similar to: [ggplot2] Densityplot, grouping and NAs

Does anyone (Hadley??) know if there's a straightforward way in ggplot2 to get data divided by a single factor to plot as a rectangular grid of subplots? So far I've only been able to get such data plotted as a single row or single column of skinny subplots. The code below gives an example implemented with lattice, and my best attempt in ggplot2 cheers Ben Bolker ------------ g=

Dear R experts, I am trying to arrange multiple plots, creating one graph for each size1 factor variable in my data frame, and each plot has the median price on the y-axis and the size2 on the x-axis grouped by clarity: library(ggplot2) df <- data.frame(price=matrix(sample(1:1000, 100, replace = TRUE), ncol = 1)) df$size1 = 1:nrow(df) df$size1 = cut(df$size1, breaks=11)

Hi All, I'm fiddling with an program to read a text file containing periods that SAS uses for missing values. I know that if I had the original SAS data set instead of a text file, R would handle this conversion for me. Data frames do not allow missing values in their indices but vectors do. Why is that? A search of the error message points out the problem and solution but not why they

#After spending the entire day working on this question, I have decided to reach out for support: #I am trying to overlay a densityplot from one data set over a histogram of another, if I were to plot the two individually, they would look like: # data frame construction data.frame.A <- data.frame(rnorm(12*8), c(rep("one", 4), rep("two", 4), rep("three", 4)),

Hi all, I am trying to plot a weighted density plot for two different types and want to show the data points on the x axis. The code is as follows. The data points are very concentrated. Is there a better way to present it( should I set the alpha value or something else)? Thanks! YL library(ggplot2) x <- rnorm(10000) a <- rnorm(5000) b <- rnorm(5000) weights.x <- abs(a/sum(a))

Hi all, I was trying to draw a stacked density plot like that : library(ggplot2); library(plyr) dat <- cbind(rnorm(300), rep(c(1,2), each=150)) ggplot() + geom_density(aes(x=dat[,1], fill=factor(dat[,2]), position="stack")) + xlab("") + ylab("") + scale_colour_manual(name = "Pallet", labels = c("X", "Y")) Here

Hi R-help I'm trying to create a grid plot in which each plot in the grid contains two density plots (colored by factor) and two vertical lines at the respective medians (also colored by the factor). Using the diamonds dataset as an example, the following commands give me price density plots by factor cut in a single, ungridded plot. p <- ggplot(data=diamonds, aes(x=price)) +

Dear all, I have a data.frame with some NAs that can happens anywere, and I would like to keep only rows without NAs. Thanks in advance for your help, and Merry Xmas. myvect<-runif(100) myvect[sample(1:100)[1:5]]<-NA myDF<-data.frame(matrix(myvect,ncol=5)) myDF miltinho [[alternative HTML version deleted]]

Hi, This seems like there should be a simple answer, but having spent most of the day trying to find it, I'm becoming less convinced and as such am asking it here. Here's a sub-set of my data (a data.frame in R): myDF time value trial 1 2011-03-01 01:00:00 64092 FALSE 2 2011-03-01 02:00:00 47863 FALSE 3 2011-03-01 03:00:00 43685

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

Text is really small and legend boxes are huge in this plot when saved to .png with ggsave. Plot is correct (i.e. looks the same as the screen) when saved with dev.print. Saving to .pdf with ggsave give the correct output. I'm a noob at ggplot2 so this may be user error rather than a bug. However the interface to ggsave seems simple enough to exclude many possibilities for screwing this up

A new version of the ggplot2 web application is available at http://www.yeroon.net/ggplot2. New features include 1D geom?s (histogram,?density, freqpoly), syntax mode (by clicking the tiny arrow at the?bottom), and some additional facet options. Furthermore some minor?improvements and fixes, most notably for Internet Explorer. As usual, a little demo video that shows how to use the new features:

I am learning ggplot2 commands and I have figured out how to create histograms and density curves but I am not sure how to add a density curve on top of a histogram. Here are the two graphs that I created. ## Histogram t<-rnorm(500) w<-qplot(t, main="Normal Random Sample", fill=I("blue"), colour=I("black"), geom="histogram") w ##Density Curve

Ultimately my aim is to get a plot of density faceted by 2 factors with a horizontal boxplot overlaid on each density plot in the grid to indicate summary stats. So I've been experimenting with creating boxplots and density plots. Here's some representative data. series = c('C2','C4','C8','C10','C15','C20') ids =

On converting character variables to ordered factors, regression result has strange names. Is it possible to obtain same variable names with and without intercept? Thanks, Naresh mydf <- data.frame(date = seq.Date(as.Date("2024-01-01"), as.Date("2024-03-31"), by = 1)) mydf[, "wday"] <- weekdays(mydf$date, abbreviate = TRUE) mydf.work <- subset(mydf, !(wday

Hello! I have a data frame with dates. I need to create a new "month" that starts on the 20th of each month - because I'll need to aggregate my data later by that "shifted" month. I wrote the code below and it works. However, I was wondering if there is some ready-made function in some package - that makes it easier/more elegant? Thanks a lot! # Example data:

Hi All, I've been successfully using the with function for analyses and the transform function for multiple transformations. Then I thought, why not use "with" for both? I ran into problems & couldn't figure them out from help files or books. So I created a simplified version of what I'm doing: rm( list=ls() ) x1<-c(1,3,3) x2<-c(3,2,1) x3<-c(2,5,2)

Hi all, Can anyone explain why the following use of the subset() function produces a different outcome than the use of the "[" extractor? The subset() function as used in density(subset(mydf, ht >= 150.0 & wt <= 150.0, select = c(age))) appears to me from documentation to be equivalent to density(mydf[mydf$ht >= 150.0 & mydf$wt <= 150.0, "age"])

Dear all, I wanted to make a two-way-table of two variables with a counting variable stored in another column of a dataframe. In version 1.9.1, the behavior is as expected as shown in the simplified example code. > sex <- rep(c("F", "M"), 5) > income <- c(rep("low", 5), rep("high", 5)) > count <- 1:10 > mydf <-