What’s Next?

We did our analysis, we have our visualization of the data, and our code is cleaned up and streamlined. All’s well and good with the world.

So are we done?

Absolutely Not

Stuffing data into a visualization is only part of the job, and it’s where we’ll stop today. However, the true meat of data analysis comes in the interpretation! You’ve done all this work now, what have you learned from this data? What trends can you discern? Write about them in your Jupyter notebook, right beneath your figures!

Once you’ve gotten all your ideas fleshed out and justified by the data, commit it to GitHub and share it with the world!

Glad That’s All Over

If you found this run-through overwhelming yet interesting, please consider signing up for our full Code 501: Introduction to Data Analysis and Visualization with Python course. It’s a week-long full time workshop detailing such methods as these, as well as other aspects of the data analysis process. By its end, you’ll have the skills to produce your OWN data project!