as.data.frame() is effectively a thin wrapper around data.frame, and hence is rather slow (because it calls data.frame() on each element before cbinding together). as_tibble is a new S3 generic with more efficient methods for matrices and data frames.

as_tibble(x, ...)

# S3 method for tbl_df
as_tibble(x, ...)

# S3 method for data.frame
as_tibble(x, validate = TRUE, ...)

# S3 method for list
as_tibble(x, validate = TRUE, ...)

# S3 method for matrix
as_tibble(x, ...)

# S3 method for table
as_tibble(x, n = "n", ...)

# S3 method for NULL
as_tibble(x, ...)

# S3 method for default
as_tibble(x, ...)

Arguments

x

A list. Each element of the list must have the same length.

...

Other arguments passed on to individual methods.

validate

When TRUE, verifies that the input is a valid data frame (i.e. all columns are named, and are 1d vectors or lists). You may want to suppress this when you know that you already have a valid data frame and you want to save some time.

n

Name for count column, default: "n".

Details

This is an S3 generic. tibble includes methods for data frames (adds tbl_df classes), tibbles (returns unchanged input), lists, matrices, and tables. Other types are first coerced via as.data.frame() with stringsAsFactors = FALSE. as_data_frame and as.tibble are aliases.

Examples

l <- list(x = 1:500, y = runif(500), z = 500:1) df <- as_tibble(l) m <- matrix(rnorm(50), ncol = 5) colnames(m) <- c("a", "b", "c", "d", "e") df <- as_tibble(m) # as_tibble is considerably simpler than as.data.frame # making it more suitable for use when you have things that are # lists not_run({ l2 <- replicate(26, sample(letters), simplify = FALSE) names(l2) <- letters microbenchmark::microbenchmark( as_tibble(l2, validate = FALSE), as_tibble(l2), as.data.frame(l2) ) m <- matrix(runif(26 * 100), ncol = 26) colnames(m) <- letters microbenchmark::microbenchmark( as_tibble(m), as.data.frame(m) ) })