similar to: Add "bin" variable to dataframe

I am sure this is easy but I am not finding a function to do this. I have two columns in a matrix. The first column contains multiple entries of numbers from 1 to 100 (i.e. 10 ones, 8 twos etc.). The second column contains unique numbers. I want to sum the numbers in column two based on the indexed values in column one (e.g. sum of all values in column two associated with the value 1 in column

Dear list, I have a dataframe with two column as fellow. > head(dat) V1 V2 0.15624 0.94567 0.26039 0.66442 0.16629 0.97822 0.23474 0.72079 0.11037 0.83760 0.14969 0.91312 I want to get the column V2 mean value based on the bin of column of V1. I write the code as fellow. It works, but I think this is not the elegant way. Any suggestions?

Hello I have a large series of data value -- effectivly say the point across the x-axis where a pitch crosses home plate. What I want to do is find the % of ground balls at various distances across home plate. I therefore need to 'bin' the two data sets I have - plate location for ground balls and plate location for all other outcomes. Question is how can I set up a series of bins

Dear all, I would like to aggregate a data frame (consisting of 2 columns - one for the bins, say factors, and one for the values) along bins and quantiles within the bins. I have tried aggregate(data.frame$values, list(bin = data.frame $bin,Quantile=cut2(data.frame$bin,g=10)),sum) but then the quantiles apply to the population as a whole and not the individual bins. Upon this

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

Hi, I'd really appreciate if someone could give me some help or advice about this - I've tried everything I know and am clueless about how to proceed! I've written a script to import ASCII data of raster maps, bin them into categories, calculate the mean values within these bins and plot the two in a simple graph. I'm running into problems with my x axis, as R cannot add the bin

Hi there, probably there is a very simple solution, but I cannot think of one... I have a vector with values: data <- c(1,6,3,4,8,4,2,9) and I have a vector with bin breaks: bins <- c(1,3,5,7,9,11) Now, I'd like to get for each data point the index of the bin-vector where the value falls in (or equals the lower bin break). In the example case, I'd like to get:

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)

Hello, I'm using the Hmisc cut2 function to bin a set of data. It produces bins that I like with results like this: [96,270]:171 [69, 96): 54 [49, 69): 40 [35, 49): 28 [28, 35): 14 [24, 28): 8 (Other) : 48 I would like to take a second set of data, and assign it to bins based on factors defined by my call to cut 2. Does anyone know how I can do this? Thank you, -S -- View this message

Hello, I am trying to fit gamma, negative exponential and inverse power functions to a dataset, and then test whether the fit of each curve is good. To do this I have been advised to calculate predicted values for bins of data (I have grouped a continuous range of distances into 1km bins), and then apply a chi-squared test. Example: > data <- data.frame(distance=c(1,2,3,4,5,6,7),

I have a data frame with data similar to this: NameA GrpA NameB GrpB Dist A Alpha B Alpha 0.2 A Alpha C Beta 0.2 A Alpha D Beta 0.4 B Alpha C Beta 0.2 B Alpha D Beta 0.1 C Beta D Beta 0.3 Dist is a distance measure between two entities. The table displays all to all distances, but the

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

Hello all, this is not really an * question but it is somehow related, i am trying to develop a working proposal for cheap and quick telephony services using Voip running over *. By running a wireless network (over 802.11 a/b/g devices), i plan to be able to reach customers directly with eithe table top or handheld 802.11 sip enabled phones. But the disadvantage is that how do i power each radio

Hello, I have created two histograms with: hist2d(gps2, nbins=200, col = c("white",heat.colors(16))) Both of them have the same range and the same number of bins. Now I would like to compare them bin by bin and plot the results. Could someone please tell me how to do that. I searched the man pages and the web, but couldn't find anything. Thank you very much. Phil

Dear R users, I would like to great a frequency table from raw data and then access the classes/bins and their respective frequencies separately. Here the code to create the frequency tables: x1 <- c(1,5,1,1,2,2,3,4,5,3,2,3,6,4,3,8) t1 <- table(x1) print(t1[1]) Its easy to plot this, but how do I actually access the frequencies alone and the bins alone? Basically I am looking to get:

Hi there, First off, despite this being my first post here, I have scanned the R help forums a lot in the past few months to help with some questions, so a big thank you to the community as a whole for being so helpful! I'm somewhat of an R newbie, and have run up against a problem that I can't seem to solve. If anyone is able to help I would really appreciate it! I'm looking at a

Hello all. I noticed that the default setting for breaks in the construction of histograms in hist() is ?right = TRUE?. I think ?right=FALSE? would be more consistent with usual definitions of lower and upper limits for bins in applied statistics, and I suggest that you consider making it the default for hist(). For example, I generated the following frequency distribution for duration of

hi all : i have the data below and then below that, i call the hist function three times using the Scott method for the widths of the bins. the bin width is different for the three histograms but I would like it to always be 0.05 regfardless of the data set being histogrammed. I'm sure there must be a manual way to do this which is fine with me. i tried breaks=0.05 but it wasn't happy

Hi R-users, I am trying to divide a vector (say X) into equal frequency bins. If one uses the hist() function, then a histogram is plotted, but with bins of equal widths, and not with bins having the same number of data points. I have then tried the histogram() function as follows: histogram(X, nint=10, breaks=NULL, equal.widths=F) This works as I want. However, I can't extract which

Hi, I'm trying to setup some complicated binning with statistics and could use a little help. I've found the bin2 function from the ash package, but it doesn't do everything I need. My intention is to copy some of their code and then modify as needed. I have a vector of two columns: head(data) r1 r2 [1,] 0.03516559 0.03102128 [2,] 0.02162539 0.14847034