polars.DataFrame.write_csv#

DataFrame.write_csv( file: None = None, *, has_header: bool = True, separator: str = ',', line_terminator: str = '\n', quote: str = '"', batch_size: int = 1024, datetime_format: str | None = None, date_format: str | None = None, time_format: str | None = None, float_precision: int | None = None, null_value: str | None = None, quote_style: CsvQuoteStyle | None = None, ) → str[source]#

Write to comma-separated values (CSV) file.

Parameters:

file: File path to which the result should be written. If set to None (default), the output is returned as a string instead.
has_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_value: A string representing null values (defaulting to the empty string).
quote_style{‘necessary’, ‘always’, ‘non_numeric’}: 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. Always. - 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.

Examples

>>> import pathlib
>>>
>>> df = pl.DataFrame(
...     {
...         "foo": [1, 2, 3, 4, 5],
...         "bar": [6, 7, 8, 9, 10],
...         "ham": ["a", "b", "c", "d", "e"],
...     }
... )
>>> path: pathlib.Path = dirpath / "new_file.csv"
>>> df.write_csv(path, separator=",")