stephhazlitt commented on code in PR #14514:
URL: https://github.com/apache/arrow/pull/14514#discussion_r1028813972


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r/vignettes/read_write.Rmd:
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@@ -0,0 +1,163 @@
+---
+title: "Reading and writing data files"
+description: >
+  Learn how to read and write CSV, Parquet, and Feather files with arrow 
+output: rmarkdown::html_vignette
+---
+
+The arrow package provides functions for reading single data files into 
memory, in
+several common formats. By default, calling any of these functions
+returns an R data frame. To return an Arrow Table, set argument
+`as_data_frame = FALSE`.
+
+- `read_parquet()`: read a file in Parquet format
+- `read_feather()`: read a file in the Apache Arrow IPC format (formerly 
called the Feather format)
+- `read_delim_arrow()`: read a delimited text file (default delimiter is comma)
+- `read_csv_arrow()`: read a comma-separated values (CSV) file
+- `read_tsv_arrow()`: read a tab-separated values (TSV) file
+- `read_json_arrow()`: read a JSON data file
+
+For writing data to single files, the arrow package provides the
+following functions, which can be used with both R data frames and 
+Arrow Tables:
+
+- `write_parquet()`: write a file in Parquet format
+- `write_feather()`: write a file in Arrow IPC format
+- `write_csv_arrow()`: write a file in CSV format
+
+All these functions can read and write files in the local filesystem or
+to cloud storage. For more on cloud storage support in arrow, see the [cloud 
storage article](./fs.html).
+
+The arrow package also supports reading and writing multi-file datasets,
+which enable analysis and processing of larger-than-memory data, and provide 

Review Comment:
   ```suggestion
   This enables analysis and processing of larger-than-memory data, and 
provides 
   ```



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