dstrsplit.Rddstrsplit takes raw or character vector and splits it
into a dataframe according to the separators.
dstrsplit(x, col_types, sep="|", nsep=NA, strict=TRUE, skip=0L, nrows=-1L,
quote="")character vector (each element is treated as a row) or a raw vector (newlines separate rows)
required character vector or a list. A vector of
classes to be assumed for the output dataframe. If it is a list,
class(x)[1] will be used to determine the class of the
contained element. It will not be recycled, and must
be at least as long as the longest row if strict is TRUE.
Possible values are "NULL" (when the column is skipped) one of
the six atomic vector types ('character', 'numeric',
'logical', 'integer', 'complex', 'raw')
or POSIXct.
'POSIXct' will parse date format in the form "YYYY-MM-DD hh:mm:ss.sss"
assuming GMT time zone. The separators between digits can be any
non-digit characters and only the date part is mandatory. See also
fasttime::asPOSIXct for details.
single character: field (column) separator. Set to NA
for no seperator; in other words, a single column.
index name separator (single character) or NA if no
index names are included
logical, if FALSE then dstrsplit will not
fail on parsing errors, otherwise input not matching the format
(e.g. more columns than expected) will cause an error.
integer: the number of lines of the data file to skip before beginning to read data.
integer: the maximum number of rows to read in. Negative and other invalid values are ignored.
the set of quoting characters as a length 1 vector. To disable
quoting altogether, use quote = "" (the default). Quoting
is only considered for columns read as character.
If nsep is specified then all characters up to (but excluding)
the occurrence of nsep are treated as the index name. The
remaining characters are split using the sep character into
fields (columns). dstrsplit will fail with an error if any
line contains more columns then expected unless strict is
FALSE. Excessive columns are ignored in that case. Lines may
contain fewer columns in which case they are set to NA.
Note that it is legal to use the same separator for sep and
nsep in which case the first field is treated as a row name and
subsequent fields as data columns.
If nsep is specified, the output of dstrsplit contains
an extra column called 'rowindex' containing the row index. This is
used instead of the rownames to allow for duplicated indicies (which
are checked for and not allowed in a dataframe, unlike the case with
a matrix).
dstrsplit returns a data.frame with as many rows as
they are lines in the input and as many columns as there are
non-NULL values in col_types, plus an additional column if
nsep is specified. The colnames (other than the row index)
are set to 'V' concatenated with the column number unless
col_types is a named vector in which case the names are
inherited.
input = c("apple\t2|2.7|horse|0d|1|2015-02-05 20:22:57",
"pear\t7|3e3|bear|e4|1+3i|2015-02-05",
"pear\te|1.8|bat|77|4.2i|2001-02-05")
z = dstrsplit(x = input,
col_types = c("integer", "numeric", "character","raw","complex","POSIXct"),
sep="|", nsep="\t")
lapply(z,class)
#> $rowindex
#> [1] "character"
#>
#> $V1
#> [1] "integer"
#>
#> $V2
#> [1] "numeric"
#>
#> $V3
#> [1] "character"
#>
#> $V4
#> [1] "raw"
#>
#> $V5
#> [1] "complex"
#>
#> $V6
#> [1] "POSIXct" "POSIXt"
#>
z
#> rowindex V1 V2 V3 V4 V5 V6
#> 1 apple 2 2.7 horse 0d 1+0.0i 2015-02-05 20:22:57
#> 2 pear 7 3000.0 bear e4 1+3.0i 2015-02-05 00:00:00
#> 3 pear NA 1.8 bat 77 0+4.2i 2001-02-05 00:00:00
# Ignoring the third column:
z = dstrsplit(x = input,
col_types = c("integer", "numeric", "character","raw","complex","POSIXct"),
sep="|", nsep="\t")
z
#> rowindex V1 V2 V3 V4 V5 V6
#> 1 apple 2 2.7 horse 0d 1+0.0i 2015-02-05 20:22:57
#> 2 pear 7 3000.0 bear e4 1+3.0i 2015-02-05 00:00:00
#> 3 pear NA 1.8 bat 77 0+4.2i 2001-02-05 00:00:00