dplyr (version 0.5.0)

bind: Efficiently bind multiple data frames by row and column.

Description

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 c() or unlist() but uses consistent dplyr coercion rules.

Usage

bind_rows(..., .id = NULL)
bind_cols(...)
combine(...)

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.

When column-binding, rows are matched by position, not value so all data frames must have the same number of rows. To match by value, not position, see left_join etc. When row-binding, columns are matched by name, and any values that don't match will be filled with NA.

.id

Data frames identifier.

When .id is supplied, a new column of identifiers is created to link each row to its original data frame. The labels are taken from the named arguments to bind_rows(). When a list of data frames is supplied, the labels are taken from the names of the list. If no names are found a numeric sequence is used instead.

Value

bind_rows and bind_cols return the same type as the first input, either a data frame, tbl_df, or grouped_df.

Deprecated functions

rbind_list() and rbind_all() have been deprecated. Instead use bind_rows().

Examples

one <- mtcars[1:4, ]
two <- mtcars[11:14, ]

# You can either supply data frames as arguments
bind_rows(one, two)
# Or a single argument containing a list of data frames
bind_rows(list(one, two))
bind_rows(split(mtcars, mtcars$cyl))

# 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))

# Rows do need to match when column-binding
bind_cols(data.frame(x = 1), data.frame(y = 1:2))


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))