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Session.read_pandas(dataframe, /, *, data_types=frozendict({}), default_values=frozendict({}), keys=frozenset({}), partitioning=None, table_name, **kwargs)

Read a pandas DataFrame into a table.
This is just a shortcut for:
inferred_data_types = session.tables.infer_data_types(dataframe)
table = session.create_table(
    table_name,
    data_types={**inferred_data_types, **data_types},
    default_values=...,
    keys=...,
    partitioning=...,
)
table.load(dataframe)
The longer variant can be refactored to move the load() call inside a data_transaction().
All the named indices of the DataFrame are included into the table. Multilevel columns are flattened into a single string name.
  • Parameters:
    • data_types (Mapping [str , DataType ]) – Data types for some or all columns of the table. Data types for non specified columns will be inferred from the dataframe dtypes.
    • dataframe (pd.DataFrame) – The DataFrame to load.
    • default_values (Mapping [str , Constant | None ]) – See create_table()’s default_values.
    • keys (AbstractSet [str ] | Sequence [str ]) – See create_table()’s keys.
    • partitioning (str | None) – See create_table()’s partitioning.
    • table_name (str) – See create_table()’s name.
    • kwargs (Unpack [ _ReadPandasPrivateParameters ])
  • Return type: Table