Summary

In this chapter, we learned how to use pandas for the data collection portion of data analysis and to describe our data with statistics, which will be helpful when we get to the drawing conclusions phase. We learned the main data structures of the pandas library, along with some of the operations we can perform on them. Next, we learned how to create DataFrame objects from a variety of sources, including flat files and API requests. Using earthquake data, we discussed how to summarize our data and calculate statistics from it. Subsequently, we addressed how to take subsets of data via selection, slicing, indexing, and filtering. Finally, we practiced adding and removing both columns and rows from our dataframe.

These tasks also form the backbone of our pandas workflow and the foundation for the new topics we will cover in the next few chapters on data wrangling, aggregation, and data visualization. Be sure to complete the exercises provided in the next section before moving...