code: def to_parquet(df, path, engine='auto', compression='snappy', index=None,
                 partition_cols=None, **kwargs):
      
      impl = get_engine(engine)
      return impl.write(df, path, compression=compression, index=index,
                        partition_cols=partition_cols, **kwargs)
docs: Write a DataFrame to the parquet format.
  
      Parameters
      ----------
      path : str
          File path or Root Directory path. Will be used as Root Directory path
          while writing a partitioned dataset.
  
          .. versionchanged:: 0.24.0
  
      engine : {'auto', 'pyarrow', 'fastparquet'}, default 'auto'
          Parquet library to use. If 'auto', then the option
          ``io.parquet.engine`` is used. The default ``io.parquet.engine``
          behavior is to try 'pyarrow', falling back to 'fastparquet' if
          'pyarrow' is unavailable.
      compression : {'snappy', 'gzip', 'brotli', None}, default 'snappy'
          Name of the compression to use. Use ``None`` for no compression.
      index : bool, default None
          If ``True``, include the dataframe's index(es) in the file output. If
          ``False``, they will not be written to the file. If ``None``, the
          engine's default behavior will be used.
  
          .. versionadded 0.24.0
  
      partition_cols : list, optional, default None
          Column names by which to partition the dataset
          Columns are partitioned in the order they are given
  
          .. versionadded:: 0.24.0
  
      kwargs
          Additional keyword arguments passed to the engine