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