pyspark.pandas.Series.to_hdf#
- Series.to_hdf(path_or_buf, key, mode='a', complevel=None, complib=None, append=False, format=None, index=True, min_itemsize=None, nan_rep=None, dropna=None, data_columns=None, errors='strict', encoding='UTF-8')#
- Write the contained data to an HDF5 file using HDFStore. - Note - This method should only be used if the resulting DataFrame is expected to be small, as all the data is loaded into the driver’s memory. - New in version 4.0.0. - Parameters
- path_or_bufstr or pandas.HDFStore
- File path or HDFStore object. 
- keystr
- Identifier for the group in the store. 
- mode{‘a’, ‘w’, ‘r+’}, default ‘a’
- Mode to open file: - ‘w’: write, a new file is created (an existing file with the same name would be deleted). 
- ‘a’: append, an existing file is opened for reading and writing, and if the file does not exist it is created. 
- ‘r+’: similar to ‘a’, but the file must already exist. 
 
- complevel{0-9}, default None
- Specifies a compression level for data. A value of 0 or None disables compression. 
- complib{‘zlib’, ‘lzo’, ‘bzip2’, ‘blosc’}, default ‘zlib’
- Specifies the compression library to be used. These additional compressors for Blosc are supported (default if no compressor specified: ‘blosc:blosclz’): {‘blosc:blosclz’, ‘blosc:lz4’, ‘blosc:lz4hc’, ‘blosc:snappy’, ‘blosc:zlib’, ‘blosc:zstd’}. Specifying a compression library which is not available issues a ValueError. 
- appendbool, default False
- For Table formats, append the input data to the existing. 
- format{‘fixed’, ‘table’, None}, default ‘fixed’
- Possible values: - ‘fixed’: Fixed format. Fast writing/reading. Not-appendable, nor searchable. 
- ‘table’: Table format. Write as a PyTables Table structure which may perform worse but allow more flexible operations like searching / selecting subsets of the data. 
- If None, pd.get_option(‘io.hdf.default_format’) is checked, followed by fallback to “fixed”. 
 
- indexbool, default True
- Write DataFrame index as a column. 
- min_itemsizedict or int, optional
- Map column names to minimum string sizes for columns. 
- nan_repAny, optional
- How to represent null values as str. Not allowed with append=True. 
- dropnabool, default False, optional
- Remove missing values. 
- data_columnslist of columns or True, optional
- List of columns to create as indexed data columns for on-disk queries, or True to use all columns. By default only the axes of the object are indexed. Applicable only to format=’table’. 
- errorsstr, default ‘strict’
- Specifies how encoding and decoding errors are to be handled. See the errors argument for - open()for a full list of options.
- encodingstr, default “UTF-8”
 
 - See also - DataFrame.to_orc
- Write a DataFrame to the binary orc format. 
- DataFrame.to_parquet
- Write a DataFrame to the binary parquet format. 
- DataFrame.to_csv
- Write out to a csv file. 
 - Examples - >>> df = ps.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, ... index=['a', 'b', 'c']) >>> df.to_hdf('data.h5', key='df', mode='w') - We can add another object to the same file: - >>> s = ps.Series([1, 2, 3, 4]) >>> s.to_hdf('data.h5', key='s')