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Data Wrangling with Python by Katharine Jarmul, Jacqueline Kazil

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Chapter 15. Conclusion

Congratulations! You’ve reached the end of the book. When you first began, you likely knew little Python and you hadn’t used programming to investigate data.

Your experience now should be quite different. You’ve gained knowledge and experience finding and cleaning data. You’ve honed your skills by focusing your questions and determining what you can and cannot answer given a particular dataset. You can write simple regexes and complex web scrapers. You have learned how to store and deploy your code and connect with databases. You can scale your data and processes in the cloud and manage your data wrangling via automation.

The fun doesn’t have to end here, however! There is plenty more to learn and do in your career as a data wrangler. You can take the skills and tools you have learned here and continue to push your knowledge, and in turn the boundaries of the field of data wrangling. We encourage you to advance your quest for excellence and keep asking difficult questions of your data, processes, and methods.

Duties of a Data Wrangler

As we’ve established throughout this book and our investigations, the data out there and the conclusions you can reach as a data wrangler are vast. But along with those opportunities come responsibilities.

There are no data wrangling police; however, you have learned some ethics throughout our book. You’ve learned to be a conscientious web scraper. You’ve learned to pick up the phone and ask for more information. You’ve learned ...

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