Does Query.jl have a good way to implement mutations that depend on each other?

Specific Domains Data
1

The following doesn’t work because latter definitions can’t depend on previous ones:

DataFrame(bad=[1,2], good=[0, 3]) |> @map((
			count = _.bad + _.good,
			bad_rate = _.bad/_.count,
			bad_pct =round(_.bad_rate*100;digits=1)
		))

Is there any convenient way to do such things? I thought @mutate might work, but it doesn’t.

2

I think I’ve found a way to do this using the LINQ @let syntax. It’s a little longer, but it seems pretty clear to me.

	df = DataFrame(bad=[1,2], good=[0, 3]) 
	
	@from i in df begin
		@let count = i.bad + i.good
		@let bad_rate = i.bad/count
		@let bad_pct =round(bad_rate*100;digits=1)
		@select {i.good, i.bad, count, bad_rate, bad_pct}
		@collect DataFrame  # Optional
	end

The two styles can even be combined if necessary, with only a little contortion:

DataFrame(bad=[1,2], good=[0, 3]) |> df -> (
	@from i in df begin
		@let count = i.bad + i.good
		@let bad_rate = i.bad/count
		@let bad_pct =round(bad_rate*100;digits=1)
		@where bad_rate > 0.7
		@select {i.good, i.bad, count, bad_rate, bad_pct}
	end) |> save("somewhere.csv")
3

I would write this as

DataFrame(bad=[1,2], good=[0, 3]) |>
@mutate(count = _.bad + _.good) |>
@mutate(bad_rate = _.bad/_.count) |>
@mutate(bad_pct =round(_.bad_rate*100;digits=1))
4

That works. Thanks!