Comments (3)
I tend to prefer using existing functionality. This could be:
df[Symbol(variable, :_std)] = df[:a] + df[:b]
# or
df[Symbol(variable, :_std)] = @with df :a + :b
To implement this in the @transform
macro, you'd need to add the capability to:
https://github.com/JuliaStats/DataFramesMeta.jl/blob/master/src/DataFramesMeta.jl#L408
The first step would be to identify the syntax to use. Something like @suffix()
might be better because it tags where the magic is happening.
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I agree that the normal DataFrames is easy, but I think Symbol()
is a bit ugly and would prefer something more user-facing. I will try and take a crack at this by the end of the week.
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On second thought, it would be best to start with a more basic task: Be able to use an arbitrary vector column names to create new columns.
I think the main issue is the inconsistency between
@transform(df, newCol = f(:oldCol))
and
df[:newCol] = f(df[:oldCol])
With DataFrames, you could have a vector of symbols [:newVar1, :newVar2, ...] and use that to create a bunch of new variables. There is no equivalent way to rename variables with DataFramesMeta. So that might be a task that takes precedence over any suffix commands.
from dataframesmeta.jl.
Related Issues (20)
- operators do not work inside function call inside macros HOT 3
- typos HOT 3
- Macro @rolling for scrolling through a column or columns of values? HOT 3
- Add a `@bycol` macro-flag HOT 5
- Add metadata for working with DataFrames HOT 1
- Access subdf in @by and @combine HOT 7
- Request - grouped by columns available as single values rather than vectors HOT 5
- Request: `@order` to mimic `DataFrames.order` in `@orderby` HOT 2
- Very slow `@astable` macro outside a function HOT 4
- `@with` macro clashes with `Base.@with` in Julia 1.11+ HOT 8
- `ByRow` not defined when importing DataFramesMeta HOT 1
- docs question HOT 7
- Request @rsubset_rtransform HOT 7
- Special-case `==` as with other one-argument functions HOT 2
- Add an alternative syntax escaping than `$` HOT 1
- MethodError occurred when broadcasting a string inside @astable HOT 3
- Speculative future of `@groupby` macro
- Allow reference to previously defined columns in @transform HOT 7
- `groupby` derived columns
- Add convenience function to look up a single value in a `DataFrame` HOT 2
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