pandas.HDFStore.append

HDFStore.append(self, 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