melt_table | R Documentation |
For certain non-rectangular data formats, it can be useful to parse the data into a melted format where each row represents a single token.
melt_table()
and melt_table2()
are designed to read the type of textual
data where each column is separated by one (or more) columns of space.
melt_table2()
allows any number of whitespace characters between columns,
and the lines can be of different lengths.
melt_table()
is more strict, each line must be the same length,
and each field is in the same position in every line. It first finds empty
columns and then parses like a fixed width file.
melt_table(
file,
locale = default_locale(),
na = "NA",
skip = 0,
n_max = Inf,
guess_max = min(n_max, 1000),
progress = show_progress(),
comment = "",
skip_empty_rows = FALSE
)
melt_table2(
file,
locale = default_locale(),
na = "NA",
skip = 0,
n_max = Inf,
progress = show_progress(),
comment = "",
skip_empty_rows = FALSE
)
file |
Either a path to a file, a connection, or literal data (either a single string or a raw vector). Files ending in Literal data is most useful for examples and tests. To be recognised as
literal data, the input must be either wrapped with Using a value of |
locale |
The locale controls defaults that vary from place to place.
The default locale is US-centric (like R), but you can use
|
na |
Character vector of strings to interpret as missing values. Set this
option to |
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.
See |
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 |
comment |
A string used to identify comments. Any text after the comment characters will be silently ignored. |
skip_empty_rows |
Should blank rows be ignored altogether? i.e. If this
option is |
A tibble()
of four columns:
row
, the row that the token comes from in the original file
col
, the column that the token comes from in the original file
data_type
, the data type of the token, e.g. "integer"
, "character"
,
"date"
, guessed in a similar way to the guess_parser()
function.
value
, the token itself as a character string, unchanged from its
representation in the original file.
If there are parsing problems, a warning tells you
how many, and you can retrieve the details with problems()
.
melt_fwf()
to melt fixed width files where each column
is not separated by whitespace. melt_fwf()
is also useful for reading
tabular data with non-standard formatting. readr::read_table()
is the
conventional way to read tabular data from whitespace-separated files.
# One corner from http://www.masseyratings.com/cf/compare.htm
massey <- meltr_example("massey-rating.txt")
cat(readLines(massey))
melt_table(massey)
# Sample of 1978 fuel economy data from
# http://www.fueleconomy.gov/feg/epadata/78data.zip
epa <- meltr_example("epa78.txt")
writeLines(readLines(epa))
melt_table(epa)
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