Description Usage Arguments Details Value See Also Examples
A connection to the file filename is created. Column types have to be specified. These are not determined automatically as for example read.csv does. This has been done to increase speed.
1 2 3 4 5 6 7 8 9 10 |
filename |
character containing the filename of the CSV-file |
column_types |
character vector containing the types of data in each of the columns. Valid types are: double, integer, categorical and string. |
column_names |
optional character vector containing the names of the columns. |
sep |
optional character specifying the field separator used in the file. |
dec |
optional character specifying the decimal mark. |
trim |
optional logical specifying whether or not white space at the end of factor levels or character strings should be trimmed. |
skip |
optional numeric specifying the number of lines at the beginning of the file that should be skipped. |
ignore_failed_conversion |
ignore (set to |
After the connection is created data can be extracted using indexing (as in a
normal data.frame) or methods such as read_lines
and
next_block
can be used to read in blocks. For processing the
file in blocks the convenience function process_blocks
can be
used.
The CSV-file should not contain headers. Use the skip
option to skip
any headers.
Object of type laf
. Values can be extracted from this
object using indexing, and methods such as read_lines
,
next_block
.
See read.csv
for conventional access of CSV files. And
detect_dm_csv
to automatically determine the column types.
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 | # Create temporary filename
tmpcsv <- tempfile(fileext="csv")
# Generate test data
ntest <- 10
column_types <- c("integer", "integer", "double", "string")
testdata <- data.frame(
a = 1:ntest,
b = sample(1:2, ntest, replace=TRUE),
c = round(runif(ntest), 13),
d = sample(c("jan", "pier", "tjores", "corneel"), ntest, replace=TRUE)
)
# Write test data to csv file
write.table(testdata, file=tmpcsv, row.names=FALSE, col.names=FALSE, sep=',')
# Create LaF-object
laf <- laf_open_csv(tmpcsv, column_types=column_types)
# Read from file using indexing
first_column <- laf[ , 1]
first_row <- laf[1, ]
# Read from file using blockwise operators
begin(laf)
first_block <- next_block(laf, nrows=2)
second_block <- next_block(laf, nrows=2)
# Cleanup
file.remove(tmpcsv)
|
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