I have 3 data sets that I want to rbind together. I have renamed my columns to be the same:
names(DF1) <- c("A", "B", "C") names(DF2) <- c("A", "B", "C") names(DF3) <- c("A", "B", "C") They have each got different numbers of observations (34, 54, 23, respectively)
However, when I try with an rbind function, it returns the error:
total <- rbind(DF1, DF2, DF3) Error in match.names(clabs, names(xi)) : names do not match previous names
From other answered questions the error should arise because of differently named columns, but I have checked and rechecked that they have been renamed the same.
I would like to end up with a total dataset with a total of 111 observations with column titles. I am a beginner to R, so many of the answers from other questions elude me. Would anyone be able to answer this in layman terms?
34 Answers
You can use do.call, like so:
do.call("rbind", list(DF1, DF2, DF3)) Note that second argument of do.call is a list.
The tidyverse approach is to use bind_rows() from the dplyr package:
bind_rows(DF1, DF2, DF3) For performance gains try rbindlist from the data.table package eg.
rbindlist(list(DF1,DF2,DF3)) This may help you:
You can use rbind.fill from plyr package (can be used even if column name is not the same)
Here is the example from dataset in optmatch package in R
library(optmatch) library(plyr) data(nuclearplants) x<-nuclearplants data1<-as.data.frame(x$cost) data1<-data1[1:20,] data1<-as.data.frame(data1) data2<-as.data.frame(x$date) rbind.fill(data1,data2) data1 x$date 1 460.05 NA 2 452.99 NA 3 443.22 NA 4 652.32 NA 5 642.23 NA 6 345.39 NA 7 272.37 NA 8 317.21 NA 9 457.12 NA 10 690.19 NA 11 350.63 NA 12 402.59 NA 13 412.18 NA 14 495.58 NA 15 394.36 NA 16 423.32 NA 17 712.27 NA 18 289.66 NA 19 881.24 NA 20 490.88 NA 21 NA 68.58 22 NA 67.33 23 NA 67.33 24 NA 68.00 25 NA 68.00 26 NA 67.92 27 NA 68.17 28 NA 68.42 29 NA 68.42 30 NA 68.33 31 NA 68.58 32 NA 68.75 33 NA 68.42 34 NA 68.92 35 NA 68.92 36 NA 68.42 37 NA 69.50 38 NA 68.42 39 NA 69.17 40 NA 68.92 41 NA 68.75 42 NA 70.92 43 NA 69.67 44 NA 70.08 45 NA 70.42 46 NA 71.08 47 NA 67.25 48 NA 67.17 49 NA 67.83 50 NA 67.83 51 NA 67.25 52 NA 67.83 
