<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/"></div></div><div><a data-url="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/" data-counturl="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/" data-count="horizontal" data-text="Visualizing multiple dimensions of Google Analytics in R" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="http://www.tatvic.com/blog/visualizing-multiple-dimensions-google-analytics-r/"> Tatvic Blog » R</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<h3>Stack bar chart</h3>
<ul>
<li> It is used when we wish to visualize a combination of categorical variables
<pre>ggplot(data, aes(date, fill = region)) + geom_bar()+ labs(title = &amp;quot;Stacked Bar Chart&amp;quot;, x = &amp;quot;Date&amp;quot;, y = &amp;quot;Count of Regions&amp;quot;) where date : ga:date and region : ga:region</pre>
</li>
<li>Example
<pre> ggplot(train, aes(Outlet_Location_Type, fill = Outlet_Type)) + geom_bar()+ labs(title = &amp;quot;Stacked Bar Chart&amp;quot;, x = &amp;quot;Outlet Location Type&amp;quot;, y = &amp;quot;Count of Outlets&amp;quot;)</pre>
</li>
</ul>
<p><a target="_blank" href="https://i2.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/08/Stacked-bar-chart.png"><img alt="Stacked bar chart" class="wp-image-6207" src="https://i2.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/08/Stacked-bar-chart.png?resize=456%2C286" data-recalc-dims="1"></a></p>
<p> </p>
<h3>Heat Map</h3>
<ul>
<li dir="ltr">
<p dir="ltr">It uses intensity (density) of colors to display relationship between two or three or many variables in a two dimensional image.</p>
</li>
<li dir="ltr">It allows us to explore two dimensions as the axis and the third dimension by intensity of color.
<pre>ggplot(data, aes(date, region)) + geom_raster(aes(fill = transactions))+ labs(title =&quot;Heat Map&quot;, x = &quot;Date&quot;, y = &quot;Region&quot;)+ scale_fill_continuous(name = &quot;Transactions&quot;) where date : ga:date, region : ga:region and transactions : ga:transactions</pre>
</li>
</ul>
<ul>
<li dir="ltr">
<p dir="ltr">Example</p>
<pre>ggplot(train, aes(Outlet_Identifier, Item_Type)) + geom_raster(aes(fill = Item_MRP)) + labs(title =&quot;Heat Map&quot;, x = &quot;Outlet Identifier&quot;, y = &quot;Item Type&quot;) + scale_fill_continuous(name = &quot;Item MRP&quot;)</pre>
<p><a target="_blank" href="https://i1.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/08/Heat-map.png"><img alt="Heat map" class="wp-image-6208" src="https://i1.wp.com/www.tatvic.com/blog/wp-content/uploads/2016/08/Heat-map.png?resize=456%2C286" data-recalc-dims="1"></a>

<p> </p>
<p>The post <a target="_blank" href="http://www.tatvic.com/blog/visualizing-multiple-dimensions-google-analytics-r/">Visualizing multiple dimensions of Google Analytics in R</a> appeared first on <a target="_blank" href="http://www.tatvic.com/blog">Tatvic Blog</a>.</p>
<p><div><div><div><div data-width="55" data-show-faces="false" data-send="true" data-layout="box_count" data-height="62" data-href="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/"></div></div><div><a data-url="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/" data-counturl="https://www.r-bloggers.com/visualizing-multiple-dimensions-of-google-analytics-in-r/" data-count="vertical" data-text="Visualizing multiple dimensions of Google Analytics in R" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.tatvic.com/blog/visualizing-multiple-dimensions-google-analytics-r/"> Tatvic Blog » R</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a title="The R Project for Statistical Computing" rel="nofollow" href="https://www.r-project.org/">R</a> news and <a title="R tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=tutorial">tutorials</a> on topics such as: <a title="Data science" rel="nofollow" href="https://www.r-bloggers.com/?s=data%20science">Data science</a>, <a title="Big Data" rel="nofollow" href="https://www.r-bloggers.com/?s=Big%20Data">Big Data, <a title="R jobs" rel="nofollow" href="https://www.r-users.com/">R jobs</a>, visualization (<a title="ggplot and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=ggplot2">ggplot2</a>, <a title="Boxplots using lattice and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=boxplot">Boxplots</a>, <a title="Maps and gis" rel="nofollow" href="https://www.r-bloggers.com/?s=map">maps</a>, <a title="Animation in R" rel="nofollow" href="https://www.r-bloggers.com/?s=animation">animation</a>), programming (<a title="RStudio IDE for R" rel="nofollow" href="https://www.r-bloggers.com/?s=RStudio">RStudio</a>, <a title="Sweave and literate programming" rel="nofollow" href="https://www.r-bloggers.com/?s=sweave">Sweave</a>, <a title="LaTeX in R" rel="nofollow" href="https://www.r-bloggers.com/?s=LaTeX">LaTeX</a>, <a title="SQL and databases" rel="nofollow" href="https://www.r-bloggers.com/?s=SQL">SQL</a>, <a title="Eclipse IDE for R" rel="nofollow" href="https://www.r-bloggers.com/?s=eclipse">Eclipse</a>, <a title="git and github, Version Control System" rel="nofollow" href="https://www.r-bloggers.com/?s=git">git</a>, <a title="Large data in R using Hadoop" rel="nofollow" href="https://www.r-bloggers.com/?s=hadoop">hadoop</a>, <a title="Web Scraping of google, facebook, yahoo, twitter and more using R" rel="nofollow" href="https://www.r-bloggers.com/?s=Web+Scraping">Web Scraping</a>) statistics (<a title="Regressions and ANOVA analysis tutorials" rel="nofollow" href="https://www.r-bloggers.com/?s=regression">regression</a>, <a title="principal component analysis tutorial" rel="nofollow" href="https://www.r-bloggers.com/?s=PCA">PCA</a>, <a title="Time series" rel="nofollow" href="https://www.r-bloggers.com/?s=time+series">time series</a>, <a title="finance trading" rel="nofollow" href="https://www.r-bloggers.com/?s=trading">trading</a>) and more...
<img height="1" alt="" width="1" src="http://feeds.feedburner.com/~r/RBloggers/~4/7OEJgky5GXo"></a></div></ul>