Columns¶

class getml.pipeline.Columns(name, targets, peripheral)[source]¶

Custom class for handling the columns inserted into the pipeline.

Example:

names, importances = my_pipeline.columns.importances()

# Sets all categorical and numerical columns that are not
# in the top 20% to unused.
my_pipeline.columns.select(
    population_table,
    peripheral_tables,
    share_selected_columns=0.2
)

Methods

`importances`([target_num, sort])	Returns the data for the column importances.
`select`(population_table[, …])	Sets all categorical or numerical columns that are not sufficiently important to unused.
`to_pandas`()	Returns all information related to the columns in a pandas data frame.