readr (version 1.0.0)

read_table: Read text file where columns are separated by whitespace.

Description

This is designed to read the type of textual data where each column is separate by one (or more) columns of space. Each line is the same length, and each field is in the same position in every line. It's similar to read.table, but rather parsing like a file delimited by arbitrary amounts of whitespace, it first finds empty columns and then parses like a fixed width file. spec_table returns the column specification rather than a data frame.

Usage

read_table(file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = "NA", skip = 0, n_max = Inf, guess_max = min(n_max, 1000), progress = interactive())
spec_table(file, col_names = TRUE, col_types = NULL, locale = default_locale(), na = "NA", skip = 0, n_max = 0, guess_max = 1000, progress = interactive())

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 & 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).

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 with a numeric prefix.

col_types
One of NULL, a cols specification, or a string. See vignette("column-types") 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, D = date, T = date time, t = time, ? = guess, or _/- to skip the column.

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 use for missing values. Set this option to character() to indicate no missing values.
skip
Number of lines to skip before reading data.
n_max
Maximum number of records to read.
guess_max
Maximum number of records to use for guessing column types.
progress
Display a progress bar? By default it will only display in an interactive session. The display is updated every 50,000 values and will only display if estimated reading time is 5 seconds or more.

See Also

read_fwf to read fixed width files where each column is not separated by whitespace. read_fwf is also useful for reading tabular data with non-standard formatting.

Examples

Run this code
# One corner from http://www.masseyratings.com/cf/compare.htm
massey <- readr_example("massey-rating.txt")
cat(read_file(massey))
read_table(massey)

# Sample of 1978 fuel economy data from
# http://www.fueleconomy.gov/feg/epadata/78data.zip
epa <- readr_example("epa78.txt")
cat(read_file(epa))
read_table(epa, col_names = FALSE)

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