similar to: Merging by factor variables

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

Hallo Everyone I have the kind of problem that one should never have because one must always plan well and communicate with your team. But now I haven't so here is my problem. I have data coming in on a daily basis from surveys in 10 towns. The questionnaire has 62 variables but some of the regions have used older versions of the questionnaire that have a few variables less. I want to combine

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)

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 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

Hey Folks, Could somebody show me how to loop through a list of dataframes? I want to be able to generically access their elements and do something with them. For instance, instead of this: df1<- data.frame(x=(1:5),y=(1:5)); df2<- data.frame(x=(1:5),y=(1:5)); df3<- data.frame(x=(1:5),y=(1:5)); plot(df1$x,df1$y); plot(df2$x,df2$y); plot(df3$x,df3$y); I would like to do something like:

Hi all, I need to test the significnce of difference between slopes of two regression lines and regression line with theoretical line. I try to use Slope.test function from emu package, but an error occured... library(emu) d1<-data.frame(P1=c(1,2,3,5,7,8,9,13,14,15), P2=c(1,2,5,8,11,13,15,15,18,24), R=c(2,7,8,9,16,21,27,31,33,36)) # First data set m1<-lm(R~P1+P2+P1*P2,data=d1) # Regr.

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

Why does this sapply code change df3 but not df1? Thanks df1 <- read.table(text=" cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 ", header=TRUE) df2 <-df1*2 df1 df2 df3 <-sapply(names(df1),function(x) {df1[[x]]<- df2[[x]]}) df1 df3 [[alternative HTML version deleted]]

Hello R user, I have several data frames with >100 columns and I did a linear regression over time of each column df1.lm <- lapply(df1, function(x) lm(x~year)$coeff[2]) that worked fine and I get slope of each column oder time - until I divided df1 by df2 df3 <- df1/df2 > df3.lm <- lapply(df3, function(x) lm(x~year)$coeff[2]) Error in lm.fit(x, y, offset = offset, ...) :

Hi everybody. I'll first explain my problem and what I'm trying to do. Admit this example: I'm working on 5 different weather stations. I have first in one file 3 of these 5 weather stations, containing their data. Here's an example of this file: DF1 <- data.frame(station=c("ST001","ST004","ST005"),data=c(5,2,8)) And my two other stations in

Windows 2000 reports that "Rgui.exe has generated errors and will be = closed by Windows. You will need to restart the program." when using = rbind.=20 df1 <- data.frame(cbind(x=3D1, y=3D1:1000), fac=3Dsample(LETTERS[1:3], = 1000, repl=3DTRUE)) df2 <- data.frame(cbind(x=3D1, y=3D1:10), fac=3Dsample(LETTERS[4:6], = 10, repl=3DTRUE)) df3 <- data.frame(cbind(x=3D1,

All, I have a workspace containing only data frame objects. I would like to loop though each one and clean-up text columns in them. How can I have R loop through the list? I have tried to find an answer in R help but the closest solution I can find is to make a static list of data frames, as illustrated in this recent post: ---------begin post On Tuesday 19 February 2008 (19:51:15), TLowe wrote:

Hello all, I have a quandry I have been scratching my head about for a while. I've searched the manual and the web and have not been able to find an acceptable result, so I am hoping for some help. I have two data frames and I want to index into the first using the second, and replace the specific values I have indexed with more values from the second data.frame. I can do this

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 <-

I have a dataframe where I would like to order first by variable, year, and then within that variable by month. So far the only way that I have seen to do this is to order by year and then subset year and sort by month and then do an rbind to get things back together. Is this the right approach? Example: us.state <-rep("California", 23)

Hello I want to keep track of my units in the data frame. I have been advised in the past on this list to create a new "units" attribute of the data frame and keep the units strings there. It works fine as long as I don't manipulate the data frame. Here's an example: -------------CODE BEGIN ----------------------- df1 <- data.frame(x = 1:10, y = runif(10))

Hello, I'd like to create a model with a factor-type response variable. This is an example: > mydata <- data.frame(factor_var = as.factor(c(rep('one', 100), rep('two', 100), rep('three', 100))), real_var = c(rnorm(150), rnorm(150) + 5)) > summary(mydata) factor_var real_var one :100 Min. :-2.742877 three:100 1st Qu.:-0.009493 two

Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1). I have a solution for this problem (see self contained example below) but it's awkward and

Holabueno, aunque hay muchas posibilidades para fusionar ambas tablas, usando la tuya sería algo así:Df3<-merge(Df1,Df2,by="Reviewer.Username", all = TRUE) El Lunes 16 de enero de 2017 20:08, Jesús Para Fernández <j.para.fernandez en hotmail.com> escribió: Los data.frames para unirlos lo mejor es que tengan el mismo numero de columnas o variables. El dataframe2