[R] 'matplot' for matrix with NAs: broken lines
Martin Maechler
maechler at stat.math.ethz.ch
Thu May 6 18:34:22 CEST 2010
>>>>> "TS" == Tao Shi <shitao at hotmail.com>
>>>>> on Wed, 5 May 2010 20:11:26 +0000 writes:
TS> Thanks, Gabor! So, there is no way I can change some graphic parameters in 'matplot' to get this?
TS> I forgot to mention that I purposely use type="b", so I know where the missing data are. With imputed data, either using "b" or "l", there is no way to keep track of NAs. Plus, in my real data sometimes there is only one non-missing value in a particular column and na.approx can't work (well I could selectively impute the NAs ... )
TS> So far, my best solution to this is to use "xyplot". It does this by default, but of course I need some data manipulation first.
"does this by default" meaning what?
I don't think it does impute missing, does it?
Can you elaborate, using your example (below)?
I found Gabor's answer appropriate,
I really cannot see why matplot() should behave differently here...
----
Martin Maechler
TS> ----------------------------------------
>> From: ggrothendieck at gmail.com
>> Date: Wed, 5 May 2010 15:45:44 -0400
>> Subject: Re: [R] 'matplot' for matrix with NAs: broken lines
>> To: shitao at hotmail.com
>> CC: r-help at r-project.org
>>
>> Try this:
>>
>> library(zoo)
>> matplot(na.approx(b), type = "l")
>>
>> On Wed, May 5, 2010 at 2:30 PM, Tao Shi wrote:
>>>
>>> Hi list,
>>>
>>> I know that points involving NAs are not plotted in 'matplot', but when I plot them as lines, I still want the lines to connect all the points (i.e. not broken where there are NAs). Please see the example below. How can I achieve this in 'matplot'? If I can't, any good alternatives so I don't have to use 'plot' + 'lines' and loop through all the columns.
>>>
>>> Many thanks!
>>>
>>> ...Tao
>>>
>>>> set.seed(1234)
>>>> a=b=matrix(rnorm(9), 3,3)
>>>> b[2,2]=NA
>>>> matplot(a, type="b")
TS> [[elided Hotmail spam]]
>>>> matplot(b, type="l") ## Now my data for the second column are missing from the graph
>>>
>>>
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