append(self, key: 'str', value: 'DataFrame | Series', format=None, axes=None, index=True, append=True, complib=None, complevel: 'int | None' = None, columns=None, min_itemsize: 'int | dict[str, int] | None' = None, nan_rep=None, chunksize=None, expectedrows=None, dropna: 'bool | None' = None, data_columns: 'Literal[True] | list[str] | None' = None, encoding=None, errors: 'str' = 'strict')
Does not check if data being appended overlaps with existing data in the table, so be careful
Format to use when storing object in HDFStore. Value can be one of:
'table'
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 the input data to the existing.
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 :None:None:`here
<https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#query-via-data-columns>`.
Do not write an ALL nan row to the store settable by the option 'io.hdf.dropna_table'.
Append to Table in file. Node must already exist and be Table format.
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them