similar to: subset() multiple arguments

I would like to do the following in ggplot: what am I missing? River.Mile <-c(202, 198, 190, 185, 179, 148, 119, 61) TSS <- c(1:8) DOC <- seq(2, by= 0.6, length.out=8) z <- data.frame(River.Mile, TSS, DOC) xyplot(TSS+DOC~River.Mile, data=z, auto.key=TRUE) thanks -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources

I would like to be able to do the xyplot in ggplot below. I read in the archive that Hadley was working on this for the next release, and I can not find the documentation (Aug. 23rd). River.Mile <- c(215 ,202, 198, 190, 185, 179, 148, 119, 61) Cu <- rnorm(9) Fe <- rnorm(9) Mg <- rnorm(9) Ti <- rnorm(9) Ir <- rnorm(9) r <- data.frame(River.Mile, Cu, Fe, Mg, Ti, Ir) z <-

I would like to Summarize values that are repeated measures at a certain river mile with box plot i.e. The data matrix looks like this 123 124 125 #fiver mile 0.5 0.6 0.7 0.4 0.5 0.6 ... ... ... #values I would like to make a boxplot with the river mile naming the different box plot. How do you suppress the X123? Stephen -- Let's not

below is my data frame. I would like to compute summary statistics for mgl for each river mile (mean, median, mode). My apologies in advance- I would like to get something like the SAS print out of PROC Univariate. I have performed an ANOVA and a tukey LSD and I would just like the summary statistics. thanks stephen RM mgl 1 215 0.9285714 2 215 0.7352941 3 215 1.6455696 4 215

I would like to be able to reverse the xlim on qplot this is the code that I am using qplot(a[,"River.Mile"], a[,26] ,ylab=colnames(a)[26], xlab="RiverMile", xlim=rev(c(60, 216)))+geom_smooth()+scale_x_continuous(breaks=c(215,202,198,190,185,179,148,119,61),

merge can only merge two objects at a time- I would like to merge more than two objects at a time. s.d <- structure(list(RiverMile = c(202L, 198L, 190L, 185L, 179L, 148L, 119L, 61L)), .Names = "RiverMile", row.names = c(NA, -8L), class = "data.frame") #s.d is all of the river miles that can occur in all of the data frames that I want to put together feb06 <-

This is an example of two months of data from a twenty four month data set that I would like to apply this too. These data are subsets of the same stations throught time, but differing ones were included on different sampling dates. I would like to subset these data and then put them together as a big matrix with the by column being RiverMile. What is the easiest way to proceed as this is a

taxa <- (structure(list(Date = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("2006/04", "2006/05", "2006/07", "2006/10", "2006/12", "2007/02", "2007/04", "2007/06", "2007/08", "2007/10", "2007/12", "2008/01"), class =

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

I would like to reproduce a figure found in HBN Hynes "The Ecology of Running Waters" on page 79 reprint first edition copyright 2001. This is a graph with graphs of insect abundance through time lined up in 3d as you proceed down river. any help is appreciated Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they

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

Does anyone know of a package to make a map from GIS data, and/or would it be easier in one of the free GIS programs. I would like to make a map of the savannah river area with our sampling locations. thanks stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are

I would like to be able to grab x and y columns out of a dataframe and then grab all of the columns that are not equal to x or y. I am sure that I am missing something easy. ftbr_UTM_downstream <- (structure(list(site = c("Jennie_Creek_Main_Stem", "Wolf_Pit_Creek_Main_Stem", "Little_Rockfish_Main_Stem_North", "Big_Muddy_Creek_Main_Stem",

I am new Ruby on Rails, so excuse me if my question seems pretty obvious. I am trying to validate uniqueness of a filed: class EventType < ActiveRecord::Base belongs_to :sport validates_uniqueness_of :event_type end When I run it, I get this error message: Showing /event_type/new.rhtml where line #27 raised undefined method `each'' for nil:NilClass <select

Hello, I'm doing some analysis on a rather large data set. In this case, some simple commands are failing. For example, this one: > x$eventtype <- factor(x$eventtype) Error in unique.default(x) : length 1093574297 is too large for hashing ...I think this is a bug, because "hashing" should not be required for the "factor" function. Am I right? The whole column

I have dissolved oxygen traces that are continuous (fifteen minutes) for two years (save for a couple of days, weeks, or minutes there depending on the perogative of the river). These traces are spaced out by river mile. I have figured out how to prepare data as to the sunspot example, but I can not figure out how to get multiple traces into the prepSEIS function and this is the warning that I

Hi everybody, I'm trying to construct contrasts for an ANOVA to determine if there is a significant trend in the means of my groups. In the following example, based on the type of 2x3 ANOVA I'm trying to perform, does the linear polynomial contrast generated by contr.poly allow me to test for a linear trend across groups? doi=data.frame( Group=c( rep(1, 5), rep(2, 5), rep(3, 5),

d <- structure(list(Site = structure(c(8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L, 8L, 12L, 7L, 6L, 11L, 5L, 10L, 4L, 3L, 2L, 1L, 9L,

I am thinking about submitting a package to CRAN that contains some units conversion functions that I use on a regular basis. Would this be helpful to the community, or would it be better to keep this as a personal package? I don't want to clutter CRAN. many thanks, -- Stephen Sefick ************************************************** Auburn University Biological Sciences 331 Funchess

x <- "1041281__2009_08_20_.lev" I would like to split this string up and only extract the leading numbers. 1041281 to use as a label for a data column in a bigger for loop function to read in data. regards, -- Stephen Sefick Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us