Well... first off, there's a trivial conversion to tacit available here:
13 :'h{"1~\:1{h=.(~.,:#/.~)n=.y'
[: (] {"1~ [: \: 1 { ]) ~. ,: #/.~
And I guess that's good enough, so let's just name it:
hsbc=: 13 :'h{"1~\:1{h=.(~.,:#/.~)n=.y'
n=: 9 13 6 9 13 13 10 14 7 14
As for vertical boxes, maybe something like this would be close enough
to what you want?
vbox=: ]each@{.,:'#' ,.@#each~ {:
vbox hsbc n
+--+-+--+-+--+-+
|13|9|14|6|10|7|
+--+-+--+-+--+-+
|# |#|# |#|# |#|
|# |#|# | | | |
|# | | | | | |
+--+-+--+-+--+-+
Though personally, I might be more inclined towards horizontal boxes
(partially because the proportional font I see used in email contexts
messes up vertical boxes so badly, but also see my hbar suggestion)
hbox=: ]each@{.,.'#' #each~ {:
hbox hsbc n
Or, getting rid of the boxes:
hbar=: ":@,.@{. ,.' ' ,. '#' #every~ {:
hbar hsbc n
13 ###
9 ##
14 ##
6 #
10 #
7 #
(This sort of thing still looks better with a fixed width font, in my opinion.)
Thanks,
--
Raul
On Fri, Jul 24, 2020 at 6:45 PM Skip Cave <[email protected]> wrote:
>
> I find that a histogram of the data sorted by count, is useful in many
> cases, in place of the mode:
>
> ]n=.?10#15
>
> 9 13 6 9 13 13 10 14 7 14
>
> h{"1~\:1{h=.(~.,:#/.~)n
>
> 13 9 14 6 10 7
>
> 3 2 2 1 1 1
>
>
> I'm sure there are more concise ways to express this, and it would be nice
> to have vertical boxes for each quantity, but this gets what I need done.
>
>
> Skip
>
> Skip Cave
> Cave Consulting LLC
>
>
> On Fri, Jul 24, 2020 at 1:47 PM Raul Miller <[email protected]> wrote:
>
> > https://en.wikipedia.org/wiki/Mode_(statistics)#Uniqueness_and_definedness
> >
> > "Finally, as said before, the mode is not necessarily unique. Certain
> > pathological distributions (for example, the Cantor distribution) have
> > no defined mode at all."
> >
> > That said, just as we can redefine median to be the mean of the two
> > median values when the length of the sequence is even, we could
> > redefine mode as the median of the candidate mode values when there is
> > more than one "most frequently occuring value".
> >
> > Thanks,
> >
> > --
> > Raul
> >
> > On Fri, Jul 24, 2020 at 2:36 PM Devon McCormick <[email protected]>
> > wrote:
> > >
> > > Hi - I've started reading "Fun Q" which is a book on machine learning
> > using
> > > the q language. Early on, the author points out that his "mode"
> > function -
> > > where "mode" is stats-talk for "the most frequent observation" - is
> > > order-dependent.
> > >
> > > I checked my own "mode" and found that this is true of mine as well:
> > > mode
> > > ~. {~ [: (i. >./) #/.~
> > > mode 1 2 2 3 3
> > > 2
> > > mode 1 3 3 2 2
> > > 3
> > >
> > > This might be an ill-defined statistical concept but does anyone have any
> > > insight based on practice? Is this order-dependence just a weakness of
> > the
> > > definition of "mode"?
> > >
> > > I could not find "mode" defined in any of the J standard libraries.
> > >
> > > Thanks,
> > >
> > > Devon
> > >
> > > --
> > >
> > > Devon McCormick, CFA
> > >
> > > Quantitative Consultant
> > > ----------------------------------------------------------------------
> > > For information about J forums see http://www.jsoftware.com/forums.htm
> > ----------------------------------------------------------------------
> > For information about J forums see http://www.jsoftware.com/forums.htm
> >
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