diff --git a/Rmd/cleaningFeederData.Rmd b/Rmd/cleaningFeederData.Rmd
index 0e3e22755e3abeaf866a305344e3e67e0ee0643d..c0e765fc08fb920c7525b43b5fe67962b22388ea 100644
--- a/Rmd/cleaningFeederData.Rmd
+++ b/Rmd/cleaningFeederData.Rmd
@@ -27,7 +27,6 @@ output:
     toc: yes
     toc_depth: 2
     fig_width: 5
-always_allow_html: yes
 bibliography: '`r paste0(here::here(), "/bibliography.bib")`'
 ---
 
@@ -64,7 +63,7 @@ We have some electricity substation feeder data that has been cleaned to give me
 
 There seem to be some NA kW values and a lot of missing time stamps. We want to select the 'best' (i.e most complete) days within a day-of-the-week/season/year sampling frame. If we can't do that we may have to resort to seasonal mean kW profiles by hour & day of the week...
 
-Code used to generate this report: https://git.soton.ac.uk/ba1e12/spatialec/-/blob/master/isleOfWight/cleaningFeederData.Rmd
+The code used to generate this report is in: https://git.soton.ac.uk/ba1e12/dataCleaning/Rmd/
 
 # Data prep
 
@@ -78,8 +77,7 @@ origDataDT <- drake::readd(origData) # readd the drake object
 uniqDataDT <- drake::readd(uniqData) # readd the drake object
 
 kableExtra::kable(head(origDataDT), digits = 2,
-                  caption = "Counts per feeder (long table)") %>%
-  kable_styling()
+                  caption = "First 6 rows of data")
 ```
 
 Do a duplicate check by feeder_ID, dateTime & kW. In theory there should not be any.
@@ -89,16 +87,19 @@ message("Original data nrows: ", tidyNum(nrow(origDataDT)))
 
 message("Unique data nrows: ", tidyNum(nrow(uniqDataDT)))
 
-message("So we have ", tidyNum(nrow(origDataDT) - nrow(uniqDataDT)), " duplicates...")
+nDups <- tidyNum(nrow(origDataDT) - nrow(uniqDataDT))
+
+message("So we have ", tidyNum(nDups), " duplicates...")
 
 pc <- 100*((nrow(origDataDT) - nrow(uniqDataDT))/nrow(origDataDT))
 message("That's ", round(pc,2), "%")
 
 feederDT <- uniqDataDT[!is.na(rDateTime)] # use dt with no duplicates
 origDataDT <- NULL # save memory
+
 ```
 
-There were `r tidyNum(nrow(origDataDT) - nrow(uniqDataDT))` duplicates - that's `r round(pc,2)` % of the observations loaded.
+There were `r tidyNum(nDups)` duplicates - that's ~ `r round(pc,2)` % of the observations loaded.
 
 So we remove the duplicates...
 
@@ -321,23 +322,19 @@ ggplot2::ggplot(aggDT, aes(x = rDate, colour = season,
 aggDT[, rDoW := lubridate::wday(rDate, lab = TRUE)]
 h <- head(aggDT[season == "Spring"][order(-propExpected)])
 kableExtra::kable(h, caption = "Best Spring days overall", 
-                  digits = 3) %>%
-  kable_styling()
+                  digits = 3)
 
 h <- head(aggDT[season == "Summer"][order(-propExpected)])
 kableExtra::kable(h, caption = "Best Summer days overall", 
-                  digits = 3) %>%
-  kable_styling()
+                  digits = 3)
 
 h <- head(aggDT[season == "Autumn"][order(-propExpected)])
 kableExtra::kable(h, caption = "Best Autumn days overall",
-                  digits = 3) %>%
-  kable_styling()
+                  digits = 3) 
 
 h <- head(aggDT[season == "Winter"][order(-propExpected)])
 kableExtra::kable(h, caption = "Best Winter days overall", 
-                  digits = 3) %>%
-  kable_styling()
+                  digits = 3)
 ```
 
 # Summary
diff --git a/Rmd/cleaningFeederData_allData.log b/Rmd/cleaningFeederData_allData.log
new file mode 100644
index 0000000000000000000000000000000000000000..6b5d84b71adad7b6aebdb2e1541ba91b2f1c5685
--- /dev/null
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diff --git a/_drakeCleanFeeders.R b/_drakeCleanFeeders.R
index d914fad43611a6b5a84ddc855076e820725c0381..f58757e31956474fd898a3e4759af9b4323e5b3b 100644
--- a/_drakeCleanFeeders.R
+++ b/_drakeCleanFeeders.R
@@ -1,12 +1,15 @@
 # basic _drake.R style file
-# but adapted for use in a project with multiple plans
+# but adapted for use in a project where there might be multiple plans in the same folder
+# called using r_make() from make_cleanFeeders.R
+# see https://books.ropensci.org/drake/projects.html#usage for explanation
+
+# Libraries/Packages ----
+# the drake book suggests putting this in packages.R but...
 
-# Libraries ----
 library(dataCleaning) # remember to build it first :-)
 dataCleaning::setup() # load env.R set up the default paths etc
 
 makeLibs <- c("data.table", # data munching
-              "drake", # for plans
               "here", # here
               "lubridate", # dates and times
               "hms", # times
@@ -17,7 +20,7 @@ makeLibs <- c("data.table", # data munching
 dataCleaning::loadLibraries(makeLibs)
 
 # Parameters ----
-updateData <- "yep" # edit this in any way (at all) to get drake to re-load the data
+updateData <- "rerun" # edit this in any way (at all) to get drake to re-load the data
 updateReport <- "yes" # edit this in any way (at all) to get drake to re-load the data
 
 # Some data to play with:
@@ -32,6 +35,7 @@ authors <- "Ben Anderson & Ellis Ridett"
 
 # Functions ----
 # for use in drake
+# the drake book suggests putting this in functions.R but...
 
 addSeason <- function(dt,dateVar,h){
   dt <- dt[, tmpM := lubridate::month(get(dateVar))] # sets 1 (Jan) - 12 (Dec). May already exist but we can't rely on it
@@ -79,7 +83,10 @@ getData <- function(f,updateData){
 makeUniq <- function(dt){
   # we suspect there may be duplicates by feeder_ID, dateTime & kW
   # remove them (report this in the .Rmd)
-  uniq <- unique(dt, by = c("rDateTime", "feeder_ID", "kW"))
+  uniq <- unique(dt, by = c("rDateTime", # dateTime
+                            "feeder_ID", # our constructed unique feeded ID
+                            "kW") # kW
+                 )
   return(uniq)
 }
 
@@ -150,6 +157,8 @@ makeReport <- function(f,version, type = "html", updateReport){
 
 
 # Set the drake plan ----
+# the drake book suggests putting this in plan.R but...
+# I had expected r_make() to load drake() in the new clean R session  but it doesn't
 my_plan <- drake::drake_plan(
   origData = getData(dFile, updateData), # returns data as data.table. If you edit 'update' in any way it will reload - drake is watching you!
   uniqData = makeUniq(origData), # remove duplicates
@@ -162,4 +171,5 @@ my_plan <- drake::drake_plan(
 )
 
 # see https://books.ropensci.org/drake/projects.html#usage
-drake_config(my_plan, verbose = 2)
\ No newline at end of file
+# I had expected r_make() to load drake() in the new clean R session  but it doesn't
+drake::drake_config(my_plan, verbose = 2)
\ No newline at end of file
diff --git a/docs/cleaningFeederData_allData.html b/docs/cleaningFeederData_allData.html
index 92aca205c594e41143da788420897e439d825ad7..955d5694fa48e53065a3d23ad4cf159368a3e7f8 100644
--- a/docs/cleaningFeederData_allData.html
+++ b/docs/cleaningFeederData_allData.html
@@ -181,7 +181,7 @@ summary {
 <h1 class="title toc-ignore">Testing electricity substation/feeder data</h1>
 <h3 class="subtitle">Outliers and missing data...</h3>
 <h4 class="author">Ben Anderson &amp; Ellis Ridett</h4>
-<h4 class="date">Last run at: 2020-07-09 00:56:06</h4>
+<h4 class="date">Last run at: 2020-07-09 09:48:01</h4>
 
 </div>
 
@@ -214,7 +214,7 @@ dataCleaning::loadLibraries(rmdLibs)</code></pre>
 <h1>Intro</h1>
 <p>We have some electricity substation feeder data that has been cleaned to give mean kW per 15 minutes.</p>
 <p>There seem to be some NA kW values and a lot of missing time stamps. We want to select the 'best' (i.e most complete) days within a day-of-the-week/season/year sampling frame. If we can't do that we may have to resort to seasonal mean kW profiles by hour &amp; day of the week...</p>
-<p>Code used to generate this report: <a href="https://git.soton.ac.uk/ba1e12/spatialec/-/blob/master/isleOfWight/cleaningFeederData.Rmd" class="uri">https://git.soton.ac.uk/ba1e12/spatialec/-/blob/master/isleOfWight/cleaningFeederData.Rmd</a></p>
+<p>The code used to generate this report is in: <a href="https://git.soton.ac.uk/ba1e12/dataCleaning/Rmd/" class="uri">https://git.soton.ac.uk/ba1e12/dataCleaning/Rmd/</a></p>
 </div>
 <div id="data-prep" class="section level1">
 <h1>Data prep</h1>
@@ -226,11 +226,11 @@ dataCleaning::loadLibraries(rmdLibs)</code></pre>
 uniqDataDT &lt;- drake::readd(uniqData) # readd the drake object
 
 kableExtra::kable(head(origDataDT), digits = 2,
-                  caption = &quot;Counts per feeder (long table)&quot;) %&gt;%
+                  caption = &quot;First 6 rows of data&quot;) %&gt;%
   kable_styling()</code></pre>
 <table class="table" style="margin-left: auto; margin-right: auto;">
 <caption>
-Counts per feeder (long table)
+First 6 rows of data
 </caption>
 <thead>
 <tr>
@@ -487,14 +487,16 @@ Winter
 
 message(&quot;Unique data nrows: &quot;, tidyNum(nrow(uniqDataDT)))
 
-message(&quot;So we have &quot;, tidyNum(nrow(origDataDT) - nrow(uniqDataDT)), &quot; duplicates...&quot;)
+nDups &lt;- tidyNum(nrow(origDataDT) - nrow(uniqDataDT))
+
+message(&quot;So we have &quot;, tidyNum(nDups), &quot; duplicates...&quot;)
 
 pc &lt;- 100*((nrow(origDataDT) - nrow(uniqDataDT))/nrow(origDataDT))
 message(&quot;That's &quot;, round(pc,2), &quot;%&quot;)
 
 feederDT &lt;- uniqDataDT[!is.na(rDateTime)] # use dt with no duplicates
 origDataDT &lt;- NULL # save memory</code></pre>
-<p>There were duplicates - that's 0.38 % of the observations loaded.</p>
+<p>There were 83,606 duplicates - that's ~ 0.38 % of the observations loaded.</p>
 <p>So we remove the duplicates...</p>
 </div>
 </div>
@@ -1500,7 +1502,7 @@ Fri
 </div>
 <div id="runtime" class="section level1">
 <h1>Runtime</h1>
-<p>Analysis completed in 196.02 seconds ( 3.27 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 3.6.0 (2019-04-26) running on x86_64-redhat-linux-gnu.</p>
+<p>Analysis completed in 218.48 seconds ( 3.64 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 3.6.0 (2019-04-26) running on x86_64-redhat-linux-gnu.</p>
 </div>
 <div id="r-environment" class="section level1">
 <h1>R environment</h1>
@@ -1539,8 +1541,8 @@ Fri
 ## [1] stats     graphics  grDevices utils     datasets  methods   base     
 ## 
 ## other attached packages:
-## [1] kableExtra_1.1.0   skimr_2.1.2        ggplot2_3.3.2      hms_0.5.3         
-## [5] lubridate_1.7.9    here_0.1           drake_7.12.4       data.table_1.12.0 
+## [1] kableExtra_1.1.0   drake_7.12.4       skimr_2.1.2        ggplot2_3.3.2     
+## [5] hms_0.5.3          lubridate_1.7.9    here_0.1           data.table_1.12.0 
 ## [9] dataCleaning_0.1.0
 ## 
 ## loaded via a namespace (and not attached):
diff --git a/docs/cleaningFeederData_allData.pdf b/docs/cleaningFeederData_allData.pdf
index 6268d3469501440f1ee512c5b142717b1624b0ef..f35c9dcc5876b5611e31e47b0cd6875d89d891bb 100644
Binary files a/docs/cleaningFeederData_allData.pdf and b/docs/cleaningFeederData_allData.pdf differ
diff --git a/make_cleanFeeders.R b/make_cleanFeeders.R
index fbf91a625f79c9e8031f9396b045b2fbc14ae1bb..11702eab02002bb7b61c9e4129df538f7f2a28f2 100644
--- a/make_cleanFeeders.R
+++ b/make_cleanFeeders.R
@@ -4,9 +4,9 @@
 # Set up ----
 startTime <- proc.time()
 
-library(drake)
 # use r_make to run the plan inside a clean R session so nothing gets contaminated
 drake::r_make(source = "_drakeCleanFeeders.R") # where we keep the drake plan etc
+
 # we don't keep this in /R because that's where the package functions live
 # we don't use "_drake.R" because we have lots of different plans