diff --git a/isleOfWight/beisIoWData.Rmd b/isleOfWight/beisIoWData.Rmd
index cf956e7e601c9b53452657f702950b05d9f72eff..136c6ea67e70341e4af0dffd9b687d735d253907 100644
--- a/isleOfWight/beisIoWData.Rmd
+++ b/isleOfWight/beisIoWData.Rmd
@@ -271,12 +271,11 @@ Next we code the EPC records:
 ```{r recoding}
 
 # flag the ones with 
-# EPC < C : D, E, F, G and H
+# EPC < C : D, E, F, & G
 dt[, lowEPC := ifelse(CURRENT_ENERGY_RATING == "D" |
                        CURRENT_ENERGY_RATING == "E" |
                        CURRENT_ENERGY_RATING == "F" |
-                       CURRENT_ENERGY_RATING == "G" |
-                       CURRENT_ENERGY_RATING == "H",
+                       CURRENT_ENERGY_RATING == "G" ,
                       "lowEPC", "okEPC")
    ]
 # main fuel type not mains gas
@@ -313,7 +312,7 @@ dt[, lowEPCoffGas := ifelse(lowEPC == "lowEPC" &
 
 Now:
 
- * we add up the number of households that do not have gas and have EPCs D-H per LSOA. 
+ * we add up the number of households that do not have gas and have EPCs D-G per LSOA. 
  
 We need to do this so that we can count the ones in LSOAs with high income deprivation. There is no other way to do this because income is not a variable on the EPC and LSOA level income distributions are not available.
 
diff --git a/isleOfWight/beisIoWData.html b/isleOfWight/beisIoWData.html
index 9192e776eed961229c108f85873265ebe015588d..ed249ad606a8368e56a68f858300495d2317a066 100644
--- a/isleOfWight/beisIoWData.html
+++ b/isleOfWight/beisIoWData.html
@@ -1592,7 +1592,7 @@ div.tocify {
 <h1 class="title toc-ignore">Exploring Isle of Wight Data</h1>
 <h3 class="subtitle">Code and notes</h3>
 <h4 class="author">Ben Anderson (<a href="mailto:b.anderson@soton.ac.uk" class="email">b.anderson@soton.ac.uk</a>), <a href="http://www.energy.soton.ac.uk/">SERG, Energy &amp; Climate Change</a>, University of Southampton</h4>
-<h4 class="date">Last run at: 2020-04-23 22:59:45</h4>
+<h4 class="date">Last run at: 2020-04-23 23:06:26</h4>
 
 </div>
 
@@ -2423,12 +2423,11 @@ nrow(dt)</code></pre>
 <li>we want main fuel type to be not mains gas</li>
 </ul>
 <pre class="r"><code># flag the ones with 
-# EPC &lt; C : D, E, F, G and H
+# EPC &lt; C : D, E, F, &amp; G
 dt[, lowEPC := ifelse(CURRENT_ENERGY_RATING == &quot;D&quot; |
                        CURRENT_ENERGY_RATING == &quot;E&quot; |
                        CURRENT_ENERGY_RATING == &quot;F&quot; |
-                       CURRENT_ENERGY_RATING == &quot;G&quot; |
-                       CURRENT_ENERGY_RATING == &quot;H&quot;,
+                       CURRENT_ENERGY_RATING == &quot;G&quot; ,
                       &quot;lowEPC&quot;, &quot;okEPC&quot;)
    ]
 # main fuel type not mains gas
@@ -2805,7 +2804,7 @@ Sum
 #table(dt$lowEPCoffGas)</code></pre>
 <p>Now:</p>
 <ul>
-<li>we add up the number of households that do not have gas and have EPCs D-H per LSOA.</li>
+<li>we add up the number of households that do not have gas and have EPCs D-G per LSOA.</li>
 </ul>
 <p>We need to do this so that we can count the ones in LSOAs with high income deprivation. There is no other way to do this because income is not a variable on the EPC and LSOA level income distributions are not available.</p>
 <pre class="r"><code>hhCountByLSOADT &lt;- dt[, .(nHHs = .N), 
@@ -8928,7 +8927,7 @@ kwhNDMedianGas
 </div>
 <div id="runtime" class="section level1">
 <h1><span class="header-section-number">5</span> Runtime</h1>
-<p>Analysis completed in 60.06 seconds ( 1 minutes) using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 3.6.3 (2020-02-29) running on x86_64-apple-darwin15.6.0.</p>
+<p>Analysis completed in 54.74 seconds ( 0.91 minutes) using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 3.6.3 (2020-02-29) running on x86_64-apple-darwin15.6.0.</p>
 </div>
 <div id="r-environment" class="section level1">
 <h1><span class="header-section-number">6</span> R environment</h1>