Starting on javascript

Author: Susan Vanderplas

part-advanced-topics/07-intro-interactive-graphics.qmd

@@ -6,9 +6,7 @@ There are *many* other options out there - `Observable`, `d3.js`, `highCharts`,
 While I'd love to include them all, they are all being updated too, which would leave me with a lot of things to maintain to keep this chapter current. 
 Some additional coverage of JavaScript graphics is available in @sec-javascript-graphics.
 
-Plotly content is included even though the `plotly` [documentation for R, julia, F#, and Matlab is being deprecated.](https://web.archive.org/web/20251024184918/https://community.plotly.com/t/retire-the-documentation-for-r-matlab-julia-and-f/94147). 
-Plotly is still a reliable library (and has a lovely `ggplot2` interface), so because [the R package is still being maintained (for now)](https://www.reddit.com/r/rstats/comments/1nto2ir/plotly_is_retiring_its_r_documentation/njh81sw/) I have left it included as part of this chapter. 
-
+Plotly content is included even though the `plotly` [documentation for R, julia, F#, and Matlab is being deprecated.](https://web.archive.org/web/20251024184918/https://community.plotly.com/t/retire-the-documentation-for-r-matlab-julia-and-f/94147), because  [the R package is still being maintained (for now)](https://www.reddit.com/r/rstats/comments/1nto2ir/plotly_is_retiring_its_r_documentation/njh81sw/) and is supported by Posit. 
 
 ## {{< fa bullseye >}} Objectives 
 

part-advanced-topics/08-javascript-graphics.qmd

@@ -19,7 +19,8 @@ This is particularly useful when working with interactive graphics.
 Observable graphics can be created in two ways: via a hosted service at https://observablehq.com/, and via the Observable JS ("OJS") core library scripts, which can be included into standalone documents (like quarto). 
 In fact, Quarto handles this natively, and will include the necessary libraries if you use an `{ojs}` executable code block.
 
-First, we have to create an OJS block to read in some data. 
+First, we do a bit of preprocessing in R to get our data into a form we can use. 
+
 ```{r}
 library(dplyr)
 library(tidyr)
@@ -28,9 +29,15 @@ frognames <- read.csv('https://raw.githubusercontent.com/rfordatascience/tidytue
   group_by(scientificName) |> 
   slice_head(n=1)
 frogs <- dplyr::left_join(frogid, frognames, by = "scientificName")
-write.csv(frogs, file = "../data/frogs.csv", row.names = F)
+
+ojs_define(data = frogs)
 ```
+The last step is to use the `ojs_define()` function in R (also works in python) to make the frogs data available to OJS chunks. 
+Note that this will not work until the document is compiled, because OJS does not work interactively in quarto notebooks. 
+
 
 ```{ojs}
-frogs = FileAttachment('../data/frogs.csv').csv({typed: true})
+filtered = transpose(data).filter(function(frog) {
+  return scientificName.includes(frog.scientificName) 
+})
 ```