<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>R Markdown on Cian White</title>
    <link>http://www.cianwhite.org/tags/r-markdown/</link>
    <description>Recent content in R Markdown on Cian White</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-uk</language>
    <lastBuildDate>Thu, 26 Mar 2020 00:00:00 +0000</lastBuildDate>
    
	<atom:link href="http://www.cianwhite.org/tags/r-markdown/index.xml" rel="self" type="application/rss+xml" />
    
    
    <item>
      <title>Creating Static and Interactive Maps in R</title>
      <link>http://www.cianwhite.org/notebooks/mapping_in_r/</link>
      <pubDate>Thu, 26 Mar 2020 00:00:00 +0000</pubDate>
      
      <guid>http://www.cianwhite.org/notebooks/mapping_in_r/</guid>
      <description>Irish COVID 19 Intertactive Map Aim Shapefiles Covid data Using ggplot to make maps Creating Thematic Maps Animated Maps Using Leaflet    Reading time: 13 minute(s) @ 200 WPM.
A note: if you are reading this on Rpubs, the links will only work is you Control Click.
Irish COVID 19 Intertactive Map Aim To create a map that tracks the spread of COVID 19 in Ireland as the pandemic progresses.</description>
    </item>
    
    <item>
      <title>Principal Component Analysis in R</title>
      <link>http://www.cianwhite.org/notebooks/pca/</link>
      <pubDate>Tue, 03 Mar 2020 00:00:00 +0000</pubDate>
      
      <guid>http://www.cianwhite.org/notebooks/pca/</guid>
      <description>Prinicpal Component Analysis Standardising Variables Constructing a PCA Theory Behind PCA Results PCA Visualisation Deciding how many principal components to retain Interpreting the Results Graphical parameters with ggbiplot Multivariate Packages Predicting using PCA    Prinicpal Component Analysis I am setting up a notebook for how to run principal component analyses. PCA techniques are very useful for data exploration when the dataset is ‘wide’, there are a lot of columns for the amount of rows of datapoints.</description>
    </item>
    
  </channel>
</rss>