Skip to content

This is a fairly standard format for log files - it uses both quotes and square brackets for quoting, and there may be literal quotes embedded in a quoted string. The dash, "-", is used for missing values.


  col_names = FALSE,
  col_types = NULL,
  trim_ws = TRUE,
  skip = 0,
  n_max = Inf,
  show_col_types = should_show_types(),
  progress = show_progress()



Either a path to a file, a connection, or literal data (either a single string or a raw vector).

Files ending in .gz, .bz2, .xz, or .zip will be automatically uncompressed. Files starting with http://, https://, ftp://, or ftps:// will be automatically downloaded. Remote gz files can also be automatically downloaded and decompressed.

Literal data is most useful for examples and tests. To be recognised as literal data, the input must be either wrapped with I(), be a string containing at least one new line, or be a vector containing at least one string with a new line.

Using a value of clipboard() will read from the system clipboard.


Either TRUE, FALSE or a character vector of column names.

If TRUE, the first row of the input will be used as the column names, and will not be included in the data frame. If FALSE, column names will be generated automatically: X1, X2, X3 etc.

If col_names is a character vector, the values will be used as the names of the columns, and the first row of the input will be read into the first row of the output data frame.

Missing (NA) column names will generate a warning, and be filled in with dummy names ...1, ...2 etc. Duplicate column names will generate a warning and be made unique, see name_repair to control how this is done.


One of NULL, a cols() specification, or a string. See vignette("readr") for more details.

If NULL, all column types will be inferred from guess_max rows of the input, interspersed throughout the file. This is convenient (and fast), but not robust. If the guessed types are wrong, you'll need to increase guess_max or supply the correct types yourself.

Column specifications created by list() or cols() must contain one column specification for each column. If you only want to read a subset of the columns, use cols_only().

Alternatively, you can use a compact string representation where each character represents one column:

  • c = character

  • i = integer

  • n = number

  • d = double

  • l = logical

  • f = factor

  • D = date

  • T = date time

  • t = time

  • ? = guess

  • _ or - = skip

By default, reading a file without a column specification will print a message showing what readr guessed they were. To remove this message, set show_col_types = FALSE or set options(readr.show_col_types = FALSE).


Should leading and trailing whitespace (ASCII spaces and tabs) be trimmed from each field before parsing it?


Number of lines to skip before reading data. If comment is supplied any commented lines are ignored after skipping.


Maximum number of lines to read.


If FALSE, do not show the guessed column types. If TRUE always show the column types, even if they are supplied. If NULL (the default) only show the column types if they are not explicitly supplied by the col_types argument.


Display a progress bar? By default it will only display in an interactive session and not while knitting a document. The automatic progress bar can be disabled by setting option readr.show_progress to FALSE.


#> ── Column specification ──────────────────────────────────────────────────
#> cols(
#>   X1 = col_character(),
#>   X2 = col_logical(),
#>   X3 = col_character(),
#>   X4 = col_character(),
#>   X5 = col_character(),
#>   X6 = col_double(),
#>   X7 = col_double()
#> )
#> # A tibble: 2 × 7
#>   X1           X2    X3                   X4             X5       X6    X7
#>   <chr>        <lgl> <chr>                <chr>          <chr> <dbl> <dbl>
#> 1 NA    "Microsoft\\JohnDoe" 08/Apr/2001:1… GET …   200  3401
#> 2    NA    "frank"              10/Oct/2000:1… GET …   200  2326