There is a problem built into your question: you are treating carb graphically
as a continuous variable, yet by asking for a line plot of mean values you seem
to be assuming it is discrete. Below are several possible interpretations of
your intent.
Continuous:
library(ggplot2)
p <- ggplot( mtcars, aes( x=carb, y=mpg ) ) + geom_point()
p + stat_summary( geom="ribbon", fun.ymin="min",
fun.ymax="max" )
p2 <- p + stat_summary( geom="ribbon"
, fun.ymin="min"
, fun.ymax="max"
, alpha=0.2
, fill="blue"
)
# local regression
p + geom_smooth()
# literal interpretation
p2 + geom_hline( yintercept = mean( mtcars$mpg ), colour="red" )
# linear regression
p2 + geom_smooth( method="lm", se=FALSE, colour="red" )
Discrete:
mtcarsmean <- aggregate( mtcars$mpg, mtcars[ , "carb", drop=FALSE
], mean )
# discrete means
p2 + geom_line( data=mtcarsmean, mapping=aes( x=carb, y=x ),
colour="red" )
The reason this has to be done explicitly outside of the geom_smooth mechanism
is because of this conflict between graphically continuous and conceptually
discrete data.
--
Sent from my phone. Please excuse my brevity.
On December 22, 2015 11:43:23 PM PST, pushan chakraborty <pushan.zoology at
gmail.com> wrote:>Dear list
>
>I want to put a line command in the following and also want to
>attribute
>colour in the geom line command line. It would be a ribbon plot showing
>the
>mean line. Is there any help?
>
>
>p <- ggplot(mtcars, aes(x=carb, y=mpg)) + geom_point()
>
>p + stat_summary(geom="ribbon", fun.ymin="min",
fun.ymax="max")
>
>p + stat_summary(geom="ribbon", fun.ymin="min",
fun.ymax="max",
> alpha=0.2, fill="blue")
>
>
>
>
>
>--
>Pushan Chakraborty
>CSIR - SRF
>
>Center for Pollination Studies, University of Calcutta
>35, Ballyguanje Circular Road, Kolkata - 700019
> &
>Wildlife Institute of India
>Chandrabani, Dehradun - 248001
>
>webpage:
>
>http://cpscu.in/?page_id=51
>
>Skype: cpushan
>
> [[alternative HTML version deleted]]
>
>______________________________________________
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