Aggregation
Aggregation models perform multiple Bach instructions that run some of the more common data analyses or
product analytics metrics. Always return aggregated data in some form from the
DataFrame the model is applied to. Aggregation models can be accessed with the
aggregate accessor from a model hub instance.
class modelhub.Aggregate
(mh)Models that return aggregated data in some form from the original DataFrame with Objectiv data.
unique_users(data[, groupby]) | Calculate the unique users in the Objectiv data. |
unique_sessions(data[, groupby]) | Calculate the unique sessions in the Objectiv data. |
session_duration(data[, groupby, ...]) | Calculate the duration of sessions. |
frequency(data) | Calculate a frequency table for the number of users by number of sessions. |
retention_matrix(data[, time_period, ...]) | Finds the number of users in a given cohort who are active at a given time period, where time is computed with respect to the beginning of each cohort. |
top_product_features(data[, location_stack, ...]) | Calculate the top used features in the product. |
top_product_features_before_conversion(data, ...) | Calculates what users did before converting by combining several models from the model hub. |
drop_off_locations(data[, location_stack, ...]) | Find the locations/features where users drop off, and their usage/share. |
funnel_conversion(data[, location_stack, ...]) | Calculates conversion numbers for all locations stacks in the data. |