similar to: ggplot multiple scales but a stat for only one of them

Dear R-ers, apologies for not providing the full code. I just need a point in the right direction. I have a data frame ('temp') with 1,200 rows and 2 variables. I am using ggplot2 to create a scatter plot: This is my code and it works fine, it creates a scatter plot: library(ggplot2) sp10<-ggplot(temp,aes(x=p.used_L1,y=l.to.r.ratio_L1)) sp10 + geom_point() However, when I change the

I'm trying to treat a continuous variable as discrete for plotting multiple regression lines in a scatterplot as a function of the level on the moderating variable. In the example below, there is only one regression line plotted to the whole data. I would like a separate regression line for each discrete level of the moderator. The moderator is continuous, so I'd like to treat it as

In the example below, from http://www.ling.upenn.edu/~joseff/rstudy/summer2010_ggplot2_intro.html I'd like to make (a) the fitted line thicker and (b) change the background fill color for the confidence envelope around each fitted line to a low-alpha transparent version of the same color used for the separate fitted lines for GENDER, rather than grey for both. How can I do this?

Hello All, I have plotted a scatter plot in ggplot2 and added a regression line and a regression equation. But the processing is very very slow. One reason might be because I have so many data pairs. Is there any way to speed up this code ? I need to create a multiple layout as well. The code I have used is as follows: setwd("C:/Users/jzd0009/Documents/R software") mydata <-

Hi all, Does one of you know if there is any way to combine a "nls" method in the stat_smooth of ggplot? Regards -- ------------- Benoit Boulinguiez Ph.D student Ecole de Chimie de Rennes (ENSCR) Bureau 1.20 Equipe CIP UMR CNRS 6226 "Sciences Chimiques de Rennes" Avenue du G?n?ral Leclerc CS 50837 35708 Rennes CEDEX 7 Tel 33 (0)2 23 23 80 83 Fax 33 (0)2 23 23 81 20

This is what I have now so far. p=ggplot(data = test, aes(x = YEAR, y = TOTAL, colour = TREATMENT)) + geom_point() + geom_smooth(method = "lm", se=FALSE) + facet_wrap(~COUNTRY) > p +scale_x_continuous(limits=c(1,4)) http://r.789695.n4.nabble.com/file/n3626510/graph.gif I would also like to: 1.) change the headline for the faced wraps ?high? and ?low?. Is there any other way of

I'm interested in creating a graphic -like- this: c <- ggplot(mtcars, aes(qsec, wt)) c + geom_point() + stat_smooth(fill="blue", colour="darkblue", size=2, alpha = 0.2) but I need to show 2 sets of bands (with different shading) using 5%, 25%, 75%, 95% limits that I specify and where the heavy blue line is the median. I don't understand how to do this with

Dear all I would like to superpose some smoothing line through boxplot in ggplot > dput(ad) structure(list(konc.f = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L,

With ggplot2, I can plot the glm stat_smooth for binomial data when the response is binary or a two-level factor as follows: data("Donner", package="vcdExtra") ggplot(Donner, aes(age, survived)) + geom_point(position = position_jitter(height = 0.02, width = 0)) + stat_smooth(method = "glm", family = binomial, formula = y ~ x, alpha = 0.2, size=2) But how can I

Hi all, I am using ggplot2 and continuing to find it very useful and pretty. However, I am trying to create some graphics for publication that would be included in an MS Word document (not my choice!) in Windows Vista. The problem is that I want to use stat_smooth() to add an fitted linear model line along with its 95% confidence band, but I cannot seem to get the confidence band in a format

Hello, I have a ggplot that has the looks of the plot that I want, but it doesn't have the right layout. The data is an ordered melted dataframe: - ID - type (to use for a faced grid) - time - type - time - value (POSIXct) - pos (to use for a faced grid, this is an index to split the plot) The goal of the plot is to create a time line for each ID (different points of time). The ID's

Dear list (but probably mostly Hadley): In ggplot, operations to modify 'guides' are accessed through grid objects, but I did not find mention of creating new guides or possibly removing them altogether using ggplot functions. I wonder if this is something I need to learn grid to learn more about (which I hope to do eventually). Also, ggplot()+geom_object() [where 'object' can be

Whats going on here? df<-data.frame(x=1:10,y=1:10) ggplot()+geom_point(data=df,aes(x=x,y=y)) ## this is the normal usage right? ggplot()+geom_point(data=df,aes(x=df[,1],y=df[,2])) ## but I can also feed it column indices ggplot()+geom_point(aes(x=df[,'x'],y=df[,'y'])) ## or column names. ## but if i wrap it in a function... plot.func.one<-function(dff,x.var,y.var){

is it possible to map 2 plots(c and d) in a single output plot? library(ggplot2) c <- ggplot(mtcars, aes(qsec, wt)) d <- ggplot (mtcars, aes(qsec, wt)) c + stat_smooth(fill="darkgrey", colour="blue", size=2, alpha = 0.2) d + stat_smooth(fill="darkgrey", colour="red", size=2, alpha = 0.2) -- View this message in context:

ggplot2 ------------------------------------------------------------ ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and avoid bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce

ggplot2 ------------------------------------------------------------ ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and avoid bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce

I have a more complicated function I am trying to write, but I run in to a problem when I want to add something to the plot from more than one data set while simultaneously controlling the appearance of the additional layer. # Toy data: foo <- data.frame ( x = 1:4, y = 4:1 , membership = c( "A", "A", "B", "B" ) ) bar <- data.frame ( x = 1:4 + 1 , y

AF_E PS_E 90.838 2.206 83.139 1.751 134.272 3.710 84.043 2.076 105.184 2.788 157.249 3.783 50.280 1.027 96.973 2.355 123.582 3.398 60.417 1.236 123.501 3.315 90.128 1.566 193.783 5.167 116.036 2.994 100.289 2.216 56.943 1.106 102.272 2.692 145.579 3.810 53.105 1.202 127.212 3.061 102.838 2.383 126.352 2.723 13.661 0.190 164.352 4.870 159.945 4.160 54.382 0.884 128.253 3.598 181.208 4.767 145.118

Hi I am plotting line chart using ggplot and want to use geom_line and geom_point simultaneously. I get the plot but now I have two legends. None of the legend is representing the true values. I need the legend with shape and color both. Thanks > con = textConnection("inputs var1 var2 var3+ 100 10 5 2+ 1000 20 10 4+ 5000 30 15 8+ 10000 40 20 16+ 30000 50 25 32")> data =

Hello Everyone, I have recently been introduced to the ggplot package by Hadley Wickham and must say I am quite impressed so far at how easy it is to make attractive plots, but one thing I am struggling over is how to consolidate legends. I have 3 plots that I would like to put on a single page and all 3 map the same dimension of the data to the colour aesthetic. Right now, when I plot all