thr3ads.net - R help - [R] Color-coding data points in complex dotplot (ggplot2) [Apr 2019]

If this information is useful, please help other people find it:
Share via:

Michael Eisenring

2019-Apr-05 23:53 UTC

[R] Color-coding data points in complex dotplot (ggplot2)

Dear R-List members,

I produced a dot plot (see attachment 1) on 6 different treatments (trees
under 6 different conditions; in column " Location.Treatment " in my
raw
data). For each of these " Location.treatment" categories, I
calculated a
mean value and the SE for a specific compound (%CT).

I am able to produce a plot where all the 6 treatments (in column "
Location.Treatment") are separated (see code and Fig. 1) so that each of
two
"con" and "exp" treatments (in the column
"treatment") are nested within one
of the three locations (High, mid, low; in the column "Location") (see
plot
that the code produces). This is the plot structure I want.

Now I would like to assign colors to the raw data points ( the "point
cloud"
next to each mean +SE value). Each of these points stems from a different
"Genotype" and I would like to color code the points with regard to
the
genotypes (e.g. all points from Genotype A should be green, all points from
Genotype B should be red etc.) I would like to use my own specified colors
in the code (not the standard palette).

I tried did the following (without success)

1.      I added "aes(color=Genotype,.." into
"geom_point(..)"

2.      I added my specific colors to "scale_color_manual"

scale_color_manual(labels=c("Control","Damaged"),values=c("red","black","#06
7c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3"....
..



However, if I do that my "nested" plot structure disappears (i.e. I
cannot
visually differentiate between "con" and "exp" treatments
nested within mid
/high/. See Fig. 2)

Basically, all I want is to produce a plot that looks like the one from my
actual code( Fig.1) but where the individual data points are colored
according to "Genotypes"

Below is my code and my raw data.

Help is very much appreciated!

Thanks a lot,

Mike



#CODE-----------------------------------------------------

require(ggplot2)



#REMOVE START FOR ANALYSIS

dta<-subset(dta_complete,Time=="Stop")

dta



#Calculation of SE

data_summary <- function(x) {

  m <- mean(x)

  ymin <- m-sd(x)/sqrt(length(x))

  ymax <- m+sd(x)/sqrt(length(x))

  return(c(y=m,ymin=ymin,ymax=ymax))

}



pd1 = position_dodge(0.5)



plot_CT<- ggplot(dta, aes(x=Location, y=CT,
colour=Treatment,shape=Treatment)) +

  stat_summary(fun.data=data_summary, position=pd1, geom="errorbar",
width=0.05) +

  stat_summary(fun.data=data_summary, position=pd1, geom="point",
size=2) +

  geom_point(position=position_jitterdodge(dodge.width=0.8, jitter.height=0,
jitter.width=0.2),

             alpha=0.7) +

  labs(title="", x="", y = "CT (% dw)")+

  scale_color_manual(labels=c("Control",
"Damaged"),values=c("red","black"),guide =
guide_legend(reverse = TRUE) )+

  scale_shape_manual(labels=c("Control",
"Damaged"),name="Treatment",values
= c(16,16),guide = guide_legend(reverse = TRUE) )+

  #Style of background

  theme_classic()+

  #Change title

  theme(plot.title = element_text(color="black", size=17,
face="bold"))+

  #Font size axis

  theme(axis.text=element_text(size=12),

        axis.title=element_text(size=17))+

  scale_x_discrete("Location",labels = c("Low",
"Mid", "High"),expand=c(0.1,
0.5))+

  coord_flip()



plot_CT



#DATA-----------------------------------------------------------------------
-----------------

structure(list(Location = structure(c(2L, 3L, 1L, 2L, 3L, 1L,

2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,

1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,

2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,

3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,

1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,

3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,

1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,

2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,

3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,

1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,

2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,

3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), .Label = c("High", "Low",
"Mid"

), class = "factor"), Treatment = structure(c(2L, 2L, 2L, 1L,

1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,

1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,

2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,

1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,

1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,

2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,

2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,

1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,

2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,

2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,

1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,

2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Con",
"Exp"

), class = "factor"), Time = structure(c(2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Start",
"Stop"

), class = "factor"), Genotype = structure(c(7L, 7L, 7L, 7L,

7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L,

2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 1L,

1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L,

4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L,

6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 7L,

7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L,

1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,

4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L,

7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L,

2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L,

1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L,

8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("A",
"B",

"C", "D", "E", "F", "G",
"H"), class = "factor"), Time.Location structure(c(5L,

6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 4L, 5L, 6L, 4L,

5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,

6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,

4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,

5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,

6L, 4L, 5L, 6L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,

5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,

6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,

4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,

5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,

6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,

4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L), .Label =
c("StartHigh",


"StartLow", "StartMid", "StopHigh",
"StopLow", "StopMid"), class "factor"),

    Location.Treatment = structure(c(4L, 6L, 2L, 3L, 5L, 1L,

    4L, 6L, 2L, 3L, 5L, 1L, 4L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,

    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,

    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,

    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,

    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,

    5L, 1L, 4L, 6L, 2L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,

    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,

    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,

    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,

    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,

    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,

    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,

    2L, 3L, 5L, 1L), .Label = c("HighCon", "HighExp",
"LowCon",

    "LowExp", "MidCon", "MidExp"), class =
"factor"), CT = c(4.61538,

    3.96739, 7.34797, 3.58108, 2.89655, 2.7993, 10.56122, 10.68396,

    15.57252, 6.79245, 9.23469, 9.18, 1.1087, 4.26136, 1.14504,

    2.20238, 3.15789, 9.54082, 11.05263, 15.84783, 10.48986,

    12.62195, 15.12931, 5.51471, 8.20313, 11.85811, 3.38115,

    7.5, 9.69512, 8.64407, 11.30597, 14.42797, 8.8125, 11.82482,

    11.53061, 6.97674, 9.62766, 10.88028, 5.50403, 9.73558, 8.56419,

    11.84524, 16.34892, 18.15789, 10.58036, 14.80932, 12.06081,

    12.96992, 9.86014, 12.45652, 6.625, 6.93396, 9.10714, 3.66142,

    9.19811, 10.88346, 2.88851, 6.85096, 10.27778, 8.29787, 13.00885,

    14.38017, 7.5, 11.77734, 13.84615, 2.22772, 5.28, 5.25641,

    1.0514, 2.73256, 4.11111, 11.39098, 11.10236, 13.00781, 7.95259,

    10.15748, 13.16327, 8.90625, 10.04587, 13.625, 6.27049, 9.27966,

    10.94037, 5.80189, 7.76978, 7.34266, 3.80952, 3.75, 7.29545,

    10.45872, 16.83206, 5.95238, 7.70833, 10.92391, 11.03659,

    14.39338, 14.88281, 8.22917, 11.63603, 14.7561, 11.9469,

    14.65649, 16.84615, 8.37209, 13.27982, 13.69128, 7.77778,

    12.59124, 12.32955, 7.00472, 8.41121, 7.22222, 9.43878, 10.33613,

    14.16667, 9.60526, 8.77232, 11.91589, 7.01786, 12.29592,

    11.83673, 8.55634, 11.17347, 12.68836, 2.7551, 6, 7.21374,

    2.52101, 4.03846, 4.80634, 5.49569, 4.78723, 6.02273, 3.04511,

    3.59244, 2.48239, 1.54412, 5.74219, 7.68595, 1.33065, 2.625,

    4.42164, 9.66942, 11.875, 17.91667, 10.81731, 13.05288, 16.23853,

    11.93662, 14.31818, 14.09396, 7.82374, 15.5042, 10.86207,

    6.87023, 11.69492, 12.65957, 3.48684, 5.29018, 7.89474, 10.53309,

    17.05479, 16.63866, 7.43119, 12.06522, 12.05607, 6.14865,

    10.44, 14.69512, 9.24757, 9.04018, 12.38255, 2.22222, 3.90756,

    5.85616, 2.23958, 3.8125, 3.01056, 11.60256, 12.22222, 11.8007,

    7.76316, 10.08197, 12.78777, 9.20455, 12.1875, 16.59449,

    6.82331, 10.91518, 11.5748)), row.names = 192:381, class =
"data.frame")

John Kane

2019-Apr-06 12:23 UTC

head link

[R] Color-coding data points in complex dotplot (ggplot2)

HI Michael
Your code runs but we did not get any attached figure.  You might want
to try sending it as a .pdf file. They usually make it through the
spam filters

On Sat, 6 Apr 2019 at 08:09, Michael Eisenring <michael.eisenring at
gmx.ch> wrote:>
> Dear R-List members,
>
> I produced a dot plot (see attachment 1) on 6 different treatments (trees
> under 6 different conditions; in column " Location.Treatment " in
my raw
> data). For each of these " Location.treatment" categories, I
calculated a
> mean value and the SE for a specific compound (%CT).
>
> I am able to produce a plot where all the 6 treatments (in column "
> Location.Treatment") are separated (see code and Fig. 1) so that each
of two
> "con" and "exp" treatments (in the column
"treatment") are nested within one
> of the three locations (High, mid, low; in the column "Location")
(see plot
> that the code produces). This is the plot structure I want.
>
> Now I would like to assign colors to the raw data points ( the "point
cloud"
> next to each mean +SE value). Each of these points stems from a different
> "Genotype" and I would like to color code the points with regard
to the
> genotypes (e.g. all points from Genotype A should be green, all points from
> Genotype B should be red etc.) I would like to use my own specified colors
> in the code (not the standard palette).
>
> I tried did the following (without success)
>
> 1.      I added "aes(color=Genotype,.." into
"geom_point(..)"
>
> 2.      I added my specific colors to "scale_color_manual"
>
>
scale_color_manual(labels=c("Control","Damaged"),values=c("red","black","#06
>
7c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3"....
> ..
>
>
>
> However, if I do that my "nested" plot structure disappears (i.e.
I cannot
> visually differentiate between "con" and "exp"
treatments nested within mid
> /high/. See Fig. 2)
>
> Basically, all I want is to produce a plot that looks like the one from my
> actual code( Fig.1) but where the individual data points are colored
> according to "Genotypes"
>
> Below is my code and my raw data.
>
> Help is very much appreciated!
>
> Thanks a lot,
>
> Mike
>
>
>
> #CODE-----------------------------------------------------
>
> require(ggplot2)
>
>
>
> #REMOVE START FOR ANALYSIS
>
> dta<-subset(dta_complete,Time=="Stop")
>
> dta
>
>
>
> #Calculation of SE
>
> data_summary <- function(x) {
>
>   m <- mean(x)
>
>   ymin <- m-sd(x)/sqrt(length(x))
>
>   ymax <- m+sd(x)/sqrt(length(x))
>
>   return(c(y=m,ymin=ymin,ymax=ymax))
>
> }
>
>
>
> pd1 = position_dodge(0.5)
>
>
>
> plot_CT<- ggplot(dta, aes(x=Location, y=CT,
> colour=Treatment,shape=Treatment)) +
>
>   stat_summary(fun.data=data_summary, position=pd1,
geom="errorbar",
> width=0.05) +
>
>   stat_summary(fun.data=data_summary, position=pd1, geom="point",
size=2) +
>
>   geom_point(position=position_jitterdodge(dodge.width=0.8,
jitter.height=0,
> jitter.width=0.2),
>
>              alpha=0.7) +
>
>   labs(title="", x="", y = "CT (% dw)")+
>
>   scale_color_manual(labels=c("Control",
> "Damaged"),values=c("red","black"),guide =
guide_legend(reverse = TRUE) )+
>
>   scale_shape_manual(labels=c("Control",
"Damaged"),name="Treatment",values
> = c(16,16),guide = guide_legend(reverse = TRUE) )+
>
>   #Style of background
>
>   theme_classic()+
>
>   #Change title
>
>   theme(plot.title = element_text(color="black", size=17,
face="bold"))+
>
>   #Font size axis
>
>   theme(axis.text=element_text(size=12),
>
>         axis.title=element_text(size=17))+
>
>   scale_x_discrete("Location",labels = c("Low",
"Mid", "High"),expand=c(0.1,
> 0.5))+
>
>   coord_flip()
>
>
>
> plot_CT
>
>
>
>
#DATA-----------------------------------------------------------------------
> -----------------
>
> structure(list(Location = structure(c(2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), .Label = c("High",
"Low", "Mid"
>
> ), class = "factor"), Treatment = structure(c(2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
>
> 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
>
> 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
>
> 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Con",
"Exp"
>
> ), class = "factor"), Time = structure(c(2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Start",
"Stop"
>
> ), class = "factor"), Genotype = structure(c(7L, 7L, 7L, 7L,
>
> 7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L,
>
> 4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L,
>
> 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 7L,
>
> 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
>
> 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L,
>
> 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L,
>
> 8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("A",
"B",
>
> "C", "D", "E", "F", "G",
"H"), class = "factor"), Time.Location > structure(c(5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L), .Label =
c("StartHigh",
>
>
> "StartLow", "StartMid", "StopHigh",
"StopLow", "StopMid"), class > "factor"),
>
>     Location.Treatment = structure(c(4L, 6L, 2L, 3L, 5L, 1L,
>
>     4L, 6L, 2L, 3L, 5L, 1L, 4L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
>
>     6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
>
>     6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L), .Label = c("HighCon", "HighExp",
"LowCon",
>
>     "LowExp", "MidCon", "MidExp"), class =
"factor"), CT = c(4.61538,
>
>     3.96739, 7.34797, 3.58108, 2.89655, 2.7993, 10.56122, 10.68396,
>
>     15.57252, 6.79245, 9.23469, 9.18, 1.1087, 4.26136, 1.14504,
>
>     2.20238, 3.15789, 9.54082, 11.05263, 15.84783, 10.48986,
>
>     12.62195, 15.12931, 5.51471, 8.20313, 11.85811, 3.38115,
>
>     7.5, 9.69512, 8.64407, 11.30597, 14.42797, 8.8125, 11.82482,
>
>     11.53061, 6.97674, 9.62766, 10.88028, 5.50403, 9.73558, 8.56419,
>
>     11.84524, 16.34892, 18.15789, 10.58036, 14.80932, 12.06081,
>
>     12.96992, 9.86014, 12.45652, 6.625, 6.93396, 9.10714, 3.66142,
>
>     9.19811, 10.88346, 2.88851, 6.85096, 10.27778, 8.29787, 13.00885,
>
>     14.38017, 7.5, 11.77734, 13.84615, 2.22772, 5.28, 5.25641,
>
>     1.0514, 2.73256, 4.11111, 11.39098, 11.10236, 13.00781, 7.95259,
>
>     10.15748, 13.16327, 8.90625, 10.04587, 13.625, 6.27049, 9.27966,
>
>     10.94037, 5.80189, 7.76978, 7.34266, 3.80952, 3.75, 7.29545,
>
>     10.45872, 16.83206, 5.95238, 7.70833, 10.92391, 11.03659,
>
>     14.39338, 14.88281, 8.22917, 11.63603, 14.7561, 11.9469,
>
>     14.65649, 16.84615, 8.37209, 13.27982, 13.69128, 7.77778,
>
>     12.59124, 12.32955, 7.00472, 8.41121, 7.22222, 9.43878, 10.33613,
>
>     14.16667, 9.60526, 8.77232, 11.91589, 7.01786, 12.29592,
>
>     11.83673, 8.55634, 11.17347, 12.68836, 2.7551, 6, 7.21374,
>
>     2.52101, 4.03846, 4.80634, 5.49569, 4.78723, 6.02273, 3.04511,
>
>     3.59244, 2.48239, 1.54412, 5.74219, 7.68595, 1.33065, 2.625,
>
>     4.42164, 9.66942, 11.875, 17.91667, 10.81731, 13.05288, 16.23853,
>
>     11.93662, 14.31818, 14.09396, 7.82374, 15.5042, 10.86207,
>
>     6.87023, 11.69492, 12.65957, 3.48684, 5.29018, 7.89474, 10.53309,
>
>     17.05479, 16.63866, 7.43119, 12.06522, 12.05607, 6.14865,
>
>     10.44, 14.69512, 9.24757, 9.04018, 12.38255, 2.22222, 3.90756,
>
>     5.85616, 2.23958, 3.8125, 3.01056, 11.60256, 12.22222, 11.8007,
>
>     7.76316, 10.08197, 12.78777, 9.20455, 12.1875, 16.59449,
>
>     6.82331, 10.91518, 11.5748)), row.names = 192:381, class =
"data.frame")
>
>
>
>
>
>
>
>
>
>
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.


-- 
John Kane
Kingston ON Canada

Michael Eisenring

2019-Apr-06 20:09 UTC

head link

[R] Color-coding data points in complex dotplot (ggplot2)

Hi John,
Thanks for this informantion.
Attached are the figures in a single PDF

Mike

-----Urspr?ngliche Nachricht-----
Von: John Kane [mailto:jrkrideau at gmail.com] 
Gesendet: Samstag, 6. April 2019 07:23
An: Michael Eisenring <michael.eisenring at gmx.ch>
Cc: R. Help Mailing List <r-help at r-project.org>
Betreff: Re: [R] Color-coding data points in complex dotplot (ggplot2)

HI Michael
Your code runs but we did not get any attached figure.  You might want to try
sending it as a .pdf file. They usually make it through the spam filters

On Sat, 6 Apr 2019 at 08:09, Michael Eisenring <michael.eisenring at
gmx.ch> wrote:>
> Dear R-List members,
>
> I produced a dot plot (see attachment 1) on 6 different treatments 
> (trees under 6 different conditions; in column " Location.Treatment
"
> in my raw data). For each of these " Location.treatment"
categories, I
> calculated a mean value and the SE for a specific compound (%CT).
>
> I am able to produce a plot where all the 6 treatments (in column "
> Location.Treatment") are separated (see code and Fig. 1) so that each 
> of two "con" and "exp" treatments (in the column
"treatment") are
> nested within one of the three locations (High, mid, low; in the 
> column "Location") (see plot that the code produces). This is the
plot structure I want.
>
> Now I would like to assign colors to the raw data points ( the "point
cloud"
> next to each mean +SE value). Each of these points stems from a 
> different "Genotype" and I would like to color code the points
with
> regard to the genotypes (e.g. all points from Genotype A should be 
> green, all points from Genotype B should be red etc.) I would like to 
> use my own specified colors in the code (not the standard palette).
>
> I tried did the following (without success)
>
> 1.      I added "aes(color=Genotype,.." into
"geom_point(..)"
>
> 2.      I added my specific colors to "scale_color_manual"
>
>
scale_color_manual(labels=c("Control","Damaged"),values=c("red","black
> ","#06 
>
7c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3"....
> ..
>
>
>
> However, if I do that my "nested" plot structure disappears (i.e.
I
> cannot visually differentiate between "con" and "exp"
treatments
> nested within mid /high/. See Fig. 2)
>
> Basically, all I want is to produce a plot that looks like the one 
> from my actual code( Fig.1) but where the individual data points are 
> colored according to "Genotypes"
>
> Below is my code and my raw data.
>
> Help is very much appreciated!
>
> Thanks a lot,
>
> Mike
>
>
>
> #CODE-----------------------------------------------------
>
> require(ggplot2)
>
>
>
> #REMOVE START FOR ANALYSIS
>
> dta<-subset(dta_complete,Time=="Stop")
>
> dta
>
>
>
> #Calculation of SE
>
> data_summary <- function(x) {
>
>   m <- mean(x)
>
>   ymin <- m-sd(x)/sqrt(length(x))
>
>   ymax <- m+sd(x)/sqrt(length(x))
>
>   return(c(y=m,ymin=ymin,ymax=ymax))
>
> }
>
>
>
> pd1 = position_dodge(0.5)
>
>
>
> plot_CT<- ggplot(dta, aes(x=Location, y=CT,
> colour=Treatment,shape=Treatment)) +
>
>   stat_summary(fun.data=data_summary, position=pd1,
geom="errorbar",
> width=0.05) +
>
>   stat_summary(fun.data=data_summary, position=pd1, geom="point",
> size=2) +
>
>   geom_point(position=position_jitterdodge(dodge.width=0.8, 
> jitter.height=0, jitter.width=0.2),
>
>              alpha=0.7) +
>
>   labs(title="", x="", y = "CT (% dw)")+
>
>   scale_color_manual(labels=c("Control",
> "Damaged"),values=c("red","black"),guide =
guide_legend(reverse =
> TRUE) )+
>
>   scale_shape_manual(labels=c("Control", 
> "Damaged"),name="Treatment",values
> = c(16,16),guide = guide_legend(reverse = TRUE) )+
>
>   #Style of background
>
>   theme_classic()+
>
>   #Change title
>
>   theme(plot.title = element_text(color="black", size=17, 
> face="bold"))+
>
>   #Font size axis
>
>   theme(axis.text=element_text(size=12),
>
>         axis.title=element_text(size=17))+
>
>   scale_x_discrete("Location",labels = c("Low",
"Mid",
> "High"),expand=c(0.1, 0.5))+
>
>   coord_flip()
>
>
>
> plot_CT
>
>
>
> #DATA-----------------------------------------------------------------
> ------
> -----------------
>
> structure(list(Location = structure(c(2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
>
> 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
>
> 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
>
> 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), .Label = c("High",
"Low", "Mid"
>
> ), class = "factor"), Treatment = structure(c(2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
>
> 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
>
> 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
>
> 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
>
> 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
>
> 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
>
> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
>
> 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Con",
"Exp"
>
> ), class = "factor"), Time = structure(c(2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Start",
"Stop"
>
> ), class = "factor"), Genotype = structure(c(7L, 7L, 7L, 7L,
>
> 7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L,
>
> 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 1L,
>
> 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L,
>
> 4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L,
>
> 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 7L,
>
> 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L,
>
> 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
>
> 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L,
>
> 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L,
>
> 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L,
>
> 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L,
>
> 8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("A",
"B",
>
> "C", "D", "E", "F", "G",
"H"), class = "factor"), Time.Location =
> structure(c(5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
>
> 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
>
> 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
>
> 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L), .Label = 
> c("StartHigh",
>
>
> "StartLow", "StartMid", "StopHigh",
"StopLow", "StopMid"), class =
> "factor"),
>
>     Location.Treatment = structure(c(4L, 6L, 2L, 3L, 5L, 1L,
>
>     4L, 6L, 2L, 3L, 5L, 1L, 4L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
>
>     6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
>
>     6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
>
>     5L, 1L, 4L, 6L, 2L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
>
>     1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
>
>     2L, 3L, 5L, 1L), .Label = c("HighCon", "HighExp",
"LowCon",
>
>     "LowExp", "MidCon", "MidExp"), class =
"factor"), CT = c(4.61538,
>
>     3.96739, 7.34797, 3.58108, 2.89655, 2.7993, 10.56122, 10.68396,
>
>     15.57252, 6.79245, 9.23469, 9.18, 1.1087, 4.26136, 1.14504,
>
>     2.20238, 3.15789, 9.54082, 11.05263, 15.84783, 10.48986,
>
>     12.62195, 15.12931, 5.51471, 8.20313, 11.85811, 3.38115,
>
>     7.5, 9.69512, 8.64407, 11.30597, 14.42797, 8.8125, 11.82482,
>
>     11.53061, 6.97674, 9.62766, 10.88028, 5.50403, 9.73558, 8.56419,
>
>     11.84524, 16.34892, 18.15789, 10.58036, 14.80932, 12.06081,
>
>     12.96992, 9.86014, 12.45652, 6.625, 6.93396, 9.10714, 3.66142,
>
>     9.19811, 10.88346, 2.88851, 6.85096, 10.27778, 8.29787, 13.00885,
>
>     14.38017, 7.5, 11.77734, 13.84615, 2.22772, 5.28, 5.25641,
>
>     1.0514, 2.73256, 4.11111, 11.39098, 11.10236, 13.00781, 7.95259,
>
>     10.15748, 13.16327, 8.90625, 10.04587, 13.625, 6.27049, 9.27966,
>
>     10.94037, 5.80189, 7.76978, 7.34266, 3.80952, 3.75, 7.29545,
>
>     10.45872, 16.83206, 5.95238, 7.70833, 10.92391, 11.03659,
>
>     14.39338, 14.88281, 8.22917, 11.63603, 14.7561, 11.9469,
>
>     14.65649, 16.84615, 8.37209, 13.27982, 13.69128, 7.77778,
>
>     12.59124, 12.32955, 7.00472, 8.41121, 7.22222, 9.43878, 10.33613,
>
>     14.16667, 9.60526, 8.77232, 11.91589, 7.01786, 12.29592,
>
>     11.83673, 8.55634, 11.17347, 12.68836, 2.7551, 6, 7.21374,
>
>     2.52101, 4.03846, 4.80634, 5.49569, 4.78723, 6.02273, 3.04511,
>
>     3.59244, 2.48239, 1.54412, 5.74219, 7.68595, 1.33065, 2.625,
>
>     4.42164, 9.66942, 11.875, 17.91667, 10.81731, 13.05288, 16.23853,
>
>     11.93662, 14.31818, 14.09396, 7.82374, 15.5042, 10.86207,
>
>     6.87023, 11.69492, 12.65957, 3.48684, 5.29018, 7.89474, 10.53309,
>
>     17.05479, 16.63866, 7.43119, 12.06522, 12.05607, 6.14865,
>
>     10.44, 14.69512, 9.24757, 9.04018, 12.38255, 2.22222, 3.90756,
>
>     5.85616, 2.23958, 3.8125, 3.01056, 11.60256, 12.22222, 11.8007,
>
>     7.76316, 10.08197, 12.78777, 9.20455, 12.1875, 16.59449,
>
>     6.82331, 10.91518, 11.5748)), row.names = 192:381, class = 
> "data.frame")
>
>
>
>
>
>
>
>
>
>
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see 
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.


--
John Kane
Kingston ON Canada

-------------- next part --------------
A non-text attachment was scrubbed...
Name: FIG 1 and FIG 2.pdf
Type: application/pdf
Size: 252813 bytes
Desc: not available
URL:
<https://stat.ethz.ch/pipermail/r-help/attachments/20190406/95b5c29b/attachment.pdf>

R help - Apr 2019 - Color-coding data points in complex dotplot (ggplot2)

[R] Color-coding data points in complex dotplot (ggplot2)

[R] Color-coding data points in complex dotplot (ggplot2)

[R] Color-coding data points in complex dotplot (ggplot2)