Chapter 3: Preparing Data for Time Series Analysis
In this chapter, we will introduce the common first steps in a time series analysis project. We will explore different sources of time series data and show you how to clean the raw data through equal spacing, missing value imputation, and time aggregation.
After preparing the data using these steps, we can proceed with visualization, descriptive analysis, and modeling of time series data.
Additionally, we will introduce preprocessing techniques in the upcoming sections:
- Introducing different sources of time series data
- Time granularity and time aggregation
- Equal spacing and time alignment
- Missing value imputation
You will learn about the common first steps of almost all time series applications. Also, you will learn about the different techniques used at each preprocessing step and gain an understanding of how to select the best approach for your data and application. Finally, you will also learn how...
