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# pandas.HDFStore.put

HDFStore.put(key, value, format=None, index=True, append=False, complib=None, complevel=None, min_itemsize=None, nan_rep=None, data_columns=None, encoding=None, errors='strict', track_times=True, dropna=False)

  Store object in HDFStore.

  This method writes a pandas DataFrame or Series into an HDF5 file using either the fixed or table format. The table format allows additional operations like incremental appends and queries but may have performance trade-offs. The fixed format provides faster read/write operations but does not support appends or queries.

  Parameters:
    key str

      Key of object to store in file.

    value{Series, DataFrame}

      Value of object to store in file.

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

      Format to use when storing object in HDFStore. Value can be one of:

      `'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.

    index bool, default True

      Write DataFrame index as a column.

    append bool, default False

      This will force Table format, append the input data to the existing.

    complib default None

      This parameter is currently not accepted.

    complevel int, 0-9, default None

      Specifies a compression level for data. A value of 0 or None disables compression.

    min_itemsize int, dict, or None

      Dict of columns that specify minimum str sizes.

    nan_rep str

      Str to use as str nan representation.

    data_columns list of columns or True, default None

      List of columns to create as data columns, or True to use all columns. See here.

    encoding str, default None

      Provide an encoding for strings.

    errors str, default ‘strict’

      The error handling scheme to use for encoding errors. The default is ‘strict’ meaning that encoding errors raise a UnicodeEncodeError. Other possible values are ‘ignore’, ‘replace’ and ‘xmlcharrefreplace’ as well as any other name registered with codecs.register_error that can handle UnicodeEncodeErrors.

    track_times bool, default True

      Parameter is propagated to ‘create_table’ method of ‘PyTables’. If set to False it enables to have the same h5 files (same hashes) independent on creation time.

    dropna bool, default False, optional

      Remove missing values.

  See also

  `HDFStore.info`

    Prints detailed information on the store.

  `HDFStore.get_storer`

    Returns the storer object for a key.

  Examples

      >>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["A", "B"])
      >>> store = pd.HDFStore("store.h5", "w")
      >>> store.put("data", df)