Another attempt at an astable flag #298

pdeffebach · 2021-09-14T20:54:05Z

This attempt should be a more robust strategy than the current @t flag in DataFrameMacros.jl.

I will outline it in more detail shortly.

pdeffebach · 2021-09-15T14:17:26Z

More progress! Not ready for a review yet as i have not added a complete test set or begun documenting.

pdeffebach · 2021-09-16T14:03:46Z

Ready for a review!

This is a big PR. In the process, I have to finally remove some deprecated functionality for grouped data frames. In particular

@by df :a (n1 = :a, n2 = :b)

used to work. In the past release we had a warning that this needed to be

@by df :a $AsTable = (n1 = :a, n2 = :b)

and now we throw an error in the original expression.

Here is the docstring for @astable

`astable(args...)`

Return a NamedTuple from a transformation inside DataFramesMeta.jl macros.

@astable acts on a single block. It works through all top-level expressions
and collects all such expressions of the form :y = x, i.e. assignments to a
Symbol, which is a syntax error outside of the macro. At the end of the
expression, all assignments are collected into a NamedTuple to be used
with the AsTable destination in the DataFrames.jl transformation
mini-language.

Concretely, the expressions

df = DataFrame(a = 1)

@rtransform df @astable begin
    :x = 1
    y = 50
    :z = :x + y + :a
end

becomes the pair

function f(a)
    x_t = 1
    y = 50
    z_t = x_t + y + a

    (; x = x_t, z = z_t)
end

transform(df, [:a] => f => AsTable)

@astable is useful when performing intermediate calculations
yet store their results in new columns. For example, the following fails.

@rtransform df begin
    :new_col_1 = :x + :y
    :new_col_2 = :new_col_1 + :z
end

This because DataFrames.jl does not guarantee sequential evaluation of
transformations. @astable solves this problem

@rtransform df @astable begin
    :new_col_1 = :x + :y
    :new_col_2 = :new_col_1 + :z
end

Examples

julia> df = DataFrame(a = [1, 2, 3], b = [4, 5, 6]);

julia> d = @rtransform df @astable begin
           :x = 1
           y = 5
           :z = :x + y
       end
3×4 DataFrame
 Row │ a      b      x      z
     │ Int64  Int64  Int64  Int64
─────┼────────────────────────────
   1 │     1      4      1      6
   2 │     2      5      1      6
   3 │     3      6      1      6

julia> df = DataFrame(a = [1, 1, 2, 2], b = [5, 6, 70, 80]);

julia> @by df :a @astable begin
           $(DOLLAR)"Mean of b" = mean(:b)
           $(DOLLAR)"Standard deviation of b" = std(:b)
       end
2×3 DataFrame
 Row │ a      Mean of b  Standard deviation of b
     │ Int64  Float64    Float64
─────┼───────────────────────────────────────────
   1 │     1        5.5                 0.707107
   2 │     2       75.0                 7.07107

This implementation is more complicated than that of @t from DataFrameMacros.jl. In DataFrameMacros.jl, the following will fail

df = DataFrame(a = 1)
@transform df @t begin 
    :x = 1
    b + :x 
end

this is because it sends :x to src in src => fun => dest even though it doesn't exist in the DataFrame. @astable does not have this problem, at the cost of a more complicated implementation.

cc @bkamins @nalimilan

bkamins · 2021-09-16T14:09:19Z

transform(df, [:a] => f => AsTable)

I would think it should be transform(df, [:a] => ByRow(f) => AsTable)?

pdeffebach · 2021-09-16T14:17:32Z

Good catch. Will update.

nalimilan

Looks pretty cool! This will require a breaking release, right?

Using @astable to ensure operations are run sequentially is clever. The name is a bit surprising for this, but well... I also hope the compilation overhead isn't too large.

nalimilan · 2021-09-19T17:04:32Z

src/macros.jl

+julia> @by df :a @astable begin
+           $(DOLLAR)"Mean of b" = mean(:b)
+           $(DOLLAR)"Standard deviation of b" = std(:b)
+       end


This example can be achieved without @astable, right? Maybe do m = mean(:b); std(:b, mean=m) to illustrate the power of this function? Or, simpler, call extrema(:b) to create two columns.

Also, I wouldn't use long column names with spaces in them: better illustrate a single feature at a time.

great. changed.

src/parsing_astable.jl

src/parsing.jl

src/macros.jl

nalimilan · 2021-09-19T17:19:32Z

src/macros.jl

+`@astable` is useful when performing intermediate calculations
+yet store their results in new columns. For example, the following fails.
+
+```
+@rtransform df begin
+    :new_col_1 = :x + :y
+    :new_col_2 = :new_col_1 + :z
+end
+```
+
+This because DataFrames.jl does not guarantee sequential evaluation of
+transformations. `@astable` solves this problem


While this is an interesting side-effect, the main goal of AsTable is to allow returning multiple columns from a single "function". Probably worth mentioning? For example it's useful with extrema to compute the minimum and the maximum at the same time.

src/macros.jl

pdeffebach · 2021-09-21T13:27:11Z

Using @astable to ensure operations are run sequentially is clever. The name is a bit surprising for this, but well... I also hope the compilation overhead isn't too large.

This macro does more than that. It allows for local variables to per persistent as well. If I were to just force sequential transform calls, I would just create a transform call for each :y = f(:x) expression.

Co-authored-by: Milan Bouchet-Valat <[email protected]>

…eta.jl into astable_2

pdeffebach · 2021-09-21T15:54:14Z

This is ready for another round of reviews. I have added docs to the manual as well.

bkamins · 2021-09-21T17:19:31Z

docs/src/index.md

+information. 
+
+In a single block, all assignments of the form `:y = f(:x)` 
+or `$y = f(:x)` at the top-level are generate new columns.


Suggested change

or `$y = f(:x)` at the top-level are generate new columns.

or `$y = f(:x)` at the top-level generate new columns.

maybe add what $y has to resolve to (I understand it has to be Symbol, or strings are also accepted?)

Good catch. Turns out I was allowing unexpected behavior and patched the code.

src/macros.jl

bkamins · 2021-09-21T17:37:33Z

src/macros.jl

+
+Column assignment in `@astable` follows the same rules as
+column assignment more generally. Construct a new column
+from a string by escaping it with `$DOLLAR`.


can you add an example of this?

src/macros.jl

pdeffebach · 2021-09-22T22:14:13Z

Thanks, I've responded to the most recent round of reviews.

I have added more tests. I can't think of any new tests to add at the moment, they seem pretty well covered.

pdeffebach · 2021-09-22T22:17:47Z

cc @jkrumbiegel, if you want to review.

nalimilan · 2021-09-23T07:50:39Z

This macro does more than that. It allows for local variables to per persistent as well. If I were to just force sequential transform calls, I would just create a transform call for each :y = f(:x) expression.

Yes I know. What I'm saying is that mentioning sequential operations as the main justification for it was a bit weird.

src/macros.jl

src/parsing_astable.jl

nalimilan · 2021-09-23T07:44:04Z

test/astable_flag.jl

+        :b_max = ex[2]
+    end
+
+    @test sort(d.b_min) == [5, 7]


This kind of test is quite fragile. Better sort the whole data frame and compare it to the reference to make sure that groups and values match.

…eta.jl into astable_2

Co-authored-by: Milan Bouchet-Valat <[email protected]>

pdeffebach · 2021-09-23T14:48:15Z

I don't understand the changes to the github review interface, but I think i've addressed lingering issues.

I just added some checks to make sure you can't do @passmissing and @astable at the same time. I think this is intuitive in the @byrow case, but I want to finish #276 , which makes @passmissing work on column-wise transformations, before I do this.

pdeffebach · 2021-09-23T14:48:33Z

Tests pass and this can be merged.

bkamins · 2021-09-23T17:58:38Z

test/astable_flag.jl

+end
+
+@testset "@astable with just assignments, mutating" begin
+    # After finalizing above testset


@pdeffebach - this seems to be WIP?

Sorry about that. Thank you working on it now.

bkamins · 2021-09-23T17:59:32Z

test/astable_flag.jl

+
+    d = @rtransform df @astable begin
+        :x = 1
+


newline is not needed. Also I am not clear why you add nothing here and below? Does it change anything?

oh, I remember.

@transform df begin :x = 1 end

is valid code and does the same thing as the same with @astable does. So I wanted to test something that made sure it was hittng the @astable path and not the vanilla path.

I have deleted the extra new lines.

test/astable_flag.jl

pdeffebach

Thanks for the round of reviews. I think I have addressed everything. Sorry about forgetting some of the tests.

src/macros.jl

pdeffebach · 2021-09-23T18:04:39Z

test/astable_flag.jl

+end
+
+@testset "@astable with just assignments, mutating" begin
+    # After finalizing above testset


Sorry about that. Thank you working on it now.

pdeffebach · 2021-09-23T20:53:55Z

test/astable_flag.jl

+
+    d = @rtransform df @astable begin
+        :x = 1
+


oh, I remember.

@transform df begin :x = 1 end

is valid code and does the same thing as the same with @astable does. So I wanted to test something that made sure it was hittng the @astable path and not the vanilla path.

I have deleted the extra new lines.

test/astable_flag.jl

bkamins

Looks good. Just please check why Documenter fails before merging. Thank you!

docs/src/index.md

src/macros.jl

nalimilan · 2021-09-24T07:44:30Z

src/parsing.jl

+    println(MacroTools.prettify(fun))
+


Suggested change

println(MacroTools.prettify(fun))

Co-authored-by: Milan Bouchet-Valat <[email protected]>

pdeffebach · 2021-09-24T13:32:42Z

Thanks for the review. @nalimilan ready to merge?

bkamins · 2021-09-24T22:00:14Z

Bravo!

pdeffebach added 3 commits September 14, 2021 12:52

initial attempt

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finally working

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start adding tests

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pdeffebach mentioned this pull request Sep 15, 2021

add astable macro #291

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pdeffebach added 5 commits September 16, 2021 04:58

more tests

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more tests

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add docstring

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tests pass

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add type annotation

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better docs

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update index.md

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Co-authored-by: Milan Bouchet-Valat <[email protected]>

Merge branch 'astable_2' of https://github.com/pdeffebach/DataFramesM…

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…eta.jl into astable_2

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clean named tuple creation

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add example with string

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changes

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Merge branch 'astable_2' of https://github.com/pdeffebach/DataFramesM…

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…eta.jl into astable_2

fix some errors

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add macro check

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add errors for bad flag combo

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better grouping tests

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Update src/parsing_astable.jl

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Co-authored-by: Milan Bouchet-Valat <[email protected]>

add snipper to transform, select, combine, by

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pdeffebach merged commit cc066df into JuliaData:master Sep 24, 2021

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Another attempt at an astable flag #298

Another attempt at an astable flag #298

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	or `$y = f(:x)` at the top-level are generate new columns.
	or `$y = f(:x)` at the top-level generate new columns.

Another attempt at an astable flag #298

Another attempt at an astable flag #298

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pdeffebach commented Sep 14, 2021

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astable(args...)

Examples

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`astable(args...)`

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