similar to: Efficient selection and alteration of dataframe records

Dear R Users, I am trying to write a wrapper around summarize and xYplot from Hmisc and am having trouble understanding how to pass arguments from the function I am writing to the nested functions. There must be a way, but I have not been able to figure it out. An example is below. Any advice would be greatly appreciated. Thanks, Dan # some example data df=expand.grid(rep=1:4,

So the general strategy for getting these into separate panels in ggplot is to have a single variable that will be your response and a factor variable that indexes which original variable it came from. This can be accomplished in many ways, but the way I use is with the melt() function in the reshape2 package. For example, library(reshape2) plotDF <- melt(SPYdf, ??? ??? ??? ??? ??? ???

Hello: I have done this before but cannot figure out how to do it again. I would like to graph campaign evolution of news stories on certain topics. The campaign time period is as follows: campaign<-seq.Date(from=as.Date('2011-09-06'), to=as.Date('2011-10-5'), by=1) I have a table of newspaper story frequencies containing a certain word that can be turned into a data.frame

Hi Charlie, Thanks. This is helpful. As mentioned in my original question, I want to be able to plot a few such charts on the same page, say a 2 x 2 grid with such a chart for each of 4 different stocks. Using your solution I accomplished this by making a list pLst of your ggplots and then calling cowplot::plot_grid( plotlist=pLst, nrow=2, ncol=2 ) That worked fine. The one issue I have is that

For this kind of control you will probably need to move to base graphics and utilize the `fig` argument in par(), in which case you would want to run the plot() command twice: once with your first outcome and once with your second, changing the par() settings before each one to control the size. On 01/19/2018 01:39 PM, Eric Berger wrote: > Hi Charlie, > Thanks. This is helpful. As

That (the need for base graphics) is false. It certainly **can** be done in base graphics -- see ?layout for a perhaps more straightforward way to do it along the lines you suggest. However both lattice and ggplot are based on grid graphics, which has a similar but slightly more flexible ?grid.layout function which would allow one to size and place subsequent ggplot or lattice graphs in an

Thanks for the reminder about lattice! I did some searching and there's a good example of manipulating the size of subplots using the `position` argument (see pp. 202-203 in the Trellis Users Guide: http://ml.stat.purdue.edu/stat695t/writings/Trellis.User.pdf). This is not within the paneling environment with the headers like in other trellis plots though, so you'll have to do a bit

Hi Charlie, I am comfortable to put the data in any way that works best. Here are two possibilities: an xts and a data frame. library(quantmod) quantmod::getSymbols("SPY") # creates xts variable SPY SPYxts <- SPY[,c("SPY.Close","SPY.Volume")] SPYdf <- data.frame(Date=index(SPYxts),close=as.numeric(SPYxts$SPY.Close),

Could you provide some information on your data structure (e.g., are the two time series in separate columns in the data)? The solution is fairly straightforward once you have the data in the right structure. And I do not think tidyquant is necessary for what you want. Best, Charlie -- Charles Redmon GRA, Center for Research Methods and Data Analysis PhD Student, Department of Linguistics

Hi all, Suppose I have 2 data.frame , a and b, how can I add them together to get c? Thanks > a A a 1 b 2 c 3 > b A a 6 c 1 > c A a 7 b 2 c 4 -- Best, Zhenjiang [[alternative HTML version deleted]]

Hi, I am trying to combine a long list but I can't work out how to do it, for example: abun<-list(rep(0,5),rep(0,7),rep(0,4),rep(0,10)) nb<-c(5,5,1,8) fill.abun <- function(x, y) { set <- sample(1:length(x), size = y) x[set] <- rlnorm(length(set)) return(x) } abun <- mapply(fill.abun, abun, nb) abun ## I want all the data in one

Hello, I am really new to R and it's still a challenge to me. Currently I'm working on my Master's Thesis. My supervisor works with SAS and is not familiar with R at all. I want to run an Anova, a tukey-test and as a result I want to have the tukey-grouping ( something like A - AB - B) I came across the HSD.test in the agricolae-package, but... unfortunately I do not get an output

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

Hello, Im working on a 50933 point count bird abundance dataset. I've succeeded in calculating a distance matrix for this entire set, but I don't have sufficient memory to convert this to a matrix, as below... abun.dist <- dist(abun.mat[1:50993,1:235) test <- rowMeans(as.matrix(abun.dist)) Error in matrix(0, size, size) : too many elements specified ive been able to run a hclust()

Dear members of the list, I'm fitting ordinal regressions using polr, and in some models I get the error copied below. Dependent variable is an ordered factor of bird abundance categories, and predictors are continuous habitat variables. > ro6 <- polr(formula = abun ~ InOmbrot + Oliva.OC + ToCultAr + DivCulArb + AltitMax + COORXY) > summary(ro6) Re-fitting to get Hessian

Can anyone point me in the right direction of figuring out what downweight() is doing? I am using vegan to perform CCA on diatom assemblage data. I have a lot of rare species, so I want to reduce the influence of rare species in my CCA. I have read that some authors reduce rare species by only including species with an abundance of at least 1% in at least one sample (other authors use 5% as a

Hi everyone, I am working with the dbFD function of the FD package, and there's something funny happening with the value of sing.sp in the output. Basically, I have a species-function matrix and a community matrix. One site in particular has 6 species, 4 of which have identical functional coding. I thus expect nbsp = 6 and sing.sp = 2 for this site. However, nbsp = sing.sp = 6. This

Hello I'm currently using the dbFD function of the FD package and i'm having some things that I can't do. Is there any way to check the relations between dbFD indexes? Function cor for example? I can't manage to put the informations correctly dbFD function gives a lot of output (indexes - nbsp, sing.sp, FRic, FEve, FDiv, FDis and RaoQ). I want to see the relationships between

Dear all, I have a question about FD package. I?m trying to calculate functional diversity indices using insect data. My trait data includes dispersal ability (0, 0.5, 1), body size (continuous) and five feeding guilds coded as in percentages (for example; 0,0,0.5,0.5,0) since some of the species can have two different feeding guilds. However, the package only calculates when I run ?calc.Frich=