On Sat, Apr 23, 2011 at 10:37 AM, Peter Ehlers <ehl...@ucalgary.ca> wrote:
> On 2011-04-23 07:13, David Neu wrote:
>>
>> On Sat, Apr 23, 2011 at 9:47 AM, David Winsemius<dwinsem...@comcast.net>
>> wrote:
>>>
>>> On Apr 23, 2011, at 9:26 AM, David Neu wrote:
>>>
>>>> Hi,
>>>>
>>>> I'd like to change the default orientation of bwplot() and stripplot()
>>>> so the plots are displayed vertically. Passing horizontal=FALSE into
>>>> stripplot in the simple code below doesn't seem to be the answer.
>>>>
>>>> library(lattice);
>>>> x<- rnorm(100);
>>>> y<- as.factor(sapply(1:100, function(k) sample(c("A","B","C"), 1,
>>>> prob=c(1/2, 1/3, 1/6))));
>>>> my.df<- data.frame(x=x, y=y);
>>>> stripplot(~x | y, data=my.df, as.table=TRUE, layout=c(1,3), hor);
>>>
>>> A) hor is not defined
>>> B) it doesn't make sense to me to have the continuous variable as the
>>> independent variable here, despite if being named `x`.
>>>
>>> Try:
>>> stripplot(x~y , data=my.df, as.table=TRUE, layout=c(1,3),
>>> horizontal=FALSE);
>>>
>>> (I didn't recognize the as.table argument, but experimentation seems to
>>> produce a top-down order to the plots.)
>>>
>>> --
>>> David Winsemius, MD
>>> West Hartford, CT
>>>
>>>
>>
>> Many thanks for your reply!
>>
>>> A) hor is not defined
>>
>> Ugggh, cut and paste mistake.
>>
>>> B) it doesn't make sense to me to have the continuous variable as the
>>> independent variable here, despite if being named `x`.
>>
>> I have data from related experiments in that involves two variables
>> conditioned on a third. This data is displayed in an xyplot. The
>> reason I'm trying to get the vertical orientation in the stripplot is
>> that in some experiments the variable plotted on the horizontal axis
>> is invariant and in these cases for consistency I'd like the variable
>> that is plotted on the vertical axis to continue to appear vertically.
>>
>> For example in non-lattice graphics the following works:
>> stripchart(rnorm(100), vert=TRUE).
>>
>>> Try:
>>> stripplot(x~y , data=my.df, as.table=TRUE, layout=c(1,3),
>>> horizontal=FALSE);
>>
>> Yes, that's moving closer, but the strips containing the conditioning
>> info are missing.
>
> You can define a 'phantom' single-level factor
>
> my.df$fac <- rep("", 100)
> stripplot(x ~ fac | y, data = my.df, layout = c(1, 3))
>
> and I'd consider 'jitter'.
>
> BTW, your method of generating 'y' seems overly complicated:
>
> y <- sample(c("A","B","C"), 100,
> replace=TRUE,
> prob=c(1/2, 1/3, 1/6))
>
> Peter Ehlers
>
>
Ahh, that's nice.
BTW, for my understanding, could you please explain why you suggested
the use of 'jitter'? I'm thinking it's to aid in the visualization.
Many thanks for your help!
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