Data Wrangling with Python

Chapter 1. Introduction to Python

Whether you are a journalist, an analyst, or a budding data scientist, you likely picked up this book because you want to learn how to analyze data programmatically, summarize your findings, and clearly communicate those findings to others. You might show your findings in a report, a graphic, or summarized statistics. Essentially, you are trying to tell a story.

Traditional storytelling or journalism often uses an individual story to paint a relatable face on overall findings or trends. In that type of storytelling, the data becomes a secondary feature. However, other storytellers, such as Christian Rudde, author of Datacylsm (Broadway Books) and one of the founders of OkCupid, argue the data itself is and should be the primary subject.

To begin, you need to identify the topic you want to explore. Perhaps you are interested in exploring communication habits of different people or societies, in which case you might start with a specific question (e.g., what are the qualities of successful information sharing among people on the Web?). Or you might be interested in historical baseball statistics and question whether they show changes in the game over time.

After you have identified your area of interest, you need to find data you can examine to explore your topic further. In the case of human behavior, you could investigate what people share on Twitter, drawing data from the Twitter API. If you want to delve into baseball history, you could use ...