Pandas DataFrame: to_parquet() function

DataFrame - to_parquet() function

The to_parquet() function is used to write a DataFrame to the binary parquet format. This function writes the dataframe as a parquet file.


DataFrame.to_parquet(self, fname, engine='auto', compression='snappy', index=None, partition_cols=None, **kwargs)


Name Description Type / Default Value Required / Optional
fname  File path or Root Directory path. Will be used as Root Directory path while writing a partitioned dataset. str Required
engine   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. {'auto', 'pyarrow', 'fastparquet'}
Default Value: 'auto'
compression Name of the compression to use. Use None for no compression. {'snappy', 'gzip', 'brotli', None}
Default Value: 'snappy'
index   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 behavior depends on the chosen engine. bool
Default Value: None
partition_cols    Column names by which to partition the dataset Columns are partitioned in the order they are given list
Default Value: None
**kwargs Additional arguments passed to the parquet library.   Required


Download the Pandas DataFrame Notebooks from here.

Previous: DataFrame - info() function
Next: DataFrame - to_pickle() function

Follow us on Facebook and Twitter for latest update.