csv_convert_options function

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 = "."
)

Arguments

• check_utf8: Logical: check UTF8 validity of string columns?
• null_values: Character vector of recognized spellings for null values. Analogous to the na.strings argument to read.csv() or na in readr::read_csv().
• true_values: Character vector of recognized spellings for TRUE values
• false_values: Character vector of recognized spellings for FALSE values
• strings_can_be_null: Logical: can string / binary columns have null values? Similar to the quoted_na argument to readr::read_csv()
• col_types: A Schema or NULL to infer types
• auto_dict_encode: Logical: Whether to try to automatically dictionary-encode string / binary data (think stringsAsFactors). This setting is ignored for non-inferred columns (those in col_types).
• auto_dict_max_cardinality: If auto_dict_encode, string/binary columns are dictionary-encoded up to this number of unique values (default 50), after which it switches to regular encoding.
• 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 include_columns is provided, should columns named in it but not found in the data be included as a column of type null()? The default (FALSE) means that the reader will instead raise an error.
• 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) NULL, the default, which uses the ISO-8601 parser; (b) a character vector of strptime parse strings; or (c) a list of TimestampParser objects.
• decimal_point: Character to use for decimal point in floating point numbers.

Examples

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")))