Package 'readr'

Either column objects created by ⁠col_*()⁠, or their abbreviated character names (as described in the col_types argument of read_delim()). If you're only overriding a few columns, it's best to refer to columns by name. If not named, the column types must match the column names exactly.

Any named columns not explicitly overridden in ... will be read with this column type.

The data frame object to extract from

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.

A tokenizer that specifies how to break the file up into fields, e.g., tokenizer_csv(), tokenizer_fwf()

Number of lines to skip before reading data.

Optionally, maximum number of rows to count fields for.

Full and abbreviated month names.

Full and abbreviated week day names. Starts with Sunday.

Names used for AM and PM.

A BCP 47 locale, made up of a language and a region, e.g. "en" for American English. See date_names_langs() for a complete list of available locales.

A data frame.

Delimiter used to separate values. Defaults to " " for write_delim(), "," for write_excel_csv() and ";" for write_excel_csv2(). Must be a single character.

String used for missing values. Defaults to NA. Missing values will never be quoted; strings with the same value as na will always be quoted.

If FALSE, will overwrite existing file. If TRUE, will append to existing file. In both cases, if the file does not exist a new file is created.

If FALSE, column names will not be included at the top of the file. If TRUE, column names will be included. If not specified, col_names will take the opposite value given to append.

How to handle fields which contain characters that need to be quoted.

• needed - Values are only quoted if needed: if they contain a delimiter, quote, or newline.

• all - Quote all fields.

• none - Never quote fields.

The type of escape to use when quotes are in the data.

• double - quotes are escaped by doubling them.

• backslash - quotes are escaped by a preceding backslash.

• none - quotes are not escaped.

The end of line character to use. Most commonly either "\n" for Unix style newlines, or "\r\n" for Windows style newlines.

Use the escape argument instead.

A character string specifying an input as specified in datasource(), a raw vector, or a list of raw vectors.

Number of lines to read. If n_max is -1, all lines in file will be read.

Only report guesses above this threshold of certainty.

Character representations of day and month names. Either the language code as string (passed on to date_names_lang()) or an object created by date_names().

Default date and time formats.

Symbols used to indicate the decimal place, and to chunk larger numbers. Decimal mark can only be ⁠,⁠ or ..

Default tz. This is used both for input (if the time zone isn't present in individual strings), and for output (to control the default display). The default is to use "UTC", a time zone that does not use daylight savings time (DST) and hence is typically most useful for data. The absence of time zones makes it approximately 50x faster to generate UTC times than any other time zone.

Use "" to use the system default time zone, but beware that this will not be reproducible across systems.

For a complete list of possible time zones, see OlsonNames(). Americans, note that "EST" is a Canadian time zone that does not have DST. It is not Eastern Standard Time. It's better to use "US/Eastern", "US/Central" etc.

Default encoding. This only affects how the file is read - readr always converts the output to UTF-8.

Should diacritics be stripped from date names and converted to ASCII? This is useful if you're dealing with ASCII data where the correct spellings have been lost. Requires the stringi package.

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.

Single character used to separate fields within a record.

Single character used to quote strings.

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.

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

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.

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

Should missing values inside quotes be treated as missing values (the default) or strings. This parameter is soft deprecated as of readr 2.0.0.

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

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.

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.

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.

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.

Column positions, as created by fwf_empty(), fwf_widths() or fwf_positions(). To read in only selected fields, use fwf_positions(). If the width of the last column is variable (a ragged fwf file), supply the last end position as NA.

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.

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

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

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.

Maximum number of lines to read.

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.

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.

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.

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.

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

Number of lines to skip before reading data.

Maximum number of lines to read.

Maximum number of lines to use for guessing column types. Will never use more than the number of lines read. See vignette("column-types", package = "readr") for more details.

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.

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

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.

Character vector of values to parse.

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

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.

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

A character vector of dates to parse.

A format specification, as described below. If set to "", date times are parsed as ISO8601, dates and times used the date and time formats specified in the locale().

Unlike strptime(), the format specification must match the complete string.

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

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.

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

Character vector of values to parse.

Character vector of the allowed levels. When levels = NULL (the default), levels are discovered from the unique values of x, in the order in which they appear in x.

Is it an ordered factor?

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

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.

If TRUE and x contains at least one NA, then NA is included in the levels of the constructed factor.

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

Character vector of values to parse.

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

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.

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

If TRUE, guess integer types for whole numbers, if FALSE guess numeric type for all numbers.

Character vector of values to parse.

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

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.

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

A data frame (from ⁠read_*()⁠) or a vector (from ⁠parse_*()⁠).

Row and column of problem

What readr expected to find

What it actually got

Name (character string) of data set to read.

Name of package from which to find data set. By default, all attached packages are searched and then the 'data' subdirectory (if present) of the current working directory.

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.

Single character used to separate fields within a record.

Single character used to quote strings.

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.

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

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).

Columns to include in the results. You can use the same mini-language as dplyr::select() to refer to the columns by name. Use c() to use more than one selection expression. Although this usage is less common, col_select also accepts a numeric column index. See ?tidyselect::language for full details on the selection language.

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.

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.

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

Should missing values inside quotes be treated as missing values (the default) or strings. This parameter is soft deprecated as of readr 2.0.0.

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

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.

Maximum number of lines to use for guessing column types. Will never use more than the number of lines read. See vignette("column-types", package = "readr") for more details.

Handling of column names. The default behaviour is to ensure column names are "unique". Various repair strategies are supported:

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

• "unique" (default value): Make sure names are unique and not empty.

• "check_unique": No name repair, but check they are unique.

• "unique_quiet": Repair with the unique strategy, quietly.

• "universal": Make the names unique and syntactic.

• "universal_quiet": Repair with the universal strategy, quietly.

• 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.

The number of processing threads to use for initial parsing and lazy reading of data. If your data contains newlines within fields the parser should automatically detect this and fall back to using one thread only. However if you know your file has newlines within quoted fields it is safest to set num_threads = 1 explicitly.

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.

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.

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.

Read values lazily? By default, this is FALSE, because there are special considerations when reading a file lazily that have tripped up some users. Specifically, things get tricky when reading and then writing back into the same file. But, in general, lazy reading (lazy = TRUE) has many benefits, especially for interactive use and when your downstream work only involves a subset of the rows or columns.

Learn more in should_read_lazy() and in the documentation for the altrep argument of vroom::vroom().

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.

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.

A single string, or a raw vector to write to disk.

If FALSE, will overwrite existing file. If TRUE, will append to existing file. In both cases, if the file does not exist a new file is created.

Use the file argument instead.

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.

Column positions, as created by fwf_empty(), fwf_widths() or fwf_positions(). To read in only selected fields, use fwf_positions(). If the width of the last column is variable (a ragged fwf file), supply the last end position as NA.

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).

Columns to include in the results. You can use the same mini-language as dplyr::select() to refer to the columns by name. Use c() to use more than one selection expression. Although this usage is less common, col_select also accepts a numeric column index. See ?tidyselect::language for full details on the selection language.

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.

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.

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

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

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.

Maximum number of lines to read.

Maximum number of lines to use for guessing column types. Will never use more than the number of lines read. See vignette("column-types", package = "readr") for more details.

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.

Handling of column names. The default behaviour is to ensure column names are "unique". Various repair strategies are supported:

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

• "unique" (default value): Make sure names are unique and not empty.

• "check_unique": No name repair, but check they are unique.

• "unique_quiet": Repair with the unique strategy, quietly.

• "universal": Make the names unique and syntactic.

• "universal_quiet": Repair with the universal strategy, quietly.

• 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.

The number of processing threads to use for initial parsing and lazy reading of data. If your data contains newlines within fields the parser should automatically detect this and fall back to using one thread only. However if you know your file has newlines within quoted fields it is safest to set num_threads = 1 explicitly.

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.

Read values lazily? By default, this is FALSE, because there are special considerations when reading a file lazily that have tripped up some users. Specifically, things get tricky when reading and then writing back into the same file. But, in general, lazy reading (lazy = TRUE) has many benefits, especially for interactive use and when your downstream work only involves a subset of the rows or columns.

Learn more in should_read_lazy() and in the documentation for the altrep argument of vroom::vroom().

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.

Either NULL, or a character vector column names.

Number of lines the tokenizer will read to determine file structure. By default it is set to 100.

Width of each field. Use NA as width of last field when reading a ragged fwf file.

Starting and ending (inclusive) positions of each field. Use NA as last end field when reading a ragged fwf file.

If the first element is a data frame, then it must have all numeric columns and either one or two rows. The column names are the variable names. The column values are the variable widths if a length one vector, and if length two, variable start and end positions. The elements of ... are used to construct a data frame with or or two rows as above.

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.

Number of lines to skip before reading data.

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.

Number of lines to read. If n_max is -1, all lines in file will be read.

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.

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

Read values lazily? By default, this is FALSE, because there are special considerations when reading a file lazily that have tripped up some users. Specifically, things get tricky when reading and then writing back into the same file. But, in general, lazy reading (lazy = TRUE) has many benefits, especially for interactive use and when your downstream work only involves a subset of the rows or columns.

Learn more in should_read_lazy() and in the documentation for the altrep argument of vroom::vroom().

The number of processing threads to use for initial parsing and lazy reading of data. If your data contains newlines within fields the parser should automatically detect this and fall back to using one thread only. However if you know your file has newlines within quoted fields it is safest to set num_threads = 1 explicitly.

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.

A character vector or list of raw vectors to write to disk.

The line separator. Defaults to ⁠\\n⁠, commonly used on POSIX systems like macOS and linux. For native windows (CRLF) separators use ⁠\\r\\n⁠.

If FALSE, will overwrite existing file. If TRUE, will append to existing file. In both cases, if the file does not exist a new file is created.

Use the file argument instead.

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.

The file path to read from/write to.

A function to handle reference objects.

R object to write to serialise.

Compression method to use: "none", "gz" ,"bz", or "xz".

Serialization format version to be used. The default value is 2 as it's compatible for R versions prior to 3.5.0. See base::saveRDS() for more details.

If TRUE a text representation is used, otherwise a binary representation is used.

Use the file argument instead.

Additional arguments to connection function. For example, control the space-time trade-off of different compression methods with compression. See connections() for more details.

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).

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.

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

Number of lines to skip before reading data.

Maximum number of lines to read.

Maximum number of lines to use for guessing column types. Will never use more than the number of lines read. See vignette("column-types", package = "readr") for more details.

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.

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

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.

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.

Name of file. If NULL, the example files will be listed.

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.

Single character used to separate fields within a record.

Single character used to quote strings.

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.

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

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).

Columns to include in the results. You can use the same mini-language as dplyr::select() to refer to the columns by name. Use c() to use more than one selection expression. Although this usage is less common, col_select also accepts a numeric column index. See ?tidyselect::language for full details on the selection language.

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.

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.

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

Should missing values inside quotes be treated as missing values (the default) or strings. This parameter is soft deprecated as of readr 2.0.0.

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

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.

Maximum number of lines to use for guessing column types. Will never use more than the number of lines read. See vignette("column-types", package = "readr") for more details.

Handling of column names. The default behaviour is to ensure column names are "unique". Various repair strategies are supported:

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

• "unique" (default value): Make sure names are unique and not empty.

• "check_unique": No name repair, but check they are unique.

• "unique_quiet": Repair with the unique strategy, quietly.

• "universal": Make the names unique and syntactic.

• "universal_quiet": Repair with the universal strategy, quietly.

• 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.

The number of processing threads to use for initial parsing and lazy reading of data. If your data contains newlines within fields the parser should automatically detect this and fall back to using one thread only. However if you know your file has newlines within quoted fields it is safest to set num_threads = 1 explicitly.

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.

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.

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.

Read values lazily? By default, this is FALSE, because there are special considerations when reading a file lazily that have tripped up some users. Specifically, things get tricky when reading and then writing back into the same file. But, in general, lazy reading (lazy = TRUE) has many benefits, especially for interactive use and when your downstream work only involves a subset of the rows or columns.

Learn more in should_read_lazy() and in the documentation for the altrep argument of vroom::vroom().

A data frame.

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

If NULL, column types will be imputed using all rows.

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

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

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.

If TRUE, guess integer types for whole numbers, if FALSE guess numeric type for all numbers.

Should be a single integer, such as 1 or 2.

Code to run with the changed edition.

Environment that controls scope of changes. For expert use only.

A data frame or tibble to write to disk.

File or connection to write to.

Delimiter used to separate values. Defaults to " " for write_delim(), "," for write_excel_csv() and ";" for write_excel_csv2(). Must be a single character.

String used for missing values. Defaults to NA. Missing values will never be quoted; strings with the same value as na will always be quoted.

If FALSE, will overwrite existing file. If TRUE, will append to existing file. In both cases, if the file does not exist a new file is created.

If FALSE, column names will not be included at the top of the file. If TRUE, column names will be included. If not specified, col_names will take the opposite value given to append.

How to handle fields which contain characters that need to be quoted.

• needed - Values are only quoted if needed: if they contain a delimiter, quote, or newline.

• all - Quote all fields.

• none - Never quote fields.

The type of escape to use when quotes are in the data.

• double - quotes are escaped by doubling them.

• backslash - quotes are escaped by a preceding backslash.

• none - quotes are not escaped.

The end of line character to use. Most commonly either "\n" for Unix style newlines, or "\r\n" for Windows style newlines.

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.

Use the file argument instead.

Use the escape argument instead.