Cohort values must be integers greater than 0. A list of integers representing the size of cohorts being projected. The number of periods that should be projected. This is the retention profile generated with create_profile. Theseus.project_cohorted_DAU( self, profile, periods, cohorts, DAU_target = None, DAU_target_timeline = None, start_date = 1 )īuild a forward DAU projection based on a retention profile created via the create_profile method When this is set to True, the average day-indexed retention values are graphed. ot_retention( self, profile, show_average_values = True ) Returns: a dict containing the retention profile and various other meta data for the retention data provided. the retention profile curve will only be fit across the data provided and won't be projected past that). If profile_max is not provided, profile_max will be set to the maximum value from the days paramter (ie. The timeline over which the retention profile will be projected. Form can only take one of the values of: . If form is not supplied, the best fit function will be fit to the retention data. The function that should be fit to the retention data to produce the retention profile. Day 0 retention is assumed to always be 100, so Day 0 retention values need not be supplied. Values cannot be less than 0 or greater than 100. 80% retention is provided in retention_values as 80, not. Note that the retention values should represent percentages but be provided as integers (eg. have the same index as) the days parameter. A list of integer retention values that correspond to (ie. Values cannot be less than 0. Day 0 retention is assumed to always be 100, so Day 0 retention values need not be supplied. The list must be of the same length as retention_values. have the same index as) retention values in the retention_values parameter. A list of integer day values that correspond to (ie. Generate a retention profile from day-indexed retention data. Theseus.create_profile( self, days, retention_values, form = 'best_fit', profile_max = None ) Th = th.theseus() Method References _profile Import theseus_growth as th Instantiating Theseus The purpose of this thread is to provide documentation on the various functions that are available in the Theseus class. Theseus was created by Eric Benjamin Seufert of Heracles.įor usage examples, see the Theseus GitHub page. This QuantMar thread contains the full documentation for the Theseus Python library. Theseus is an open source Python library that provides straightforward tools for cohort analysis and general marketing performance analysis.
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