pandas.HDFStore.append
-
HDFStore.append(self, 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} -
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