csv_convert_options | R Documentation |
CSV Convert Options
csv_convert_options(
check_utf8 = TRUE,
null_values = c("", "NA"),
true_values = c("T", "true", "TRUE"),
false_values = c("F", "false", "FALSE"),
strings_can_be_null = FALSE,
col_types = NULL,
auto_dict_encode = FALSE,
auto_dict_max_cardinality = 50L,
include_columns = character(),
include_missing_columns = FALSE,
timestamp_parsers = NULL,
decimal_point = "."
)
check_utf8 |
Logical: check UTF8 validity of string columns? |
null_values |
Character vector of recognized spellings for null values.
Analogous to the |
true_values |
Character vector of recognized spellings for |
false_values |
Character vector of recognized spellings for |
strings_can_be_null |
Logical: can string / binary columns have
null values? Similar to the |
col_types |
A |
auto_dict_encode |
Logical: Whether to try to automatically
dictionary-encode string / binary data (think |
auto_dict_max_cardinality |
If |
include_columns |
If non-empty, indicates the names of columns from the CSV file that should be actually read and converted (in the vector's order). |
include_missing_columns |
Logical: if |
timestamp_parsers |
User-defined timestamp parsers. If more than one
parser is specified, the CSV conversion logic will try parsing values
starting from the beginning of this vector. Possible values are
(a) |
decimal_point |
Character to use for decimal point in floating point numbers. |
tf <- tempfile()
on.exit(unlink(tf))
writeLines("x\n1\nNULL\n2\nNA", tf)
read_csv_arrow(tf, convert_options = csv_convert_options(null_values = c("", "NA", "NULL")))
open_csv_dataset(tf, convert_options = csv_convert_options(null_values = c("", "NA", "NULL")))
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