processing-data-r-js.qmd

# Should you manipulate data with R or JavaScript?

[I made the Goodreads API endpoint](plumber-goodreads.qmd) return three things:

1. The total number of books read in the year
2. A data frame of monthly counts
3. The full data

Technically this isn't necessary. I could just return the full data and leave it up to the end user (also me) to summarize it somehow. [That's what I did with the Fitbit data](plumber-fitbit.qmd)—I returned a data frame with a row per day and then summarized it myself before plotting it.

The [Arquero JavaScript library](https://observablehq.com/@uwdata/introducing-arquero) lets you do this with {dplyr}-like syntax (and [this guide](https://observablehq.com/@observablehq/data-wrangling-with-arquero-from-r) is indispensable for translating from dplyr to Arquero):

```{ojs}
//| echo: fenced
d3 = require('d3')
import { aq, op } from "@uwdata/arquero"

books = await d3.json(
  // This is my live API so it runs in your browser.
  // Use your local API URL on your computer.
  "https://api.andrewheiss.com/books_simple?year=2023"
)

// Convert the books JSON to an Arquero data frame
books_df = aq.from(books.full_data)

total_books = books_df
  .rollup({
    total_books: d => d.count()
  })
total_books.view()
```

```{ojs}
//| echo: fenced
books_by_month = books_df
  .groupby("read_month_fct")
  .rollup({
    count: d => d.count()
  })
books_by_month.view()
```

That works. But I'm not very proficient with JavaScript, and in my case I know that I want to show a bar chart with monthly totals, so I'd prefer to let R do the heavy lifting here and just spit out a plot-ready data frame that I don't have to make on my own. 

The magic of this whole {plumber} system is that you can make the API return whatever data you want in whatever structure you want. Handle the bulk of the processing in R and return lots of different pre-calculated values, or return raw-er data that you process on the fly with Arquero. Return whatever you're most comfortable working with!