Abstract: 

Pandas can be tricky, and there is a lot of bad advice floating around. This tutorial will cut through some of the biggest issues I've seen with Pandas code after working with the library for a while and writing three books on it.

We will discuss:

* Proper types
* Chaining
* Aggregation
* Debugging

Session Outline:

Are you confused or frustrated with Pandas? Or maybe your own Pandas code when you come back to it later, you find it confusing or difficult to work with.

I've taught Pandas to thousands in Corporate settings, Universities, and Virtually. I've also seen the bad code that my students write and have strong opinions on how to correct it.

This workshop assumes you want to apply idiomatic constructs to existing code. There will be some lecture and then breakout time to apply the constructs on your own:

We will cover

* Types
* Chaining
* Mutation
* Aggregation
* Debugging

Tutorial Outline
==================

* Introduction (5 min)
* Loading data & Types (40 min)
* Lab
* Chaining (45 min)
* Lab
* Mutation (5 min)
* Aggregation (40 min)
* Lab
* Debugging (45 min)
* Lab

Background Knowledge:

* Laptop with Jupyter/Pandas installed
* Python familiarity
* Jupyter familiarity
* Lambda functions
* List comprehensions

Bio: 

Matt Harrison has been using Python since 2000. He runs MetaSnake, a Python and Data Science consultancy and corporate training shop. In the past, he has worked across the domains of search, build management and testing, business intelligence, and
storage.

He has presented and taught tutorials at conferences such as Strata, SciPy, SCALE, PyCON, and OSCON as well as local user conferences.