similar to: Problems with a specific calculate.

note: whole function is below- I am sure I am doing something silly. when I use it like USGS(input="precipitation") it is choking on the precip.1 <- subset(DF, precipitation!="NA") b <- ddply(precip.1$precipitation, .(precip.1$gauge_name), cumsum) DF.precip <- precip.1 DF.precip$precipitation <- b$.data part, but runs fine outside of the function: days=7

Hi all, i'm sure there is an easy way to do this, but i'm stumped, so any help would be appreciated. i have a single column of data for precipitation every 15 minutes over a year. i want to sum the precip to daily data. so the first 96 records = the first day, the second 96 records = the second day, and so on.... is there a way to write a for loop that would sum the data to daily, and

Hello, I have two different files which I'd like to combine to make one data frame but I've no idea how to do it! The first file has two columns; one is the date, the following is a binary code for debris flow events. Then my other file has also two columns; the date and then precipitation data. The thing is, is that the two date columns don't all contain the same dates. The binary

Hello I have a matlab MAT file that contains one single variable: a. The structure of a is as follows: a.river1.flow (flow values) a.river1.date_flow (date) a.river1.precip (precipitation values) a.river1.date_precip a.river2.flow a.river2.date_flow a.river2.precip a.river2.date_precip I have used readMat to load the variable a in R, however I have no idea how readMat translates a. I managed

Hi all, I want to arrange two ggplot2 plots on the same page with their x-axes lined up - even though one is a boxplot and the other is a line plot. Is there a simple way to do this? I know I could do this using facetting if they were both the same type of plot (for example, if they were both boxplots), but I haven't been able to figure it out for two different types of plots. Below is my

Hello, I am new to R exploratory data analysis and plotting. Is anyone aware of a way to overlay a set of conditional histograms with conditional PDFs? Below, I generate a lattice plot of precipitation histograms based on different months and stations, given a subset of the dataset: histogram(~ data | month * station, data = sta.stack[sta.stack[,"type"]=="precip" &

Dear R-users Sorry for posting the previous message too soon before I have finished it. I have matrix (mprecip) with headers: > dim(mprecip) [1] 6268 170 > mprecip date GilzeRijen Eindhoven Volkel ZuidLimburg Arcen Ubachsberg 1 01/01/1978 NA 0.0 NA 0.1 NA NA 2 01/02/1978 NA 0.0 NA 0.0 NA NA 3

Hi R user, Would you mind to help me on how I can change a value in a specific column and row in a big table? but the column of the table is a factor (not numeric). Here is an example. I want to change dat[4:5,3]<-"20" but it generated NA> do you have any suggestions for me? dat<-structure(list(Sites = structure(1:5, .Label = c("Site1", "Site2",

Hello, This maybe a newbie question. I have a dataframe that looks like the sample at the bottom of the email. I have monthly precipitation data from several sites over several years. For each site, I need to extract years that have a complete series of 12 monthly precipitation values, while excluding that year for sites with incomplete data. I can't figure out how to do this gracefully

The simplest would be to convert precip to character and then back to a factor if you really want it to be a factor. This will also remove the levels that no longer exist. str(dat) # 'data.frame': 5 obs. of 3 variables: # $ Sites : Factor w/ 5 levels "Site1","Site2",..: 1 2 3 4 5 # $ temp : num 14 15 12 12.5 17 # $ precip: Factor w/ 5 levels

Dear R community, I am having trouble determining how to create the graph I want utilizing my relatively limited knowledge of R. So far I have been using the lattice library to create most of what I need. The dataset (enviro) consists of 2 variables (Temp and Precip) for each Day of a 2-yr period (Year). I wish to display Temp and Precip along the y axis plotted by Day on the x axis to allow

Dear group, First I provide you with an example, I found in the newsgroup. Then I'd like to explain my problem to you by means of the output. enviro <- data.frame(Year = rep(2001:2002, each = 365), Day = rep(1:365, 2), Precip = pmax(0, rnorm(365 * 2)), Temp = 2 + 0.2 * rnorm(365 * 2)) xyplot(Precip + Temp ~ Day | Year,

Dear all, I'm having trouble getting the correct spacing between x-axis labels on a barplot. This is the command I'm using to generate the plot: temp <- barplot(precip, beside=TRUE, xaxt="n", las=1, xpd=FALSE, col="grey28", ylim=c(0, max(precip))) Here is the structure of temp: > str(temp) ?num [1:96, 1] 0.7 1.9 3.1 4.3 5.5 6.7 7.9 9.1 10.3 11.5 ... And here

"It seems therefore that there is no other way than read in individually > 100 weather tables using read.tables., right? Using file.choose() doesn't change the work." Yes. With that many files, file.choose() does not make sense. However, I still do not understand what is the problem with using lapply() on the character vector of file names with read.table() as you did in your

I have a file, each column of which is a separate year, and each row of each column is mean precipitation for that month. Looks like this (except it goes back to 1964). month X2000 X2001 X2002 X2003 X2004 X2005 X2006 X2007 X2008 X2009 1 1.600 1.010 4.320 2.110 0.925 3.275 3.460 0.675 1.315 2.920 2 2.960 3.905 3.230 2.380 2.720 1.880 2.430 1.380

Dear R-users, I am trying to make a plot with ggplot-geom_tile(), but cannot remove some unwanted (white) lines through my plot. Below a reproducible example: ##### library(ggplot2) tot=as.data.frame(rep(seq(-50,50,5),each=21)) names(tot)="precip" temp=rep(seq(-5,5,0.5),21) tot$temp=temp disc=array(dim=c(21,21)) for(i in 1:21){ for(y in 1:21){ temp<-

Hi, I am using mgcv:gam and have developed a model with 5 smoothed predictors and one factor. gam1 <- gam(log.sp~ s(Spr.precip,bs="ts") + s(Win.precip,bs="ts") + s( Spr.Tmin,bs="ts") + s(P.sum.Tmin,bs="ts") + s( Win.Tmax,bs="ts") +factor(site),data=dat3) The total deviance explained = 70.4%. I would like to extract the variance explained

Dear all, quite a naive question: I have a data frame and I computed "the kernel density estimate" with density on each column. Now I'd like to export in a txt file the density function output for each column, but, when if I use write.table, I get a message "Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce class "density" into a

Hi all, I sent a request round last week asking for help with using a "for" loop to read and separate a large dataset. The response I got worked great, but now I have another problem with using my loop. Basically I have a number of different files containing columned data. There are 132 datasets, named such that I have something in the form... precip_colxxx.txt ...where xxx is a

Look at the bottom of the message for my question #here is a little function that I wrote USGS <- function(input="discharge", days=7){ library(chron) library(gsubfn) #021973269 is the Waynesboro Gauge on the Savannah River Proper (SRS) #02102908 is the Flat Creek Gauge (ftbrfcms) #02133500 is the Drowning Creek (ftbrbmcm) #02341800 is the Upatoi Creek Near Columbus (ftbn) #02342500 is