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 to explain and document your process when you present your findings. You’ve learned how to ask hard questions about difficult topics, particularly when the data sources may have other motivations.

As you pursue learning and growing as a data wrangler, your ethical sense will grow and help guide and challenge you in your work and processes. In a way, you are now an investigative journalist. The conclusions you reach and the questions you ask can and will make a difference in your field. With that knowledge, you have the burden of duty.

Your duties include:

• Using your knowledge, skills, and ability for just and good causes

• Helping contribute to the knowledge of others around you

• Giving back to the community that helped you

• Challenging opposition to the ethics you have learned so far and continue to develop

We encourage you to step up and meet these challenges through your career as a data wrangler. Do you like working with others and teaching? Become a mentor! Do you enjoy a particular open source package? Become a code or documentation contributor! Have you been researching an important social or health issue? Contribute your findings to the academic or social community! Have you experienced difficulties from a particular community or source? Share your story with the world.

Beyond Data Wrangling

Your skills have developed over the course of this book, but you still have much to learn. Depending on your skillset and interests, there are quite a few areas for further exploration.

Where Do You Go from Here?

So, where do you go now? You have a litany of new skills, and you have the ability to question both your own assumptions and the data you find. You also have a working knowledge of Python and numerous useful libraries at your fingertips.

If you don’t yet have a passion for a particular field or dataset, you’ll want to discover ways to continue your progress and advancement as a data wrangler with new fields of study. There are many great data analysts out there writing inspirational stories. Here are a few:

• FiveThirtyEight, once a blog started by Nate Silver for The New York Times, is now a site with numerous writers and analysts investigating a variety of topics. After the Ferguson grand jury decision to not indict Darren Wilson, FiveThirtyEight published an article showing the outcome was an outlier. With controversial topics, being able to show a data trend or tendency can help take some of the emotions out of the story and reveal what the data is actually saying.

• A study of income gaps by The Washington Post used tax and census data to conclude the “ol’ boy network” was still alive in terms of job acquisition and initial salaries, but usually flattened or showed no correlation after those initial jobs were acquired.

• We’ve studied some of the impacts of groups in Africa who use child labor, including for mining conflict minerals. A recent report by Amnesty International and Global Witness found most American firms are not adequately checking their supply pipelines to ensure their products do not use conflict minerals.

There are millions of untold stories in the world. If you have a passion or a belief, it’s likely your insights and data wrangling skills can help people and communities. If you don’t have a passion yet, we encourage you to keep learning by keeping up with data analysis in the news, documentaries, and online.

No matter where your interests lie, there is a wide world of possibilities available to deepen your learning and grasp of the concepts introduced in this book. Whatever sparked your interest the most is a great path for future learning. We hope this book is just a taste of what you’ll be doing throughout your career as a data wrangler.