path to a local file.

One or more characters used to delimit fields within a file. If NULL the delimiter is guessed from the set of c(",", "\t", " ", "|", ":", ";").

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 with a numeric suffix.

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 supply the correct types yourself.

If a column specification created by cols(), it 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, use col_types = cols().

One or more selection expressions, like in dplyr::select(). Use c() or list() to use more than one expression. See ?dplyr::select for details on available selection options.

Either a string or 'NULL'. If a string, the output will contain a variable with that name with the filename(s) as the value. If 'NULL', the default, no variable will be created.

Number of lines to skip before reading data.

Maximum number of records to read.

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

Single character used to quote strings.

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

Should leading and trailing whitespace be trimmed from each field before parsing it?

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

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.

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.

Maximum number of records to use for guessing column types.

Control which column types use Altrep representations, either a character vector of types, TRUE or FALSE. See vroom_altrep() for for full details.

Number of threads to use when reading and materializing vectors. If your data contains newlines within fields the parser will automatically be forced to use a single thread only.

Display a progress bar? By default it will only display in an interactive session and not while knitting a document. The display is updated every 50,000 values and will only display if estimated reading time is 5 seconds or more. The automatic progress bar can be disabled by setting option readr.show_progress to FALSE.

Handling of column names. By default, vroom ensures column names are not empty and unique. See .name_repair as documented in tibble::tibble() for additional options including supplying user defined name repair functions.