# pandas.HDFStore.append

`HDFStore.``append`(key, value, format=None, append=True, columns=None, dropna=None, **kwargs)

  Append to Table in file. Node must already exist and be Table format.

  Parameters:

  key : object

  value : {Series, DataFrame}

  format : ‘table’ is the default

  > 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 True, 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.

  min_itemsize : dict of columns that specify minimum string sizes

  nan_rep : string to use as string nan representation

  chunksize : size to chunk the writing

  expectedrows : expected TOTAL row size of this table

  encoding : default None, provide an encoding for strings

  dropna : boolean, default False, do not write an ALL nan row to

  > the store settable by the option ‘io.hdf.dropna_table’

  Notes

  Does not check if data being appended overlaps with existing data in the table, so be careful

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