Data.table: rbind a list of data tables with unequal columns [duplicate] - r

Question

This question already has answers here:
rbindlist data.tables with different number of columns
(1 answer)
Rbind with new columns and data.table
(5 answers)
Closed 4 years ago.
I have a list of data tables that are of unequal lengths. Some of the data tables have 35 columns and others have 36.
I have this line of code, but it generates an error
> lst <- unlist(full_data.lst, recursive = FALSE)
> model_dat <- do.call("rbind", lst)
Error in rbindlist(l, use.names, fill, idcol) :
Item 1362 has 35 columns, inconsistent with item 1 which has 36 columns. If instead you need to fill missing columns, use set argument 'fill' to TRUE.
Any suggestions on how I can modify that so that it works properly.

Answer 1

Here's a minimal example of what you are trying to do.
No need to use any other package to do this. Just set fill=TRUE in rbindlist.
You can do this:
df1 <- data.table(m1 = c(1,2,3))
df2 <- data.table(m1 = c(1,2,3), m2=c(3,4,5))
df3 <- rbindlist(list(df1, df2), fill=T)
print(df3)
m1 m2
1: 1 NA
2: 2 NA
3: 3 NA
4: 1 3
5: 2 4
6: 3 5

Answer 2

If I understood your question correctly, I could possibly see only two options for having your data tables appended.
Option A: Drop the extra variable from one of the datasets
table$column_Name <- NULL
Option B) Create the variable with missing values in the incomplete dataset.
full_data.lst$column_Name <- NA
And then do rbind function.

Answer 3

Try to use rbind.fill from package plyr:
Input data, 3 dataframes with different number of columns
df1<-data.frame(a=c(1,2,3,4,5),b=c(1,2,3,4,5))
df2<-data.frame(a=c(1,2,3,4,5,6),b=c(1,2,3,4,5,6),c=c(1,2,3,4,5,6))
df3<-data.frame(a=c(1,2,3),d=c(1,2,3))
full_data.lst<-list(df1,df2,df3)
The solution
library("plyr")
rbind.fill(full_data.lst)
a b c d
1 1 1 NA NA
2 2 2 NA NA
3 3 3 NA NA
4 4 4 NA NA
5 5 5 NA NA
6 1 1 1 NA
7 2 2 2 NA
8 3 3 3 NA
9 4 4 4 NA
10 5 5 5 NA
11 6 6 6 NA
12 1 NA NA 1
13 2 NA NA 2
14 3 NA NA 3