[R] graphs

Fri Mar 13 17:27:06 CET 2015

__Dear all,

You can see the plot specif curves in the enclosed document. Inclusion of all plot specif curves in one plot may not be look  good and finally it will be unreadable. I am agree with Petrr and John. This graph is more readable.

Best regards
Salam

______________________________________
From: John Kane <jrkrideau at inbox.com>
Sent: Friday, March 13, 2015 4:12 PM
To: PIKAL Petr; Mir Salam; r-help at r-project.org
Subject: Re: [R] graphs

@Petr

I agree. I think Mir would get a totally unreadable graph. I occasionally look at some spagetti graphs from climate research, and I find 8 - 12 lines are incomprehensible (I'm not a subject matter expert)'

@Mir

Is there any logical way to break down the data ? I think Petr is correct in that ggplot2 should be able to do it but I'd suggest thinking about, perhaps, facetting the data to produce some reasonable number of panels.

Here is a simple three-panel plot to illustrate what I mean but I have easily produced a 9 or 10 panel plot which reduces visual clutter immensely.

library(plyr) library(ggplot2)

df1 = data.frame(basel_asset_class = c("bank","bank","bank","bank","bank","bank","bank","corporate","corporate","corporate","corporate","corporate","corporate","corporate","sovereign","sovereign","sovereign","sovereign","sovereign","sovereign","sovereign"), ratings = c("AAA","AA","A","BBB","BB","B","CCC","AAA","AA","A","BBB","BB","B","CCC","AAA","AA","A","BBB","BB","B","CCC"), default_probability = c(0.0027,0.0029,0.0031,0.0034,0.0037,0.004,0.0043,0.0025,0.0024,0.0024,0.0023,0.0022,0.0021,0.0021,0.003,0.0031,0.0032,0.0033,0.0034,0.0035,0.0036))

names(df1) <- c("class", "rate", "default")

p <- ggplot(df1, aes(rate, default,colour=class)) + geom_point() + facet_grid(class ~.) + theme(legend.position="none")
p

John Kane
Kingston ON Canada

> -----Original Message-----
> From: petr.pikal at precheza.cz
> Sent: Fri, 13 Mar 2015 11:34:42 +0000
> To: mir.salam at uef.fi, r-help at r-project.org
> Subject: Re: [R] graphs
>
> Hi
>
> Your example is not reproducible, but I presume you could use ggplot
> together with predict. However, I wonder how do you want to distinguish
> 68 curves in one picture.
> I would
>
> Cheers
> Petr
>
>
>> -----Original Message-----
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Mir
>> Salam
>> Sent: Sunday, March 08, 2015 10:57 PM
>> To: r-help at r-project.org
>> Subject: [R] graphs
>>
>> Dear all,
>>
>>  I need help to get different 68  plots specifc fitted curves in one
>> plot with respective field data observations (age vs dominant height).
>>
>>
>>
>> aspdomH2<-groupedData(domH2~age|plotno,data=aspdomH2)
>>
>>
>>
>> names(aspdomH2)
>>
>> plotno, age, origin, soilcharacter, domH2,
>>
>>
>>
>> plotno-different plot no. I have 68 plots
>>
>> age- every plot have from age 5 to 30 years
>>
>> origin- two, native aspen and hybrid aspen
>>
>> domH2<-dominant height
>>
>> soilcharacter-3, clay, silt and mold. both origin have different soil
>> charcter
>>
>>
>>
>> #### then I fit model
>>
>> fm2cham.nlme<-nlme(domH2~cham(age,b0,b1,b2),
>>                data=aspdomH2,
>>                fixed = list(b0~1+origin+soilcharacter,b1~ 1,b2 ~
>> 1+origin+soilcharacter),
>>                random = b0+b2~1|plotno,
>>                start=c(b0=26.3387,0,0,0,b1=0.1065,b2=1.9453,0,0,0),
>>                weights=varPower(form = ~age, 0.5),
>>                correlation=corAR1())
>>
>>
>>
>> #### parameter values
>>
>> Fixed effects: list(b0 ~ 1 + origin + soil character, b1 ~ 1, b2 ~ 1 +
>> origin + soil character)
>>
>>                                         Value
>> b0.(Intercept)                 21.081124
>> b0.origin1                        7.735064
>> b0.soilcharactermold   10.689051
>> b0.soilcharactersilt       3.906585
>> b1                                      0.079035
>> b2.(Intercept)                  1.616360
>> b2.origin1                        -0.384421
>> b2.soilcharactermold      0.612285
>> b2.soilcharactersilt          0.527462
>>
>>
>>
>> ##### I can easily get the augmented plot.  I got  different 68 plots
>> specific curves.
>>
>> #######
>>
>> Any body can help me how can I will get all 68 plots specific fitted
>> curves in one plot with respective plot specific age and dominant
>> height obervations? (x axis will represent age, y axis will represent
>> dominant height and fitted curves of all 68 plots)
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>       [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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>> PLEASE do read the posting guide http://www.R-project.org/posting-
>> guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
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