pandas.DataFrame.to_hdf

DataFrame.to_hdf(path_or_buf, key, **kwargs)

Write the contained data to an HDF5 file using HDFStore.

Parameters:

path_or_buf : the path (string) or HDFStore object

key : string

identifier for the group in the store

mode : optional, {‘a’, ‘w’, ‘r+’}, default ‘a’

'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+'

It is similar to 'a', but the file must already exist.

format : ‘fixed(f)|table(t)’, default is ‘fixed’

fixed(f) : Fixed format

Fast writing/reading. Not-appendable, nor searchable

table(t) : Table format

Write as a PyTables Table structure which may perform worse but allow more flexible operations like searching / selecting subsets of the data

append : boolean, default False

For Table formats, append the input data to the existing

data_columns : list of columns, or True, default None

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. See here.

Applicable only to format=’table’.

complevel : int, 0-9, default 0

Specifies a compression level for data. A value of 0 disables compression.

complib : {‘zlib’, ‘lzo’, ‘bzip2’, ‘blosc’, None}, default None

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.

fletcher32 : bool, default False

If applying compression use the fletcher32 checksum

dropna : boolean, default False.

If true, ALL nan rows will not be written to store.