Bind any number of data frames by row, making a longer result. This is
similar to do.call(rbind, dfs), but the output will contain all columns
that appear in any of the inputs.
Arguments
- ...
Data frames to combine. Each argument can either be a data frame, a list that could be a data frame, or a list of data frames. Columns are matched by name, and any missing columns will be filled with
NA.- .id
The name of an optional identifier column. Provide a string to create an output column that identifies each input. The column will use names if available, otherwise it will use positions.
Examples
df1 <- tibble(x = 1:2, y = letters[1:2])
df2 <- tibble(x = 4:5, z = 1:2)
# You can supply individual data frames as arguments:
bind_rows(df1, df2)
#> # A tibble: 4 × 3
#> x y z
#> <int> <chr> <int>
#> 1 1 a NA
#> 2 2 b NA
#> 3 4 NA 1
#> 4 5 NA 2
# Or a list of data frames:
bind_rows(list(df1, df2))
#> # A tibble: 4 × 3
#> x y z
#> <int> <chr> <int>
#> 1 1 a NA
#> 2 2 b NA
#> 3 4 NA 1
#> 4 5 NA 2
# When you supply a column name with the `.id` argument, a new
# column is created to link each row to its original data frame
bind_rows(list(df1, df2), .id = "id")
#> # A tibble: 4 × 4
#> id x y z
#> <chr> <int> <chr> <int>
#> 1 1 1 a NA
#> 2 1 2 b NA
#> 3 2 4 NA 1
#> 4 2 5 NA 2
bind_rows(list(a = df1, b = df2), .id = "id")
#> # A tibble: 4 × 4
#> id x y z
#> <chr> <int> <chr> <int>
#> 1 a 1 a NA
#> 2 a 2 b NA
#> 3 b 4 NA 1
#> 4 b 5 NA 2