R NYC Conference

Norfolk data science
@josibake

What is R NYC?

• Annual R conference hosted by
  • Lander Analytics - Author of "R for Everyone"
  • WorkBench - Enterprise focused venture capital fund
  • Also run the R NYC meetup

What was I doing there??

• Great price!
• Great speakers
• And of course..

Speakers

Speakers I was going to see:

• Wes McKinney - Pandas author
• Andrew Gelman - Statistician
• David Robinson - Data scientist, StackOverflow
• Dan Whitenack - Data scientist, Pachyderm
• Ricardo Bion - Data science manager, Airbnb

Speakers I enjoyed most

• JD Long - Agricultural economist
• Friederike Schüür - Research scientist, Fast Forward Labs
• Sandy Griffith - Data scientist, Flatiron Health

Where is R being used?

• Facebook - you know..
• JetBlue
• Bidalgo
• ATT Bell labs
• StackOverflow

Things that were R

• Get to know the R-Studio IDE
• Enabling productivity by moving from Excel to R
• Notabale R packages
  • rthreejs
  • tidytext

Things that were data science

• Having Empathy (JD Long)
  • Understanding the near vs the far
  • Effectively communicating with a human audience
  • Practicing active listening
• Systematizing our process (Andrew Gelman)
  • Studying and formalizing our process
• Data science and the agile process (Friederike Schüür)
  • Tension between software development and data science
  • Discovery vs creating
  • Staying in tune with the needs of the business

How to's

• Setting up a data science workspace

  • git
  • bash
  • project templates
  • make

• How to contribute to Open Source and why

  • Data science is community driven
  • It's what employers are looking for
  • Contributing to the docs is still contributing!
  • Create reproducible bug reports
• How to tweet a conference
  • @ the conference or speaker
  • Use the #hashtag
  • Photos!

Things that weren't R at all

• Upcoming security legislation on data
  • Your data is yours and subject to the same rights
  • How to better anonymize data
• Wes McKinney!
  • Apache Arrow
  • Interoperable dataframes
  • Zero-copy in memory data structures

My observations

• R is a close "Knitr" community
• R users like to drink
• Very humanitarian focused
• Less focus on technology and infrastructure
• Very hands on

Takeaways

• Go to conferences!
• Get involved with open source
  • Write your own packages!
  • Contriute to packages you use
• R, Python, data science etc, don't have to be your day job for you to get involved

Questions