similar to: sample points - sp package

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 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 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

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

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

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 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)

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

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 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 <-

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

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 <-

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

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.

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

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 ) ;

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

Dear all, I have 3 datasets all of which share the same longitude and latitude values, which I'm looking to plot onto a scattergraph. The third dataset has values which can only be either '1' or '2'. So to incorporate all three datasets onto two axes, I'm wondering if I can plot dataset1 and dataset2 as normal, but then use colour to determine whether these points are

Dear all, I had to place points at random, one in each of larger number of polygons (actually in objects of class 'SpatialPolygonsDataFrame' , see sp library), and tried first to do it using spsample (from sp). Surprisingly, every 5-15 trials, the output was a NULL value. The doc says that ' this may occur when trying to hit a small and awkwardly shaped polygon in a large

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