similar to: Merge data frames but with a twist.

Dear all, Lets say I have several data frames as follows: > set.seed(42) > dates <- as.Date(c("2010-01-19", "2010-01-20")) > times <- c("09:30:00", "11:30:00", "13:30:00", "15:30:00") > shows <- c("Red Dwarf", "Being Human", "Doctor Who") > > df1 <- data.frame(Date = dates[1],

Dear all, Lets say I have the following data frame: > df1 <- data.frame(Show=c('Star Trek', 'Babylon 5', 'Dr Who'), Size=c(0.7, 0.0, 0.701), Date=as.Date(c('2007-08-03', '2007-08-03', '2007-08-03'), format='%Y-%m-%d')) > df2 <- data.frame(Show=c('Star Trek', 'Dr Who', 'Torchwood'), Size=c(0.8, 0.85,

Hi, I have a data frame, data, containing two columns: one- the TimeStamp (formatted using data$TimeStamp <- as.POSTIXct(as.character(data$TimeStamp), format = "%d/%m/%Y %H:%M") ) and two- the data value. The data frame has been read from a .csv file and should contain 48 values for each day of the year (values sampled at 30 minute intervals). However, there are only

# Hello, # I have a list with 6 categories and with different numbers of rows. # I would like to change each of them into a unique data frame in order to match # values with other data frames and perform some calculations. # Or I could make each category or list element have the same number of rows and create one large data.frame. # below is a creation of a sample list # I apologize for the

I have two dataframes in R that were tab seperated .txt files y<-read.table("foo.txt", header=T) x<-read.table("foo.txt", header=T) these are set up like this: Datetime Temp 01/01/07 00:01 11.5 01/01/07 00:16 11.6 etc etc to 66000 rows in y and 33000 rows in x The two files overlap with the same data for a period of time but contain

> for (d in paste('df', 1:3, sep='')) { + assign(d, as.data.frame(replicate(3, rnorm(4)))) + } > dats = list(df1,df2,df3) > for (i in 1:length(dats)) { + names(dats[[i]]) = c('w', 'l', 'h') + } > dats [[1]] w l h 1 1.24319239 -0.05543649 0.05409178 2 0.05124331 -1.89346950 0.33896273 3 -1.69686777 -0.35963008

Hi all, I was just radomly playing with R and got the following error when trying to filter a data frame using a string: > Angel <- c(7,8,6,9,10) > Buffy <- c(8,9,4,9,10) > Firefly <- c(9,9,10,10,10) > DrHorrible <- c(10,9,9,10,10) > my.df <- data.frame(Angel, Buffy, Firefly, DrHorrible) > my.df["DrHorrible"] DrHorrible 1 10 2 9 3

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 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

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:

#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

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 series of data frames that are identical structurally, i.e. - made with the same code, but I need to add them together so that they become one, longer, data frame, i.e. - each of the slot vectors are increased in length by the length of the added data frame vectors. So if I have df1 with a slot A so that length(df1$A) = 100 and I have df2 with a slot A so that length(df2$A)=200 then I

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

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

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 I have 2 data frames df1 and df2. I would like to create a new data frame new_df which will contain only the common rows based on the first 2 columns (chrN and start). The column score in the new data frame should be replaced with a column containing the average score (average_score) from df1 and df2. df1= data.frame(chrN= c(“chr1”, “chr1”, “chr1”, “chr1”, “chr2”, “chr2”, “chr2”),

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

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

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, ...) :