similar to: geom_ribbon removes missing values

Thank you, but this split the area into two and distorts the shape of the plot. (compared to ``` p + geom_abline(slope = slope_1, intercept = intercept_1 - 1/w[2], linetype = "dashed", col = "royalblue") + geom_abline(slope = slope_1, intercept = intercept_1 + 1/w[2], linetype = "dashed", col = "royalblue") ``` Why there

Hi Put fill outside aes p+geom_ribbon(aes(ymin = slope_1*x + intercept_1 - 1/w[2], ymax = slope_1*x + intercept_1 + 1/w[2]), fill = "blue", alpha=0.1) The "hole" is because you have two levels of data (red and blue). To get rid of this you should put new data in ribbon call. Something like newdat <- trainset newdat$z <- factor(0) p+geom_ribbon(data=newdat, aes(ymin =

Colleagues, Here is my reproducible code for a graph using geom_smooth set.seed(55) scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) library(ggplot2) library(cowplot) ggplot(scatter_data,aes(x=x_var,y=y_var))+ ? geom_point()+ ? geom_smooth(se=TRUE,fill="blue",color="black",linetype="dashed")+

Hi, I would like to plot a bunch of tree ring width data (time series) using ggplots, but I'm having trouble figuring out how to do it. My data is in a data.frame, with years as rownames and a distinct tree ring series in each column. So, something like this: rwl<-matrix(rnorm(800), nrow = 100) colnames(rwl) <- paste('V', 1:8, sep = '')

G'day Thomas, On Sat, 12 Aug 2023 04:17:42 +0000 (UTC) Thomas Subia via R-help <r-help at r-project.org> wrote: > Here is my reproducible code for a graph using geom_smooth The call "library(tidyverse)" was missing. :) > I'd like to add a black boundary around the shaded area. I suspect > this can be done with geom_ribbon but I cannot figure this out. Some >

also from this site: https://plotly.com/ggplot2/geom_ribbon/ I get the answer is geom_ribbon but I am still missing something ``` #! plot p = ggplot(data = trainset, aes(x=x, y=y, color=z)) + geom_point() + scale_color_manual(values = c("red", "blue")) # show support vectors df_sv = trainset[svm_model$index, ] p = p + geom_point(data = df_sv, aes(x=x, y=y),

Hi What about something like p+geom_ribbon(aes(ymin = slope_1*x + intercept_1 - 1/w[2], ymax = slope_1*x + intercept_1 + 1/w[2], fill = "grey70", alpha=0.1)) Cheers Petr > -----Original Message----- > From: Luigi Marongiu <marongiu.luigi at gmail.com> > Sent: Friday, October 23, 2020 11:11 AM > To: PIKAL Petr <petr.pikal at precheza.cz> > Cc: r-help

?s 05:17 de 12/08/2023, Thomas Subia via R-help escreveu: > Colleagues, > > Here is my reproducible code for a graph using geom_smooth > set.seed(55) > scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) > ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) > > library(ggplot2) > library(cowplot) > > ggplot(scatter_data,aes(x=x_var,y=y_var))+

Consider the following situation: we have quantified algal concentrations for a variety of species using many samples at each of three years. It seems to make sense to generate a line plot (matplot-like), with each species plotted as a separate line, with the points connected to emphasize the temporal pattern. The problem: lots of overlapping error bars. The question: from both a

Hello, I am running SVM and showing the results with ggplot2. The results include the decision boundaries, which are two dashed lines parallel to a solid line. I would like to remove the dashed lines and use a shaded area instead. How can I do that? Here is the code I wrote.. ``` library(e1071) library(ggplot2) set.seed(100) x1 = rnorm(100, mean = 0.2, sd = 0.1) y1 = rnorm(100, mean = 0.7, sd =

Hi Did you try google? I got several answers using your question e.g. https://stackoverflow.com/questions/54687321/fill-area-between-lines-using-g gplot-in-r Cheers Petr > -----Original Message----- > From: R-help <r-help-bounces at r-project.org> On Behalf Of Luigi Marongiu > Sent: Friday, October 23, 2020 9:59 AM > To: r-help <r-help at r-project.org> > Subject:

I have 2 datafiles 'target' and 'observed' as shown below (I will gladly email these 2 small files to whomever). X25. And X75. Indicate the value of 25th and 75th-percentile of the target ('what should be') and the observed ('what is'). The i.value is simply the month. > target X i.value X25. X75. 1 one.month 1 10.845225 17.87237 2

Hi everyone, Hadley, it seems there's a bug in geom_ribbon() when using it in a log-scaled plot: d<-data.frame(x=c(1:20),y1=rnorm(20)+3,y2=rnorm(20)+5) p<-ggplot() p<-p+geom_ribbon(data=d,aes(x=d[["x"]],min=d[["y1"]],max=d[["y2"]])) p<-p+geom_line(data=d,aes(x=d[["x"]],y=d[["y1"]]),colour="blue")

Hi, I'm really struggling with barplot I have a data.frame with 3 columns. The first column represents an "incident" type The second column represents a "month" The third column represents a "time" Code for a sample data.frame incidents <- rep(c('a','b','d','e'), each =25) months <- rep(c(1,2), each =10) times

Hi, I'm trying to plot a longitudinal data set, using ggplot and adding some summary info (eg. mean, 1 sd bounds) using geom=ribbon. The summary info is based on a subset of the original data (eg. less an outlier). But I'm having trouble getting the ribbons to show up correctly. It's probably something obvious that I'm missing as a novice at ggplot2, and any help is much

Dear R-helpers, the problem I'm facing today is to convince lattice to paint some areas in gray. The areas I would like to have in gray, are confidence bands I've googled around in the mailing list archives and eventually find some clues. This link is my starting point http://tolstoy.newcastle.edu.au/R/e2/help/07/04/15595.html I'm reproducing here the code for your convenience est

Hi, I want to plot grouped bars to compare 95% confidence interval estimates from two models. Each bar represents a 95% confidence interval estimate of a coefficient from one of the two models. Each group represents confidence interval estimates of the same coefficient from the two models. I think such a bar plot will nicely present whether 95% confidence interval estimates of the same

Hi R fans, As a newbie following the five-hour rule (after hitting my head against the wall for five hours, post to this list), I am appealing for some help understanding geom_rect() in ggplot2. What I want to do is very simple. I want to generate a plot of rectangles. Each one represents a business cycle. The x-values will be pairs representing the start and end of each cycle. The y-values

Hello I have created a graph using the following commands: <<< startBReP3O1T <- diffs$BReP3O1T - diffs$diff_BReP3O1T endBReP3O1T <- diffs$BReP3O1T x <- seq(47,89, length = 10) ymin <- min(min(startBReP3O1T), min(endBReP3O1T)) ymax <- max(max(startBReP3O1T), max(endBReP3O1T)) y <- seq(ymin, ymax, length = 10) plot(x,y, type = 'n', xlab = 'Age', ylab =

plot.hclust: Setting up a window for a dendrogram assumes the first link is the shortest and the last is the longest. This is not always the case when the clustering was done with hclust, method="median" or method="centroid", and the dendrogram sometimes doesn't fit within the window. I propose the fix listed below. src/main/ --- plot.c Wed Sep 17 01:03:39 2003 +++