Python Tutorial : The target (Intermediate Predictive Analytics in Python)

Want to learn more? Take the full course at https://learn.datacamp.com/courses/intermediate-predictive-analytics-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Once the timeline is set and the population is in place, you are ready to add the target to the basetable. The target is a special column in the basetable, namely the value, zero or one, that you want to predict. In a predictive modeling setting, the value of the target equals one if a certain event happens during the target period for the observation, and zero otherwise. These events can take many forms, depending on what you want to predict. In the donations example, it could be whether a donor donates a certain amount during a given period, whether a donor changes address during a given period or whether a donor unsubscribes from the donor list. Again, one should keep in mind the timeline when adding the target to the basetable. The true target is unknown by definition: it is the unknown event that you want to predict. In order to obtain a basetable that has a target column on which the model can be constructed, we need to use a timeline earlier in time where the target is known. For instance, assume today is August 1st 2018 and you want to construct a predictive model that predicts whether someone will donate in August 2018. Then you should define the target on a similar timeline, for instance one year earlier. The target in the basetable is then 1 if the donor donated in August 2017 and 0 otherwise. Coding the target in Python strongly depends on the definition of the target and how the information about the target event is stored in the data. For instance, consider the case where the target is whether someone unsubscribes from the donor list in 2017, and a list called `unsubscribe` with ids of donors that unsubscribe in 2017 is given. The basetable is already initialized in the pandas dataframe `basetable`. All you