Description Usage Arguments Examples
Read a delimited file into a tibble
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | vroom(
file,
delim = NULL,
col_names = TRUE,
col_types = NULL,
col_select = NULL,
id = NULL,
skip = 0,
n_max = Inf,
na = c("", "NA"),
quote = "\"",
comment = "",
trim_ws = TRUE,
escape_double = TRUE,
escape_backslash = FALSE,
locale = default_locale(),
guess_max = 100,
altrep = TRUE,
altrep_opts = deprecated(),
num_threads = vroom_threads(),
progress = vroom_progress(),
.name_repair = "unique"
)
|
file |
path to a local file. |
delim |
One or more characters used to delimit fields within a
file. If |
col_names |
Either If If Missing ( |
col_types |
One of If If a column specification created by 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
|
col_select |
One or more selection expressions, like in
|
id |
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. |
skip |
Number of lines to skip before reading data. |
n_max |
Maximum number of records to read. |
na |
Character vector of strings to interpret as missing values. Set this
option to |
quote |
Single character used to quote strings. |
comment |
A string used to identify comments. Any text after the comment characters will be silently ignored. |
trim_ws |
Should leading and trailing whitespace be trimmed from each field before parsing it? |
escape_double |
Does the file escape quotes by doubling them?
i.e. If this option is |
escape_backslash |
Does the file use backslashes to escape special
characters? This is more general than |
locale |
The locale controls defaults that vary from place to place.
The default locale is US-centric (like R), but you can use
|
guess_max |
Maximum number of records to use for guessing column types. |
altrep |
Control which column types use Altrep representations,
either a character vector of types, |
altrep_opts |
\Sexpr[results=rd, stage=render]{lifecycle::badge("deprecated")} |
num_threads |
Number of threads to use when reading and materializing
vectors. If your data contains embedded newlines (newlines within fields)
you must use |
progress |
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 |
.name_repair |
Handling of column names. By default, vroom ensures
column names are not empty and unique. See |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | # get path to example file
input_file <- vroom_example("mtcars.csv")
input_file
# Read from a path
# Input sources -------------------------------------------------------------
# Read from a path
vroom(input_file)
# You can also use literal paths directly
# vroom("mtcars.csv")
## Not run:
# Including remote paths
vroom("https://github.com/r-lib/vroom/raw/master/inst/extdata/mtcars.csv")
## End(Not run)
# Or directly from a string (must contain a trailing newline)
vroom("x,y\n1,2\n3,4\n")
# Column selection ----------------------------------------------------------
# Pass column names or indexes directly to select them
vroom(input_file, col_select = c(model, cyl, gear))
vroom(input_file, col_select = c(1, 3, 11))
# Or use the selection helpers
vroom(input_file, col_select = starts_with("d"))
# You can also rename specific columns
vroom(input_file, col_select = list(car = model, everything()))
# Column types --------------------------------------------------------------
# By default, vroom guesses the columns types, looking at 1000 rows
# throughout the dataset.
# You can specify them explcitly with a compact specification:
vroom("x,y\n1,2\n3,4\n", col_types = "dc")
# Or with a list of column types:
vroom("x,y\n1,2\n3,4\n", col_types = list(col_double(), col_character()))
# File types ----------------------------------------------------------------
# csv
vroom("a,b\n1.0,2.0\n", delim = ",")
# tsv
vroom("a\tb\n1.0\t2.0\n")
# Other delimiters
vroom("a|b\n1.0|2.0\n", delim = "|")
# Read datasets across multiple files ---------------------------------------
mtcars_by_cyl <- vroom_example(vroom_examples("mtcars-"))
mtcars_by_cyl
# Pass the filenames directly to vroom, they are efficiently combined
vroom(mtcars_by_cyl)
|
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