docs/dev/r/reference/csv_convert_options.md

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# CSV Convert Options

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CSV Convert Options

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## Usage

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``` r
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 = "."
)
```

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## 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](https://rdrr.io/r/base/strptime.html) parse strings;
    or (c) a list of
    [TimestampParser](https://arrow.apache.org/docs/r/reference/CsvReadOptions.md)
    objects.

-   decimal_point:

    Character to use for decimal point in floating point numbers.

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## Examples

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``` r
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")))
#> # A tibble: 4 x 1
#>       x
#>   <int>
#> 1     1
#> 2    NA
#> 3     2
#> 4    NA
open_csv_dataset(tf, convert_options = csv_convert_options(null_values = c("", "NA", "NULL")))
#> FileSystemDataset with 1 csv file
#> 1 columns
#> x: int64
```

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