In this chapter, we examined how pandas makes it simple to access data in various locations and formats, providing automatic mapping of data in these formats into DataFrame objects. We started with learning how to read and write data from local files in CSV, HTML, JSON, HDF5, and Excel formats, reading into, and writing directly, from DataFrame objects without having to worry about the details of mapping the contained data into these various formats.

We then examined how to access data from remote sources. First, we saw that the functions and methods that work with local files can also read from web and cloud data sources. We then looked at pandas support for accessing various forms of web and web-service-based data, such as Yahoo! Finance and the World Bank.

Now that we are able to load the data, the next step in using that data is to perform the cleaning of the data. Often, the data that is loaded has missing information and ill-formed content. The next chapter will focus on these...