similar to: postscript and histogram plots

I have what is probably a simple problem. I have a data file from an MCMC Bayes estimation problem that is a vector of 500,000 numeric values (just one variable) ranging from 100,000 to 700,000. I need to display the histogram of this data in a high quality graphic for a figure in a journal publication. I want 100 bins so as to display a reasonable complete and smooth histogram, and I need the

Hi, Short Version: Is there a function to re-bin a histogram to new, broader bins? Long version: I'm trying to create a histogram, however my input-data is itself in the form of a fine-grained histogram, i.e. numbers of counts in regular one-second bins. I want to produce a histogram of, say, 10-minute bins (though possibly irregular bins also). I suppose I could re-create a data set as

Hi list, After a lot of tweaking i have managed to create a histogram with an overlaying density plot. The histogram shows a sample of birth weights of babies and the density plot shows birth weights from a much larger reference populaton. My data is divided in 0.1 Kg bins so in the code below binweigh=0.1. The trouble with the current graph is that it is not very clear since the density plot

been puzzling over this for a day. Summary integer variable to use with histogram, 170,000 rows. Value is day of year. Hist works, lattice histogram with nint does not work (spurious spikes in display), lattice histogram using breaks=c(0:365) works fine. Spike values appear to be sum of two adjacent bins. Want to know if this is a familiar problem, and what the recommended work-around is.

Hallo, How can I have the control of the width of each bin in the histogram? I would like to plot my data modifying the number and the width of the bins. Is there a good pdf or manual where i can learn to use the plot/hist in R very well? I find the help not always clear Thanks a lot Ale -- View this message in context: http://www.nabble.com/Histogram-tp24325261p24325261.html Sent from the R

Hello I need to plot a histogram, but insted of using bars, I'd like to plot the data points. I've been doing it like this so far: h <- hist(x, plot = F) plot(y = x$counts / sum(x$counts), x = x$breaks[2:length(x$breaks)], type = "p", log = "xy") Sometimes I want to have a look at the "raw" data (avoiding any kind of binning). When x

I have a column of 1000 datapoints from the normal distribution with mean 2 and variance 4. How can I get a histogram of these observations with 20 bins with each bin having 50 observations? -- Thanks, Jim. [[alternative HTML version deleted]]

Is it possible to change the x-axis values in a histogram to reflect binned values? Here are my data: histexample<-c(6,7,7,8,8,8,9,9,9,9,9,10,10,10,10,10,10,10,11,11,11,11,11,11,12,12,12,12,13,13,13,14,14,14,15,16) hist(histexample) Now, I'll bin pairs of adjacent values together (e.g., 5-6, 7-8, 9-10, 11-12, 13-14, 15-16) using the following bins<-c(4.5,6.5,8.5,10.5,12.5,14.5,16.5)

I'm trying to create a histogram from the following code, but my data keeps adding the Num vector and plotting that. My data in the CSV file is just one vector. Does anyone know why? Thanks Conrad SPXdf = data.frame(read.csv(file = "SPX.csv", header = TRUE, sep = ",", dec = ".", fill = TRUE)) Max = max(SPXdf[,2]) Min = min(SPXdf[,2]) Count =

Hello, I wanted to know if there was way to convert a histogram of a data-set to a kernel density estimate directly in R ? Specifically, I have a histogram [bins, counts] of samples {X1 ... XN} of a quantized variable X where there is one bin for each level of X, and I'ld like to directly get a kde estimate of the pdf of X from the histogram. Therefore, there is no additional quantization of

Hi, I want to be able to plot a single histogram of a measured trait with trait values from two conditions on the same histogram to allow easy comparison. I have previously done this in excel by plotting the two series on a single bargraph having calculated frequencies in bins. You then get one condition plotted immediately to the right of the other. I hope that makes sense? I don't

I have been trying to draw histogram for my manscript and found some strange things that I could not figure out why. Using the same code listed below I have successfully draw histograms for a few figures with fraction labeled on Y axis less than 1 (acturally between 0 to 0.1). But one dataset gives the Y axis label 0 to 5 as fraction. This is not true, as fraction are less than 1, although the

Folks: Say I have a set of histogram breaks: breaks=c(1:10,15) # With bin ids: bin_ids=1:(length(breaks)-1) # and some data (note that some of it falls outside the breaks: data=runif(min=1,max=20,n=100) *** What is the MOST EFFICIENT way to "classify" data into the histogram bins (return the bin_ids) and, say, return NA if the value falls outside of the bins. By classify, I mean

Is there a simple way to plot a histogram with colors? For example, suppose I generate random points in the N(2,1) distribution: x <- rnorm(100000, mean = 2, sd = 1) Now I would like to plot the histogram: hist(x) but I would like to show the bars with x < 0 in red, and the bars with x >= 0 in lightgreen. Is there any simple way to do it? I think I can do it in two steps:

Dear colleagues, I have extracted the dates of several news stories from a newspaper data base to chart coverage trends of an issue over time. They are in a data frame that looks just like one generated by the reproducible code below. I can already generate a histogram of the dates with various intervals (months, quarters, weeks years) using hist.Date. However, there are two other

Hi, I am searching for a possibility to display a logarithimic y-axis in a histogram. With plot that's easy (e.g. plot(1:10, log="y") but for histograms this does not work the same way: I tried hist(rnorm(1000), freq=FALSE, seq(-4, 4, .5), ylim=c(0.001, 0.5), log="y") Which gives the expected histogram but also warnings for my log="y" command

Hello! Thanks for reading this request for assistance. I have a question regarding creating a histogram-like figure from data that are not currently in the correct format for the "hist" command. Specifically, my data have been processed and are in a matrix with columns containing the variables of interest and separate columns containing the number of times this variable was

Hi, I have tab-delimited data with an unequal number of entries per column, of the sort: A B C 1 2 2 3 4 1 5 2 2 6 2 5 2 3 6 2 I would like to make a histogram of the frequencies of each represented number in a "stacked" histogram, where you can see the contribution of each group (A, B or C) to the total height of the bar, and each bar labeled with the

Dear R user, I am using UK census data on travel to work. The authorities have provided a breakdown in each area by mode (car, bicycle etc.) and distance travelled (0 ? 2 km, 2 ? 5 km etc). Therefore, after processing, the data for Sheffield look like this https://files.one.ubuntu.com/ej2VtVbJTEaelvMRlsocRg : dshef <- read.table("distmodesheff.csv", sep=",", header=TRUE)

Hi, I have a set of observations which are divided into two sets A and B. I have some code that bins the dataset into 10 bins based on the max and min of the observed values. I would like to make a histogram of A & B using my calculated bins but plot the distribution of B on top of A (like a stacked barplot). This is possible since both sets A & B are binned using the same bin ranges.