similar to: Help with R plots

I issued the following curl command to post to the database using REST: curl -i -X POST -d "<heartrate><heartRate>102</ heartRate><sessionID>1002</sessionID><timeStamp>15068</timeStamp></ heartrate>" http://localhost:3000/heartrates I have tested the GET (with curl also) and it works fine! curl http://localhost:3000/heartrates/45

I have a csv file, heartrate excercise medicine Time 12 0 0 4:30 am 23 5 0 5:00 am 34 6 0 5:30 am 56 3 0 6:00 am 24 12

Hi Everyone, I have a some data from a sports gps device like the following: time latitude longitude altitude distance heartrate 1 1277648884 0.304048 -0.793819 260 0.000000 94 2 1277648885 0.304056 -0.793772 262 4.307615 95 3 1277648888 0.304060 -0.793696 263 11.262347 97 4 1277648894 0.304075 -0.793544 263 25.237911 103 5 1277648898

. HI there, I'd like to show demonstrate how the chi-squared distribution works, so I've come up with a sample data frame of two categorical variables y<-data.frame(gender=sample(c('Male', 'Female'), size=100000, replace=TRUE, c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=100000, replace=TRUE, c(0.5, 0.5))) And I'd like to create a list of 100

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When I use rbind() or rbind.data.frame() to add a row to an existing dataframe, it appears that attributes for the column of type "factor" are dropped. See the sample example below to reproduce the problem. Please suggest How I can fix this. Thanks, Sammy a=c("Male", "Male", "Female", "Male") b=c(1,2,3,4) c=c("great", "bad",

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

R-users it appears I am leaning on your knowledge once again.  Is there any way to add a vertical line to a histogram and qplot "stacked" plot?  Here is my current attempt:   "qplot" approach attempt: qplot(Run, data = data_dataframe, breaks = breaks, fill = Temperature, main = short_title) + scale_x_continuous("Data") + scale_y_continuous("Freq")

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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

I have written a program in C that two xy datasets, aligns these 2 datasets based on shared features, transforms them into equal sized histograms, transforms the histograms into cumulative distribution functions (via GSL) and finally performs a KS_test. I am wanting to validate my program's results and figure'd i would use R but i am kinda stuck at ithe histograms (I have 2 histogram

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

Hi, I've been passing the hist() function to tapply() to quickly generate histograms based on the list of factors supplied to tapply(). However, I have not figured out how to generate titles for each of the histograms, which paste in the unique values of the list factors as part of the histogram title. I'm hoping that someone can tell me how to do this. Thanks for your time and

Hello, R friends, I'm trying to crack this nut: Example Data. pet    gender dog    male dog    female dog    male cat    female cat    female cat    male Plot Task. Horizontal 100% bars where y axis shows gender factor (male vs. female) and x axis shows percentage of kind of pets (dog vs. cat) so that % dogs + % cats are stacked in 1 bar and sum up to 100% (for each gender group 1

Hi, I am using the densCols to draw a high volume scatter plot. Instead of using the default local density, I would like to take log of the local density and then map them to the colors. I could not figure out how to do that. For example: plot(x,y,col=densCols(x,y,"log")) ? Any help would be appreciated! Jiaxiu [[alternative HTML version deleted]]

I'm learning how to use tapply. Now I'm having a go at the following code in which dati contains almost 600 lines, Pot - numeric - are the capacities of power plants and SGruppo - text - the corresponding six technologies ("CCC", "CIC","TGC", "CSC","CPC", "TE"). .....................................................

Hi all, This seems like a basic problem, but no amount of playing with the code has solved it. I have a time-series data set like that shown below (only longer) and am seeking to plot the data with filled, circular points and error bars. I would like the error bars to be behind the points otherwise they tend to obscure the points (especially when I have a lot of points in the actual data set).

Hi, I''m attempting to create a users statistics controller, and have saved up some questions regarding this for this post. So, please comment on any one of them, if not all :-) 1) Is there a library somewhere for doing stats? (e.g. mean, median, sd, skewness..) on an array in rails? 2) What library would you recommend for "publication ready" (i.e. not cheesy) histograms,

# I have a dataframe with data and factors similar to the following: a <- rep(c("a", "b"), c(6,6)) df <- data.frame(f=a, d=rnorm(12)) df # I am trying to write a 'for' loop which will produce a jpeg histogram for each factor. I can individually isolate the data from a factor and produce a jpeg histogram like so: fnc <- function(x){ x <-

It is interesting to graph the distribution of the standardized average as n increases. Do this when the Xi are uniform on [0; 1]. Look at the histogram when n is 1, 5, 10 and 25. Do you see the normal curve taking shape? (A rule of thumb is that if the Xi are not too skewed, then n > 25 should make the average approximately normal. You might want > f=function(n,a=0,b=1) { mu=(b+a)/2