Table Classes ---------------------------------------------------- Each :obj:`datasets.Dataset` object is backed by a PyArrow Table. A Table can be loaded from either the disk (memory mapped) or in memory. Several Table types are available, and they all inherit from :class:`datasets.table.Table`. .. autoclass:: datasets.table.Table :members: validate, equals, to_batches, to_pydict, to_pandas, to_string, field, column, itercolumns, schema, columns, num_columns, num_rows, shape, nbytes, column_names, .. autoclass:: datasets.table.InMemoryTable :members: validate, equals, to_batches, to_pydict, to_pandas, to_string, field, column, itercolumns, schema, columns, num_columns, num_rows, shape, nbytes, column_names, slice, filter, flatten, combine_chunks, cast, add_column, append_column, remove_column, set_column, rename_columns, drop, from_file, from_buffer, from_pandas, from_arrays, from_pydict, from_batches .. autoclass:: datasets.table.MemoryMappedTable :members: validate, equals, to_batches, to_pydict, to_pandas, to_string, field, column, itercolumns, schema, columns, num_columns, num_rows, shape, nbytes, column_names, slice, filter, flatten, combine_chunks, cast, add_column, append_column, remove_column, set_column, rename_columns, drop, from_file, .. autoclass:: datasets.table.ConcatenationTable :members: validate, equals, to_batches, to_pydict, to_pandas, to_string, field, column, itercolumns, schema, columns, num_columns, num_rows, shape, nbytes, column_names, slice, filter, flatten, combine_chunks, cast, add_column, append_column, remove_column, set_column, rename_columns, drop, from_blocks, from_tables .. autofunction:: datasets.table.concat_tables .. autofunction:: datasets.table.list_table_cache_files