Recombining a list of Data.frames into a single data frame [duplicate]

Answer 1

Note that the basic solution

do.call("rbind", my.df.list)

will be slow if we have many dataframes. A scalable solution is:

library(data.table)
rbindlist(my.df.list)

which, from the docs, is the same as do.call("rbind", l) on data.frames, but much faster.

Answer 2

dplyr lets you use bind_rows function for that:

library(dplyr)

foo <- list(df1 = data.frame(x=c('a', 'b', 'c'),y = c(1,2,3)), 
         df2 = data.frame(x=c('d', 'e', 'f'),y = c(4,5,6)))

bind_rows(foo)

Answer 3

plyr is probably best. Another useful approach if the data frames can be different is to use reshape:

library(reshape)
data <- merge_recurse(listofdataframes)

Look at my answer to this related question on merging data frames.

Answer 4

Maybe you want to do something like:

do.call("rbind", my.df.list)

Answer 5

There might be a better way to do this, but this seems to work and it's straightforward. (My code has four lines so that it's easier to see the steps; these four could easily be combined.)

# first re-create your data frame:
A = matrix( ceiling(10*runif(8)), nrow=4)
colnames(A) = c("country", "year_var")
dfa = data.frame(A)

# now re-create the list you made from the individual rows of the data frame:
df1 = dfa[1,]
df2 = dfa[2,]
df3 = dfa[3,]
df4 = dfa[4,]
df_all = list(df1, df2, df3, df4)

# to recreate your original data frame:
x = unlist(df_all)         # from your list create a single 1D array 
A = matrix(x, nrow=4)      # dimension that array in accord w/ your original data frame
colnames(A) = c("country", "year_var")     # put the column names back on
dfa = data.frame(A)        # from the matrix, create your original data frame