Trying to add button to PDF

.gitignore

@@ -11,6 +11,18 @@ dev_*
 *_cache/
 _site/
 _book/
+README_files/
+capacity_files/
+consumption_files/
+generation_files/
+prices_files/
+*.html
+*.aux
+*.lof
+*.log
+*.lot
+*.tex
+*.toc
 
 node_modules/
 

README.md

@@ -1,28 +1,49 @@
 # AETR Web Book
-Preliminary Alaska Electricity Trends Report as a web book.
 
+Preliminary Alaska Electricity Trends Report as a web book.
 
 ## Preview and Render Locally
 
+### Prepare the environment
+
+Rendering this web-book requires R (>=4.4.0) and some R packages.
+
+1. Install R from [The Comprehensive R Archive Network](https://cran.r-project.org) using the correct method for your operating system.
+2. Install OpenSSL, which is required for one of the packages.
+
+3. Issue these commands on your command line (or however you access R) to prepare your R environment using `renv`:
+
+  ``` bash
+  % cd aetr-web-book-2024/
+  % R    # at the command line to start R
+  > renv::restore()
+  ```
 
-[Website Previewing](https://quarto.org/docs/websites/#website-preview) allows viewing of the completed website by generating HTML from the `qmd` files. VSCode and RStidio both render and preview pages automatically using a `Render` button.
+4. The Barlow font must be installed.  
+
+
+### Previewing
+
+[Web-book Previewing](https://quarto.org/docs/websites/#website-preview) allows viewing of the completed website by generating HTML from the `qmd` files.  To preview the web-book using commands in the terminal:
 
-To preview the website using commands in the terminal:
 ``` bash
-# preview the website in the current directory
+# preview the web-book in the current directory
 quarto preview
 ```
+
 It should automatically open a browser window. See `quarto preview help` for hints
 
-You can also render the website without displaying it. The generated code goes in the `_site` directory (which should be listed in .gitignore)
+You can also render the web-book without displaying it. The generated code goes in the `_book` directory (which should be listed in .gitignore)
+
 ``` bash
 # render the website in the current directory
 quarto render 
 ```
 
+VSCode and RStudio both render and preview pages automatically using a `Render` button. In VSCode, open a `.qmd` page in the editor such as `index.qmd`, and 
+
 ## Publishing via GitHub
 
-Set things up (or is that the cc business)
 
 
 ## Credits

_quarto-html.yml

@@ -9,6 +9,7 @@ book:
       text: Alaska Energy Statistics Workbooks (2011-2021)
       icon: bi-file-spreadsheet
   repo-actions: [issue]
+  downloads: pdf
 
   chapters:
     - index.qmd

consumption.qmd

@@ -248,7 +248,7 @@ print(customers_pdf)
 
 `r space()`
 
-`r if (knitr::is_html_output())"@fig-sales_per_capita-html" else if (knitr::is_latex_output()) "@fig-sales_per_capita-pdf"` <!--orig: The following table--> shows the average annual electricity consumption for each of the regions. The Coastal region led the state in consumption per capita, with an average of `r regional_consumption_per_capita("Coastal","Residential")` kWh per customer per year. This was followed by the Railbelt region with `r regional_consumption_per_capita("Railbelt","Residential")` kWh per capita and the Rural Remote region with `r regional_consumption_per_capita("Rural Remote","Residential")` kWh per capita. Overall, each region has seen reductions in consumption per capita, which may reflect improvements in energy efficient technologies and energy efficiency/conservation behaviors.
+`r if (knitr::is_html_output())"@fig-sales_per_capita-html" else if (knitr::is_latex_output()) "@fig-sales-per-capita-pdf"` <!--orig: The following table--> shows the average annual electricity consumption for each of the regions. The Coastal region led the state in consumption per capita, with an average of `r regional_consumption_per_capita("Coastal","Residential")` kWh per customer per year. This was followed by the Railbelt region with `r regional_consumption_per_capita("Railbelt","Residential")` kWh per capita and the Rural Remote region with `r regional_consumption_per_capita("Rural Remote","Residential")` kWh per capita. Overall, each region has seen reductions in consumption per capita, which may reflect improvements in energy efficient technologies and energy efficiency/conservation behaviors.
 
 `r space()`
 
@@ -317,7 +317,7 @@ girafe(code = print(sales_per_capita_html))
 ```
 
 ```{r, eval=knitr::is_latex_output(), fig.pos = "H"}
-#| label: fig-sales_per_capita-pdf
+#| label: fig-sales-per-capita-pdf
 #| fig-cap: "Average Residential Sales per Customer"
 
 sales_per_capita_pdf <-