOiRIMjro45SOi50aCY/F3C0xHfpWIgSNsaX3BcNjT6nxFYKyxJLdwosSvLLJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzycFxBDWqVYODC3KME9Cc6C7GsxXGZZDqX/IWrPGMk0/YkSUa0oZ6RwVr5J2RkepWUr591V7g/J0YINWu5yDm9giK68Dr94ignq0wkc02/5K3Jiborbf4Et8ZGSmC7l/QtZvm1ftIUC12fBw4zTlJixbuaklsbG+sJLXfvvJ9hakEeYFiqK0wlc1W2gLQvgWLhTF564ZspMiBjFrJhvvEZkZQV76uA7RV7QViJ/rNMRe6K9GqFX1mrX75l0PVqhXuevpca2+sXjV1eL7CRGA7VTF/OwI524itMJXNGl2LfcvKLVzyTu/rJCy2BpBsuIb8cxEWJOjfikGyseXrOsyrAwW6dgiaYy7sdv89ws6bg5oJim+FqFWrKNwl6jIQHGtB2PWV7yvcUzKbU0zX2UZthUE2a1lD3lJ5esk7MZCWIlPttBG99YqNUm0WI6gr38jd9KsDBbp2CJpjLiQqcZq4tku8E+7apNHeGLSRvq9wT8nsZMWgrbAnm9WSJHzr41s/eVuckSLTjUY23C82q0s8lq97zbxqKdBrh/CNmZAiqBL3KdARlNwjoeLQtze2J5/nK9xTMjtZMWgrDLJZlE3jWw8f3/rJkxHU3zhsBOVEUFQN2xNNVddeIHai3xxzIdWudr4Y+MXrTnXCXaLPtfbGOH1BX+GektnJikFbYZDNomzadxyOkzcS60D2G85BhxNUu3FPMaHrzgZVw+bq4RqjpUDXDkFzzIXEqebuZyhBrWrVCHdBEhvYGzfXDbgBRF9hqjteoBi0FX742LLDyqbRcVidSF7yjqAviA6YyoZ7xY4IquekZ/uJdHOd2djyX2mCusaIC/Q70W+OuZA41Vb2qZZ9/5K0kJ7TIEGSCYBdNX/sLvDKJgd9KxGCRvBlw7wowSubHIxN0EWxZLfwogSvbHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xycBRBwWnTST7jJVhzLshCdBfjPHmXEFkoh8O63ji1IK50rl1rRYuYj0+0T0s4ZViFBlEJmOWXx6VlrJUxJD1scED6um8loQ2NlcIpyed+sl4fiEQxOsNpHCXTBH38A3f1/YcXXQSNNkxGUL0i1Zk8DSGoE1UNBVoruwzwsP4B99SiqEcl+tDhJb55x0o+NyevLtA2GH2RYJydxti4FX0IahUqRjLsLgITx27CfqeJ9kI1lA6p7BWvlQCBnNyYl2nMpKfxsdmY1cgvbfnVxVulHfd8n/2rpFWKVxefnbk80WWKeEHbDxhxMtEoGypZAyhgC3weD6hg+DSgEi1aWf3SL3kEBa9iUPXodg/ceEGVPJGxcSt2u78RISxmiwZ4JzdWDz1K7N2fj0AJ+tlV/QuvjH2k7tObJgXfuxjzgsbMGUH/ToxgBL2kHs/OThm22d6DPc4dy0CtjYmrYtCl2X0ATK6dRtlaKz9op7fPz9eBzx9omzE/V8l/ixD2qdLC+SNodX4Cz99wNojwP4pTYenynCuYE2eb9eSF9oerLPHunC52E/PNk4eP31xY/dnDy2+s69oXYmNepOOmyIa6EzsvZXIjgWbQuEdtM3x+53UznG3OIQ8/4B/TWiuj9gXfxwPaxho2gqrY4SVe52Iln5SgRJxqHI2nMTZuRboYLXKr9KNEDEFH82RMEvTdj3zxg0aKpkI+XH/w/K72hdiY19QENYKjK8/j2ZEJPCKh2+we6hdtzrldB90cENR9AI+pPmoCP75B62GfoFag7vLrX4mOG33NpIZ6K6mjBPWkxTC8z/Ukih7FbE9dmtoK+6o+ngUDYqsorz8xXXsFfQoPZ6lda803gurjKsU78Xh2I8wV6T3cw33w4eUrr5t9gpIP+COotVY+NILS69hQgqpEPVVnwzflquokn4SgKE4FVfJExsat6FGMni7hXO/i1rMsniy2vqlE3/fHN+BB7wmxg7wmJij44jqPZ8qZxzfUDPqxe9aG/qlv5Tduwro9pQQlHwimDWCtrAbuZr6DE0Lwft6QJ+oMJKg+KfxH3+jRGCWflKAoToWr5zTGxq3oc7Y183ZIU0mGQQ89eWwcqCCkvoe+AKde0CBjXnZkSngaH5sNtV42Hs/EThmaBLrN7WGrqK1bt9WTf/DMu8TjB3yCOmtluIt3wcD7GQ5IwgyqpMS/JI10bT8qdhfGyGu8bJZG30oKI+j4TsPjUGKsvISgLLFkt/CiBK9sciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHJwHEH3K71GWi1y1Gvu1m7ro7vu1Ti+zW4ogHUw26nhqa+DrFsX/SSKidxS0Sn1YM4P1zYL2OWQu2oiNsqOnfzWNuKBJshCdzbtIfUSuMsvyMrhhH+uAvaK+W3cJWJ170r89aB77T6zdivBzZLfrV79mZB6+Ta7uOA0gF1S25H5PAQl51IeQa3s2MlvvUYcadV0z2zaQ8Zt0IOgiGUI2rpg2fSRsvMykiWjnDN0at6D5adEtIriU99ml8pGza5KSKJEK7D6/apCH2W9Itb57p582qLJTRH0BdXVgpWvLfSj0OrXejlrE8BTtxr70PrmFEGt7Nieen4jhpeHXPToVtKezrb61uqQnTWU3yhvjZd1a69oIfX3nY+9Or1HJboVV7/4i8FW98s2EB7BAn4qWnXL+X2bXSobNbvumz3XNZ7jxEcZFBLNYUG52jaC/vUIlKCPrCDRagzcZS4QTTdR0cuZSGy9z0QN+RcitMiOrfzWb0QjJRsPu93fjxHJjm03uVJRh2zKDf2Pwcu6vVe0kHqCEfR/RAgJqqQmgRUieXsPp8yeqJp9l2Oy8N+32aWy0Rr8su9e6ysFzC30sGVcQK2XuxXBHneJN1cttDQmhVaemha9nImS2vvMoNhEdgzyW9eIRAM8GhLjDoQkPsa1a9BOg2fjZd3aK0ZIvcQlXqcUPvpGq1JtzmYroa3vcowE9W12a3IGWDWungJgnfajRmNmxa6XdJfexYCdL0kKJ1mWoEQG7LyccaP/mUGxiey4rp2szDbiQdofix7dqmxioZtcqUGHRf7HxMs66hUjpF6EoOEIaloTJHwbO3DSOajvcowE9W12XQDUt9bbF2vcXocjKFXpHjWC6l5x1svxCOr7MRtZI27MGkFBdmzlt14jDrwfSaNPt26uiNYXSvU7LPY/Nl7Wrb1ihNSLEFQl79/Fq8HRqGOJopjexXsux0hQ32bXBrDkVPeVcG9JCerPdtRvTrk6qBiw87WR/Dmo7RKXN9Hd4sbuOWiCoKbBrPyWNuL4z1/p0a3aS3dNlOHYNqAGjv2Pwcu6vVf0cLoEQWPZsZ7E6Bvbd9f6e1AzipLvQT2XY0dQ32bXHsjc4YPa1eziE9S7X3TK1RZNboqgL6j1Mlj5YqGYN17sgo3eZwbFrpzs2MpvXSMu+D0otKezrb6FtjFq4NjgGbysW3vFCKnfHa2UzqukmusvSdWTQ+/0GGQSJJkUS8aeLZu4DyZ/9FbfSmYi6Pag5nbb40Z3eLeYM3AMpe9Xk6B9eiUPzAiahyVJ8pUg6AIQghYQm3s2ORCCFhCbezY5EIIWEJt7NjkQghYQm3s2ORCCFhCbezY5EIIWEJt7NjkQghYQm3s2ORCCFhCbezY5EIIWEJt7NjkQghYQm3s2ORCCFhCbezY5EIIWEJt7Njk4jqD7NhVNj7Wq3jr68dFdDAgdzsyvzpxbvxWYZY8eO9bFE1nAdu71oF2PMHALluh7D2bZbyhUHM+K9zCSfQrd6vskwdp5/1D9CToV0gQFwYZb0g+K1NAse/TYsS4eCapysKaSYyGRTccjDIIHFzi0cVmtZB9Z0B+hF0GbbqUEdeojOIXutVpar7BG4boylVbyabpLTVyYqSR7tmKsoMgR1A3p1ix7otixLt7FN5KekU/d7myIfIw+DkABHlzQ9Nybi1s6RBohITzQwGzXcp+RxVQDKzEdqbp19fM/77Y6HZK1bga1tJOvOFPpq3CXcyrvGd2se7f7qxFoMe+usbX9EdSq1nNi7/5UhKQu3qm6RpZ17nb/KEbcgf7jAPQW8+CC8ysik69dvpV5oAHZPvYTJ1oq+Z8RAoLqbvW8OimjlK7aqaVB6kcsUaNdgBy+JHu0YjrPtsffAPEUzkGhpzyz7Clit+jizVr+U5B5jjwSdWdDH2EQPMbAPbiAyOTdrnhi2+1jT02GVqISMt3a+uAGkFuhWroyYmliKh3tYgnqSbLnKeZ8TfzDtXITFGNnvmp9gtjtungzgmq2jD6CdrYEffIG6Qz64AKqHLS7IkFh+9hy/uGV6OfWqG5tnYNaiblTS8cjaLSLJagnyZ6rGKJqNvfP2PpGtT5V7FgXz2QOSh8HUNMHFxjiols5JajbPvFNb7qSykmlW+/i4T2ilvbnoHAe+rvAMT1J9lzFqEnnF0qTDjew5ksnolqfKnasiyd38fq7p8Xu4km30QcX0EcIQAHIB7J9avQiaNOt7d+DGhk1qKWVrhrv4sFU2t+FFO5JsucqRlHy0b9eOW23vktwdU5MUCycxIdJ6YLfg5LOoA8uMOcOupV7l3i7fexnng2uxCYUfA8aoPVOx+/tyeXTGqluKTU292xy0LeSQQSNTaWFoPOCVzY5GIOgbCAE5ZlNDoSgBcTmnk0OhKAFxOaeTQ6EoAXE5p5NDoSgBcTmnk0OhKAFxOaeTQ6EoAXE5p5NDoSgBcTmnk0OhKAFxOaeTQ6EoAXE5p5NDoSgBcTmnk0OhKAFxOaeTQ6OIajvle0vW5phCethdBfjlL9NjpGUxnn1HltAoiHbZMfGr3SSFkt3K10Mn7vUcEok+hR0ZtVlaIWIYFRaohiiLT5M0Glit8qOq/PTqValDyNozaoXfaQIertVI+V23UJQs9r17dOVUagaReobt+b64eUnzTC7x6F2+WJQ+au9ox997tlKqw3wJmbe+9kEKYK2yI6ri8/OliGothX/oWsja9+bsj9yhRopOCjFl0aSoCCAW/3cz7UT1C4Uh0sWvlJyCnVhm/Hc3O3+cgRaDCh/DUGVd7RnK23MpP3MqfA2FXv3JyJ0y4tob50AABuRSURBVI6b/zZXUxH0n8TAbIylYzP2bBtSbteVZ5kOUnBQio+f2zDsdv8rgkdQ7XB3eRfNQc9aCOr9UB/URnmzrFWGYrrPNlD+6uSsd7QzRYUNceZE33d07BbZsdEOPm97usfULQGmuE23vv7kzGgZrfijdovLQSk+fm7DkBxBlVJ666s6D46g3AkKyl89SFrv6OoCru+wIcy8r2gqSdBYdmxadwGC6pDK7PjtszcXb5+RLtzokUdLwUEpPn5uw5CupLr8sumsIggKyl+THHhHo630dh0TlApvc2K3yo7NuZH1PJPjsrG24pvvPmnm22ek0+znlUG6UYqPn9swpAnaXJiaaWgLQcG0GWZqWyf3h1ccCWqUv3CTBLLTwEzaJ2jVW2CbJmgkO9bhza38vC1hbcX3KzML9QkKUnBQio+f2zCkCVpv1fPO2r5mMqbN4OL8wTNXJGxnSFD3n/GO1lNCtJXWG4Kxnwhvc2K3yo5NO24XICjYiut7+NPbcAQ1sxpQii+NHgTVI4j8JYlx7EmymXFg6ULfSoSgjGNPko0QdHwIQXlmkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5ODYwhqZMfeGjTUCFboXhHi4doK6ODtsX2gEsWA4LcdNmP0vyA1RKLhwbHb3Y4frs9MY469rm0oQUmtM5hzDUF3JbYVW9aD+st4exEUNy5CUCv4bf8spESMnClBQ9Hw0Njtbsfaj3cSTeFQghK8dwQ1CUcE1St8z61XLi7qRYKalcDaHVcLWbUZD2w0b/dbCjxmMUbdEaqKmxzBO554sCk99UdXxgooEg0Pjd0qO9YtuwhBPatpa20Mb6hOQffjxZHsU8PP+9XP/mwwgl7eWU0uCAjIm3bz9kxLe0HISjaGnxqrmN8bAYuxgt9YVQx66Zr6AGsq7Zsc13WLaLi1If9ohE7ZMTwTYyKC/tMYnuQDraaxeqcFQffjxbHb/e8IlKDgYL2J56BORG0lWPRN8I+9NzoQGHKqC7LR/9RYxXSOGyD4jVXFqHegPsCVVgW/Nk8cCUTDg2PHsmPwXvZcl2dqCd9qmqg9oFOI+/HiSIyg0Ir3z+JLvCLXxlrjoj7VjaBgoQvKMJDh4Eb/U3MUAxXdxKpi7CLqA6zVSZ8+N9PRQDQ8OHYsOwbv5SUu8b7VdIWKY+gUdD9eHgmCulaMRXMbZ3bsj6COoM9u8XUN/q24cf4R1Ap+Y1UxEpT6AGv93wvr5emLhofGbpUda6YvQlDParplBGUyeiokCAqt2DKCEk3u4TkolA9CVn/jJHPQzm4BwW+sKiZdRHyAieQ4Eg0Pjd0qO3Z38+MjkY1nNe0JOt0clIHiWCNNUP2tSssc9MqZ3oKIlXzE3qZbV9/Nity7w0bvU3MUYwW/sarYpGPuW/F7ULXF2P/GouHBsaMjwDzp0edmzj6v27FnNU0JCp1i3Y8ZoAdB1X3n/Vf0L0nVk+Vi54BXNjnoW0mSoHD3vuiJN3q3bPuXw4sSvLLJwWgE5YAlu4UXJXhlkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWeTAyFoAbG5Z5ODIwj6cK2XhSiHRyPwQSluiyB5TiSK8SXD4AHUqiM+oJruKiwR2zpEt8uPR0d3Nm5JJPbXXpsHYqZslJ2JSmxzbv0R1Og4QPJJpLgtguQ50V1MIBk2BG3XEU9AULvIu01+PD76EtT2lzKjebheuzeX68MQiUqcg3U7QVE4a1aZO0EyqIsvf1ires2PxYuxeQb+xnRjjbJoUCRD7kmRdB+CailJLD9epiUcQXVDGNN1N8gs14dDK4HmrFc/8zMxQY3kk0hxrSDZKjvO6Y85ivl9EbAYl6cR1Rp/42AjyqKdItnknhSoNHH+cISAoFpdErseT9IS/zzGoRH00hvGF+7DuJL/E4ESFJqzdQQFySeR4loNLRhggpiAagomLqZzFIM8QVRr/I2DjUQrXVNFclrilxpBYWbX5no8e0s4abjtLydmrRfvw4GVuOZsIyhIPs2Wx3iJvzYin5fsCGryBFGt8TcONlKtNFUkV0mRdIqgVnDc4no8ciukswku8aa/jAZ58T4cWoltzgM3SXqCjVLcygqSOY6gNk8Q1Rp/42AjkUV7iuT8EdQRtEV+PD6GEFQpsc3jY/A+Yrk+HFyJac5DBFX3oUSK6+5DUF3Mh6AuT+pvHGzExCtfkdxnDtqToC3y45lbwieoqn6vBs/9CYM+HFyJac6DBNWSz6f+HPTKuxlmQ1AnGTaiWuNvfOtvJLJoVCRXfUTS/QlaxfLjmVsCCeq+81S/Bd9lL9OHgyuB5OQvSYxjc88mB30rEYIyjs09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwIQQuIzT2bHAhBC4jNPZscCEELiM09mxwcQ1AQ7EbA7e1re0e27YrRXYy/WuzhevVNsyH0ePKB29CseXhsYn5yAOOqffu2xIGEWo12lkGiknO7Tr44grr15AmCep84OnYPgo6q9s0k6P5Fx6k4L1IEPb1tJSisU7ZuxlTIe+c55lJr4c2LiZWrvbrFLL19+xQcRU2yWmOsM/bEtmZ384KYNQ+PTQgKcmZYALx364St2neelnA12Yq1sPrDG92d1gGSA1KVfHYGBP3pn6YE3axr4mbsCXl9tzJiLQwGbpMW8wciHCCoXYhtkrUa4wv0aLYq28pJj+3u7eLbJs4fjNBCUBIKtE7GV7iyat+RWuJfxPAI6tUEgmulnlDd2aQx+dWuL3a7/xvB69ON8eP0R1Al2A3cjJ2Ql/g9+r6D+hI/aeEDRlAgKBHDgQkzVuUpd3D3A/Oz1Ahqlb4YytKV7jCW8jw9gmJNILh+5kSctRMTMkCykvvnd9ElXgt2iULXE/JWRqFbGdUqJahytmZG0MrKia3GmFTVQlAoanhsOgf1DJat2NepfWdqCUJQqLgZvIGg+uFbB2YysyPdp9tI1WkEu8TN2BPydo6gY/sbDy2mbh9BUWNMqhp3BHWX+NBgGacS9Xjn7xCCouDayuDVRIPLNT7dpw8vX0WXeM07lKV6Qt5gDkoJejaxMLAXQbWH7Kk/B61QY+yJbeugM7vnoL0ICqEgCzActjuM9vXOAIJSwbW5dGz14+6YXON79Km6la/Cr5nMtcHKZj0hLzrmmjt7JOiLia08E8XoWd6Z0hN/oCeB2s7YJGs0xmoDVuXNAyqnFc69iweLaJMFGA677Gb7HhRqwopVaV/XI6hxeObyVWgPgmoPdflLEuPYY2Uz7fXtOPStZDSCTumKLAQ9Pht1Z8TFI55idoJOCSEoz2xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdsciAELSA292xyIAQtIDb3bHIgBC0gNvdscnAMQZ3FrFqblZZ5EbHnSzTioQfpWEUDb7lPdi64SRYz4XKdRGyyor4+tBoYHYcpjlrjPZSgo6n1oi5qbfIBNXVXYk2kA4I6i9mBlXkEJQcZQNCMYhQDphMy5BOUOA5TCEG7CGqXee89ghLHXvAMRu3x/bPv6RW/nhqZGgx/3/nKaJndQd42b74j8mQjzDWroKuLj9QLZ02sQ0a79iqm3py8Wn4E1Q0DAmzPUBkdh2EztCAu/h7gONydTdyCsZLc6KGhN70uIau2/bebzykx0xvTZccbRw+oxCq5Hq5XP/VTVIxsLGYNQTdrpz3eqxof3e2VTekVUYJ4umTbV3gQvbTbyZNBmKs6bP/o83N7DPPJ1l2xmD8UYTffJf73R2gjqG4YLSrxDZVdbm7zFZVwe1roHtn8yxhE9Rg1dqgkBz009KbXJXegU1apem+rz2E9xxtHB5X81wgBQbVYxx9BwWJWV6akxlY516SiRGEgvkLdnKdLtn2FB4G5rJWG1DU6Dltpgv1k666EJF2jGIs5aOV0pETsrN+gmnir5wZNX6iFzswmbsFWJXlt7CPh8u+6BPZqfxvVJMcbRw+oxJlIX/oEBYtZfVJZqXFlJLm6ss0V2aIdMUNdsneQkHVGmHtptWQ0TOuuPUnCh6BWgB0aKoMI2RMmK1/XUAudmU3cgpGSHFKB3vS6BPZqtpwFb/sEPdo4ekAltjnCERQsZg1btmtvBP3WTcsISnXJrq/cQXzWEWEuGUHhk6279iTJkgQFs93LO9s/ntjZXj/roH4i4ca2yM8mbsFISa6gJmymN70uIZes+G1C0KONowdUYlNt5qD+ViNQNZXZ51HYOehZrEb2dMmOee4gPusqI8xVRTTzAEdQ88nWXXuSZEmCKs21vkc3DXNGFMiWd9ZxmGz2JdxTENQ2dqgkBz006U3XJbeovfbf9gl6vHH0gEpccwR38ajHNVLjN6A9Vvd93/oOVSPjXbzTJb+7hieS4UGum7t4vOqAMBfu4i1BTZjgEg+79iTJkgRVl7mVnYGDANs3VHaOw7i5Rgk3aqHzs4lbMFaSm7kT9KbXJdYYuq6Dt9Xnmq6EMeV44+gBlWBz9P5LUqynnk9hnSRJobGnyybRdzN0bd9KjifodrQnYiUhBB07mwIJuiSEoDyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8mBELSA2NyzyYEQtIDY3LPJgRC0gNjcs8nBMQQNDCncStYWoCwU9gzejj6XZc+TKqZlbQNkkO/flGzI/YhGcpnZdOrGkwpvXEk+B1KVWP++YD1oTdYJdxK0u4yZCdpi4jsbQZVVihLLZYYZJZtO3XhS4c2KoDqLbdOsEUGdmPje+Aa/iZTHeAAiQbXa0/3K+uz67r9ZjsgJkhgTX5sdqmI9bW+N0ts3/WW+PSUf6jzAME7BC96Dem3vqXmqhRkXnMBXbTizuakFwGv7oY3W8yoBpf7trl+3dujGkwpvfgRV/65+8ieDEfTyzlvUHyuP8QA1SlBBewqq1ip0/81zRN7t/kgEQhJj4muzcyn5ugpblJLQ9pf56ob8PREwNh7HukATBS+sZ9dL2k+JEguN7eBaDLld3oHJpNLNNJvW98/ePjO/uWz+VYx+uvGkwntugv7nCC0j6H08BzUsM7KWCjVeqDx2u54RPWuFmlSskkhqsxyRE6OYMfGF7DAl31wUixoisUjGds6C5PhOwYsE3X6XSgXRGtQ0Gb5Ggt4/v3uthBvr2vzWJ5tO3XhS4e0ZN0+ORCXOIzq+xF9bQ2MkKGwAMarSpVoGOgmq6/hzX/1it2c5IncXA9dEyM5PCe2ZyY8xCeouvvb4VMGrOl4n8vb555SgsC90xLp2rzfqpH8Gai01b1F3BOa3Xt3apRtPKry5XeK12DAmqOrjQyOoEaPirkTPSjrdzA4C998sR+REMcbE10plURU7xwjq5qD+CArPP7CM+N5VdXFoBIWc8UDAq62689u8aEboLd4DJrv1sG48qfDmRlA9b7+PCKrdYekc9CJUHrtd6zqQoF5Yl1+7wbn/5jkidxcDJr42O5TYts5BRyYo3sXjHLSyCl51/VdNcW4n4K1z0Gubopq1Xl/Bh/TgWV1+qS74fQXYVZduPKnwZkdQPVNu/R7U3oOevjNiU1957A5Q1yhBdU2/go/eBu6/OY7IncVYE99PITtUxXr2zPSZV2MS1H0PGt7FN0wxk7pHn5/TQaq6CO7iH92Rm/4z+6G7pi644zIV9utW91+kG08qvNkRVN/NDvlL0mJOzkmSTJhdr9jtgIf8XA76jtR9qHriNrnfvuJ/SUpBCDojQf+Zu+BsyaVHCMoSS3YLL0rwyiYHQtACYnPPJgdC0AJic88mB0LQAmJzzyYHQtACYnPPJgdC0AJic88mB0LQAmJzzyYHQtACYnPPJgdC0AJic88mB0LQAmJzzyYHQtACYnPPJgdC0AJic88mB8cQtG2lFWw7uAgr8X6gZDbrH1ffHLikq7sYjI2HxsXRucvHEg1p9dd62edKr6PPCpeXzSH4jZDbJHaVcBZ6VdKEmZqgZj1ioLUfWl5fguKh5yMoLPIepdOyszmE0VNblKBkVa11JVa/fuNKr7zWysjQtdjqlH1LXXdItYTMrhd++3S4MitJUJOyPTTIjXWaNLMhauO+DVmhjmt5glI1Ma056J43dsm06hdjaGk7zm8pWFcNvYmrrLWPdWaxiXa18vWT1Y//+AGCeq7Ezevtut42WW/Xba7FoGPwLXXdIUFGsj07egT9YxFaCGoPbaQeRPc82FTYb8jfHSEgqLFbm4eg/yYGkQ86NbFTWXsCGJBd21daT3J5hx3nfwrazfamM0Me6RL/nyJgn6J8/fAI6okUKu3a+/qTs9AiF9+PLXXdIT018BSXeI+gxDQS9MeDTYV7x0ZbXjsHnfYZI6kRFLVwnkawckK9ypPtqUFnTTvO38m8YbXJzgx5hjkoytc7CEpdiXVNb5+9uXj7zAmKw/cjS92ajKCeGnhaguqjU6ve4abCvWO7AzK5xHtaOFRZV07qTEYfLZL+8uVN0Dy4E7xhDZKf2lvAGQiK8vX+I2i9+e6TZpJjnpDQ8n5sqetewSNHXG2zjKCY5nBT4QENyZSg/UbQh5evLknXhCMo2h9jD45Va6JdaytfbyEoKIU9V2L11n5lZqE6/cC1mExyLpylrj2kvouPpMyjFQMXo+2pPweFNP3MvjIE9WuOGwGEz+rJJeSd1p1sb1Kt9NQERfl6LDs+s0phz5X4uul+dQ+Prr3R+5GlrjukNkwnAuWH65Hv4iFlODTIjcHv18tsUoIawXDu4/QysqEE9VTW0AhEdg235FoRTzou2ukEHz2S04NDK0H5uvwliXFs7tnkoG8lQlDGsblnkwMhaAGxuWeTAyFoAbG5Z5MDIWgBsblnkwMhaAGxuWczB4SgjGNzz2YOCEEZx+aezRwQgjKOzT2bOSAEZRybezZzQAjKODb3bOaAEJRxbO7ZzAEhKOPY3LOZA0JQxrG5ZzMH4uV27RbGB9epoYJOrRUMjB9HQne3hNLmA2mCEXCwOUwz2pCghLPlpVl4iww9+WAuUgTVZlHX4BPigm+nXgU4IQ7Ljvu1qJammdXL2zP7SonyxnTUSxD0wi5s7AA1Aqabswmq99/Cel/Iwi3T1ku1t0RbkIsUQcH3GdeJq+BbbXQTGUK/Hzgo+VDKUrtc3khV7eJXom0Fr0pjTte8B6/qzcmrGUdQFYrIbUA++7UP3apdnT8YAXu2SeqfN1Rjex/paXsR1K4x93z4lJXMxa0VgM1CUOuaaM4WCO6UbiPEnx+rH/uxw5ok+9s5dTWk2lYDpWJRyndU/41+if/jEcIR9PKOZKvlCSc3RAntjICtejb0aSYuyUHs3e+KcHAEvSQ+fErzc+1EnmMR9N/GINlo32en1jfBjU7jeCPKZRHNQc9aCOr9CJxyVemmh63bJF5kxkJiBAW5L0lT6+ao1rl2RsBESxv5NDsxde/YaMtLRcfmIHo43a88feu0LQG+zy6YCQ6GzEdb+S6LTlVnL4Lq2Y0bQe1cZ06CXriHe7g03SMzUFALRsDWiDj0aaaq6f6xdXBty2uzQC9o20DUCXPalgDfZxqsCW4IWsQIegxB9RXVekjDq3p+goLvdjCCenpjYwRsjYhDn+ZANd0zttl/e3rrssCDgJssbJyDoOD7DMFs8Pd8DhoTFDW8+BvR9voEBUaqC7t9fAo91jjoQVBwC4dsyRwUVbTGCDgyP648je1RBNXTcrwfCu7ilc/tzREP3RneEuD7TO/irdt0SXfxoOEFx+IP8JkxsN0j6BaktuZ70K0T3s4+B72qUXusb8m//vKm9vTGdnR9SkyRH67tVxW44Zi7+PP14e9B1TRwrMcydmZjfZ9v7F3aUwi7L+R7ULZIkKQdI50iR8WeDLyymQNlElTdLYz0JFlelOCVzRwok6CFxOaezRwQgjKOzT2bOSAEZRybezZzQAjKODb3bOaAEJRxbO7ZzAEhKOPY3LOZA0JQxrG5ZzMHhKCMY3PPZg4IQRnH5p7NHBCCMo7NPZs5IARlHJt7NnNACMo4Nvds5kBf2XHbhtlUBN3dUl0kF+Tuj7eAG0QJp7oO8HBtm7XKs3Dpk02v45M197xXMqfcjgneX4KqFbv15jiGDiGoU12H8OjAgqBH7z432gjqzHKs6621nj29NUOEW4T+Yp6FsH0J6mfnLJetmu+oVFOUMOucTZOB6joyHdb72N9WrjGP8F9OZOOsq9rNjN9hYq53Y6E1L6x+9EcjgoaKXLSeJQ7CmqAtEokpsNv9yQgtBPWzQ8vlLLVFE+d3RiBKdO35fOdc2IzYODIddnLnKs9/ebf7dzGIaE4bUNvjP4RmxiQx7N33aQQ1suNWRW6NkiXUgGjH1hmG0MQIahzeToPs0HIZdLdTxLbiime3RHXdapnpterR/ss9ryVw/NDM2DebJSJDxmgTzYWKXLSeRQdh/er1DQuC4hzUyw4tly/zRtBOgjrPZy2D19q0VtNhr1WP9l9OtIRNxh4/MDMuhaChIle9MtcCYnQMI+gscuu+44afXW0v7lPOQf0R1Kha20dQ2qpH+y/3bQlz/NDMuBCCRopctJ7VGx5bgW+9aXlUzBTo2S1+dmi5POVdvPF8voUmAw12q+mw16rH+i93Z4MG1O1mxqUQlNrampHSWs/egtEx+CE3d/EjSdO60ZOgdZDdyt2fTvg9KL2LB9V1u+mwkzW/y/BfTmRD7+L14058M+NWguYbF08K+UsS49jcs5kDQlDGsblnMweEoIxjc89mDghBGcfmns0cEIIyjs09mzmwWjoBgaALQlABawhBBawhBBWwhhBUwBpCUAFrCEEFrCEEFbCGEFTAGkJQAWsIQQWsIQQVsIYQVMAaQlABawhBBawhBBWwhhBUwBpCUAFrCEEFrCEEFbCGIehv/cTCaQgE7dAEbX0qsEDAAEJQAWso1wT1BNi1etA/74dBC76KWKlnE6oRVD0eut7mPCxbIBgfK3V9VwTdq9FTPQJWIGAE83johqDm2ZbOJUkgYAE3gsrVXcARq3pvRtD9LM9KFgiGYVWdK48p5YagnukuLBXwwurk04adm9WZ/ppJ+ClgBvlbvIA1hKAC1hCCClhDCCpgDSGogDWEoALWEIIKWEMIKmANIaiANYSgAtb4/9vqBc0y9k2kAAAAAElFTkSuQmCC" /><!-- --></p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>grouptag_counts <span class="sc">%&gt;%</span></span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarise</span>(</span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a> <span class="at">oldest =</span> <span class="fu">min</span>(createdAt),</span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a> <span class="at">newest =</span> <span class="fu">max</span>(createdAt),</span>
<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a> <span class="at">count =</span> <span class="fu">max</span>(count)</span>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">%&gt;%</span></span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">arrange</span>(<span class="fu">desc</span>(count))</span></code></pre></div>
<div class="kable-table">
<table style="width:100%;">
<colgroup>
<col width="36%" />
<col width="27%" />
<col width="27%" />
<col width="8%" />
</colgroup>
<thead>
<tr class="header">
<th align="left">grouptag</th>
<th align="left">oldest</th>
<th align="left">newest</th>
<th align="right">count</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="left">edu</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-02-28 09:47:17</td>
<td align="right">431</td>
</tr>
<tr class="even">
<td align="left">Save Dnipro</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">354</td>
</tr>
<tr class="odd">
<td align="left">Luftdaten</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-01-27 15:22:54</td>
<td align="right">244</td>
</tr>
<tr class="even">
<td align="left">CS:iDrop</td>
<td align="left">2023-01-10 10:22:33</td>
<td align="left">2023-02-27 09:53:33</td>
<td align="right">140</td>
</tr>
<tr class="odd">
<td align="left">HU Explorers</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-12-14 10:11:34</td>
<td align="right">124</td>
</tr>
<tr class="even">
<td align="left">#stropdeaer</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">101</td>
</tr>
<tr class="odd">
<td align="left">321heiss</td>
<td align="left">2022-06-27 14:12:25</td>
<td align="left">2022-08-08 10:22:21</td>
<td align="right">91</td>
</tr>
<tr class="even">
<td align="left">GIZ Clean Air Day Project</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">76</td>
</tr>
<tr class="odd">
<td align="left">Captographies</td>
<td align="left">2021-05-21 15:24:45</td>
<td align="left">2023-01-31 12:11:49</td>
<td align="right">62</td>
</tr>
<tr class="even">
<td align="left">Futurium</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">39</td>
</tr>
<tr class="odd">
<td align="left">Bad_Hersfeld</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">37</td>
</tr>
<tr class="even">
<td align="left">TKS Bonn</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">36</td>
</tr>
<tr class="odd">
<td align="left">kerekdomb_</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">34</td>
</tr>
<tr class="even">
<td align="left">Mikroprojekt Mitmachklima</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-08-23 13:14:11</td>
<td align="right">34</td>
</tr>
<tr class="odd">
<td align="left">Bottrop-Feinstaub</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">33</td>
</tr>
<tr class="even">
<td align="left">Luchtwachters Delft</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">33</td>
</tr>
<tr class="odd">
<td align="left">Futurium 2021</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">32</td>
</tr>
<tr class="even">
<td align="left">Feinstaub</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-08-01 16:27:10</td>
<td align="right">29</td>
</tr>
<tr class="odd">
<td align="left">luftdaten.info</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">28</td>
</tr>
<tr class="even">
<td align="left">ifgi</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">26</td>
</tr>
<tr class="odd">
<td align="left">SUGUCS</td>
<td align="left">2022-11-30 15:25:32</td>
<td align="left">2023-01-23 13:17:54</td>
<td align="right">25</td>
</tr>
<tr class="even">
<td align="left">cleanairfrome</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-05-15 21:13:30</td>
<td align="right">24</td>
</tr>
<tr class="odd">
<td align="left">freshairbromley</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-01-31 10:18:57</td>
<td align="right">24</td>
</tr>
<tr class="even">
<td align="left">WAUW!denberg</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">23</td>
</tr>
<tr class="odd">
<td align="left">Riga</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">22</td>
</tr>
<tr class="even">
<td align="left">bad_hersfeld</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-06-14 09:34:02</td>
<td align="right">21</td>
</tr>
<tr class="odd">
<td align="left">KJR-M</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">21</td>
</tr>
<tr class="even">
<td align="left">Mikroklima</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-09-05 08:38:57</td>
<td align="right">21</td>
</tr>
<tr class="odd">
<td align="left">Smart City MS</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">20</td>
</tr>
<tr class="even">
<td align="left">SekSeeland</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">19</td>
</tr>
<tr class="odd">
<td align="left">Luftdaten.info</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">18</td>
</tr>
<tr class="even">
<td align="left">1</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-04-25 15:07:39</td>
<td align="right">17</td>
</tr>
<tr class="odd">
<td align="left">Apeldoorn</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">17</td>
</tr>
<tr class="even">
<td align="left">luftdaten</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">17</td>
</tr>
<tr class="odd">
<td align="left">BurgerMeetnet</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-05-10 21:22:35</td>
<td align="right">16</td>
</tr>
<tr class="even">
<td align="left">Haus C</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">16</td>
</tr>
<tr class="odd">
<td align="left">AGIN</td>
<td align="left">2022-11-28 17:33:12</td>
<td align="left">2022-11-28 17:42:18</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">APPI</td>
<td align="left">2023-01-26 13:38:22</td>
<td align="left">2023-01-26 13:40:59</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">BRGL</td>
<td align="left">2022-11-06 19:23:43</td>
<td align="left">2022-11-06 22:08:36</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">BRGW</td>
<td align="left">2022-11-02 10:28:52</td>
<td align="left">2022-11-02 13:32:12</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">Burgermeetnet</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">HTLJ</td>
<td align="left">2022-11-21 22:04:17</td>
<td align="left">2022-11-21 22:05:47</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">MakeLight</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">MSGB</td>
<td align="left">2022-11-14 09:08:57</td>
<td align="left">2022-11-14 10:19:24</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">MSHO</td>
<td align="left">2022-12-20 09:28:40</td>
<td align="left">2022-12-20 10:01:38</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">MSIN</td>
<td align="left">2022-11-21 17:02:39</td>
<td align="left">2022-11-21 23:06:22</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">MSKE</td>
<td align="left">2023-01-05 15:40:58</td>
<td align="left">2023-01-05 15:52:02</td>
<td align="right">15</td>
</tr>
<tr class="even">
<td align="left">PMSI</td>
<td align="left">2023-01-20 14:22:03</td>
<td align="left">2023-01-20 14:31:52</td>
<td align="right">15</td>
</tr>
<tr class="odd">
<td align="left">Haus B</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">14</td>
</tr>
<tr class="even">
<td align="left">UrbanGarden</td>
<td align="left">2023-02-02 19:27:40</td>
<td align="left">2023-02-18 14:50:19</td>
<td align="right">14</td>
</tr>
<tr class="odd">
<td align="left">Соседи по воздуху</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-01-27 09:50:43</td>
<td align="right">14</td>
</tr>
<tr class="even">
<td align="left">PIE</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">13</td>
</tr>
<tr class="odd">
<td align="left">RB-DSJ</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">13</td>
</tr>
<tr class="even">
<td align="left">co2mofetten</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-01-17 07:38:21</td>
<td align="right">12</td>
</tr>
<tr class="odd">
<td align="left">Sofia</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">12</td>
</tr>
<tr class="even">
<td align="left">Haus D</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">11</td>
</tr>
<tr class="odd">
<td align="left">home</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">11</td>
</tr>
<tr class="even">
<td align="left">Netlight</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">11</td>
</tr>
<tr class="odd">
<td align="left">#STROPDEAER</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-02-16 15:12:50</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">AirAberdeen</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">Balthasar-Neumann-Schule 1</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">Bestäuberprojekt</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">Che Aria Tira?</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">dwih-sp</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">esri-de</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">HBG Bonn</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">IntegrA</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">makerspace-partheland</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-02-20 18:34:50</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">Mikroklima H</td>
<td align="left">2022-05-07 17:29:00</td>
<td align="left">2022-05-07 17:47:42</td>
<td align="right">10</td>
</tr>
<tr class="even">
<td align="left">montorioveronese.it</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-12-29 07:45:57</td>
<td align="right">10</td>
</tr>
<tr class="odd">
<td align="left">ATSO</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">9</td>
</tr>
<tr class="even">
<td align="left">clevermint</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">9</td>
</tr>
<tr class="odd">
<td align="left">Fläming</td>
<td align="left">2022-08-15 19:16:48</td>
<td align="left">2022-12-13 06:29:22</td>
<td align="right">9</td>
</tr>
<tr class="even">
<td align="left">Mikroklima C-R</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">9</td>
</tr>
<tr class="odd">
<td align="left">Ostroda</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">9</td>
</tr>
<tr class="even">
<td align="left">RSS</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">9</td>
</tr>
<tr class="odd">
<td align="left">test</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-12-18 22:20:34</td>
<td align="right">9</td>
</tr>
<tr class="even">
<td align="left">2</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2023-01-07 15:44:29</td>
<td align="right">8</td>
</tr>
<tr class="odd">
<td align="left">Data4City</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="even">
<td align="left">DBDS</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="odd">
<td align="left">IKG</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="even">
<td align="left">IVKOWeek</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-07-05 09:42:31</td>
<td align="right">8</td>
</tr>
<tr class="odd">
<td align="left">Koerber-Stiftung</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="even">
<td align="left">M7</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-11-28 13:00:44</td>
<td align="right">8</td>
</tr>
<tr class="odd">
<td align="left">Natlab Ökologie</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="even">
<td align="left">PGKN</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="odd">
<td align="left">Raumanmeri</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
<tr class="even">
<td align="left">stw</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="left">2022-03-30 11:25:43</td>
<td align="right">8</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
<div id="plot-rate-of-growth-and-inactivity-per-week" class="section level1">
<h1>Plot rate of growth and inactivity per week</h1>
<p>First we group the boxes by <code>createdAt</code> into bins of one
week:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>bins <span class="ot">=</span> <span class="st">&#39;week&#39;</span></span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a>mvavg_bins <span class="ot">=</span> <span class="dv">6</span></span>
<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a>growth <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb7-5"><a href="#cb7-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">week =</span> <span class="fu">cut</span>(<span class="fu">as.Date</span>(createdAt), <span class="at">breaks =</span> bins)) <span class="sc">%&gt;%</span></span>
<span id="cb7-6"><a href="#cb7-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(week) <span class="sc">%&gt;%</span></span>
<span id="cb7-7"><a href="#cb7-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">count =</span> <span class="fu">length</span>(week)) <span class="sc">%&gt;%</span></span>
<span id="cb7-8"><a href="#cb7-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">event =</span> <span class="st">&#39;registered&#39;</span>)</span></code></pre></div>
<p>We can do the same for <code>updatedAt</code>, which informs us about
the last change to a box, including uploaded measurements. This method
of determining inactive boxes is fairly inaccurate and should be
considered an approximation, because we have no information about
intermediate inactive phases. Also deleted boxes would probably have a
big impact here.</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>inactive <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a> <span class="co"># remove boxes that were updated in the last two days,</span></span>
<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a> <span class="co"># b/c any box becomes inactive at some point by definition of updatedAt</span></span>
<span id="cb8-4"><a href="#cb8-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(updatedAt <span class="sc">&lt;</span> <span class="fu">now</span>() <span class="sc">-</span> <span class="fu">days</span>(<span class="dv">2</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb8-5"><a href="#cb8-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">week =</span> <span class="fu">cut</span>(<span class="fu">as.Date</span>(updatedAt), <span class="at">breaks =</span> bins)) <span class="sc">%&gt;%</span></span>
<span id="cb8-6"><a href="#cb8-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(week) <span class="sc">%&gt;%</span></span>
<span id="cb8-7"><a href="#cb8-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(<span class="at">count =</span> <span class="fu">length</span>(week)) <span class="sc">%&gt;%</span></span>
<span id="cb8-8"><a href="#cb8-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">event =</span> <span class="st">&#39;inactive&#39;</span>)</span></code></pre></div>
<p>Now we can combine both datasets for plotting:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>boxes_by_date <span class="ot">=</span> <span class="fu">bind_rows</span>(growth, inactive) <span class="sc">%&gt;%</span> <span class="fu">group_by</span>(event)</span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(boxes_by_date, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">as.Date</span>(week), <span class="at">colour =</span> event)) <span class="sc">+</span></span>
<span id="cb9-4"><a href="#cb9-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">xlab</span>(<span class="st">&#39;Time&#39;</span>) <span class="sc">+</span> <span class="fu">ylab</span>(<span class="fu">paste</span>(<span class="st">&#39;rate per &#39;</span>, bins)) <span class="sc">+</span></span>
<span id="cb9-5"><a href="#cb9-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_date</span>(<span class="at">date_breaks=</span><span class="st">&quot;years&quot;</span>, <span class="at">date_labels=</span><span class="st">&quot;%Y&quot;</span>) <span class="sc">+</span></span>
<span id="cb9-6"><a href="#cb9-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_colour_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="at">registered =</span> <span class="st">&#39;lightgreen&#39;</span>, <span class="at">inactive =</span> <span class="st">&#39;grey&#39;</span>)) <span class="sc">+</span></span>
<span id="cb9-7"><a href="#cb9-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="fu">aes</span>(<span class="at">y =</span> count), <span class="at">size =</span> <span class="fl">0.5</span>) <span class="sc">+</span></span>
<span id="cb9-8"><a href="#cb9-8" aria-hidden="true" tabindex="-1"></a> <span class="co"># moving average, make first and last value NA (to ensure identical length of vectors)</span></span>
<span id="cb9-9"><a href="#cb9-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_line</span>(<span class="fu">aes</span>(<span class="at">y =</span> <span class="fu">rollmean</span>(count, mvavg_bins, <span class="at">fill =</span> <span class="fu">list</span>(<span class="cn">NA</span>, <span class="cn">NULL</span>, <span class="cn">NA</span>))))</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<p>We see a sudden rise in early 2017, which lines up with the fast
growing grouptag <code>Luftdaten</code>. This was enabled by an
integration of openSenseMap.org into the firmware of the air quality
monitoring project <a href="https://sensor.community/de/">luftdaten.info</a>. The dips in mid
2017 and early 2018 could possibly be explained by production/delivery
issues of the senseBox hardware, but I have no data on the exact time
frames to verify.</p>
</div>
<div id="plot-duration-of-boxes-being-active" class="section level1 tabset">
<h1 class="tabset">Plot duration of boxes being active</h1>
<p>While we are looking at <code>createdAt</code> and
<code>updatedAt</code>, we can also extract the duration of activity of
each box, and look at metrics by exposure and grouptag once more:</p>
<div id="by-exposure" class="section level2">
<h2>…by exposure</h2>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>duration <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(exposure) <span class="sc">%&gt;%</span></span>
<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(updatedAt)) <span class="sc">%&gt;%</span></span>
<span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">duration =</span> <span class="fu">difftime</span>(updatedAt, createdAt, <span class="at">units=</span><span class="st">&#39;days&#39;</span>))</span>
<span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(duration, <span class="fu">aes</span>(<span class="at">x =</span> exposure, <span class="at">y =</span> duration)) <span class="sc">+</span></span>
<span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>() <span class="sc">+</span></span>
<span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span> <span class="fu">ylab</span>(<span class="st">&#39;Duration active in Days&#39;</span>)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
<p>The time of activity averages at only 158 days, though there are
boxes with 2394 days of activity, spanning a large chunk of
openSenseMap’s existence.</p>
</div>
<div id="by-grouptag" class="section level2">
<h2>…by grouptag</h2>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>duration <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(grouptag) <span class="sc">%&gt;%</span></span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a> <span class="co"># only include grouptags with 8 or more members</span></span>
<span id="cb11-4"><a href="#cb11-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="fu">length</span>(grouptag) <span class="sc">&gt;=</span> <span class="dv">8</span> <span class="sc">&amp;</span> <span class="sc">!</span><span class="fu">is.na</span>(grouptag) <span class="sc">&amp;</span> <span class="sc">!</span><span class="fu">is.na</span>(updatedAt)) <span class="sc">%&gt;%</span></span>
<span id="cb11-5"><a href="#cb11-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">duration =</span> <span class="fu">difftime</span>(updatedAt, createdAt, <span class="at">units=</span><span class="st">&#39;days&#39;</span>))</span>
<span id="cb11-6"><a href="#cb11-6" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb11-7"><a href="#cb11-7" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(duration, <span class="fu">aes</span>(<span class="at">x =</span> grouptag, <span class="at">y =</span> duration)) <span class="sc">+</span></span>
<span id="cb11-8"><a href="#cb11-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>() <span class="sc">+</span></span>
<span id="cb11-9"><a href="#cb11-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span> <span class="fu">ylab</span>(<span class="st">&#39;Duration active in Days&#39;</span>)</span></code></pre></div>
<p><img 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" /><!-- --></p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a>duration <span class="sc">%&gt;%</span></span>
<span id="cb12-2"><a href="#cb12-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">summarize</span>(</span>
<span id="cb12-3"><a href="#cb12-3" aria-hidden="true" tabindex="-1"></a> <span class="at">duration_avg =</span> <span class="fu">round</span>(<span class="fu">mean</span>(duration)),</span>
<span id="cb12-4"><a href="#cb12-4" aria-hidden="true" tabindex="-1"></a> <span class="at">duration_min =</span> <span class="fu">round</span>(<span class="fu">min</span>(duration)),</span>
<span id="cb12-5"><a href="#cb12-5" aria-hidden="true" tabindex="-1"></a> <span class="at">duration_max =</span> <span class="fu">round</span>(<span class="fu">max</span>(duration)),</span>
<span id="cb12-6"><a href="#cb12-6" aria-hidden="true" tabindex="-1"></a> <span class="at">oldest_box =</span> <span class="fu">round</span>(<span class="fu">max</span>(<span class="fu">difftime</span>(<span class="fu">now</span>(), createdAt, <span class="at">units=</span><span class="st">&#39;days&#39;</span>)))</span>
<span id="cb12-7"><a href="#cb12-7" aria-hidden="true" tabindex="-1"></a> ) <span class="sc">%&gt;%</span></span>
<span id="cb12-8"><a href="#cb12-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">arrange</span>(<span class="fu">desc</span>(duration_avg))</span></code></pre></div>
<div class="kable-table">
<table style="width:100%;">
<colgroup>
<col width="35%" />
<col width="16%" />
<col width="16%" />
<col width="16%" />
<col width="14%" />
</colgroup>
<thead>
<tr class="header">
<th align="left">grouptag</th>
<th align="left">duration_avg</th>
<th align="left">duration_min</th>
<th align="left">duration_max</th>
<th align="left">oldest_box</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="left">Ostroda</td>
<td align="left">335 days</td>
<td align="left">335 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Mikroklima C-R</td>
<td align="left">332 days</td>
<td align="left">321 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Apeldoorn</td>
<td align="left">331 days</td>
<td align="left">263 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">freshairbromley</td>
<td align="left">304 days</td>
<td align="left">28 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Mikroklima</td>
<td align="left">283 days</td>
<td align="left">42 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Mikroklima H</td>
<td align="left">283 days</td>
<td align="left">229 days</td>
<td align="left">297 days</td>
<td align="left">305 days</td>
</tr>
<tr class="odd">
<td align="left">Smart City MS</td>
<td align="left">272 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Feinstaub</td>
<td align="left">223 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">makerspace-partheland</td>
<td align="left">217 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">co2mofetten</td>
<td align="left">213 days</td>
<td align="left">0 days</td>
<td align="left">334 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Luftdaten</td>
<td align="left">211 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">luftdaten.info</td>
<td align="left">200 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Burgermeetnet</td>
<td align="left">190 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">esri-de</td>
<td align="left">190 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">#stropdeaer</td>
<td align="left">187 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Sofia</td>
<td align="left">172 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">WAUW!denberg</td>
<td align="left">168 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">KJR-M</td>
<td align="left">167 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">IKG</td>
<td align="left">163 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">AirAberdeen</td>
<td align="left">155 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">M7</td>
<td align="left">155 days</td>
<td align="left">92 days</td>
<td align="left">243 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">1</td>
<td align="left">148 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">BurgerMeetnet</td>
<td align="left">141 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Luftdaten.info</td>
<td align="left">139 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Bottrop-Feinstaub</td>
<td align="left">133 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">cleanairfrome</td>
<td align="left">130 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">montorioveronese.it</td>
<td align="left">130 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">stw</td>
<td align="left">130 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">RB-DSJ</td>
<td align="left">122 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Mikroprojekt Mitmachklima</td>
<td align="left">118 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">BRGL</td>
<td align="left">113 days</td>
<td align="left">109 days</td>
<td align="left">114 days</td>
<td align="left">122 days</td>
</tr>
<tr class="even">
<td align="left">Luchtwachters Delft</td>
<td align="left">111 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Fläming</td>
<td align="left">110 days</td>
<td align="left">23 days</td>
<td align="left">180 days</td>
<td align="left">205 days</td>
</tr>
<tr class="even">
<td align="left">BRGW</td>
<td align="left">109 days</td>
<td align="left">98 days</td>
<td align="left">118 days</td>
<td align="left">126 days</td>
</tr>
<tr class="odd">
<td align="left">PIE</td>
<td align="left">103 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Riga</td>
<td align="left">103 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">kerekdomb_</td>
<td align="left">100 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">luftdaten</td>
<td align="left">100 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">home</td>
<td align="left">95 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Bad_Hersfeld</td>
<td align="left">94 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">MSGB</td>
<td align="left">94 days</td>
<td align="left">50 days</td>
<td align="left">106 days</td>
<td align="left">114 days</td>
</tr>
<tr class="even">
<td align="left">dwih-sp</td>
<td align="left">92 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">AGIN</td>
<td align="left">91 days</td>
<td align="left">87 days</td>
<td align="left">92 days</td>
<td align="left">100 days</td>
</tr>
<tr class="even">
<td align="left">HTLJ</td>
<td align="left">91 days</td>
<td align="left">58 days</td>
<td align="left">99 days</td>
<td align="left">107 days</td>
</tr>
<tr class="odd">
<td align="left">Соседи по воздуху</td>
<td align="left">87 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">bad_hersfeld</td>
<td align="left">84 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Captographies</td>
<td align="left">82 days</td>
<td align="left">0 days</td>
<td align="left">648 days</td>
<td align="left">656 days</td>
</tr>
<tr class="even">
<td align="left">Save Dnipro</td>
<td align="left">75 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">PGKN</td>
<td align="left">68 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">MSHO</td>
<td align="left">61 days</td>
<td align="left">36 days</td>
<td align="left">70 days</td>
<td align="left">78 days</td>
</tr>
<tr class="odd">
<td align="left">Netlight</td>
<td align="left">61 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">#STROPDEAER</td>
<td align="left">55 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Futurium</td>
<td align="left">54 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">test</td>
<td align="left">54 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">ifgi</td>
<td align="left">52 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">MSIN</td>
<td align="left">52 days</td>
<td align="left">0 days</td>
<td align="left">79 days</td>
<td align="left">107 days</td>
</tr>
<tr class="odd">
<td align="left">2</td>
<td align="left">50 days</td>
<td align="left">0 days</td>
<td align="left">331 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">ATSO</td>
<td align="left">48 days</td>
<td align="left">0 days</td>
<td align="left">279 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">MakeLight</td>
<td align="left">47 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Haus B</td>
<td align="left">44 days</td>
<td align="left">0 days</td>
<td align="left">239 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Futurium 2021</td>
<td align="left">43 days</td>
<td align="left">0 days</td>
<td align="left">329 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">DBDS</td>
<td align="left">42 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">IVKOWeek</td>
<td align="left">42 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">PMSI</td>
<td align="left">38 days</td>
<td align="left">38 days</td>
<td align="left">38 days</td>
<td align="left">47 days</td>
</tr>
<tr class="odd">
<td align="left">edu</td>
<td align="left">37 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">GIZ Clean Air Day Project</td>
<td align="left">37 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">TKS Bonn</td>
<td align="left">32 days</td>
<td align="left">0 days</td>
<td align="left">335 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">HU Explorers</td>
<td align="left">28 days</td>
<td align="left">0 days</td>
<td align="left">319 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">321heiss</td>
<td align="left">24 days</td>
<td align="left">0 days</td>
<td align="left">43 days</td>
<td align="left">254 days</td>
</tr>
<tr class="even">
<td align="left">SUGUCS</td>
<td align="left">9 days</td>
<td align="left">0 days</td>
<td align="left">53 days</td>
<td align="left">98 days</td>
</tr>
<tr class="odd">
<td align="left">APPI</td>
<td align="left">3 days</td>
<td align="left">0 days</td>
<td align="left">7 days</td>
<td align="left">41 days</td>
</tr>
<tr class="even">
<td align="left">MSKE</td>
<td align="left">3 days</td>
<td align="left">0 days</td>
<td align="left">7 days</td>
<td align="left">62 days</td>
</tr>
<tr class="odd">
<td align="left">RSS</td>
<td align="left">3 days</td>
<td align="left">0 days</td>
<td align="left">28 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">CS:iDrop</td>
<td align="left">2 days</td>
<td align="left">0 days</td>
<td align="left">36 days</td>
<td align="left">57 days</td>
</tr>
<tr class="odd">
<td align="left">UrbanGarden</td>
<td align="left">2 days</td>
<td align="left">0 days</td>
<td align="left">16 days</td>
<td align="left">34 days</td>
</tr>
<tr class="even">
<td align="left">Balthasar-Neumann-Schule 1</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Bestäuberprojekt</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Che Aria Tira?</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">clevermint</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Data4City</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Haus C</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Haus D</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">HBG Bonn</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">IntegrA</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Koerber-Stiftung</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">Natlab Ökologie</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="odd">
<td align="left">Raumanmeri</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
<tr class="even">
<td align="left">SekSeeland</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">0 days</td>
<td align="left">343 days</td>
</tr>
</tbody>
</table>
</div>
<p>The time of activity averages at only 90 days, though there are boxes
with 648 days of activity, spanning a large chunk of openSenseMap’s
existence.</p>
</div>
<div id="by-year-of-registration" class="section level2">
<h2>…by year of registration</h2>
<p>This is less useful, as older boxes are active for a longer time by
definition. If you have an idea how to compensate for that, please send
a <a href="https://github.com/sensebox/opensensmapr/pulls">Pull
Request</a>!</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="co"># </span><span class="al">NOTE</span><span class="co">: boxes older than 2016 missing due to missing updatedAt in database</span></span>
<span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a>duration <span class="ot">=</span> boxes <span class="sc">%&gt;%</span></span>
<span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">year =</span> <span class="fu">cut</span>(<span class="fu">as.Date</span>(createdAt), <span class="at">breaks =</span> <span class="st">&#39;year&#39;</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb13-4"><a href="#cb13-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">group_by</span>(year) <span class="sc">%&gt;%</span></span>
<span id="cb13-5"><a href="#cb13-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">filter</span>(<span class="sc">!</span><span class="fu">is.na</span>(updatedAt)) <span class="sc">%&gt;%</span></span>
<span id="cb13-6"><a href="#cb13-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">duration =</span> <span class="fu">difftime</span>(updatedAt, createdAt, <span class="at">units=</span><span class="st">&#39;days&#39;</span>))</span>
<span id="cb13-7"><a href="#cb13-7" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb13-8"><a href="#cb13-8" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(duration, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">substr</span>(<span class="fu">as.character</span>(year), <span class="dv">0</span>, <span class="dv">4</span>), <span class="at">y =</span> duration)) <span class="sc">+</span></span>
<span id="cb13-9"><a href="#cb13-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_boxplot</span>() <span class="sc">+</span></span>
<span id="cb13-10"><a href="#cb13-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">coord_flip</span>() <span class="sc">+</span> <span class="fu">ylab</span>(<span class="st">&#39;Duration active in Days&#39;</span>) <span class="sc">+</span> <span class="fu">xlab</span>(<span class="st">&#39;Year of Registration&#39;</span>)</span></code></pre></div>
<p><img src="data:image/png;base64,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" /><!-- --></p>
</div>
</div>
<div id="more-visualisations" class="section level1">
<h1>More Visualisations</h1>
<p>Other visualisations come to mind, and are left as an exercise to the
reader. If you implemented some, feel free to add them to this vignette
via a <a href="https://github.com/sensebox/opensensmapr/pulls">Pull
Request</a>.</p>
<ul>
<li>growth by phenomenon</li>
<li>growth by location -&gt; (interactive) map</li>
<li>set inactive rate in relation to total box count</li>
<li>filter timespans with big dips in growth rate, and extrapolate the
amount of senseBoxes that could be on the platform today, assuming there
were no production issues ;)</li>
</ul>
</div>
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