similar to: converting histogram to barchart

Hi I have recently been analyzing birthweight data from a clinic. The data has obvious defects in that there is digit preference on certain weights making them overrepresented. This shows as spikes in the histogram on certain well rounded weights like 2, 2.5, 3, etc. I would like to show this to government officials but can't figure out how I should present the finding in an easy to

Dear all, I've got a quite large dataframe (stor) with rows subject and rt (reaction time). I would like to split the reaction times per subject into 6 bins of equal size. Right now, I'm using the following code: bindata <- function(rt) { bindata <- rep(-1,length(rt)) binwidth <- length(rt)/6 bindata[order(rt)[(0*binwidth)+1:(1*binwidth)]] <- 1

Dear all, I want to use the histogtam as a density estimator, with the binwidths calculated using scott's formula which is binwidth = 3.49*ST.dev.*n^(-1/3) for the following data  (30 data points) 12-9-3-6-1-23-21-7-18-16-15-4-19-22-20-2-3-18-8-10-1-7-5-4-11-12-3-9-19-7 so first,I' ve tried this manually, and substituted in the above formula and I got st.dev.=7.02745 and thus the

Hi, Here are three plots: library(ggplot2) data(diamonds) randind <- sample(nrow(diamonds),1000,replace=FALSE) dsmall <- diamonds[randind,] qplot(carat, data=dsmall, geom="histogram",binwidth=1) qplot(carat, data=dsmall, geom="histogram",binwidth=.1) qplot(carat, data=dsmall, geom="histogram",binwidth=.01) What are ways to put these three plots on a single

Hello all, I have a peculiar and particular bug that I stumbled across with ggplot2. I cannot seem to replicate it with anything other than my specific data set. Here is the problem: - when I try to plot a histogram, allowing for ggplot2 to decide the binwidths itself, I get the following error: - stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to

It appears I broke ggplot in my script, but that maybe it is because the caffeine has worn off or maybe it is late in the day.   I thought I was beginning to understand ggplot, but I have encountered a silly little issue.   For some reason the following does not produce a histogram with fill due to the Person's characteristics: (Note that VADeaths_flat_df$Data works fine...)    

Hello My dataset is as follows: jobno recruits 1100 18 1200 1 1850 5 2100 190 2789 25 3000 1 . . . . the dataset has 130 rows I want to plot barplot from left side and cumulative curve from right side in one graph itself using layers in ggplot2. I sorted the recruits 1st in decreasing order

Hola a todos Me gustaría saber si me pueden ayudar con lo siguiente. Realicé un Boxplot usando ggplot2 para visualizar el comportamiento de dos variables. Visualmente no se notan las diferencias porque la gráfica de la derecha (parásitos en el abdomen) llega hasta 20 en el eje y. ¿Cómo puedo hacer para que las dos gráficas muestren la misma escala en el eje Y, es decir, que las dos lleguen a 60?

Hallo I am not familiar with any of packages you use (except of MASS and ggplot2) and the code is too complicated without any hint where the error could come from and what is the message you get. I wonder if anybody would like to go through your whole code. 1. data seems to be read correctly ICUData <- read.csv(file = "ICUData.csv", stringsAsFactors = TRUE) ICUData.neuro <-

I'm trying to overlay two histograms using transparency to enable viewing of multiple distributions on a single scale. So far ggplot2 seems to do what I want. However I'm having a problem generating the legend coloring appropriate to each distribution in the plot. Here is a test case to show my best (failed) effort so far: library(ggplot2) x <- data.frame(X=rnorm(1000, mean=0)) y

R-help users, Thanks in advance for any assistance ... I truly appreciate your expertise. I searched help and could not figure this out, and think you can probably offer some helpful tips. I apologize if I missed something, which I'm sure I probably did. I have data for many "samples". (e.g. 1950, 1951, 1952, etc.) For each "sample", I have many data-frames.

Venables and Ripley describe a speedup where you take a structure like x<-NULL for(i in sequence) y<-c(y,function(x,i)) and convert it to one like x<-numeric(its length) for(i in sequence) y[i]<-function(x,i) I tried this speedup on some simple examples and it made them twice as fast. But now I am hitting a snag with some real code. This original version works:

I have the following data frame: > algaedata = year DIV cellsperml 2001 BAC 72.808 2001 CHL 3.273 2002 BAC 14.002 2002 CYA 220.896 2002 UNI 464.699 2003 BAP 0 2003 BAC 1.782 2004 CYA 315.799 2005 UNI 222.532 2005 BAP 0.2 2005 CYA 163.627 2005 BAC 324.949 2006 CHL 1.636 2006 BAC 199.145 2007 CHL 19.635 2007 CYA 134.174 2007 BAC 485.405 2007 CHL 11.454 2007 CYA 104.721 ...which makes a fine

Dear R users, I have got the following data frame, called my_df: gender day_birth month_birth year_birth labour 1 F 22 10 2001 1 2 M 29 10 2001 2 3 M 1 11 2001 1 4 F 3 11

I'm having trouble figuring out how to format Date variables when used as axis labels in graphs. The particular case here is an attempt to re-create Nightingale's coxcomb graph with ggplot2, where I'd like the months to be labeled as "Mar 1885", "Apr 1885", using a date format of "%b %Y" applied to label the dates, or really anything other than

Hi All, I have a for loop inside the function and I cannot get UUU to give me an updated grid.dens object when I run the function (it does update when I run just the for loop). Here's a simplified version of my function: UUU=function(pop, grid.dens) { for (i in 1:10){ Food=grid.dens[pop$yloc[i],pop$xloc[i]] #use initial grid.dens values Consumed=(pop$weight[i]*0.25) Left=Food-Consumed

Hello, I'm working on using the LLVM JIT for a little project of mine, amazing work first off! I have a question about optimization passes. I initially have this function I've created, in python it looks like this: OS_end = 50OS_start = 0OS_timestep = 1birth_rate = .3population = 30.0for time in range(OS_start, OS_end, OS_timestep): births = birth_rate * population deaths = 0.1

Dear list members I want to analyze separately the months of a time series. In other words, I want to plot and fit models for each month separately. Taking the example of http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/src/timeseries.html births <- scan("http://robjhyndman.com/tsdldata/data/nybirths.dat") birthstimeseries <- ts(births, frequency=12,

Hi With ggplot2 I can very easily create beautiful histograms but I would like to put two histograms on the same plot. The histograms may be over-lapping. When they are overlapping the bars are shown on top of each other (so that the overall height is the sum of the two). Is there any way to get them to display overlapping (with smaller value in front, larger value behind) so that the overall

Dear developers, the current implementation of hist.default() calculates 'density' (and 'intensities') as dens <- counts/(n*h) where h has been calculated before as h <- diff(fuzzybreaks) which results in 'fuzzy' values for the density, see e.g. > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE) > print(tmp$density,digits=15) [1]