Columns¶
-
class
getml.pipeline.
Columns
(pipeline, targets, peripheral, data=None)[source]¶ Container which holds a pipeline’s columns. Columns can be accessed by name, index or with a numpy array. The container supports slicing and is sort- and filterable.
Further, the container holds global methods to request columns’ importances and apply a column selection to data frames provided to the pipeline.
Note:
The container is an iterable. So, in addition to
filter()
you can also use python list comprehensions for filtering.Example:
all_my_columns = my_pipeline.columns first_column = my_pipeline.columns[0] all_but_last_10_columns = my_pipeline.columns[:-10] important_columns = [column for column in my_pipeline.columns if column.importance > 0.1] 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
filter
(conditional)Filters the columns container.
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.
sort
([by, key, descending])Sorts the Columns container.
Returns all information related to the columns in a pandas data frame.
Attributes
Holds the names of a
Pipeline
’s columns.