similar to: Matching rows in a Data set? I'm Stuck!!

Hi R users, I need your help to write a code in r that does the following calculation from three different datasets; ac = 1/sum (NPP from date 1 to date 2, dataset=1) * (biomass at date 2 -biomass at date 1, dataset = 2) + (littfall at date 2, dataset=3). all the dates are in yr-month-day format. Which library or function Should I use to tell R do these calculations of these variables at

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

Dear R users, I have two datasets: id1 <- c(rep(1,10), rep(2,10), rep(3,10)) value1 <- sample(1:100, 30, replace=TRUE) dataset1 <- cbind(id1,value1) id2 <- c(1,2,3) subtract.value <- c(1,3,5) dataset2 <- cbind(id2, subtract.value) I want to subtract the number of rows in the subtract.value that corresponds to the id value in dataset1. So for the 1 in id1, I want to

In clinical trial data preparation and many other data situations, the statistical programmer needs to merge and re-merge multiple input files countless times. A syntax for merging files that is clear and concise is very important for the statistical programmer's productivity. Here is how Vilno does it: inlist dataset1 dataset2 dataset3 ; joinby variable1 variable2 where ( var3<=var4 ) ;

The subject of your email is missing. Perhaps you need to read the Posting Guide (again?) about attachments. Embedding your example directly in the body of the email is generally more accessible in archives than attaching it. -- Sent from my phone. Please excuse my brevity. On April 27, 2016 1:14:17 PM GMT+01:00, G.Maubach at gmx.de wrote: >Hi All, > >I am addressing this post to all

Hi All, I am addressing this post to all who are new to R. When learing R in the last weeks I took some notes for myself to have code snippets ready for the data analysis process. I put these snippets together as a script template for future use. Almost all of the given command prototypes are tested. The template script contains snippets for best practices and leaves out the commands that

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 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

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

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,

Hello all, I am new to xtable. I have several datasets in the form of matrices. Consider the following two simple datasets which are 2 x 3 matrices. The rows in both matrices have the same meaning. For example the first row of both matrices are variable 1 and the second row of both matrices are variable 2. dataset1 = matrix( c(1,2,3,4, 5, 6 ), 2 , 3) dataset2 = matrix( c(4,3,5,10, 1, 0), 2, 3)

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)

Hello. I'm trying to run a series of commands in two different datasets. For make it efficient I want to make a loop for it. Until now the only command for loops i found it's the for() command it's only for series of numbers and not a series of strings, witch it's what i'm needing. It would be something like this for(i in dataset1 dataset2) { i <-

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.

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

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-users, I need to load outputs from multiple previous calculations into one R session for comparison and (cross-)analysis. The previous calculations are stored in different directories in .Rdata files (I don't know if this is the best storage for later usage, but the previous project could be recalculated and saved into different format, if needed, potentially.) I can load consequently

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, all, I?d like to do the clustering analysis in my dataset. The example data are as follows: Dataset 1: 500, 490, 486, 490, 491, 493, 480, 461, 504, 476, 434, 500, 470, 495, 3116, 3142, 12836, 3062, 3091, 3141, 3177, 3150, 3114, 3149; Dataset 2: 506, 473, 495, 494, 434, 459, 445, 475, 476, 128367, 470, 513, 466, 476,482, 1201, 469, 502; I had so many datasets like that. Basically, every

HI, You may try this: dat1<- read.table(text=" CustID TripDate Store Bread Butter Milk Eggs 1 2-Jan-12 a 2 0 2 1 1 6-Jan-12 c 0 3 3 0 1 9-Jan-12 a 3 3 0 0 1 31-Mar-13 a 3 0 0 0 2 31-Aug-12 a 0 3 3 0 2 24-Sep-12 a 3 3 0 0 2 25-Sep-12 b 3 0 0 0 ",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<- dat1[,-c(1:3)] res<- lapply(seq_len(ncol(dat2)),function(i)