Combine (rbind) data frames and create column with name of original data frames

Question

I have several data frames that I want to combine by row. In the resulting single data frame, I want to create a new variable identifying which data set the observation came from.

# original data frames df1 <- data.frame(x = c(1, 3), y = c(2, 4)) df2 <- data.frame(x = c(5, 7), y = c(6, 8))  # desired, combined data frame df3  <- data.frame(x = c(1, 3, 5, 7), y = c(2, 4, 6, 8),                    source = c("df1", "df1", "df2", "df2") # x y source # 1 2    df1 # 3 4    df1 # 5 6    df2 # 7 8    df2 

How can I achieve this? Thanks in advance!

Answer 1

It's not exactly what you asked for, but it's pretty close. Put your objects in a named list and use do.call(rbind...)

> do.call(rbind, list(df1 = df1, df2 = df2))       x y df1.1 1 2 df1.2 3 4 df2.1 5 6 df2.2 7 8 

Notice that the row names now reflect the source data.frames.

Update: Use cbind and rbind

Another option is to make a basic function like the following:

AppendMe <- function(dfNames) {   do.call(rbind, lapply(dfNames, function(x) {     cbind(get(x), source = x)   })) } 

This function then takes a character vector of the data.frame names that you want to "stack", as follows:

> AppendMe(c("df1", "df2"))   x y source 1 1 2    df1 2 3 4    df1 3 5 6    df2 4 7 8    df2 

Update 2: Use combine from the "gdata" package

> library(gdata) > combine(df1, df2)   x y source 1 1 2    df1 2 3 4    df1 3 5 6    df2 4 7 8    df2 

Update 3: Use rbindlist from "data.table"

Another approach that can be used now is to use rbindlist from "data.table" and its idcol argument. With that, the approach could be:

> rbindlist(mget(ls(pattern = "df\\d+")), idcol = TRUE)    .id x y 1: df1 1 2 2: df1 3 4 3: df2 5 6 4: df2 7 8 

Update 4: use map_df from "purrr"

Similar to rbindlist, you can also use map_df from "purrr" with I or c as the function to apply to each list element.

> mget(ls(pattern = "df\\d+")) %>% map_df(I, .id = "src") Source: local data frame [4 x 3]      src     x     y   (chr) (int) (int) 1   df1     1     2 2   df1     3     4 3   df2     5     6 4   df2     7     8 

Answer 2

Another approach using dplyr:

df1 <- data.frame(x = c(1,3), y = c(2,4)) df2 <- data.frame(x = c(5,7), y = c(6,8))  df3 <- dplyr::bind_rows(list(df1=df1, df2=df2), .id = 'source')  df3 Source: local data frame [4 x 3]    source     x     y    (chr) (dbl) (dbl) 1    df1     1     2 2    df1     3     4 3    df2     5     6 4    df2     7     8