similar to: Awk and Vilno

Hi Ahmed, Your problem appears trivial as you have already specified the form of the calculation. Learn how to "extract" specified elements from a data structure: # first value sum(dataset1$NPP[dataset1$date >= date1 & dataset1$date <= date2]) # second value dataset2$biomass[dataset2$date == date2] - dataset2$biomass[dataset2$date == date1] # third value

Hi, I'm having (yet another) problem with R. I have a few data sets that have this sort of format dataset1 ID DATA 1234 value 2345 value 3456 value dataset2 ID DATA 1111 value 2345 value 3333 value What i really want to do is write an R script that says "if the ID of dataset1 and 2 match (2nd row), print out that whole row into a new dataset3". No idea how to do that though.

In response to those who asked for a better explanation of what the Vilno software does, here's a simple example that gives some idea of what it does. LABRESULTS is a dataset with multiple rows per patient , with lab sodium measurements. It has columns: PATIENT_ID, VISIT_NUM, and SODIUM. DEMO is a dataset with one row per patient, with demographic data. It has columns: PATIENT_ID, GENDER.

As noted on the R-project web site itself ( www.r-project.org -> Manuals -> R Data Import/Export ), it can be cumbersome to prepare messy and dirty data for analysis with the R tool itself. I've also seen at least one S programming book (one of the yellow Springer ones) that says, more briefly, the same thing. The R Data Import/Export page recommends examples using SAS, Perl, Python, and

Dear R users, A co-worker and I are writing a function to facilitate graph plotting in R. The function makes use of a lot of lists in its defaults. However, we discovered that R does not necessarily preserve the defaults if we were to input them in the form of list() when initializing the function. For example, if you feed the function codes below into R: myfunction=function( list1=list

Dear R experts, I would like to please ask for your help with repeating steps in an apply statement. I have a dataframe that lists multiple variables for a given id and visit, as well as drug treatment. > head(exp) id visit variable1 variable2 variable3 variable4 drug 1 3 1 13 10 7 11 0 2 3 5 10 15 9 9 0 3 3 12

Hello I am writing an article demonstrating how quantile plots work. In one figure, I generate 3 sets of normal data, and add different sorts of outliers to each. I then make 9 qqnorm plots, in a 3x3 array: Outlier1 Outler2 Outlier3 Dataset1 Dataset2 Dataset3 which I did using mfrow = c(3,3). I'd like to use the space on the page as efficiently as possible,so I

Hoping someone out there can help me...this seems like an easy task but I can't figure it out... I want to replace variables in one dataset (Dataset1) with a variable from another dataset (Dataset2). All the values for variables x1 and x2 in Dataset1 have a unique match to the variable uniquenum in Dataset2. For example, in Dataset1 grpnum A has a value of 343 for variable x1. In Dataset2,

When I make a sample in sp, for example a random samping of 5 points in dataset1: sample.dataset1=spsample(dataset1, n = 5, "random") I have a sp object for the selected sampling... My question is : How can I extract from dataset2 the points & data for the coordinates(sample.dataset1) ? The dataset2 would be an object with the same area and coordinate system, but I would like to

Dear friends, my question is how to aggregate dataset and the inverse manipulation. e.g.My dataset data structure1: x 1 1 2 3 3 data structure2: x freq 1 2 2 1 3 2 Then how to generate dataset2 from dataset1 and generate dataset1 from dataset2? e.g. dataset2 from dataset1 : x<-c(1,1,2,3,3) a<-tab(x) as.data.frame(a) *But i can't do the inverse manipulation:generate dataset1 from

Hello everyone, Peter (see my earlier post) recommended the following script for finding the means and standard deviations and putting them in table form. However, I would like the standard deviations under the means in brackets. Can anyone check this code to see how this can be adjusted? library(xtable) dataset1 = matrix( c(1,2,3,4, 5, 6 ), 2 , 3) dataset2 = matrix( c(4,3,5,10, 1, 0), 2, 3)

Readers, Is it possible to create a plot command based upon the indices of missing values in a data set? dataset1<-read.table(text=' 10 2 20 NA 30 5 40 7 50 NA 60 NA 70 2 80 6 90 NA 100 9 ') dataset2<-read.table(text=' 0.2 0.4 0.1 0.9 0.2 0.3 1.1 0.7 0.9 0.6 0.4 ') The 'approx' function is used to obtain the interpolated values for 'NA' in dataset1.

Hello everyone, I have two sets of data, with the following structure: DataSet1 Location Part Sample 1 Sample 2 A 1 value value A 2 value value A 3 value value B 1 value value DataSet2 Location Sample 1 Sample 2 A

I am attempting to replicate some of my experience from SAS in R and assume there are best methods for using a combination of summary(), subset, and which() to produce a subset of mean values by categorical or ordinal factors. within sas I would write proc means mean data=dataset; class factor1 factor2 var variable1 variable2; RUN; producing an output with means for each variable by factor

In a loop, I compose the name of a csv file using paste, then read it (e.g., dataset1.csv, dataset2.csv, etc). The name of the dataframe assigned to the imported csv is also composed with paste (e.g., dataset1, dataset2, etc.). Now I want to perform operations on the dataframes dataset1, dataset2, etc. However, the paste function only renders a string on which I can not, for example, do operations

Hello, I'm using SPSS at work but really would like to switch to R. Right now I'm trying to learn R in reproducing calculations I did with SPSS but am stuck with something that is quite simple and comprehensible in SPSS-Syntax: IF (variable1.fac = 0 AND variable2.num = 0) variable3=1. IF (variable1.fac = 0 AND variable2.num >= 1) variable3=2. IF (variable1.fac = 1 AND variable2.num =

Dear list, I am trying to use lme to build the analogue of the following SAS MIXED random specification: random int+Variable1+Variable2 /subject = Subject group=Condition type=vc; which gives a Condition-blocked heterogeneity in the random effects variance-covariance matrix. Needless to say, I have a hard time in specifying Condition-specific heterogeneities in the variance-covariance

Hi all, Please consider the following: DataSet1.. <- data.frame(Bldgtype=c("SFDM","SFDM","SFDM","SFDM","SFDM","SFDM","APT"), Taz=c("254","254","254","564","564","564","564"),stringsAsFactors = FALSE) PeriodResType_Zx <-

Hi everyone, I've got two data sets as below. My question now is: how can I use Dataset2 as a filter for Dataset1? My goal is just to keep the rows of Dataset1 where the first column (Date) matches the Dates in Dataset2. I would appreciate any solutions to this issue. Many thanks! S.B. Dataset1: Date A B C D 1

Dear R listers -- I have several questions about using the ppr command in the modreg module. I discovered -- quite by accident -- that if I re-order the data, I obtain different results. The output below shows what I mean. I have two datasets (dataset1 and dataset2) that are identical (tested using proc compare in SAS) except for the fact that the records are in different order. Below I have