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You can, but then every step starts with a drop table if exists; insert into …



Or you nest your queries:

    select second from (select 42 as first, (select 69) as second);
Intermediate steps won't be stored but until queries take a while to execute it's a nice way to do step-wise extension of an analysis.

Edit: It's a rather neat and underestimated property of query results that you can query them in the next scope.


We all have different definitions on what is difficult. Maybe annoying or bothersome had been better words, but below beats nesting things:

    df |> select(..) |>
        filter(...) |>
        mutate(...) |>
        ...
And every time I've learned something about the intermediate result I can add another line, or save the result in a new variable and branch my exploration. And I can easily just highlight and run and number of of steps from step 1 onwards.

Even oldschool

    df2 <- df[...]
    df2 <- df2[...]
Gives me the same benefit.


Yeah, sure, I do a lot of such things in RAM in Elixir, some Lisp, PHP or, if I must, Python.

But sometimes I just happen to have just imported a data set in a SQL client or I'm hooked into a remote database where I don't have anything but the SQL client. When developing an involved analysis query nesting also comes in handy sometimes, e.g. to mock away a part of the full query.



Absolutely, if the engine has them and they're not wonky somehow.




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