Conditioning Your Data
IN THIS CHAPTER
Working with NumPy and pandas
Working with symbolic variables
Considering the effect of dates
Fixing missing data
Slicing, combining, and modifying data elements
The characteristics, content, type, and other elements that define your data in its entirety is the data shape. The shape of your data determines the kinds of tasks you can perform with it. In order to make your data amenable to certain types of analysis, you must shape it into a different form. Think of the data as clay and you as the potter, because that’s the sort of relationship that exists. However, instead of using your hands to shape the data, you rely on functions and algorithms to perform the task. This chapter helps you understand the tools you have available to shape data and the ramifications of shaping it.
Also in this chapter, you consider the problems associated with shaping. For example, you need to know what to do when data is missing from a dataset...