tiledbsoma.io.update_var

tiledbsoma.io.update_var(exp: Experiment, new_data: DataFrame, measurement_name: str, *, context: SOMATileDBContext | None = None, platform_config: Dict[str, Mapping[str, Any]] | object | None = None, default_index_name: str = 'var_id') → None

Given a new Pandas dataframe with desired contents, updates the SOMA experiment’s specified measurement’s entire var to incorporate the changes (this is distinct from append_var which adds new rows, while allowing no schema/column changes).

All columns present in current SOMA-experiment storage but absent from the new dataframe will be dropped. All columns absent in current SOMA-experiment storage but present in the new dataframe will be added. Any columns present in both will be left alone, with the exception that if the new dataframe has a different type for the column, the entire update will raise a ValueError exception.

Parameters:

  • exp – The SOMAExperiment whose var is to be updated. Must

  • write. (be opened for)

  • measurement_name – Specifies which measurement’s var within the experiment

  • updated. (is to be)

  • new_data – a Pandas dataframe with the desired contents.

  • context – Optional SOMATileDBContext containing storage parameters, etc.

  • platform_config – Platform-specific options used to update this array, provided in the form {"tiledb": {"create": {"dataframe_dim_zstd_level": 7}}}

  • default_index_name – What to call the new_data index column if it is nameless in Pandas, or has name "index".

Returns:

None

Lifecycle

Maturing.