rbind dataframes with a different column name

Question

I've 12 data frames, each one contains 6 columns: 5 have the same name, 1 is different. Then when I call rbind() I get:

Error in match.names(clabs, names(xi)) :    names do not match previous names 

The column that differs is: "goal1Completions". There are 12 goalsCompletions... they are: "goal1Completions", "goal2Completions", "goal3Completions"... and so on.

The best way I can think of is: renaming every column in every data frame to "GoalsCompletions" and then using "rbind()".

Is there a simpler way?

Look on Google O found this package: "gtools". It has a function called: "smartbind". However, after using smartbind() i want to see the the data frame with "View()", my R session crashes...

My data (an example of the first data frame):

       date      source     medium   campaign   goal1Completions    ad.cost           Goal 1   2014-10-01  (direct)    (none)   (not set)          0           0.0000            Vida 2   2014-10-01   Master      email     CAFRE            0           0.0000            Vida 3   2014-10-01  apeseg      referral (not set)          0           0.0000            Vida 

Answer 1

My favourite use of mapply:

Example Data

a <- data.frame(a=runif(5), b=runif(5)) > a           a         b 1 0.8403348 0.1579255 2 0.4759767 0.8182902 3 0.8091875 0.1080651 4 0.9846333 0.7035959 5 0.2153991 0.8744136 

and b

b <- data.frame(c=runif(5), d=runif(5)) > b           c         d 1 0.7604137 0.9753853 2 0.7553924 0.1210260 3 0.7315970 0.6196829 4 0.5619395 0.1120331 5 0.5711995 0.7252631 

Solution

Using mapply:

> mapply(c, a,b)    #or as.data.frame(mapply(c, a,b)) for a data.frame               a         b  [1,] 0.8403348 0.1579255  [2,] 0.4759767 0.8182902  [3,] 0.8091875 0.1080651  [4,] 0.9846333 0.7035959  [5,] 0.2153991 0.8744136  [6,] 0.7604137 0.9753853  [7,] 0.7553924 0.1210260  [8,] 0.7315970 0.6196829  [9,] 0.5619395 0.1120331 [10,] 0.5711995 0.7252631 

And based on @Marat's comment below:

You can also do data.frame(mapply(c, a, b, SIMPLIFY=FALSE)) or, alternatively, data.frame(Map(c,a,b)) to avoid double data.frame-matrix conversion

Answer 2

You could use rbindlist which takes different column names. Using @LyzandeR's data

library(data.table) #data.table_1.9.5 rbindlist(list(a,b)) #            a         b # 1: 0.8403348 0.1579255 # 2: 0.4759767 0.8182902 # 3: 0.8091875 0.1080651 # 4: 0.9846333 0.7035959 # 5: 0.2153991 0.8744136 # 6: 0.7604137 0.9753853 # 7: 0.7553924 0.1210260 # 8: 0.7315970 0.6196829 # 9: 0.5619395 0.1120331 #10: 0.5711995 0.7252631 

Update

Based on the object names of the 12 datasets (i.e. 'Goal1_Costo', 'Goal2_Costo',..., 'Goal12_Costo'),

 nm1 <- paste(paste0('Goal', 1:12), 'Costo', sep="_")  #or using `sprintf`  #nm1 <- sprintf('%s%d_%s', 'Goal', 1:12, 'Costo')  rbindlist(mget(nm1))