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pandas.Series.to_hdf
Series.to_hdf(path_or_buf, key, **kwargs)
[source]-
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’
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'w'
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Write; a new file is created (an existing file with the same name would be deleted).
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'a'
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Append; an existing file is opened for reading and writing, and if the file does not exist it is created.
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'r+'
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It is similar to
'a'
, but the file must already exist.
format : ‘fixed(f)|table(t)’, default is ‘fixed’
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fixed(f) : Fixed format
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Fast writing/reading. Not-appendable, nor searchable
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table(t) : Table format
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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 None
Specifies a compression level for data. A value of 0 disables compression.
complib : {‘zlib’, ‘lzo’, ‘bzip2’, ‘blosc’}, default ‘zlib’
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.
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© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.22.0/generated/pandas.Series.to_hdf.html