Founded by Josh Reich and Drew Conway, the New York Open Statistical Programming Meetup started as the New York R Meetup with a handful of people in an office at Union Square Ventures. Since then it has grown to over 8,000 members and has been hosted at NYU, Columbia, AOL, iHeartRadio, eBay, Work-Bench and other locations.

Our mission is to spread knowledge of statistical programming techniques in open-source languages such as R, Python, Julia and Go, and data science in general. Another important aspect is community building and socializing. The meetups start with pizza, followed by a 45-90 minute talk, ending with a trip to the local bar.

Attending

To attend please visit the meetup page.

Presentations and Videos

Whenever possible we make presentations available at the Presentations page.

We now stream and host videos of meetups on Facebook and YouTube and older videos are scattered on a variety of services. They are also listed on the Presentations page.

Jobs

Job openings and other announcements are on the meetup discussion board.

Upcoming Meetup

Feature-Based Time Series Analysis

June 21, 2018 06:30:00 PM

We have Rob Hyndman, author of the forecast package, coming to us all the from Australia.

If you want to learn more about forecasting from Rob, he's teaching a three-day workshop (http://bit.ly/2wMsua4) the following week.

Thank you to eBay for hosting both the meetup and the workshop.

About the Talk:

It is becoming increasingly common for organizations to collect very large amounts of data over time. Data visualization is essential for exploring and understanding structures and patterns, and to identify unusual observations. However, the sheer quantity of data available means that new time series visualisation methods are needed.

I will demonstrate an approach to this problem using a vector of features on each time series, measuring characteristics of the series. These feature vectors can then be mapped to a 2-dimensional space for visualization.

The feature-based approach to time series can also be used to identify the best forecasting model using a pre-trained classifier, and to identify anomalous time series within a collection of time series.

I will demonstrate how to do feature-based time series analysis using the tsfeatures, seer, stray and oddstream packages for R.

About Rob:

Rob J Hyndman is Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University. He is also Editor-in-Chief of the International Journal of Forecasting and a Director of the International Institute of Forecasters. Rob is the author of over 150 research papers and 5 books in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. For over 30 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations around the world. He has won awards for his research, teaching, consulting and graduate supervision.

Pizza (nyhackr.org/pizzapoll.html) begins at 6:30, the talk starts at 7, then after we head to the local bar.

Website

The nyhackr website was built as a RMarkdown website and the source code can accessed by the community on GitHub.

How to contribute

If you wish to contribute to the website the process is pretty simple.

  1. Fork and clone the repository (an example can be found here)
  2. Create a new branch for your changes (warning, this step cannot be done in RStudio!)
  3. Make your changes. You can build and view your local version by using rmarkdown::render_site()
  4. When you are done, submit a pull request. Your changes might not appear on the public site right away as we have a development version for making sure changes don’t break the site.