read_table()
is designed to read the type of textual
data where each column is separated by one (or more) columns of space.
read_table()
is like read.table()
, it allows any number of whitespace
characters between columns, and the lines can be of different lengths.
spec_table()
returns the column specifications 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 = show_progress(),
comment = "",
show_col_types = should_show_types(),
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 withhttp://
,https://
,ftp://
, orftps://
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.- 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. IfFALSE
, 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, seename_repair
to control how this is done.- col_types
One of
NULL
, acols()
specification, or a string. Seevignette("readr")
for more details.If
NULL
, all column types will be inferred fromguess_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 increaseguess_max
or supply the correct types yourself.Column specifications created by
list()
orcols()
must contain one column specification for each column. If you only want to read a subset of the columns, usecols_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, setshow_col_types = FALSE
or setoptions(readr.show_col_types = FALSE)
.- 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.- skip
Number of lines to skip before reading data.
- n_max
Maximum number of lines to read.
- guess_max
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.- 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
toFALSE
.- comment
A string used to identify comments. Any text after the comment characters will be silently ignored.
- show_col_types
If
FALSE
, do not show the guessed column types. IfTRUE
always show the column types, even if they are supplied. IfNULL
(the default) only show the column types if they are not explicitly supplied by thecol_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 isFALSE
then they will be represented byNA
values in all the columns.
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
ws <- readr_example("whitespace-sample.txt")
writeLines(read_lines(ws))
#> first last state phone
#> John Smith WA 418-Y11-4111
#> Mary Hartford CA 319-Z19-4341
#> Evan Nolan IL 219-532-c301
read_table(ws)
#>
#> ── Column specification ──────────────────────────────────────────────────
#> cols(
#> first = col_character(),
#> last = col_character(),
#> state = col_character(),
#> phone = col_character()
#> )
#> # A tibble: 3 × 4
#> first last state phone
#> <chr> <chr> <chr> <chr>
#> 1 John Smith WA 418-Y11-4111
#> 2 Mary Hartford CA 319-Z19-4341
#> 3 Evan Nolan IL 219-532-c301