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

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

key : object
value : {Series, DataFrame, Panel}
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


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 represenation
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’


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

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