Summary
In this chapter, we have learned about the pandas methods of data indexing and selection using a Series. We compared the Series.loc() and Series.iloc() methods for accessing items in a Series by labels and integer locations, respectively. We also used pandas shortcut methods, including bracket notation and extended indexing. We reviewed that most methods for DataFrames work similarly and intuitively for a pandas Series, and we highlighted a few key differences. After understanding indexes and how to access them, we illustrated differences between core pandas data structures such as lists and dictionaries, as well as some things to keep in mind regarding pandas and core Python.
At this point, you should be comfortable working with pandas data access as well as understand the common pitfalls and workarounds. With these tools in hand, you are ready to tackle data projects of any complexity. In the next chapter, Chapter 7, Data Transformation, you will apply some of these methods...
