Summary
In this chapter, we've learned about how to work with data in Python and tackled a housing dataset using some of the concepts we learned about in the chapter. We learned about the pandas package and how it helps us organize and prepare data. We also learned about the need to preprocess datasets, especially in very large datasets. We worked through missing and noisy data, as well as data transformation and the reduction of data. We also learned how to use visualization, creating plots for our datasets that can aid us in identifying correlations and trends.
The topics in this chapter are pretty broad, with entire books written about them. But we felt it important to share some of the capabilities of the Python programming language before moving on to the next two chapters of the book.
In the next chapters, we will focus entirely on applications, using problem scenarios and topics to share some exciting applications of Python and computational thinking in designing...