Michael Chow
Michael Chow
Currently we don't try to use a representation of the siu expression to allow support for unnamed arguments in funcs like mutate and summarize. Could be useful, but doesn't seem...
see `test_summarize_removes_1_grouping()`
would be useful to see a representation of the pipe...
Currently raises a NotImplementedError. One key decision here is where in resulting data kw vars should go. To be consistent with all other uses of select, I would say kwargs...
**Starts on 1** Pros: * consistent with SQL (and R) * saying the row number is 0 seems a bit unnatural Cons: * if a row number is the same...
This should throw an error ``` from siuba.data import mtcars from siuba import _, group_by, transmute mtcars >> group_by(_.cyl) >> transmute(cyl = _.cyl + 1), ``` Instead does terrible things...
Edit: see this doc on functions supported by spark sql https://spark.apache.org/docs/2.3.1/api/sql/index.html
Let's try the dbplyr approach, which... * treats it largely as a sql source, using the default translator * allows `sparklyr` to implement custom S3 methods for `copy_to` and `collect`...