Thanks for the reply. I will add it to the documentation and will work
on a use case and recipe for the n highest frequency problem.
As for
>I'm not sure if this would be better as an attribute kept directly or as a
>property that called `sum(self.values())` when accessed. I believe that
>havi
I added a couple comments at https://bugs.python.org/issue25478 about what
I mean. Raymond replied as well. So it feels like we should use that
thread there.
In a scientific context I often think of a Counter as a way to count
observations of a categorical variable. "I saw 3 As, then 7 Bs, etc"
On Tue, Mar 14, 2017 at 08:52:52AM -0700, David Mertz wrote:
> But I can imagine an occasional need to, e.g. "find outliers." However,
> that is not hard to spell as `mycounter.most_common()[-1*N:]`. Or if your
> program does this often, write a utility function `find_outliers(...)`
That's not
On Wed, Mar 15, 2017 at 10:39 AM, Steven D'Aprano
wrote:
> > But I can imagine an occasional need to, e.g. "find outliers." However,
> > that is not hard to spell as `mycounter.most_common()[-1*N:]`. Or if
> your
> > program does this often, write a utility function `find_outliers(...)`
>
> Tha
On 2017-03-15 11:06, David Mertz wrote:
Just because a data point is uncommon doesn't mean it is an outlier.
That's kinda *by definition* what an outlier is in categorical data!
Not really. Or rather, it depends what you mean by "uncommon". But
this thread is about adding "least_commo
On Wed, Mar 15, 2017 at 11:14 AM, Brendan Barnwell
wrote:
> Exactly. If you have one data point that occurs once, another that occurs
> twice, another that occurs three times, and so on up to 10, then the "least
> common" one (or two or three) isn't an outlier. To be an outlier, it would
> have
On Wed, Mar 15, 2017 at 11:06:20AM -0700, David Mertz wrote:
> On Wed, Mar 15, 2017 at 10:39 AM, Steven D'Aprano
> wrote:
>
> > > But I can imagine an occasional need to, e.g. "find outliers." However,
> > > that is not hard to spell as `mycounter.most_common()[-1*N:]`. Or if
> > your
> > > pro
