Pandas DataFrame: to_hdf() function
DataFrame - to_hdf() function
The to_hdf() function is used to write the contained data to an HDF5 file using HDFStore.
Syntax:
DataFrame.to_hdf(self, path_or_buf, key, **kwargs)
Parameters:
| Name | Description | Type/Default Value | Required / Optional | 
|---|---|---|---|
| path_or_buf | File path or HDFStore object. | str or pandas.HDFStore | Required | 
| key | Identifier for the group in the store. | str | Required | 
| mode | Mode to open file:
    
  | 
  {'a', 'w', 'r+'} Default Value: ‘a’  | 
  Required | 
| format | Possible values:
    
  | 
  {‘fixed’, ‘table’} Default Value: ‘fixed’  | 
  Required | 
| append | For Table formats, append the input data to the existing. | bool  Default Value: False  | 
  Required | 
| data_columns | 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. | list of columns Default Value: True  | 
  Optional | 
| complevel | Specifies a compression level for data. A value of 0 disables compression. | {0-9} | Optional | 
| complib | Specifies the compression library to be used. As of v0.20.2 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. | {‘zlib’, ‘lzo’, ‘bzip2’, ‘blosc’} Default Value: ‘zlib’  | 
  Required | 
| fletcher32 | If applying compression use the fletcher32 checksum. | bool Default Value: False  | 
  Required | 
| dropna | If true, ALL nan rows will not be written to store. | bool Default Value: False  | 
  Required | 
| errors | Specifies how encoding and decoding errors are to be handled. See the errors argument for open() for a full list of options. | str Default Value: ‘strict’  | 
  Optional | 
Example:
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