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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.
Parameters: key : object
value : {Series, DataFrame, Panel, Panel4D}
format: ?table? is the default
- table(t)
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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 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 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?
Notes
Does not check if data being appended overlaps with existing data in the table, so be careful
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