When printed, only the first 20 columns are printed by default. To override, set options(readr.num_columns) can be used to modify this (a value of 0 turns off printing).

spec_delim(
  file,
  delim = NULL,
  quote = "\"",
  escape_backslash = FALSE,
  escape_double = TRUE,
  col_names = TRUE,
  col_types = NULL,
  col_select = NULL,
  id = NULL,
  locale = default_locale(),
  na = c("", "NA"),
  quoted_na = TRUE,
  comment = "",
  trim_ws = FALSE,
  skip = 0,
  n_max = 0,
  guess_max = 1000,
  name_repair = "unique",
  num_threads = readr_threads(),
  progress = show_progress(),
  show_col_types = should_show_types(),
  skip_empty_rows = TRUE,
  lazy = TRUE
)

spec_csv(
  file,
  col_names = TRUE,
  col_types = NULL,
  col_select = NULL,
  id = NULL,
  locale = default_locale(),
  na = c("", "NA"),
  quoted_na = TRUE,
  quote = "\"",
  comment = "",
  trim_ws = TRUE,
  skip = 0,
  n_max = 0,
  guess_max = 1000,
  name_repair = "unique",
  num_threads = readr_threads(),
  progress = show_progress(),
  show_col_types = should_show_types(),
  skip_empty_rows = TRUE,
  lazy = TRUE
)

spec_csv2(
  file,
  col_names = TRUE,
  col_types = NULL,
  col_select = NULL,
  id = NULL,
  locale = default_locale(),
  na = c("", "NA"),
  quoted_na = TRUE,
  quote = "\"",
  comment = "",
  trim_ws = TRUE,
  skip = 0,
  n_max = 0,
  guess_max = 1000,
  progress = show_progress(),
  name_repair = "unique",
  num_threads = readr_threads(),
  show_col_types = should_show_types(),
  skip_empty_rows = TRUE,
  lazy = TRUE
)

spec_tsv(
  file,
  col_names = TRUE,
  col_types = NULL,
  col_select = NULL,
  id = NULL,
  locale = default_locale(),
  na = c("", "NA"),
  quoted_na = TRUE,
  quote = "\"",
  comment = "",
  trim_ws = TRUE,
  skip = 0,
  n_max = 0,
  guess_max = 1000,
  progress = show_progress(),
  name_repair = "unique",
  num_threads = readr_threads(),
  show_col_types = should_show_types(),
  skip_empty_rows = TRUE,
  lazy = TRUE
)

spec_table(
  file,
  col_names = TRUE,
  col_types = NULL,
  locale = default_locale(),
  na = "NA",
  skip = 0,
  n_max = 0,
  guess_max = 1000,
  progress = show_progress(),
  comment = "",
  skip_empty_rows = TRUE
)

Arguments

file

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. It must contain at least one new line to be recognised as data (instead of a path) or be a vector of greater than length 1.

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

delim

Single character used to separate fields within a record.

quote

Single character used to quote strings.

escape_backslash

Does the file use backslashes to escape special characters? This is more general than escape_double as backslashes can be used to escape the delimiter character, the quote character, or to add special characters like \\n.

escape_double

Does the file escape quotes by doubling them? i.e. If this option is TRUE, the value """" represents a single quote, \".

col_names

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 X1, X2 etc. Duplicate column names will generate a warning and be made unique, see name_repair to control how this is done.

col_types

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

If NULL, all column types will be imputed from the first 1000 rows on the input. This is convenient (and fast), but not robust. If the imputation fails, you'll need to increase the 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).

col_select

<tidy-select> Columns to include in the results, either by name or by numeric index. Use c() or list() to select with more than one expression and ?tidyselect::language for full details on the selection language.

id

The name of a column in which to store the file path. This is useful when reading multiple input files and there is data in the file paths, such as the data collection date. If NULL (the default) no extra column is created.

locale

The locale controls defaults that vary from place to place. The default locale is US-centric (like R), but you can use locale() to create your own locale that controls things like the default time zone, encoding, decimal mark, big mark, and day/month names.

na

Character vector of strings to interpret as missing values. Set this option to character() to indicate no missing values.

quoted_na

Should missing values inside quotes be treated as missing values (the default) or strings.

comment

A string used to identify comments. Any text after the comment characters will be silently ignored.

trim_ws

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

skip

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

n_max

Maximum number of lines to read.

guess_max

Maximum number of lines to use for guessing column types.

name_repair

Treatment of problematic column names:

  • "minimal": No name repair or checks, beyond basic existence of names

  • "unique": Make sure names are unique and not empty

  • "check_unique": (default value), no name repair, but check they are unique

  • "universal": Make the names unique and syntactic

  • a function: apply custom name repair (e.g., .name_repair = make.names for names in the style of base R)

  • A purrr-style anonymous function, see rlang::as_function()

This argument is passed on as repair to vctrs::vec_as_names(). See there for more details on these terms and the strategies used to enforce them.

num_threads

The number of processing threads to use for initial parsing and lazy reading of data.

progress

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.

show_col_types

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.

skip_empty_rows

Should blank rows be ignored altogether? i.e. If this option is TRUE then blank rows will not be represented at all. If it is FALSE then they will be represented by NA values in all the columns.

lazy

Read values lazily? By default the file is initially only indexed and the values are read lazily when accessed. Lazy reading is useful interactively, particularly if you are only interested in a subset of the full dataset. Note, lazy reading on windows will lock the file until all the data has been read from it, if you run into this issue set lazy = FALSE.

Value

The col_spec generated for the file.

Examples

# Input sources ------------------------------------------------------------- # Retrieve specs from a path spec_csv(system.file("extdata/mtcars.csv", package = "readr"))
#> #> ── Column specification ──────────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )
#> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )
spec_csv(system.file("extdata/mtcars.csv.zip", package = "readr"))
#> #> ── Column specification ──────────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )
#> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )
# Or directly from a string (must contain a newline) spec_csv(I("x,y\n1,2\n3,4"))
#> cols( #> x = col_double(), #> y = col_double() #> )
# Column types -------------------------------------------------------------- # By default, readr guesses the columns types, looking at the first 1000 rows. # You can specify the number of rows used with guess_max. spec_csv(system.file("extdata/mtcars.csv", package = "readr"), guess_max = 20)
#> #> ── Column specification ──────────────────────────────────────────────────────── #> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )
#> cols( #> mpg = col_double(), #> cyl = col_double(), #> disp = col_double(), #> hp = col_double(), #> drat = col_double(), #> wt = col_double(), #> qsec = col_double(), #> vs = col_double(), #> am = col_double(), #> gear = col_double(), #> carb = col_double() #> )