$30 off During Our Annual Pro Sale. View Details »

Juan Natera - Highlights of useR conference - LA R meetup - Sep 2014

Data Science LA
September 06, 2014
1
2.9k

Juan Natera - Highlights of useR conference - LA R meetup - Sep 2014

Data Science LA

September 06, 2014
Tweet

More Decks by Data Science LA

See All by Data Science LA
Opening the Black Box: Attempts to Understand the Results of Machine Learning Models - Michael Tiernay - LA Data Science Meetup - May 2017
datasciencela
2
1.5k
Scott Le Grand - DSSTNE - LA Data Science Meetup - Oct 2016
datasciencela
1
270
Tianqi Chen - XGBoost: Implementation Details - LA Workshop Talk
datasciencela
4
26k
Tianqi Chen - XGBoost: Overview and Latest News - LA Meetup Talk
datasciencela
9
750k
Erin LeDell - Intro to H2O Machine Learning in Python - Python Data Science LA Meetup - Jan 2016
datasciencela
1
140
Jeong-Yoon Lee - Winning Data Science Competitions - Data Science Meetup - Oct 2015
datasciencela
8
10k
Ulas Bardak, Maarten Bosma, Rohan Monga - Data Science @Whisper - LA Data Science Meetup - March 2015
datasciencela
5
1.6k
Eduardo Arino de la Rubia - Big Data is not Hadoop - LA DW/BI/Analytics Meetup - Febr 2015
datasciencela
3
900
Eric Klusman - The BI software market - LA DW/BI/Analytics Meetup - Febr 2015
datasciencela
2
940

Featured

See All Featured
Agile that works and the tools we love
rasmusluckow
320
19k
Designing with Data
zakiwarfel
91
4.1k
Producing Creativity
orderedlist
PRO
335
37k
Facilitating Awesome Meetings
lara
33
4.5k
Statistics for Hackers
jakevdp
782
210k
YesSQL, Process and Tooling at Scale
rocio
158
12k
Teambox: Starting and Learning
jrom
124
7.8k
Ruby is Unlike a Banana
tanoku
92
9.5k
Scaling GitHub
holman
453
140k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
1
310
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
120
29k
Code Review Best Practice
trishagee
48
11k

Transcript

  1. A short introduction to dplyr Juan Natera Los Angeles R

    Meetup 09/04/2014

  2. A bit about me • Software Engineer • Interested in

    R and its use for gaining insights about data • Open Source enthusiast • Baseball fanatic

  3. About dplyr • Developed by Hadley Wickham, Chief Scientist @

    Rstudio. • Part of a suite of packages meant to facilitate working on the “data pipeline”.

  4. Why? • People spend a lot of time getting data

    ready for analysis • Almost no learning curve (just need to learn 5 verbs) • Improves readability • It's FAST

  5. The data pipeline Tidy Transform Model Visualize

  6. The 5 verbs • flter: remove rows • select: choose

    columns • arrange: reorder rows • mutate: change data • summarize: guess...

  7. No learning curve, how? • First parameter is always a

    data.frame • Other parameters describe what you want to do with it. • Always returns a new data.frame

  8. It's Fast

  9. Let's see some code!

  10. A great book I picked up at useR 2014

  11. Questions or Comments? naterajj@gmail.com