similar to: Subtracting rows by id

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'm a beginner user of R. I am stuck at what I thought was a very obvious problem, but surprisingly, I havent found any solution on the forum or online till now. My problem is simple. I have a file which has entries like the following: #ID Value1 List_of_values ID1 0.342 0.01,1.2,0,0.323,0.67 ID2 0.010 0.987,0.056,1.3,1.5,0.4

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,

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

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

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)

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 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

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 <-

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

Dear r experts, Sorry for this basic question, but I can't seem to find a solution? I have this data frame: df <- data.frame(id = c("id1", "id1", "id1", "id2", "id2", "id2"), A = c(11905, 11907, 11907, 11829, 11829, 11829), v1 = c(NA, 3, NA,1,2,NA), v2 = c(NA,2,NA, 2, NA,NA), v3 = c(NA,1,NA,1,NA,NA), v4 = c("N",

Thanks for pointing me out "aggregate", that works fine! There is one complication though: I have mixed types (numerical and character), So the matrix is of the form: A 1.0 200 ID1 A 3.0 800 ID1 A 2.0 200 ID1 B 0.5 20 ID2 B 0.9 50 ID2 C 5.0 70 ID1 One letter always has the same ID but one ID can be shared by many letters (like ID1) I just want to keep track of the ID, and get

Dear R users, I have a big text file formatted like this: x x_string y y_string id1 id1_string id2 id2_string z z_string w w_string stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string1 y y_string1 z z_string1 w w_string1 stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string2 y y_string2 id1

Hi Together, I have a problem with the plyr package - more precisely with the ddply function - and would be very grateful for any help. I hope the example here is precise enough for someone to identify the problem. Basically, in this step I want to identify observations that are identical in terms of certain identifiers (ID1, ID2, ID3) and just want to save those observations (in this step,

Hi, From your example data, dat1<- read.table(text=" id1?? id2?? value a????? b?????? 10 c????? d??????? 11 b???? a???????? 10 c????? e???????? 12 ",sep="",header=TRUE,stringsAsFactors=FALSE) #it is easier to get the output you wanted dat1[!duplicated(dat1$value),] #? id1 id2 value #1?? a?? b??? 10 #2?? c?? d??? 11 #4?? c?? e??? 12 But, if you have cases like the one