This is an efficient implementation of the common pattern of
do.call(rbind, dfs) or
do.call(cbind, dfs) for binding many
data frames into one.
combine() acts like
unlist() but uses consistent dplyr coercion rules.
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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.
When row-binding, columns are matched by name, and any missing columns will be filled with NA.
When column-binding, rows are matched by position, so all data frames must have the same number of rows. To match by value, not position, see join.
Data frame identifier.
The output of
bind_rows() will contain a column if that column
appears in any of the inputs.
combine() it is called with exactly one list argument, the list is
simplified (similarly to
unlist(recursive = FALSE).
NULL arguments are
ignored. If the result is empty,
logical() is returned.
bind_cols() return the same type as
the first input, either a data frame,
rbind_all() have been deprecated. Instead use
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one <- mtcars[1:4, ] two <- mtcars[11:14, ] # You can supply data frames as arguments: bind_rows(one, two) # The contents of lists is automatically spliced: bind_rows(list(one, two)) bind_rows(split(mtcars, mtcars$cyl)) bind_rows(list(one, two), list(two, one)) # In addition to data frames, you can supply vectors. In the rows # direction, the vectors represent rows and should have inner # names: bind_rows( c(a = 1, b = 2), c(a = 3, b = 4) ) # You can mix vectors and data frames: bind_rows( c(a = 1, b = 2), data_frame(a = 3:4, b = 5:6), c(a = 7, b = 8) ) # Note that for historical reasons, lists containg vectors are # always treated as data frames. Thus their vectors are treated as # columns rather than rows, and their inner names are ignored: ll <- list( a = c(A = 1, B = 2), b = c(A = 3, B = 4) ) bind_rows(ll) # You can circumvent that behaviour with explicit splicing: bind_rows(!!!ll) # 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(one, two), .id = "id") bind_rows(list(a = one, b = two), .id = "id") bind_rows("group 1" = one, "group 2" = two, .id = "groups") # Columns don't need to match when row-binding bind_rows(data.frame(x = 1:3), data.frame(y = 1:4)) ## Not run: # Rows do need to match when column-binding bind_cols(data.frame(x = 1), data.frame(y = 1:2)) ## End(Not run) bind_cols(one, two) bind_cols(list(one, two)) # combine applies the same coercion rules f1 <- factor("a") f2 <- factor("b") c(f1, f2) unlist(list(f1, f2)) combine(f1, f2) combine(list(f1, f2))
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