In this chapter you will learn how to construct the foundations of your base table, namely the population and the target.

A linha do tempo da base table

Violações da linha do tempo

Dados disponíveis

Violação da linha do tempo

A população

Selecione a população relevante

Uma população compatível com a linha do tempo

Removendo objetos duplicados

O target

Calcular um target de evento

Calcular um target agregado

Crucial base table concepts

You will learn how to add variables to the base table that you can use to predict the target.

Adding fixed variables

Selecting the right value

Adding age

Adding the donor segment

Adding living place

Adding aggregated variables

Selecting the appropriate date

Maximum value last year

Recency of donations

Adding evolutions

Ratio of last month's and last year's average

Absolute difference between two years

Using evolution variables

Performance of evolution variables

Meaning of evolution

Creating variables

Once you derived variables from the raw data, it is time to clean the data and prepare it for modeling. In this Chapter we discuss the steps that need to be taken to make your data modeling-ready.

Creating dummies

Creating a dummy from a two-category variable

Creating dummies from a many-categories variable

Missing values

How to replace missing values

Creating a missing value dummy

Replace missing values with the median value

Replace missing values with a fixed value

Handling outliers

Influence of outliers on predictive models

Handle outliers with winsorization

Handle outliers with standard deviation

Transformations

Interactions

Square root transformation

Adding interactions to the basetable

Data preparation

In some cases, the target or variables change heavily with the seasons. You will learn how you can deal with seasonality by adding different snapshots to the base table.

Seasonality

Seasonality or not

Detecting seasonality

The effect of seasonality

Using multiple snapshots

Target values

Calculating snapshot targets

Calculating aggregated variables

Stacking basetables

The timegap

Events during the timegap

Calculating aggregated variables with timegap

Adding age with timegap

Congratulations

Advanced base table concepts

Donor IDs

Basetable with countries and age

Basetable used in Ex 2.13

Living place of donors

Donations

Construir bons modelos só é possível se você tiver uma boa base table para começar. Neste curso, você vai aprender a construir uma base table de qualidade, criar variáveis e preparar seus dados para modelagem. Finalizamos com tópicos avançados sobre o tema.

Introduction to Predictive Analytics in Python

Aprenda a preparar e organizar dados para análises preditivas usando Python e conceitos avançados.

Análise Preditiva Intermediária em Python

Aprenda a preparar e organizar seus dados para análises preditivas.

Selecione a população relevante

Análise Preditiva Intermediária em Python

exercicio interativo prático