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jrtechs-NodeJSBlog
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<head>  <meta charset="utf-8">  <title>R Presentation</title>      <meta name="apple-mobile-web-app-capable" content="yes" />  <meta name="apple-mobile-web-app-status-bar-style" content="black-translucent" />
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<section data-state="section" data-transition="linear" data-transition-speed="default"><h1>R Presentation</h1><p>Jeffery Russell<br/>3-29-19</p>
<div class="mediaInline slideContent" ><h3>Signin: <a href="">bit.ly/ritlug-mar-29</a></h3>
<p><img src="data:image/png;base64,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</section><section data-transition="linear" data-transition-speed="default"><h3>History</h3><div class="mediaInline slideContent" ><ul><li>Back in the day (1976) Bell Laboratories created the S statisticsl programming language</li><li>People were sad because it was exclusively licensed by AT&amp;T</li><li>During the 90&#39;s a group of people developed a S replacement called R and it was liscensed under GNU</li></ul>
<p><img src="data:image/png;base64,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
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Why use R</h3><div class="slideContent" ><ul><li>Statistics and data analysis</li><li>Machine learning</li><li>Fast prototyping</li><li>Creating graphs</li><li>Writing research papers and reports</li><li>Creating presentations (like this one)</li></ul>
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Embedding Code Output in a Document</h3><div class="slideContent" ><pre><code class="r">summary(cars)</code></pre>
<pre><code>     speed           dist        Min.   : 4.0   Min.   :  2.00   1st Qu.:12.0   1st Qu.: 26.00   Median :15.0   Median : 36.00   Mean   :15.4   Mean   : 42.98   3rd Qu.:19.0   3rd Qu.: 56.00   Max.   :25.0   Max.   :120.00  </code></pre>
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Embedding Graphs in a Document</h3><div class="slideContent" ><pre><code class="r">plot(mtcars$wt, mtcars$mpg, main=&quot;Weight vs MPG&quot;, xlab = &quot;weight&quot;, ylab=&quot;MPG&quot;)</code></pre>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfgAAAH4CAMAAACR9g9NAAADAFBMVEUAAAABAQECAgIDAwMEBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUWFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJycoKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6Ojo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tMTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1eXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29wcHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGCgoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OUlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWmpqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4uLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnKysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////isF19AAAACXBIWXMAAAsSAAALEgHS3X78AAAXlklEQVR4nO3dC1xUZf7H8cdLf1M0tswMzbZW2y626apbyB0RTU0xTSld85aauVpZamZlul0sbd1MM+xiVFre0Np1VdRISU1dc/OCiKGmZV5AIhBkgPn9zxlCcBzkHM45c56Z3/f9enUYzxme89CHuTIzRxCwJOyeANgD4ZlCeKYQnimEZwrhmUJ4phCeKYRnCuGZQnimEJ4phGcK4ZlCeKYQnimEZwrhmUJ4phCeKYRnCuGZQnim/DN8TzGO6H0RUEIl9cV/ytcWi0o/bZ6op2GgHCHEWqLdype91FRZihaP/aKsL5rWsWGL+3eZP3Ov8c/wc0QY0Rgh9lGaqJtXvraK8G3EzioHUsO/SLTgt/At29wixCCi7LZCXFdL1Em26gewnn+GP6Be2IN/JxbSIhFxYa2zsLDiLJrD17uX6JErarnCpxAtFvVK6DFxxwHKfkq0cFozfy/wz/DOG8SB4vrDG4yhCWI6UUaPa24YllPWOqv/1Xcnt+yr/mPNnxr1+0XpLsQy9ZsGiFeJnhBP0Zbwhtf23O8aSAkfcrWT7rq7Tnn4U0JkZ9UWO5SNxaMHn7LxhzTGP8PTUPHJXrEg9G6KFVvpbOO6vULEPU41vDNE3NihobhHCV/ryrtqi8m05kbx0jH1ez4X4UR3iu1nrqrVO0I0d107KOHHi4P5tcddCL9MXOVMFc1s/enM4KfhF4vxiWLX4/9XdG0jB70mxpDzHrFODf+VuDnPOdYVXvyLZonoiqv684F1zv4sfu/cKG45SZMGHlHXKeGXisTNYnFZ+D+2v6OWcpWQKNop2zq2b99+t40/ozF+Gv60iFKqfyw+F72IBguXmWr4N9X7+9+6wl9RSpuUExW38UPEko/FBDodKGoFTzvpWqWEP3TF6Fkis075vfqgxwtoo7he2VZP+VeqfT+iQX4antpeFdqB0sV9Yg7RMPHop4rdavjXxJNEe1zhlRv81IvCrxVDBquns6bcKkRghrpKCX/87nbxTZwXrupVyu38JvVrBMJLZ4KoPYpKG9UWaUQzxRNEGxdmqK1XidsKabJb+G/KvsfRuGnzm5z0+ZillB6s/saUhR9Xp9l9dFF4Gi5u3uU8Pw2XePkkC7GAKEoEKQ+4sq+uO2RA7WtOqa2L/iBuCREXhe8oHjpY9k2jhJhEtE7U7/9gQNllWg2/WIiX3MKfbq08jq8vQhFeOgVXil1ET6vPthDtiw28Ji6trHVmbKM73rko/KdNaieVfVOKEP9VvizqcFWDNomuNWr4w0KsdwtPBZPbNeww94fWvvvcnb+Gr8rZ3elE34juds/DdtzCp9ep/cq828QHds/DdtzC09qwwIC27/ruU61mYRceyiA8UwjPFMIzhfBMITxTCM8UwjOF8EwhPFMIzxTCM4XwTCE8UwjPFMIzhfBMITxTCM8UwjNlIPyZpSCx5Q6rwi8ZkADyCv3esvDzav69YLnhCM8TwjOF8EwhPFMIzxTCM4XwTCE8U7KEd+zadfnnEMFckoTPCHtifFhazXcGekkSvnsm0dEuNd8Z6CVH+OLO6rJbQc33BjrJEZ4i1UVUac33BjpJEn7yq6Wls56q+c5AL0nCF/+jU/RM3K33IknCg7chPFMIzxTCM4XwTCE8UwjPFMIzhfBMITxTCM8UwjOF8EwhPFMIz5Qvhc/dsKPE7DHZ8qHw68KmjY88afKgbPlO+OLgfKIdD5s7KF++Ez5ttLqMMndQvnwn/Jk+yqIoxtxB+fKd8PRQYknu0I9NHpQtHwpfML1z9+Umj8mXD4UHMyE8UwjPFMIzhfBMITxTCM8UwjOF8EwhPFMIzxTCM4XwTCE8UwjPFMIzhfBMITxTCM8UwjOF8EwhPFPeC1/q4RTYxlvhPwzp1Gmz69THoZ2iv6r5sGAOL4X/coCDzkb9pJza9GAR5UQfr/m4YAozwpfmerryvij82D3KYmGisnjyW2Xx0Qda5wcWMRy+8PlWdUWdli+cd99wUfjH1CNMffS+shin/gosWqBvlmA6w+EHxaVmO7K3xg9x33BR+DUjSik/5qhyKnlYCZ2LPax3nmAyw+Eblx06qriF+4aL79zN6RgXusZ1al5wXOhq7RMEaxgOf9dK15eUtu4b3B/O/eLhFNjGcPjt19/Zf3h826Ad7hvwBI7UjN+rdyQnzEhIrnQEqW9muMSNNjg1sJJJj+MrHzns+HqXPr1rPCmwnuHwJ0eGTf6pTe2Ome4bnoiv+azAcobDd++xZFBQwtmXu7lvQHipGQ4fmEV7GxRRSRP3DQgvNcPhb8ig4hVEp4LcNyC81AyHn19fPQT4h62nuG9AeKkZv1d/QP3Ty/wkp/t6hJeadX+WRXipITxTCM8UwjOF8EwhPFMIzxTCM4XwTCE8UwjPFMIzhfBMITxTCM8UwjOF8EwhPFMIzxTCM4XwTCE8UwjPFMIzhfBMITxTCM8UwjOF8ExJF9655JGn9tV8r6CRdOGfmJLxTczmmu8WtJEtfLb6WTrZ3Wu+W9BGtvDfPqkuo2q+W9BGtvD54aVEhx6o+W5BG9nC0zv3L0/oeKjmuwVtpAtP++cm4lOOrSdfePAKhGcK4ZlCeKYQnimEZwrhmUJ4phCeKYRnCuGZQnimfCP8pvET/mveaEA+En7+X3dtj1tu2nBAvhHe2bGEqDDCrOFA5Qvhc1zHrOxUatZ4QL4RnjoWKvWjTRsOyEfCJ3VNWhr1lWnDAflIeDr0z7nHzRsNyFfCg+kQnimEZwrhmTInfFbepesQXmqGw/cooIPtatXtcsJ9A8JLzXB4kUfREwvOT+3jvgHhpWZG+EAHUUkT9w0ILzXj4b93/vkQ0b4g9w0ILzXD4cObBwR2oY2NZ7pvQHipmXCvvjBtG329oeLfx9a79OltbGZgKePhnWed6jLnwortM1zC8HkmMjMcfv/ttW5eoVzsLzknruql
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Syntax</h3><div class="slideContent" ><ul><li>Syntax of R is C esk with its use of curly braces</li><li>Variables are similar to python since it infers your data type used</li><li>Type system is rather wierd, the base unit for everything is a vector&ndash; even integers</li></ul>
<pre><code class="r">if(TRUE){  print(&quot;Hello World&quot;)}</code></pre>
<pre><code>[1] &quot;Hello World&quot;</code></pre>
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Syntax cont</h3><div class="mediaOnly slideContent" ><p><img src="data:image/jpeg;base64,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
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>ML Example pt: 1</h3><div class="slideContent" ><p><img src="data:image/png;base64,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
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>ML Example pt: 2</h3><div class="slideContent" ><p><img src="data:image/png;base64,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
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Super Cool ML Example pt: 3</h3><div class="slideContent" ><pre><code class="r">sc &lt;- spark_connect(master = &quot;local&quot;)
iris_tbl &lt;- sdf_copy_to(sc, iris, name = &quot;iris_tbl&quot;, overwrite = TRUE)
partitions &lt;- iris_tbl %&gt;%  sdf_partition(training = 0.7, test = 0.3, seed = 1111)
iris_training &lt;- partitions$trainingiris_test &lt;- partitions$test
dt_model &lt;- iris_training %&gt;%  ml_decision_tree(Species ~ .)
pred &lt;- ml_predict(dt_model, iris_test)
ml_multiclass_classification_evaluator(pred)</code></pre>
<pre><code>[1] 0.9451737</code></pre>
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Resources</h3><div class="slideContent" ><ul><li><a href="https://jrtechs.net/data-science/r-programming-language">R Language Overview</a></li><li><a href="https://www.rstudio.com/">R Studio</a></li><li><a href="https://r4ds.had.co.nz/">R 4 Data Science</a></li></ul>
</div>
</section><section data-transition="linear" data-transition-speed="default"><h3>Demo&#x2F;Questions?</h3><div class="mediaOnly slideContent" ><p><img src="data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAYEBQYFBAYGBQYHBwYIChAKCgkJChQODwwQFxQYGBcUFhYaHSUfGhsjHBYWICwgIyYnKSopGR8tMC0oMCUoKSj/2wBDAQcHBwoIChMKChMoGhYaKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCj/wgARCAEcAbgDASIAAhEBAxEB/8QAHAABAAEFAQEAAAAAAAAAAAAAAAYBAgMEBQcI/8QAGgEBAAIDAQAAAAAAAAAAAAAAAAIEAQMFBv/aAAwDAQACEAMQAAAB9UAAAAAAAAAAAAMZka1pttOptrLwAAAAAAAAAAAAAAAAAAAAAAAapfr4Rnpo4jpW6lxl6PIuO0AAAAAAAAAAAAAAAAAAAAAADBGezGme21mM26WehtXYaFa4secS+/W2WAAAAAAAAAAAAAAAAAAAAAANSAek+bYl2aahLPo5sbO3k4HUYrTrxvMfRc0RkKO6AAAAAAAAAAAAAAAAAAAAABF5Ros+W9fl4o7OxboXM59G/SO/J/Ne1mPf6vN3MxktcWVEAAAAAAAAAAAAAAAAAAAAACCxj17n4l53IJtVjz3iTKPpaWTbM6vQt3iZ5NHezrAAAAAAAAAAAAAAAAAAAAAAAAjXD7/FxPGymabFmVjq92KyrMQYAAAAAAAAAAAAAAAAAAAAAAAj/G7HKxO2t9WaZFxZLInIkd8ZiAAAAAAAAAAAAAAAAAAAAAABFtLNpYns3a2wzkrSpikMalLG8MwAAAAAAAAAMdzNxGcSkzzTNrueitHd2UTzWL6Or7lWJyfdzcqD3RsTbDHPK4bvdNn579dzGTuZ59LV6o8o9EZ6ZTZTxYvIdat2fcccPke/mRzhdzk5jyZHFu0SS2/Gxp9biQTVf91yeZ+kTq5HnfLju9YQGcS0Za8fyzG32qvhMthv9JW138yqNRbXc9OeXzRjuDZUOMhY8azS2G0fUzSI6g7nIx7eJdf17z2a3PO+TcrHgp+j7PYim3mGlfvWs7PHkUfzr35t51XMZFGtzDiVkrh0lzrvyxe1OecO/Q2VM/pHlno06eny9/mb+byu1Fpbrtd7FXHsq8uEd2lXtyfdllbHJ+eZBMfNa3azWYd7V0LbaaOYSTgY87Hufn068ns8Tn57K1PQa23i6ctfssak0Ju+X83XOf6/echLVk70d6udXNXb8bEznkE693zOh5/MoBo6i009KvSpoI9Gzms4yW0riVldy2enr+p+W+r2eH5Bw93Sr9eQ4J5Dp1aSeB6sd8z14ndLT15JCO7LRJ6a1bHLiWxs+gaOl1cnO2N3M8b484hFX0FMt1Ndvp7fB2MSzaHWn06/F5fXgctWayy7T0c/U4u9nX7NZ5p37XC89FT0WClyWimXFuQs5cFuqzdSlZaK7Wt2Mw3tvm3y0R2ncwQucpv7ma/Ey2ZoW+pi5ducbWPCRu7vO6MtEq85lGjKHDdSTxnA6SCP5wmUMmEtG9qYIvtpdDTxVq97LsadMT7mnodqVfgu3czwq9q4423k5+JyOMzGJbKi21rs1Zt5nQ2dzEztMJnj2KS0ZstLddzBQnVsuxdSWvc0raaegCQoCiNttcU69ymxmFd2RRLMdzTNXQDGV1rK7S28M6mH0mET61wYHzupy6/WrtamTE5FHPX/ADzbS5Kit3KqVZDDY6HHrLT6Dbxppd8x43STRyt28ildV6qlUio1Gbc38n0Xby7Frg6vnMw8y09G7PmwVu4Ed7ophu5nnd2psw31ELWecxT1G3wIvx5n5RLRVVS9QU3mLcnrEetcDzlRV9C29TczqluSTcrp+Gi8R9G4dfsRUVu3stbYZCFpfi7mylw78d0dtxSNm71zyL0SxxdKBTOFl6ldHVrLInfOp6K7K553xRRU7/r2/wAPo3POQyLTSJ1e/qVv76Mly9y6zx+LCs3D0dSl1aV+wMSM6lcHlN/ysViPd4Fbr56698Lkk7so49niZfL7cujphp6qSRv0bbzZFXSyXvLbN2tcxEIF7d4pW7mPPgaOpsVpWFtW2uYad9+DZS7Ml4Xoe7nRzp9Gu2jEo76dTEvKLJhDqnfrWjXc6DQbKfX35vS557kb2zSWmCxzscSn6HHaM+vat3Hs8aG21pQ9SO1LXv8ATkFt7y+hsZktMRiu5ya3Zz9mPsS9i8qnEFzGtCr3V+Wf7aPnE17VLfAps4Lp19q7Uqjt+Yeh+S6r+7TRar814XdkE63mjPgqegUrcxvTfFuX/KUvpSejLdq4jgQ6Txar2tphzaOoVY2exW329LxeLDn10vPOP6DEqvY4t016uyvr4etG5aY1ZTX0dXLN4LJpap1bbZY4t9mPCzA+Zv8APq96qluJT2JSGKZhstHFrtegS2LSe55+62tJ17bMlmGLHl12bfMJ759p6Vw09GXSiDS+zxI7H+pFNHT7FePkjY9a3uN3bnnsVua3MMOLZtw4XCnNMbfL9WXxet2b1rG3/8QAMRAAAQQCAgECBAUDBQEAAAAAAgABAwQFERASEyAhBhQxUBUiJDI0MDNBIyU1QEJg/9oACAEBAAEFAv8A5By0t893ZCTF9xM+dra2t6eM+4/bpJhEtraml8QTOUsMMzWIe21tQn1k+2zn44g/k7W0U3iPqVQh6yHK/sBk1Z39gfYfbMh7QRN0s7W0UvjcBcSfS7aUsnZnf2rf2Ptloe1euX6zstovduxQkErGn90X5ZDL2hbUP22+D1LfbbdltO6LYvTsCSMAma9HNChy4G8M3f7bng3DBL4V2XZdkTovrVvN2jl9pKEbyxfsb7Zdi81aQdtDKMUbSMu7JzZGREhjVeYo1FOxLy6GP+39sytfxS9G7x15Z1BhNrKU4qxdEwLqg7Mh8hKN9h9sIWMRo1hJvbjNNs+q6rqhFAypFuD7hl/36WlpMyZUC1J9wyv7uWTKEusv3DKfXjSbgvpGXaP7fkX3L6XVJ91vt9192fSSx38X7fYfc3ZMSbmT6Uh61f8Aub9RSgKGeI39ckoRs1mF+JC6gf0mZ2fzGCqS+WNk6l/bDl6RICYx/wCl5ATEz8ZDLQ1CL4hlUXxCW6lqK1Es7cM7byyrAXCswGTAJ/EETGGficsvkGgpySmbs/vgbhWql65FTjfL2ZD/ABe2BY+2NyvxlrL2LoQ6iwN1ia6Wo5FKpVh/7SdWdvFbrnVm+GrRNYJ2EbfxBo2z9vdTPsRDIBNkL0dStZyduchuWRfGZuTu3F7LQ10eatuhz1kHx2RiujxZyVau/Z1HPLG8Gbkap4yN69DyqUHjkwMpx5FZbp88JkKjuTA9nLFYxu/dF3mxvVQwVN4y1j6aztj5i8zraw9z5Sk2ZubizVoZLuMpzU59fJYg+uSuluY1KpPrh/7CdW5nrtPJJNL8P444F8SSkFHaLHE2LijPRkYoYTIOkTFkJKUwaftUZ2q57Imc8YDsyr69lRkKG6s7bKrUItqvSx8lcxcC5792+G6Xvck8NXe38n5lEIM8hVHl713VaaOOo7a4Z9KAWlllhavJ/m9WenTF2J3ddpJcJsnq4r3yUxbmN1K6tGsV7Utp3WZP82AEZMnxn7FesE1iWZDLICG0ZKxsy4hkeKXH2huVsoDw5FhlNvlZkUEorDAB5JfFEBHViDsvBAKlkEgWPotZp8fCkjlHrazUdWuEr1uvH1Q1C10qCn+Wda0/BPpYGt5rtypDbDIU4qVov3Qyz1cZcnOWlgI/108sflexEjdiXyRzqoBQQdk7rLP+qwL9ck0wOmNnWXm8+RQv2XV1FXM2ipxg1wYAJfDU3hfLZAbc5SGS26CaUHr3mGatYjsx35mr03Pfor3poIGF3cacpLFWK2OrfjdJZmzHfq8sXy7GTm/orwd3lj7S4ivKGQ8jKeRzljEpZDxEZ1Z/l6hS2JJeWJ2Uh+RYk/8AS3xPX+ZyUQV4I2OFCYL4ipV6wk20z9Q4jmIF5O6xduCcfiWzzpNpA9XVG1BUlvXRvUTjON+QDsmdxRyv6IniVOPGHLma9ak
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