similar to: Combine two variables

Hello: Forgive me, this is surely a simple question but I can't figure it out, having consulted the help archives and "Data Manipulation With R" (Spector). I have a list of 11 data frames with one common variable in each (prov). I'd like to use lapply to go through and recode one particular level of that common variable. I can get the recode to work, but it only returns the

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Let say, I have a matrix with 8 rows and 6 columns:  >  df1  <- matrix(NA, 8, 4)  > df1       [,1] [,2] [,3] [,4]  [1,]   NA   NA   NA   NA  [2,]   NA   NA   NA   NA  [3,]   NA   NA   NA   NA  [4,]   NA   NA   NA   NA  [5,]   NA   NA   NA   NA  [6,]   NA   NA   NA   NA  [7,]   NA   NA   NA   NA  [8,]   NA   NA   NA   NA  Now I want to get **all possible** ways to fetch 6 cells at a

Hi, [some background] I have a dataset which describes a number of subjects doing a "scientific discovery". That is, they have to discover the rules underlying a particular domain. To do so, they have to set the levels of 5 variables which leads to a certain outcome. To identify what kind of "experiments" the subjects did, I want to combine these levels into one variable

Hi: I'm sure this is a very easy problem. I've consulted Data Manipulation With R and the R Book and can't find an answer. Sample list of data frames looks as follows: .xx<-list(df<-data.frame(Var1=rep('Alabama', 400), Var2=rep(c(2004, 2005, 2006, 2007), 400)), df2<-data.frame(Var1=rep('Tennessee', 400), Var2=rep(c(2004,2005,2006,2007), 400)),

Hi, what is the recommended way to vertically concatenate 2 data frames with the same column names but different number of rows? My problem is something along these lines: df1 <- data.frame(var1=var1,var2=var2,var3=var3) # nrow(df1)=1000 df2 <- data.frame(var1=var4,var2=var5,var3=var6) # nrow(df2)=2000 I tried df <- c(df1,df2), no success. stack does not seem to be appropriate

Hi R users, I have a question about plotting. The following two datasets are an example. What I have in mind is like the attached figure, but just have two rows, top row is for DF1, bottom row is for DF2. The top and bottom rows, have x-axis as var1, var2, var3, etc, while the y-axis represents A. For each row, only the leftmost panel has y-axis ticks and label. For the two rows, only the bottom

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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

Utilizo la función merge desde hace poco, pero no se me ocurre cómo utilizarla para esto. Yo pienso que se puede hacer con una combinación de ifelse-s pero no sé cómo. Seguro que hay más de una forma ce hacerlo. Quoting José María Mateos <chema en rinzewind.org>: > On Sat, Nov 10, 2018 at 07:54:19PM +0100, Manuel Mendoza wrote: >> Muy buenas. A ver si alguien puede echarme

Hello everybody! I've a file with several data six variables, three quantitative and three qualitative, I would like to select a group of data from the file to analyze then, i.e: my file is like that (but with 6 variables): Var1 Var2 2 1 5 1 8 1 7 2 3 2 8 2 I want to use only the data where var2 is "1" 2 1 5 1 8 1 Exist a

Dear All Sorry for this simple question, I could not solve it by spending days. My data looks like this: # data set.seed(1234) clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100 level for this factor var; yvar <- rnorm(40, 10,6); var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2); var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15,

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

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

Hi, I have a grouped data set and would like to calculate weighted proportions for a large number of factor variables within each group member. Rather than using dplyr::count() on each of these factors individually, the idea would be to do it for all factors at once. Does anyone know how this would work? Here is a reproducible example: ############################################################

R users, I have df like this a <- data.frame( indx = 1:20, var1 = rep(c("I20", "I40", "A50", "B60"), each=5), var1_lab= rep(c("cat", "dog", "mouse", "horse"), each=5), var2 = rep(c("B20", "X40", "D50",

Hello: What is the most efficient way to change the plotted variable names in mosaic plots in the vcd package? Should one do a separate contingency table first, change the dimension names there and then pass that to mosaic? Or is there a way to do it simply within mosaic. I was thinking something like: mosaic(~var1+var2, labelling_args=list(varnames=c('newvar1', 'newvar2')) Simon

OK, I need help!! I've been searching, but I don't understand the logic of some this dataframe addressing syntax. What is this type of code called? test [["v3"]] [is.na(test[["v2"]])] <-10 #choose column v3 where column v2 is == 4 and replace with 10 and where is it documented? The code below works for what I want to do (find the non-missing value in a row),

Dear R community members I did find a good way to merge my 200 text data files in to a single data file with one column added will show indicator for that file. filelist = list.files(pattern = "K*cd.txt") # the file names are K1cd.txt .................to K200cd.txt data_list <-lapply(filelist, read.table, header=T, comment=";", fill=T) This will create list,

Muy buenas. A ver si alguien puede echarme una mano. A partir de una matriz de distancias de 29 x 29 he obtenido una df1. Ahora tengo 841 filas con la distancia de cada combinación de esas 29 categorías. Algo así como: Var1 Var2 Dist a a 0 a b 3 a c 5 b a 3 b b 0 b c 5 c ... En otra df2, de 14563 filas, tengo las