R help - Feb 2008 - adding the mean and standard deviation to boxplots

Dear list, 
   
  How can I add the mean and standard deviation to each of the boxplots using
the example provided  in the boxplot function?
  
boxplot(len ~ dose, data = ToothGrowth,
        boxwex = 0.25, at = 1:3 - 0.2,
        subset = supp == "VC", col = "yellow",
        main = "Guinea Pigs' Tooth Growth",
        xlab = "Vitamin C dose mg",
        ylab = "tooth length", ylim = c(0, 35), yaxs = "i")
boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
        boxwex = 0.25, at = 1:3 + 0.2,
        subset = supp == "OJ", col = "orange")
legend(2, 9, c("Ascorbic acid", "Orange juice"),
       fill = c("yellow", "orange"))

Thanks for any help,
  Tom

       
---------------------------------

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>> How can I add the mean and standard deviation to each of the boxplots 
using the example provided  in the boxplot function?
 
boxplot(len ~ dose, data = ToothGrowth)
#You could add the mean as a point
points(tapply(len, dose, mean), col="red")

Alternatively, replace the median value with the mean, by writing a 
replacement for fivenum that calculates mean instead of median, then call 
bxp instead of boxplot.

As for the standard deviation, are you sure you want this?  Standard 
deviation only makes sense if the data are normally distributed, and 
boxplots are typically used to examine how the data are distributed (i.e., 
if you knew they were normally distributed already, you wouldn't need to 
draw the boxplot).

Regards,
Richie.

Mathematical Sciences Unit
HSL


------------------------------------------------------------------------
ATTENTION:

This message contains privileged and confidential inform...{{dropped:20}}

> "As for the standard deviation, are you sure you want this?  Standard 
> deviation only makes sense if the data are normally distributed..."
> --------------
> 
> -- This is false, of course. What you probably meant to say is something
> like:
> 
> "The sample standard deviation may not tell you what you think it
tells
you
> if the underlying data are not distributed something like a normal
> distribution."
Yes.  How very sloppy of me.  Consider my wrist slapped.

Regards,
Richie.

Mathematical Sciences Unit
HSL


------------------------------------------------------------------------
ATTENTION:

This message contains privileged and confidential inform...{{dropped:20}}

Not precisely what you asked for but see the notch= argument to boxplot
for a graphic measure of variability.  If you simply wish to print certain
statistics below the numbers already on the X axis then see:

https://stat.ethz.ch/pipermail/r-help/2008-January/152994.html

On Feb 4, 2008 10:41 AM, Tom Cohen <tom.cohen78 at yahoo.se>
wrote:
> Dear list,
>
>  How can I add the mean and standard deviation to each of the boxplots
using the example provided  in the boxplot function?
>
> boxplot(len ~ dose, data = ToothGrowth,
>        boxwex = 0.25, at = 1:3 - 0.2,
>        subset = supp == "VC", col = "yellow",
>        main = "Guinea Pigs' Tooth Growth",
>        xlab = "Vitamin C dose mg",
>        ylab = "tooth length", ylim = c(0, 35), yaxs =
"i")
> boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
>        boxwex = 0.25, at = 1:3 + 0.2,
>        subset = supp == "OJ", col = "orange")
> legend(2, 9, c("Ascorbic acid", "Orange juice"),
>       fill = c("yellow", "orange"))
>
> Thanks for any help,
>  Tom
>
>
> ---------------------------------
>
> J?mf?r pris p? flygbiljetter och hotellrum:
http://shopping.yahoo.se/c-169901-resor-biljetter.html
>        [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>
>

There are many ways to do it. The following will place a blue point on the
boxplot at the mean, then print the mean at the bottom of the plot. In some
plots I've gone too far and included median points and values as well. You
could also put 95% CI on the same plot, but it would get perhaps too
"busy."


# Plot boxplot of vitamin C subset
bx <- boxplot(len ~ dose, data = ToothGrowth,
        boxwex = 0.25, at = 1:3 - 0.2,
        subset = supp == "VC", col = "yellow",
        main = "Guinea Pigs' Tooth Growth",
        xlab = "Vitamin C dose mg",
        ylab = "tooth length", ylim = c(0, 35), yaxs = "i")

# keep location
at <- c(1:length(bx$names))

# find means, plot as points
SubTc <-subset(ToothGrowth, supp == "VC")
means <- by(SubTc$len, SubTc$dose, mean,na.rm=TRUE)
points(at - 0.2, means, pch = 19, col = "blue")

# write mean values 
text(at - 0.1, 1, labels = formatC(means, format = "f", digits = 1),
    pos = 2, cex = 1, col = "red")

# Orange juice subset
boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
        boxwex = 0.25, at = 1:3 + 0.2,
        subset = supp == "OJ", col = "orange")

# find means, plot as points
SubTo <-subset(ToothGrowth, supp == "OJ")
meano <- by(SubTo$len, SubTo$dose, mean,na.rm=TRUE)
points(at + 0.2,meano, pch = 19, col = "blue")

# write mean values 
text(at + 0.3, 1, labels = formatC(meano, format = "f", digits = 1),
    pos = 2, cex = 1, col = "orange")

legend(2, 9, c("Ascorbic acid", "Orange juice"),
       fill = c("yellow", "orange"))
------------------------------       
THT, I'm sure my R code is not as efficient as it could be. 

Harold Baize
Butte County Department of Behavioral Health




Tom Cohen-2 wrote:
> 
> Dear list, 
>    
>   How can I add the mean and standard deviation to each of the boxplots
> using the example provided  in the boxplot function?
>   
> boxplot(len ~ dose, data = ToothGrowth,
>         boxwex = 0.25, at = 1:3 - 0.2,
>         subset = supp == "VC", col = "yellow",
>         main = "Guinea Pigs' Tooth Growth",
>         xlab = "Vitamin C dose mg",
>         ylab = "tooth length", ylim = c(0, 35), yaxs =
"i")
> boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
>         boxwex = 0.25, at = 1:3 + 0.2,
>         subset = supp == "OJ", col = "orange")
> legend(2, 9, c("Ascorbic acid", "Orange juice"),
>        fill = c("yellow", "orange"))
> 
> Thanks for any help,
>   Tom
> 
>        
> ---------------------------------
> 
> J?mf?r pris p? flygbiljetter och hotellrum:
> http://shopping.yahoo.se/c-169901-resor-biljetter.html
> 	[[alternative HTML version deleted]]
> 
> 
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
> 
> 
-- 
View this message in context:
http://www.nabble.com/adding-the-mean-and-standard-deviation-to-boxplots-tp15271398p15278974.html
Sent from the R help mailing list archive at Nabble.com.

Tom:
You can do this with ggplot2. The code below puts  95%
CI,a smooth line and the mean(blue point)on the same
plot. 
Felipe

 library(ggplot2)
  r <- ggplot(ToothGrowth, aes(y=len, x=factor(dose)))
  r$background.fill = "cornsilk"
r + geom_boxplot(aes(colour=supp)) +
stat_summary(aes(group=supp),fun="mean_cl_normal",colour="red",geom="smooth",linetype=3,size=1)
+
  
stat_summary(aes(group=supp),fun="mean_cl_normal",colour="blue",geom="point",size=4)

   grid.gedit("label", gp=gpar(fontsize=10,
col="red")) # color the axis labels



Felipe D. Carrillo
  Fishery Biologist
  US Fish & Wildlife Service
  California, USA



     
____________________________________________________________________________________
Be a better friend, newshound, and

Dear users

This is a message I was directing to Harold Baize but because I pressed the
wrong button the message got lost grrrr!!!

So I?m doing it all over again:

Lets suppose I have three batches of data:

a <- rnorm(50,2500,300) 
b <- rnorm(50,3500,250)
c <- rnorm(50,4000,200)

# Now I want to plot them as boxplots and violin plots
require(vioplot)
vioplot (a,b,c, horizontal=T, col=?white?)
boxplot (a,b,c, horizontal=T, col=?white?)

As we know boxplot show the least-greates values, lower-upper quartiles, the
mean, and outliers (when present).

However, for some data is not important the MEDIAN but the MEAN. Also, it is
more relevant to show ERROR BARS instead of quartiles. 

So, how could I see (for the batches of data I introduced above)?

1.	a boxplot showing the MEAN and the SD instead of the lower/upper
quartile?
2.	a boxplot showing the MEAN and the STANDARD ERROR OF THE MEAN instead of
the lower/upper quartile?
3.	a boxplot showing the MEAN and the 95% CI instead of the lower/upper
quartile?

(I think in all these cases is preferable to have visual access, or to have
the line that shows, the LEAST and the GREATEST VALUES.)

In other words, that the ERROR BARS (95% CI, SD, SE) proposed here take the
place of the boxes usually used to represent the lower/upper quartile.

Now, the big question, is all this jazz possible to be implemented in violin
plots as well?

How could that be done?

Cheers,

Fernando
-- 
View this message in context:
http://www.nabble.com/adding-the-mean-and-standard-deviation-to-boxplots-tp15271398p18604571.html
Sent from the R help mailing list archive at Nabble.com.

This thread may help
http://www.nabble.com/adding-the-mean-and-standard-deviation-to-boxplots-td15271398.html


--- On Wed, 7/23/08, Fernando Marmolejo-Ramos <fernando.marmolejoramos at
adelaide.edu.au> wrote:
> From: Fernando Marmolejo-Ramos <fernando.marmolejoramos at
adelaide.edu.au>
> Subject: Re: [R] adding the mean and standard deviation to boxplots
> To: r-help at r-project.org
> Received: Wednesday, July 23, 2008, 2:24 AM
> Dear users
> 
> This is a message I was directing to Harold Baize but
> because I pressed the
> wrong button the message got lost grrrr!!!
> 
> So I?m doing it all over again:
> 
> Lets suppose I have three batches of data:
> 
> a <- rnorm(50,2500,300) 
> b <- rnorm(50,3500,250)
> c <- rnorm(50,4000,200)
> 
> # Now I want to plot them as boxplots and violin plots
> require(vioplot)
> vioplot (a,b,c, horizontal=T, col=?white?)
> boxplot (a,b,c, horizontal=T, col=?white?)
> 
> As we know boxplot show the least-greates values,
> lower-upper quartiles, the
> mean, and outliers (when present).
> 
> However, for some data is not important the MEDIAN but the
> MEAN. Also, it is
> more relevant to show ERROR BARS instead of quartiles. 
> 
> So, how could I see (for the batches of data I introduced
> above)?
> 
> 1.	a boxplot showing the MEAN and the SD instead of the
> lower/upper
> quartile?
> 2.	a boxplot showing the MEAN and the STANDARD ERROR OF THE
> MEAN instead of
> the lower/upper quartile?
> 3.	a boxplot showing the MEAN and the 95% CI instead of the
> lower/upper
> quartile?
> 
> (I think in all these cases is preferable to have visual
> access, or to have
> the line that shows, the LEAST and the GREATEST VALUES.)
> 
> In other words, that the ERROR BARS (95% CI, SD, SE)
> proposed here take the
> place of the boxes usually used to represent the
> lower/upper quartile.
> 
> Now, the big question, is all this jazz possible to be
> implemented in violin
> plots as well?
> 
> How could that be done?
> 
> Cheers,
> 
> Fernando
> -- 
> View this message in context:
>
http://www.nabble.com/adding-the-mean-and-standard-deviation-to-boxplots-tp15271398p18604571.html
> Sent from the R help mailing list archive at Nabble.com.
> 
> ______________________________________________
> R-help at r-project.org mailing list
> 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.

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