r-faq

问题 I have a list of many data.frames that I want to merge. The issue here is that each data.frame differs in terms of the number of rows and columns, but they all share the key variables (which I've called "var1" and "var2" in the code below). If the data.frames were identical in terms of columns, I could merely rbind , for which plyr's rbind.fill would do the job, but that's not the case with these data. Because the merge command only works on 2 data.frames, I turned to the Internet for ideas.

问题 I have a list of many data.frames that I want to merge. The issue here is that each data.frame differs in terms of the number of rows and columns, but they all share the key variables (which I've called "var1" and "var2" in the code below). If the data.frames were identical in terms of columns, I could merely rbind , for which plyr's rbind.fill would do the job, but that's not the case with these data. Because the merge command only works on 2 data.frames, I turned to the Internet for ideas.

问题 I have a data frame that follows the below long Pattern: Name MedName Name1 atenolol 25mg Name1 aspirin 81mg Name1 sildenafil 100mg Name2 atenolol 50mg Name2 enalapril 20mg And would like to get below (I do not care if I can get the columns to be named this way, just want the data in this format): Name medication1 medication2 medication3 Name1 atenolol 25mg aspirin 81mg sildenafil 100mg Name2 atenolol 50mg enalapril 20mg NA Through this very site I have become familiarish with the reshape

问题 I have a data frame that follows the below long Pattern: Name MedName Name1 atenolol 25mg Name1 aspirin 81mg Name1 sildenafil 100mg Name2 atenolol 50mg Name2 enalapril 20mg And would like to get below (I do not care if I can get the columns to be named this way, just want the data in this format): Name medication1 medication2 medication3 Name1 atenolol 25mg aspirin 81mg sildenafil 100mg Name2 atenolol 50mg enalapril 20mg NA Through this very site I have become familiarish with the reshape

问题 I'm trying to write a function in R to batch-analyse a number of files in a similar manner. The files are of class ExpressionSetIllumina . I can make a character (string) vector with names of all files in the directory and load each of them: list = list.files() for (i in list[1]) { load(i) } This loads files correctly > ls() [1] "i" "list" "SSD.BA.vsn" > class(SSD.BA.vsn) [1] "ExpressionSetIllumina" attr(,"package") [1] "beadarray" What I want to do now is to use i (character string "SSD.BA

来源： https://stackoverflow.com/questions/63388996/dividing-data-into-groups-by-attribute

来源： https://stackoverflow.com/questions/63388996/dividing-data-into-groups-by-attribute

问题 I have an integer which I want to convert to class Date . I assume I first need to convert it to a string, but how? My attempt: v <- 20081101 date <- as.Date(v, format("%Y%m%d")) Error in charToDate(x) : character string is not in a standard unambiguous format Using paste() works, but is that really the correct way to do the conversion? date <- as.Date(paste(v), format("%Y%m%d")) date [1] "2008-11-01" class(date) # [1] "Date" 回答1: as.character() would be the general way rather than use paste(

问题 I have an integer which I want to convert to class Date . I assume I first need to convert it to a string, but how? My attempt: v <- 20081101 date <- as.Date(v, format("%Y%m%d")) Error in charToDate(x) : character string is not in a standard unambiguous format Using paste() works, but is that really the correct way to do the conversion? date <- as.Date(paste(v), format("%Y%m%d")) date [1] "2008-11-01" class(date) # [1] "Date" 回答1: as.character() would be the general way rather than use paste(

问题 Can someone please help how to get the list of built-in data sets and their dependency packages? 回答1: There are several ways to find the included datasets in R: 1: Using data() will give you a list of the datasets of all loaded packages (and not only the ones from the datasets package); the datasets are ordered by package 2: Using data(package = .packages(all.available = TRUE)) will give you a list of all datasets in the available packages on your computer (i.e. also the not-loaded ones) 3: