The 2017 hurricane season is proving to be one of the strongest in history, and predictive modeling plays an important role in evacuation and mitigation planning. Coastal communities in the path of hurricanes face several major hazards - strong winds, heavy rainfall, relentless waves, and storm surge. Storm surge is a type of transient sea level rise where water is forced towards the shore by winds, and the right conditions can produce very high levels - Hurricane Harvey raised Galveston Bay by upwards of ten feet, and in 2012 Hurricane Sandy produced 12-foot surge in Lower Manhattan. I'll discuss the current state of storm surge modeling with focus on an open-source package called GeoClaw, developed by academic researchers across the U.S. GeoClaw uses Python and Fortran to run a dynamic simulation of coastal flooding using storm and topography datasets, and thanks to some novel dimensionality reduction it can be run on a laptop.

Selenium is an excellent package that lets you dynamically interact with websites right from your Jupyter Notebook. At Metis, we teach Selenium early in our bootcamp. We have a great Selenium tutorial that involves lets you make a reservation on OpenTable using Python. In addition, several students have already completed excellent projects using Selenium. During this talk, Seth Weidman, a Senior Data Science Instructor at Metis, as well as the following two current Metis students [TO BE DETERMINED] will be presenting the projects that they just completed.

Description: a pythonic tour of time series methodologies and packages, including ARIMA, seasonal models, and Markov approaches. Intermediate level with basic statistics and time data familiarity required. Bio: Jonathan Balaban is a senior data scientist, strategy consultant, and entrepreneur with ten years of private, public, and philanthropic experience. He currently teaches business professionals and leaders the art of impact-focused, practical data science at Metis.

I've been doing a bunch of analysis on the recent FCC public comments in Python (https://medium.com/@csinchok/an-analysis-of-the-anti-title-ii-bots-463f184829bc). Due to this work, I was quoted in Gizmodo, Ars Technica, and the BBC. I'd like to talk about how I approached this problem, how Python helped make sense of my findings, and what my conclusions are.

Have you ever tried to make something with scrap wood, and wondered how to use it optimally? Do have a bunch of pickles and jams you made, and you want to eat them in an order that maximizes variety? These are real problems a co-worker of mine had, and we used Python to solve them. I'll show the data we started with, the solutions we came up with, and a bit of the computer science behind them. See some examples of how to think through problems and design your own algorithms to solve them.

We've all used context managers provided by the Python Standard Library to read from/write to a file. Have you ever wondered what was happening underneath the hood when you used a with statement? This talk will explore context managers, discuss various use cases, and show you how to implement a context manager to manage MongoDB connections.

Brian will show how to use flask and Python to power a browser based HTML5 game over sockets. Events can be pushed to the browser or pushed to flask from the browser. Great starter for those who are interested in event driven programming.

This is a talk about creating pictures of a mathematical object---specifically, a 4-dimensional fractal "dust" that has been the subject of mathematical research in hyperbolic geometry since the 1980s. In the end this is accomplished using a little algebra, a little geometry, and a healthy dose of Python. That is, I will present a case study of using Python in several aspects of a mathematical visualization project, from the computation itself, to transforming and converting data, and finally for scripting the process of generating the images. Along the way I'll explain how Python's convenient idioms and containers (e.g. sets and set comprehensions) are a good fit for some of the algebraic and geometric questions that come up, how Scipy and Numpy enable fast numerical calculations, and how Python's strength as a language for scripting and automation allows easy orchestration of rendering of still images and frames of animations. The mathematical visualization project we describe is a collaboration with François Guéritaud (Université de Lille).

In-browser encryption is more important now than ever. When building modern web-apps, encryption is a necessity. This talk will detail how you can secure your Python-based projects with Letsencrypt, a free certificate authority available to anyone. It will cover the Python-based tools available to configure Letsencrypt and an example project utilizing it.

You are the data troll who allows what data can be pushed up. All data requests are in your hands but first you need to become an official data troll by getting your information in the data troll table (you need to be legit in the database or else it didn't happen). This is a super simple example of how Python can be friends with database, today we’ll look at Postgres!