Wednesday 1:20 p.m.–4:40 p.m. in Room 9
Analyzing Census Data with Pandas
### Census 2020 is coming! Did you know the government budgeted __12.5 billion__ dollars to count __EVERY SINGLE PERSON IN THE COUNTRY__ in 2020? Imagine how much data you could acquire with 12.5 billion dollars. ### Not so excited about Census data? How about cool `pandas` tricks? ![pandas_gif](https://media1.tenor.com/images/60379b3ecd5b8d9d886d90018dba63ab/tenor.gif?itemid=5274556) In this tutorial you will go from a simple data exploration and analysis workflow to learning more advanced techniques social scientists apply when dealing with Census data. If you've been interested in honing your `pandas` skills or you'd just ___love___ to learn how to calculate the demographically-adjusted employment rate gap for your county using `python`, well you've come to the right place. This tutorial is perfect for novice data analysts, pythonistas, social scientists, and journalists that want to learn about the powerful `pandas` library and how to use it to analyze public use micro-data, and for those who've been using it but could learn a trick or two to make their workflow even more effective. Does the acronyms ACS, CPS, PUMA, or IPUMS mean anything to you? If not, the more reason to join! Come learn something new!
No handouts have been provided yet for this tutorial