lapply

问题 This question already has answers here : Make a list of many objects from a vector of object names [duplicate] (2 answers) Closed 6 months ago . This post is similar to my other post Let's say if I have 4 matrices: x1 <- matrix(1:9, nrow = 3) x2 <- matrix(2:10, nrow = 3) x3 <- matrix(3:11, nrow = 3) x4 <- matrix(4:12, nrow = 3) And I want to put them into a list() in a way like this: [[1]] [[1]][[1]] [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 [[1]][[2]] [,1] [,2] [,3] [1,] 2 5 8 [2,] 3 6

问题 Sorry for the generic question. I'm looking for pointers for sorting out a data folder, in which I have numerous .txt files. All of them have different titles, and for the vast majority of them, the files have the same dimension, that is the column numbers are the same. However, the pain is some of the files, despite having the same number of columns, have different column names. That is in those files, some other variables were measured. I want to weed out these files, and I cannot do by

问题 Sorry for the generic question. I'm looking for pointers for sorting out a data folder, in which I have numerous .txt files. All of them have different titles, and for the vast majority of them, the files have the same dimension, that is the column numbers are the same. However, the pain is some of the files, despite having the same number of columns, have different column names. That is in those files, some other variables were measured. I want to weed out these files, and I cannot do by

问题 Sorry for the generic question. I'm looking for pointers for sorting out a data folder, in which I have numerous .txt files. All of them have different titles, and for the vast majority of them, the files have the same dimension, that is the column numbers are the same. However, the pain is some of the files, despite having the same number of columns, have different column names. That is in those files, some other variables were measured. I want to weed out these files, and I cannot do by

问题 I have a dataframe with many factors and want to create statistical tables that show the distribution for each factor, including factor levels with zero observations. For instance, these data: structure(list(engag11 = structure(c(5L, 4L, 4L), .Label = c("Strongly Disagree", "Disagree", "Neither A or D", "Agree", "Strongly Agree"), class = "factor"), encor11 = structure(c(1L, 1L, 1L), .Label = c("Agree", "Neither Agree or Disagree", "Strongly Agree"), class = "factor"), know11 = structure(c(3L

问题 I have a dataframe with many factors and want to create statistical tables that show the distribution for each factor, including factor levels with zero observations. For instance, these data: structure(list(engag11 = structure(c(5L, 4L, 4L), .Label = c("Strongly Disagree", "Disagree", "Neither A or D", "Agree", "Strongly Agree"), class = "factor"), encor11 = structure(c(1L, 1L, 1L), .Label = c("Agree", "Neither Agree or Disagree", "Strongly Agree"), class = "factor"), know11 = structure(c(3L

问题 I have data from an open ended survey. I have a comments table and a codes table. The codes table is a set of themes or strings. What I am trying to do: Check to see if a word / string exists from the relevant column in the codes table is in an open ended comment. Add a new column in the comments table for the specific theme and a binary 1 or 0 to denote what records have been tagged. There are quite a number of columns in the codes table, these are live and ever changing, column orders and

问题 I have a two nested loop which I want to do it with lapply instead of for loops. I have made up the following simple example: a<-as.list(c(1,2)) b<-as.list(c(6,7)) results<-lapply(a, function(x) lapply(b, function(y) x+y)) > results [[1]] [[1]][[1]] [1] 7 [[1]][[2]] [1] 8 [[2]] [[2]][[1]] [1] 8 [[2]][[2]] [1] 9 how can I assign names to this list, I can assign names to the first level using names(result)<-a, but I do not know how to do it for the second level. And naming should be done in

问题 I have looked far and wide for a solution to this issue, but I cannot seem to figure it out. I do not have much experience working with xts objects in R. I have 40 xts objects (ETF data) and I want to run the quantmod function WeeklyReturn on each of them individually. I have tried to refer to them by using the ls() function: lapply(ls(), weeklyReturn) I have also tried the object() function lapply(object(), weeklyReturn) I have also tried using as.xts() in my call to coerce the ls() objects

问题 I have looked far and wide for a solution to this issue, but I cannot seem to figure it out. I do not have much experience working with xts objects in R. I have 40 xts objects (ETF data) and I want to run the quantmod function WeeklyReturn on each of them individually. I have tried to refer to them by using the ls() function: lapply(ls(), weeklyReturn) I have also tried the object() function lapply(object(), weeklyReturn) I have also tried using as.xts() in my call to coerce the ls() objects