similar to: merge data

hi guys..please help me with this i am working on two data frames one goes like this: DF1 Sample_id RepairHours Denatured Dose ZeroMean FourtyFiveMean NinetyMean 1 SDM071 0 1 B 60.5 19.0 45.0 2 SDM071 1 1 B 46.0 23.0 42.5 3 SDM071 2 1 B 52.5 24.0 40.0 4 SDM071

#I want to "merge" or "join" 2 dataframes (df1 & df2) into a 3rd (mydf). I want the 3rd dataframe to contain 1 row for each row in df1 & df2, and all the columns in both df1 & df2. The solution should "work" even if the 2 dataframes are identical, and even if the 2 dataframes do not have the same column names. The rbind.fill function seems to work. For

Hi, all, My objective is to split a dataframe named "cmbine" according to the value of "classes". After the split, I will take the first instance from each class and bin them into a new dataframe, "df1". In the 2nd iteration, I will take the 2nd available instance and bin them into another new dataframe, "df2". >cmbine$names apple tiger pencil chicken

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

I have the following data: prefix <- c("cheap", "budget") roots <- c("car insurance", "auto insurance") suffix <- c("quote", "quotes") prefix2 <- c("cheap", "budget") roots2 <- c("car insurance", "auto insurance") roots3 <- c("car insurance", "auto

Hi there, I have a list of dataframes (generated by reading multiple files) and all dataframes are comparable in dimension and column names. They also have a common column, which, I'd like to use for merging. To give a simple example of what I have: df1 <- data.frame(c(LETTERS[1:5]), c(2,6,3,1,9)) names(df1) <- c("pos", "data") df3 <- df2 <- df1 df2$data

I need to merge three datasets and don't know how. If I were using SQL, I would use df3, look up the characteristics of each date in df1 and the value for each observation in df2. df1 - unique list of Dates and characteristics of those dates Date, YYYYMM, YYYYWW, DOW df2 - the raw data Date, Place, Value df3 - all posibile combinations of Date + Place (via

Hi, R-listers, Failed, when I tried to merge df1 and df2 by "codetot" in df1 and "codetoto" in df2. I want to know the reason and how to merge them together. Data frames and codes I have used were listed as followed. Thanks a lot in advance. df1: popcode codetot p3need BCPy01-01 BCPy01-01-1 100.0000 BCPy01-01 BCPy01-01-2 100.0000 BCPy01-01 BCPy01-01-3 100.0000 BCPy01-02

Hi, I am trying to find a function to match two data frames of different lengths for one field only. So, for example, df1 is: Name Position location francesca A 75 cristina B 36 And df2 is: location Country 75 UK 56 Austria And I would like to match on "Location" and the output to be something like: Name Position Location Match francesca A 75 1 cristina B 36 0 I have tried with

Hello, My problem is that I would like to merge multiple files with a common column but merge accepts only two data.frames to merge. In the real situation, I have 26 different data.frames with a common column. I can of course use merge many times (see below) but what would be more sophisticated solution? For loop? Any ideas? DF1 <- data.frame(var1 = letters[1:5], a = rnorm(5)) DF2 <-

Hi all, probably really simple to solve, but having no background in programming I haven't been able to figure this out: I have two dataframes like df1 <- data.frame(names1=c('aa','ab', 'ac', 'ad'), var1=c(1,5,7,12)) df2 <- data.frame(names2=c('aa', 'ab', 'ac', 'ad', 'ae'), var2=c(3,6,9,12,15)) Now I want merge

Dear expeRts, What is the best approach to create a third data frame from two given ones, when the new/third data frame has last column computed from the last columns of the two given data frames? ## Okay, sounds complicated, so here is an example. Assume we have the two data frames: df1 <- data.frame(Year=rep(2001:2010, each=2), Group=c("Group 1","Group 2"), Value=1:20)

Hi, I have faced a problem with the merge() function when trying to merge two data frames that have a common index but the second one does not have cases for all indexes in the first one. With usual variables R fills in the missing cases with NA if all=T is requested. But if the variable is a matrix R seems to insert NA only to the first column of the matrix and fill in the rest of the columns by

Hello! I have 2 data frames like this (well, actually, I have 200 of them): df1<-data.frame(location=c("loc 1","loc 2","loc 3"),date=c("1/1/2010","1/1/2010","1/1/2010"), a=1:3,b=11:13,c=111:113) df2<-data.frame(location=c("loc 1","loc 2","loc

Buenas, Tengo dos data.frames de la siguiente manera library(data.table) id<-c("a1","a2","a3","a4") id2<-c("a2","a3","a1","a4") y<-c(1,2,3,4) z<-c(3,5,6,7) k<-c(1,3,8,7) df1<-data.table(id,y,z) id<-c("a2","a3","a1","a4") df2<-data.table(id,x,y) Quiero

Dear list, I have been struggling with this for some time now, and for the last hour I have been struggling to make a working example for the list. I hope someone out there have some experience with plotting longitudinal data that they will share. My data is some patient data with three different time stamps. First the patients are identified at different times (first time stamp). Second, they

Hi, Two ways to create what should normally be the same data frame: > df1 <- data.frame(a=character(0), b=character(0))> df1 [1] a b <0 rows> (or 0-length row.names) > df2 <- as.data.frame(matrix(character(0), ncol=2, dimnames=list(NULL, letters[1:2]))) > df2 [1] a b <0 rows> (or 0-length row.names) unique() works as expected except that I

The rbind on empty and nonempty data frames behaves inconsistently. I am not sure if by design. In the first example, first row is deleted, which may or may not be on purpose: df1 <- data.frame() df2 <- data.frame(foo=c(1, 2), bar=c("a", "b")) rbind(df1, df2) foo bar 2 2 b Now if we continue: df1 <- data.frame(matrix(0, 0, 2)) names(df1) <- names(df2)

I would suggest the method of Sokal and Rholf (1995) S. 498, using the F test. Below I repeat the analysis by Spencer Graves: Spencer: > df1 <- data.frame(x=1:3, y=1:3+rnorm(3)) > df2 <- data.frame(x=1:3, y=1:3+rnorm(3)) > fit1 <- lm(y~x, df1) > s1 <- summary(fit1)$coefficients > fit2 <- lm(y~x, df2) > s2 <- summary(fit2)$coefficients > db <-

Hi, I'm trying to compare two linear regressions. I'm using the following approach: ################## xx<-1:100 df1 <- data.frame(x = xx, y = xx * 2 + 30 + rnorm(n=length(xx),sd=10), g = 1) df2 <- data.frame(x = xx, y = xx * 4 + 9 + rnorm(n=length(xx),sd=10), g = 2) dta <- rbind(df1, df2) dta$g <- factor(dta$g)