docs: update now that arrow is implemented

Author: machow

docs/getting_started.Rmd

@@ -70,10 +70,10 @@ But you can choose another option depending on your goals:
 
 -   `type = "csv"` uses `to_csv()` from pandas to create a `.csv` file. CSVs can read by any application, but only support simple columns (e.g. numbers, strings, dates), can take up a lot of disk space, and can be slow to read.
 -   `type = "joblib"` uses `joblib.dump()` to create a binary python data file. See the [joblib docs](https://joblib.readthedocs.io/en/latest/) for more information.
+-   `type = "arrow"` uses `pyarrow` to create an arrow/feather file. [Arrow](https://arrow.apache.org) is a modern, language-independent, high-performance file format designed for data science. Not every tool can read arrow files, but support is growing rapidly.
 
 🚧 Data formats TODO 🚧
 
--   `type = "arrow"` uses `arrow::write_feather()` to create an arrow/feather file. [Arrow](https://arrow.apache.org) is a modern, language-independent, high-performance file format designed for data science. Not every tool can read arrow files, but support is growing rapidly.
 -   `type = "json"` uses `jsonlite::write_json()` to create a `.json` file. Pretty much every programming language can read json files, but they only work well for nested lists.
 
 After you've pinned an object, you can read it back with `pin_read()`: