Chapter 10: Data Modeling – Modeling Basics
In this chapter, you will learn how to discover patterns in data using resampling and smoothing. The .resample(), .rolling(), and .ewm() pandas methods will be introduced and you will learn how to use them to filter out the noise and perform other useful explorations of data series. You will learn how sampling can sometimes include data from future times, which is a problem for predictive modeling, and how to address that. At the end of the chapter, you will see how a combination of scaling (introduced in Chapter 9, Data Modeling – Preprocessing), and smoothing can show interesting similarities between different data series, which might otherwise be overlooked.
By the end of this chapter, you will be skilled at applying scaling, sampling, and smoothing in a variety of ways to your data analyses.
This chapter covers the following topics:
- Learning the modeling basics
- Predicting future values of time series ...
