Models
The open model hub has two main types of functions: map and aggregate.
- map functions always return a series with the same shape and index as the
DataFramethey are applied to. This ensures they can be added as a column to thatDataFrame. map functions that returnDataFramecan be used with to filter the data. - aggregate functions return aggregated data in some form from the
DataFrame. Can also be accessed withagg.
Map
is_first_session(data) | Labels all hits in a session True if that session is the first session of that user in the data. |
is_new_user(data[, time_aggregation]) | Labels all hits True if the user is first seen in the period given time_aggregation. |
is_conversion_event(data, name) | Labels a hit True if it is a conversion event, all other hits are labeled False. |
conversions_counter(data, name[, partition]) | Counts the total number of conversions given a partition (ie session_id or user_id). |
conversions_in_time(data, name[, partition]) | Counts the number of time a user is converted at a moment in time given a partition (ie 'session_id' or 'user_id'). |
pre_conversion_hit_number(data, name[, ...]) | Returns a count backwards from the first conversion, given the partition. |
Aggregate
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. |