R: Generate a column specification

spec_delim {readr} | R Documentation

## Generate a column specification

### Description

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).

### Usage

    spec_delim(
      file,
      delim = NULL,
      quote = "\"",
      escape_backslash = FALSE,
      escape_double = TRUE,
      col_names = TRUE,
      col_types = list(),
      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 = list(),
      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 = list(),
      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 = list(),
      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 = list(),
      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. To be recognised as a path, it must be 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.
`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 `...1`, `...2` 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 `guess_max` rows on the input interspersed throughout the file. 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. This parameter is soft deprecated as of readr 2.0.0.
`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. 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.
`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, if you later write to the same file you read from you need to set `lazy = FALSE`. On Windows the file will be locked and on other systems the memory map will become invalid.

### 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"))
    spec_csv(system.file("extdata/mtcars.csv.zip", package = "readr"))

    # Or directly from a string (must contain a newline)
    spec_csv(I("x,y\n1,2\n3,4"))

    # Column types --------------------------------------------------------------
    # By default, readr guesses the columns types, looking at 1000 rows
    # throughout the file.
    # You can specify the number of rows used with guess_max.
    spec_csv(system.file("extdata/mtcars.csv", package = "readr"), guess_max = 20)

[Package readr version 2.0.2 Index]