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.
Syntax:
DataFrame.to_parquet(self, fname, engine='auto', compression='snappy', index=None, partition_cols=None, **kwargs)
Parameters:
| 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' |
Required |
| compression | Name of the compression to use. Use None for no compression. | {'snappy', 'gzip', 'brotli', None} Default Value: 'snappy' |
Required |
| 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 |
Required |
| partition_cols | Column names by which to partition the dataset Columns are partitioned in the order they are given | list Default Value: None |
Optional |
| **kwargs | Additional arguments passed to the parquet library. | Required |
Example:
Download the Pandas DataFrame Notebooks from here.
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