Export data to CSV file(s)
Usage
write_csv_polars(
.data,
file,
...,
include_bom = FALSE,
include_header = TRUE,
separator = ",",
line_terminator = "\n",
quote = "\"",
batch_size = 1024,
datetime_format = NULL,
date_format = NULL,
time_format = NULL,
float_precision = NULL,
null_values = "",
quote_style = "necessary"
)
Arguments
- .data
A Polars DataFrame.
- file
File path to which the result should be written.
- ...
Ignored.
- include_bom
Whether to include UTF-8 BOM (byte order mark) in the CSV output.
- include_header
Whether to include header in the CSV output.
- separator
Separate CSV fields with this symbol.
- line_terminator
String used to end each row.
- quote
Byte to use as quoting character.
- batch_size
Number of rows that will be processed per thread.
- datetime_format
A format string, with the specifiers defined by the chrono Rust crate. If no format specified, the default fractional-second precision is inferred from the maximum timeunit found in the frame’s Datetime cols (if any).
- date_format
A format string, with the specifiers defined by the chrono Rust crate.
- time_format
A format string, with the specifiers defined by the chrono Rust crate.
- float_precision
Number of decimal places to write, applied to both Float32 and Float64 datatypes.
- null_values
A string representing null values (defaulting to the empty string).
- quote_style
Determines the quoting strategy used.
"necessary"
(default): This puts quotes around fields only when necessary. They are necessary when fields contain a quote, delimiter or record terminator. Quotes are also necessary when writing an empty record (which is indistinguishable from a record with one empty field). This is the default."always"
: This puts quotes around every field."non_numeric"
: This puts quotes around all fields that are non-numeric. Namely, when writing a field that does not parse as a valid float or integer, then quotes will be used even if they aren`t strictly necessary."never"
: This never puts quotes around fields, even if that results in invalid CSV data (e.g. by not quoting strings containing the separator).
Examples
dest <- tempfile(fileext = ".csv")
mtcars |>
as_polars_df() |>
write_csv_polars(dest)
read.csv(dest)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> 2 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> 3 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> 4 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> 5 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> 6 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> 7 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> 8 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> 9 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> 10 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> 11 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> 12 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> 13 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> 14 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> 15 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> 16 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> 17 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> 18 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> 19 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> 20 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> 21 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> 22 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> 23 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> 24 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> 25 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> 26 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> 27 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> 28 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> 29 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> 30 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> 31 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> 32 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2