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(This article was first published on <strong><a href="http://www.r-exercises.com/2017/09/22/big-data-analytics-with-h20-in-r-exercises-part-1/"> R-exercises</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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We have dabbled with RevoScaleR before , In this exercise we will work with H2O , another high performance R library which can handle big data very effectively .It will be a series of exercises with increasing degree of difficulty . So Please do this in sequence .<br>
H2O requires you to have Java installed in your system .So please install Java before trying with H20 .As always check the documentation before trying these exercise set .<br>
Answers to the exercises are available <a rel="nofollow" href="http://www.r-exercises.com/2017/09/22/big-data-analytics-with-h20-in-r-exercises-part-1-solution/" target="_blank">here</a>.<br>
If you want to install the latest release from H20 , install it via this <a rel="nofollow" href="https://h2o-release.s3.amazonaws.com/h2o/rel-weierstrass/2/index.html" target="_blank">instructions</a> .</p>
<p><strong>Exercise 1</strong><br>
Download the latest stable release from h20 and initialize the cluster </p>
<p><strong>Exercise 2</strong><br>
Check the cluster information via clusterinfo </p>
<p><strong>Exercise 3</strong><br>
You can see how h2o works via the demo function , Check H2O’s glm via demo method .</p>
<p><strong>Exercise 4</strong></p>
<p>down load the <a rel="nofollow" href="https://github.com/h2oai/h2o-tutorials/tree/master/training/data" target="_blank">loan.csv</a> from H2O’s github repo and import it using H2O .<br>
<strong>Exercise 5</strong><br>
Check the type of imported loan data and notice that its not a dataframe , check the summary of the loan data .<br>
Hint -use h2o.summary() </p>
<p><strong>Exercise 6</strong><br>
One might want to transfer a dataframe from R environment to H2O , use as.h2o to conver the mtcars dataframe as a H2OFrame</p>
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<aside><img src="http://www.r-exercises.com/2017/09/22/big-data-analytics-with-h20-in-r-exercises-part-1/"></aside>
<div><strong>Learn more</strong> about importing big data in the online course <a rel="nofollow" href="http://www.r-exercises.com/product/data-mining-with-r-go-from-beginner-to-advanced/" target="_blank">Data Mining with R: Go from Beginner to Advanced</a>. In this course you will learn how to
<ul>
<li>work with different data import techniques,</li>
<li>know how to import data and transform it for a specific moddeling or analysis goal,</li>
<li>and much more.</li>
</ul>
</div>
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<p><strong>Exercise 7</strong></p>
<p>Check the dimension of the loan H2Oframe via h2o.dim</p>
<p><strong>Exercise 8</strong><br>
Find the colnames from the H2OFrame of loan data. </p>
<p><strong>Exercise 9</strong></p>
<p>Check the histogram of the loan amount of loan H2Oframe . </p>
<p><strong>Exercise 10</strong><br>
Find the mean of loan amount by each home ownership group from the loan H2OFrame</p>
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<h3>Related exercise sets:</h3>
<ol>
<li><a rel="nofollow" href="http://www.r-exercises.com/2017/09/11/big-data-analytics-with-revoscaler-exercises-2/" title="Big Data analytics with RevoScaleR Exercises-2" target="_blank">Big Data analytics with RevoScaleR Exercises-2 </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2017/05/24/data-wrangling-part-1-io/" title="Data wrangling : I/O (Part-1)" target="_blank">Data wrangling : I/O (Part-1) </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2017/06/10/density-based-clustering-exercises/" title="Density-Based Clustering Exercises" target="_blank">Density-Based Clustering Exercises </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/start-here-to-learn-r/" target="_blank">Explore all our (>1000) R exercises</a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/r-courses/" target="_blank">Find an R course using our R Course Finder</a> directory</li>
</ol>
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