Caleb Donovick wrote:
> > It captures a tiny fraction of Pandas style filtering
> > while complicating
> > the syntax of Python
> > Sure maybe I we can't represent all filters super concisely but at least
> inequalities, or any filter on single axis, would not be hard. E.g.
> db[x=LT(1)] == db[db.x < 1]
Django for example allows filtering with keyword args including inequalities in
this way: `x__lt=1` (which translates to "x < 1"). Whether that's more readable
or not is another question but at least with "keyword args" in `[]` every
package could come up with its own specifications on how this is used.
> Granted I don’t really see a way to express logical connectives between
> filters in a beautiful way -- beyond doing something like db[filter=OR(x=1,
> y=2)] which really isn't any better than db.filter(OR(x=1, y=2))
> > db['x=1']
> > Ah yes cause parsing strings is a reasonable replacement for language
> support. I have no idea why Pandas dropped support for this but I have to
> imagine it's because it's horribly ugly, prone to bugs and difficult to
> metaprogram.
Pandas didn't drop the support for query strings, they can be used via the
`df.query` method. For example: `df.query('x == 1 and y == 2')`. That's equally
explicit but creating query strings (dynamically) has of course its downsides.
Given that `[]` is used for element access, extending it to further use cases
is indeed appealing.
On the other hand one could always argue that a functional interface equally
does the job, e.g. pandas could provide a function accepting keyword args:
`df.select(x=1, y=2)`. Or the Django style: `Q(x=1) | Q(y__lt=2)`.
Semantically meaningful strings are terrible. Everytime I
> write a string literal for any reason other than I a want human to read
> that string I die a little inside. Which is part of the reason I want
> db[x=1] instead of db[{'x':1}]. And yes everything is a string under the
> hood in python but that doesn't make semantic strings less terrible. Really
> under the hood (in assembly) everything is gotos but that doesn't make
> their use better either. /rant
> On Mon, Oct 7, 2019 at 10:07 PM David Mertz me...@gnosis.cx
> wrote:
> > It's really not a worthwhile win. It captures a tiny
> > fraction of Pandas
> > style filtering while complicating the syntax of Python. Here's another
> > Pandas filter:
> > db[db.x < 1]
> >
> > No help there with the next syntax. Here's another:
> > db[(db.x == 1) | (db.y == 2)]
> >
> > A much better idea doesn't require any changes in Python, just a clever
> > class method. Pandas did this for a while, but deprecated it because...
> > reasons. Still, the OP is free to create his version:
> > db['x=1']
> >
> > Or
> > db['x<1']
> > db['x=1 or y=2']
> >
> > You can bikeshed the spelling of those predicates, but it doesn't matter,
> > they are just strings that you can see however you decide is best.
> > On Mon, Oct 7, 2019, 8:38 PM Steven D'Aprano st...@pearwood.info wrote:
> > On Tue, Oct 08, 2019 at 09:19:07AM +1100,
> > Cameron Simpson wrote:
> > On 07Oct2019 10:56, Joao S. O. Bueno jsbu...@python.org.br wrote:
> > So, in short, your idea is to allow "=" signs
> > inside [] get notation
> > to
> > be translated
> > to dicts on the call,
> > Subjectively that seems like a tiny tiny win. I'm quite -1 on this
> > idea;
> > language spec bloat to neglible gain.
> > As per Caleb's initial post, this is how Pandas currently does it:
> > db[db['x'] == 1]
> >
> > Replacing that with db[x=1] seems like a HUGE win to me.
> > Even db[{'x': 1}] is pretty clunky.
> > --
> > Steven
> >
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