similar to: Question about ggplot2 and stat_smooth

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:

Hello everyone, I was wondering if anyone was aware of a way in which I could use ggplot's stat_smooth() function for add an exponential moving average. I was thinking that I could maybe use something like: >myggplot + stat_smooth (method = 'HoltWinters( data , .9 , 0, 0)') but my efforts were futile. Perhaps there is a way to write my own custom method to throw into

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?

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

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

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

Hello, I drew a simple area plot using ggplot2 using set <- read.table(file="http://www.jovian.nl/set.csv", head=1, sep=",") library(ggplot2) ggplot() + layer( data = set, mapping = aes(x = time, y = hours), geom = "area", stat="smooth", color="red" ) + layer( data = set, mapping = aes(x = time, y = hours), geom = "area",

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,

The model frame shows the response and predictors in a data frame with nicely labelled columns: fm <- lm(wt~qsec+log(hp)+sqrt(disp), data=mtcars) model.frame(fm) # ok When the left hand side consists of more than one response, those response variables still look good, inside a matrix: fm <- lm(cbind(qsec,hp,disp)~wt, data=mtcars) model.frame(fm)[[1]] # ok A problem arises when

In the change log of ggplot2, version 0.7, I find this: "* scales: any point outside of limits is dropped (this was previously the behaviour for discrete scales, but not continuous scales)" and that makes sense for some applications. But what about if I want to summarize the data with a smooth, and (a) include the effect of all values, but (b) "zoom in" on the smooth by

Hii i have been trying to do a scatter plot with ggplot2, like the plot 6 here (http://had.co.nz/ggplot2/geom_point.html) .. where the points size vary with values > p + geom_point(aes <http://had.co.nz/ggplot2/aes.html>(size = qsec)) but am not sure how to setup the parameter - qsec could anyone please give some pointers on how to define that thanks Mo. [[alternative HTML

Dear Sirs, I am Professor at Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India. While taking classes, I found the *by() *function producing following error when I use FUN=mean or median and some other functions, however, FUN=summary works. Given below is the output of the example I used on a built-in dataset "mtcars", along with error message reproduced herewith: >

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Dear All, Thanks for your help. However, I would like to draw your attention to the following: Actually, I was replicating the Example 2.3, using the dataset "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, of a famous book "R by Example" written by "Jim Albert and Maria Rizzo" published in Springers (2012) in a Use R! Series. The

Buen día estimados Estoy tratando de hacer un tibble con los resultados de un apply que se muestran en la consola que me da R, no estoy seguro si eso se pueda hacer, pero me gustaría organizar los resultados de esa manera. mi código es: data("mtcars") Mtcars_matriz <- as.matrix(mtcars) apply(Mtcars_matriz, MARGIN =2, FUN = shapiro.test) DF2 <- tibble(Variable = NA, W = NA, Pvalue =

Good day, I'm trying to get more time series in one plot. As there are bigger differences in values of variables I need logaritmic y axis. The code I use is the following: nvz_3_data <- read.csv('/home/tomas/R_outputs/nvz_3.csv') date <- (nvz_3_data$date) NO3 <- (nvz_3_data$NO3) NH4 <- (nvz_3_data$NH4) date_p <- as.POSIXct(date, "CET") par(mfrow=c(2,1), ylog

Hello everyone, I am (happily) using ggplot2 for all my plotting now and I wondered is there is an easy way to specify xlim and ylim somewhere when using the ggplot syntax, as opposed to the qplot syntax. Eg. qplot(data=mtcars,y=wt, x=qsec,xlim=c(0,30)) <-> ggplot(mtcars, aes(y=wt, x=qsec)) + geom_point() + ??? Indeed the ggplot syntax is in general more flexible and powerful and

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by

Hello, I am making a boxplot of 13 boxes. I tried to color the box using 13 colors but failed. Only red and brown were displayed. Green, blue, and grey disappeared. Please kindly advise modification after checking the code below. Thank you in advance. Elaine R code # data input dataN <-read.csv("H:/a_mig_distance_B_NB/R_data/Mig_bird_586_20120925.csv",header=T, row.names=1)

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs