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(This article was first published on <strong><a href="http://www.r-exercises.com/2017/05/24/data-wrangling-part-1-io/?utm_source=rss&utm_medium=rss&utm_campaign=data-wrangling-part-1-io"> 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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Data wrangling is a task of great importance in data analysis. Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be a brief series with goal to craft the reader’s skills on the data wrangling task. This is the first part of this series and it aims to cover the importing and exporting of data locally.<br>
Please download the data from <a rel="nofollow" href="https://github.com/VasTsak/r-exercises-dw/tree/master/part-1" target="_blank">here</a></p>
<p>Before proceeding, it might be helpful to look over the help pages for the <code>read.csv</code>, <code>read.table</code>, <code>read_excel</code>, <code>fromJSON</code>, <code>as.data.frame</code>, <code>xmlParse</code>, <code>xmlToList</code>, <code>write.csv</code>, <code>write.table</code>, <code>write.xlsx</code>, <code>toJSON</code>, <code>write</code>, <code>write.xml</code>.</p>
<p>Moreover please load the following libraries.<br>
<code>install.packages(&quot;readxl&quot;)</code><br>
<code>library(readxl)</code><br>
<code>install.packages(&quot;xlsx&quot;)</code><br>
<code>library(xlsx)</code><br>
<code>install.packages(&quot;rjson&quot;)</code><br>
<code>library(rjson)</code><br>
<code>install.packages(&quot;plyr&quot;)</code><br>
<code>library(plyr)</code><br>
<code>install.packages(&quot;XML&quot;)</code><br>
<code>library(XML)</code><br>
<code>install.packages(&quot;kulife&quot;)</code><br>
<code>library(kulife)</code></p>
<p>Answers to the exercises are available <a rel="nofollow" href="http://www.r-exercises.com/2017/05/24/data-wrangling-part-1-io-solutions" target="_blank">here</a>.</p>
<p>If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page.</p>
<p>Exercise 1</p>
<p>Import the <code>data.csv</code> file to the <code>csv_file</code> object.</p>
<p>Exercise 2</p>
<p>Import the <code>data.txt</code> file to the <code>txt_file</code> object.</p>
<p>Exercise 3</p>
<p>Import the <code>data.xls</code> file to the <code>xls_file</code> object.</p>
<p>Exercise 4</p>
<p>Import the <code>data.xlsx</code> file to the <code>xlsx_file</code> object.</p>
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<div><strong>Learn more</strong> about Data Pre-Processing in the online course <a rel="nofollow" href="http://www.r-exercises.com/product/r-data-pre-processing-data-management-shape-your-data/" target="_blank">R Data Pre-Processing &amp; Data Management – Shape your Data!</a>. In this course you will learn how to:
<ul>
<li>import data into R in several ways while also beeing able to identify a suitable import tool</li>
<li>use SQL code within R</li>
<li>And much more</li>
</ul>
</div>
</div>
<p>Exercise 5</p>
<p>Import the <code>data.json</code> file to the <code>json_file</code> object.</p>
<p>Exercise 6</p>
<p>Import the <code>data.xml</code> file to the <code>xml_file</code> object.</p>
<p>Exercise 7</p>
<p>Export the <code>csv_file</code> as “data.csv” and <code>txt_file</code> as “data.txt”. </p>
<p>Exercise 8 </p>
<p>Export the <code>xls_file</code> as “data.xls” and <code>xlsx_file</code> as “data.xlsx”.</p>
<p>Exercise 9 </p>
<p>Export the <code>json_file</code> as “data.json”.</p>
<p>Exercise 10 </p>
<p>Export the <code>xml_file</code> as “data.xml”.</p>
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<h3>Related exercise sets:</h3>
<ol>
<li><a rel="nofollow" href="http://www.r-exercises.com/2016/08/24/using-manova-to-analyse-banking-crises/" title="Using MANOVA to Analyse a Banking Crisis Exercises" target="_blank">Using MANOVA to Analyse a Banking Crisis Exercises </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2017/01/01/building-shiny-app-exercises-part-4/" title="Building Shiny App exercises part 4" target="_blank">Building Shiny App exercises part 4 </a></li>
<li><a rel="nofollow" href="http://www.r-exercises.com/2017/05/04/accessing-and-manipulating-biological-databases-exercises-part-2/" title="Accessing and Manipulating Biological Databases  Exercises (Part 2)" target="_blank">Accessing and Manipulating Biological Databases Exercises (Part 2) </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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