An initial implementation of the subscriber profiles using R6 approach of R language.
According to some benchmarks, R6 provides the most flexible way of data structures implementation using object-oriented techniques. Among those of R language (S4, R5, R6), it's R6 objects take roughly as much memory as the plain S3 objects (for simplicity, plain R functions), though they call for some tweaking too. These data structures and functions have been wrapped into a plain R package. As a result, a number of things intended to make the developer life to be easier (uncluding that boring setwd(...), install.packages(...), library(...) routine), are implemented right out of the box.
Originally, this package was implemented to cover needs of a cellular provider. So the subscriber profile includes the following fields (self-explainable):
hash_number_A, billing_tariff.plan, billing_arpu, billing_usage, billing_top.up,
service.usage_renewal, service.usage_interest.in.new.service, service.usage_ott.stream, service.usage_last.update,
pred.model_churn.score, pred.model_mnp.out, pred.model_change.tariff, pred.model_winback,
social.data_age, social.data_sex, social.data_ethnic.group, social.data_marriage, social.data_household, social.data_wager,
tech.stream_out.of.service, tech.stream_drop.calls, tech.stream_data.speed, tech.stream_location,
value.mngt_life.stage, value.mngt_value.over.time, value.mngt_mnp.in.out, value.mngt_margin.optimisation,
web.data_cookie, web.data_browsing.history, web.data_adblock, web.data_popular.url, web.data_click.rate,
device_type, device_price, device_applications, device_last.update, hash_tariff , event , event_sub , network_service_direction, event_start_date , LAT , LON , cost, hash_number_B , number_B_category, call_duration_minutes, data_volume_mb, hash_accum_code, interest_1, interest_2, interest_3, interest_4, interest_5