In this project, we learned how to reconstruct a list of tweets based on their identification numbers. First, we located high-quality archived tweet data that conforms to Twitter's latest ToS. We learned how to split it into a set small enough for testing purposes. Then, we learned how to hydrate each tweet into a full JSON representation of itself, using the Twitter API and the twarc command-line tool. Next, we learned how to extract pieces of the JSON entities in Python, saving the fields to a new set of tables in our MySQL database. We then ran some simple queries to count the most common URLs, and we drew a bar graph using D3.

In this book, we have learned how to perform a variety of data cleaning tasks, both simple and complex. We used a variety of languages, tools, and techniques to get the job done, and along the way, I hope you were able to perfect your existing skills while learning many new ones.

At this point, our final dinner party is complete, and you are now ready to...