similar to: Efficient ways of merging data frames

Hi all, Say if I have a data table which consists of 4 column: itemID, location and price, which location is a text field and itemID and location together forms the primary keys. when I tried to run setkey (DT, itemID, location), I got the following message: Error in setkey (DT, itemID, location) : All keyed columns must be storage mode integer Is there any way I could define a non-numerical

Hi all, Thanks a lot for anyone's help in advance. I am trying to find a way to compute the day-to-day return (log return) from a n x r matrix containing, n different stocks and price quotes over r days. The time series of prices are already split by using unstack function. For the result, I would like to see a n x (r-1) matrix, where by each entry is the day-over-day return of

I am trying to merge two data frames, but one of the column headings are different in the two frames. How can I rjoin or rbind the tho frames? Johnny # Generate 2 blocks by confounding on abc d1 <- conf.design(c(1,1,1), p=2, block.name="blk", treatment.names = c("A","B","C")) d2 <- conf.design(c(1,1,1), p=2, block.name="blk",

Hi, Just wondering for the SMA and EMA in package TTR, is it possible to me to code it so that, say if I need to calculate SMA (x, n=100), when the sample size is less than 100, it will give me the SMA (x, k) where k is the sample size of the data? Right now it only gives me an invalid n error. Thanks! [[alternative HTML version deleted]]

Hi R help, Hi R help, Which is the easiest (most elegant) way to force "aov" to treat numerical variables as categorical ? Sincerely, Andrea Bernasconi DG PROBLEM EXAMPLE I consider the latin squares example described at page 157 of the book: Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter. This example use

Hello list, Thanks in advance for any help. I have many (approx 20) files that I have merged. For example d1<-read.csv("AlleleReport.csv") d2<-read.csv("AlleleReport.csv") m1 <- merge(d1, d2, by = c("IND", intersect(colnames(d1), colnames(d2))), all = TRUE) m2 <- merge(m1, d3, by = c("IND", intersect(colnames(m1), colnames(d3))), all =

System: Cenots Linux 6.9 Application: nut-2.7.5-0.20170613gitb1314c6 [with usb 0.1 from distro] Device: Mustek PowerMust 1060 LCD Comunication log file: dump.txt We are looking at the possibility of successful communicating with this device UPS Mustek PowerMust 1060 LCD. PS: wolfy on the list gives me assistance and i can install any new compiled nut version from sources. Thanks, Catalin.

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

Dear All, Here is a hypothetical sample (sorry for the clumsy code): A1 <- matrix(1:5, nrow=5, ncol=1) A2 <- matrix(6:10, nrow=5, ncol=1) A3 <- matrix(11:15, nrow=5, ncol=1) A4 <- matrix(16:20, nrow=5, ncol=1) A5 <- matrix(21:25, nrow=5, ncol=1) A6 <- matrix(26:30, nrow=5, ncol=1) B1 <- matrix(c(A1, A2, A3), nrow=5, ncol=3) B2 <- matrix(c(A2, A3, A4), nrow=5, ncol=3) B3

I wonder if there is a more efficient way to do this task. Suppose I have two data frames, such as d1 <- data.frame(x = c(1,2,3), y = c(4,5,6), z = c(7,8,9)) d2 <- d1[, c('y', 'x')] The first dataframe d1 has more variables than d2 and the variable columns are in a different order. So, what I want to do is compare the two frames on the variables that are common between

For certain reason, the content was not visible in the last mail, so posting it again. Dear Members, I have two different dataframes with a different number of rows. I need to apply a set of functions to each possible combination of rows with one row coming from 1st dataframe and other from 2nd dataframe. Though I am able to perform this task using for loops, I feel that there must be a more

Hi: I am a new R user. I have the following question and would appreciate your input Data1 (data frame 1) p1,d1,d2 (p1 is text and d1 and d2 are numeric) xyz,10,25 Data2 (data frame 2) p1,d1,d2 xyz,11,15 Now I want to create a new data frame that looks like so below. The fields d1 and s2 are summed by the product key. Data3 p1,d1,d2 xyz,21 (sum of 10 from Data1 and 11 from Data2),40 (sum of 25

Hello, The obvious way would be to preallocate the resulting data.frame, to expand an empty one on each iteration being a time expensive operation. n <- nrow(expand.grid(1:nrow(D1), 1:nrow(D2))) D4 <- data.frame(distance=integer(n),difference=integer(n)) k <- 0 for (i in 1:nrow(D1)){ for (j in 1:nrow(D2)) { k <- k + 1 D4[k, ] <-

Hello, Another way would be n <- nrow(expand.grid(1:nrow(D1), 1:nrow(D2))) D5 <- data.frame(distance=integer(n),difference=integer(n)) D5[] <- do.call(rbind, lapply(seq_len(nrow(D1)), function(i) t(sapply(seq_len(nrow(D2)), function(j){ c(distance=sqrt(sum((D1[i,1:2]-D2[j,1:2])^2)),difference=(D1[i,3]-D2[j,3])^2) } )))) identical(D3, D5) In my first answer I forgot to say that

You appear to be trying to write C code in R. Don't do this. If you can trade off space for efficiency, the calculation can be easily vectorized (assuming I correctly understand what you want to do, of course). set.seed(135) ## for reproducibility D1<-data.frame(x=1:5,y=6:10,z=rnorm(5)) D2<-data.frame(x=19:30,y=41:52,z=rnorm(12)) D.all <-merge(D1,D2, by.x=NULL,by.y=NULL) ##

Is it intended that the first suffix can no longer be blank? Seems to be caused by a bug fix to merge in R 2.15.0. $Rdevel --vanilla DF1 = data.frame(a=1:3,b=4:6) DF2 = data.frame(a=1:3,b=7:9) merge(DF1,DF2,by="a",suffixes=c("",".1")) Error in merge.data.frame(DF1, DF2, by = "a", suffixes = c("", ".1")) : there is already a column

Dear All, Is there any R function to test if two data frames, say df1 and df2, having the same row names and the same column names are identiques? Thanks in advance, Bernard --------------------------------- [[alternative HTML version deleted]]

I have numerous objects, each containing continuous data representing the same variable, movement rate, yet each having a different number of rows. e.g. d1<-as.matrix(rnorm(5)) d2<-as.matrix(rnorm(3)) d3<-as.matrix(rnorm(6)) How can I merge these three columns side-by-side in order to create a table regardless of the difference in length? I wish to analyze the output in a spreadsheet

kiotoqq wrote > I want to add a shorter column to my dataset with the function "merge", > it > should be filled with NAs wo be as long as the other colums, like this: > > id age > 9 46 > 8 56 > 6 52 > 5 NA > 4 NA > 3 NA > 1 NA > > i did this: > pa1 <- merge(pa1, an1, by="mergeid") > > and it says

I have two data sets about lots of companies' stock and fiscal data. One is monthly data with about 144,000 lines, and the other is quaterly with about 56,000. Each data set takes different company code. I need to merge these two together. I read both ask cvs. And the other file with corresponding firm code. Now I have three data sets. return$PERMNO, account$GVKEY. id is the data frames