rbind

问题 I would like to merge a large set of dataframes (about 30), which each have about 200 variables. These datasets are very much alike but not identical. Please find two example dataframes below: library(data.table) library(haven) df1 <- fread( "A B C iso year 0 B 1 NLD 2009 1 A 2 NLD 2009 0 Y 3 AUS 2011 1 Q 4 AUS 2011 0 NA 7 NLD 2008 1 0 1 NLD 2008 0 1 3 AUS 2012", header = TRUE ) df2 <- fread( "A B D E iso year 0 1 1 NA ECU 2009 1 0 2 0 ECU 2009 0 0 3 0 BRA 2011 1 0 4 0 BRA 2011 0 1 7 NA ECU

问题 I have 24 data frames that I need to combine. 20 data frames have the same 238 columns, instead 4 data frames have 256 columns. Moreover, the 4 data frames with 256 columns have a different order of columns compared to the other 20 data frames. E.g. 'answer', 'condition', 'msg_time', 'fix', etc. (20 data frames) E.g. 'acc_value', 'nitem', 'fix', 'button_press_0', 'rotation', 'previous_fix', 'accuracy', 'answer','file', 'condition', etc. (4 data frames) I would like to rbind only those columns

问题 While duplicated row (and column) names are allowed in a matrix , they are not allowed in a data.frame . Trying to rbind() some data frames having row names in common highlights this problem. Consider two data frames below: foo = data.frame(a=1:3, b=5:7) rownames(foo)=c("w","x","y") bar = data.frame(a=c(2,4), b=c(6,8)) rownames(bar)=c("x","z") # foo bar # a b a b # w 1 5 x 2 6 # x 2 6 y 4 8 # y 3 7 Now trying to rbind() them (Pay attention to the row names): rbind(foo, bar) # a b # w 1 5 # x

问题 My questions is how can join two or more data frames in system R? For example: I have two data frames: first: x y z 1 3 2 4 2 4 5 7 3 5 6 8 second: x y z 1 1 1 1 2 4 5 7 I need this: x y z 1 3 2 4 2 4 5 7 3 5 6 8 4 1 1 1 5 4 5 7 I tried to use append for each vector, like this: for( i in 1:length(first)){ mix[[i]]<-append(first[i], second[i])} f<-do.call(rbind, mix) But It didn't work like I needed. I didn't get my matrix, i got some different structure. 回答1: You have the right idea using

问题 Say I have multiple data frames which all have identical vector names and I'd like to cbind all which have a commmon pattern. So for these 3 data frames: df.1 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed=runif(10)) df.2 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed=runif(10)) df.3 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed = runif(10)) I would like to rbind everything with the

问题 Say I have multiple data frames which all have identical vector names and I'd like to cbind all which have a commmon pattern. So for these 3 data frames: df.1 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed=runif(10)) df.2 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed=runif(10)) df.3 <- data.frame(column1 = factor(sample(c("Male","Female"), 10, replace=TRUE)), speed = runif(10)) I would like to rbind everything with the

问题 I am trying to turn a nested list structure into a dataframe. The list looks similar to the following (it is serialized data from parsed JSON read in using the httr package). myList <- list(object1 = list(w=1, x=list(y=0.1, z="cat")), object2 = list(w=NULL, x=list(z="dog"))) EDIT: my original example data was too simple. The actual data are ragged, meaning that not all variables exist for every object, and some of the list elements are NULL. I edited the data to reflect this. unlist(myList)

问题 I have few huge datatable dt_1, dt_2, ..., dt_N with same cols. I want to bind them together into a single datatable . If I use dt <- rbind(dt_1, dt_2, ..., dt_N) or dt <- rbindlist(list(dt_1, dt_2, ..., dt_N)) then the memory usage is approximately double the amount needed for dt_1,dt_2,...,dt_N . Is there a way to bind them wihout increasing the memory consumption significantly? Note that I do not need dt_1, dt_2, ..., dt_N once they are combined together. 回答1: Other approach, using a

问题 I'm using R-Studio 0.99.491 and R version 3.2.3 (2015-12-10). I'm a relative newbie to R, and I'd appreciate some help. I'm doing a project where I'm trying to use the server logs on an old media server to identify which folders/files within the server are still being accessed and which aren't, so that my team knows which files to migrate. Each log is for a 24 hour period, and I have approximately a year's worth of logs, so in theory, I should be able to see all of the access over the past

问题 I am attempting to row bind many data frames together into a single massive data frame. The data frames are named sequentially with the first named df1 , the second named df2 , the third named df3 , etc. Currently, I have bound these data frames together by explicitly typing the names of the data frames; however, for a very large number of data frames (roughly 10,000 total data frames are expected) this is suboptimal. Here is a working example: # Load required packages library(plyr) #