pyspark.pandas.dataframe.to_csv
DataFrame.to_csv(path: Optional[str] = None, sep: str = ',', na_rep: str = '', columns: Optional[List[Union[Any, Tuple[Any, …]]]] = None, header: bool = True, quotechar: str = '"', date_format: Optional[str] = None, escapechar: Optional[str] = None, num_files: Optional[int] = None, mode: str = 'w', partition_cols: Union[str, List[str], None] = None, index_col: Union[str, List[str], None] = None, **options: Any) → Optional[str]Write object to a comma-separated values (csv) file.
parameters
path: str, default None
File path. If None is provided the result is returned as a string.
sep: str, default ‘,’
String of length 1. Field delimiter for the output file.
na_rep: str, default ‘’
Missing data representation.
columns: sequence, optional
Columns to write.
header: bool or list of str, default True
Write out the column names. If a list of strings is given it is assumed to be aliases for the column names.
quotechar: str, default ‘”’
String of length 1. Character used to quote fields.
date_format: str, default None
Format string for datetime objects.
escapechar: str, default None
String of length 1. Character used to escape sep and quotechar when appropriate.
num_files: the number of partitions to be written in `path` directory when
this is a path. This is deprecated. Use DataFrame.spark.repartition instead.
mode: str
Python write mode, default ‘w’.
Reference
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