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OPEN DATA SCIENCE WITH R
Make Life Easier & More Powerful with Anaconda
Christine Doig, Senior Data Scientist
2
Christine Doig is a Senior Data Scientist at Continuum
Analytics, where she worked on MEMEX, a DARPA-funded
project help...
3
• Introduction to Open Data Science
• Introduction to Anaconda, the leading Open Data Science platform
• Package and env...
OPEN DATA SCIENCE
Introduction to
“ ”
© 2015 Continuum Analytics- Confidential & Proprietary 5
An interdisciplinary field about
processes and systems to ext...
© 2015 Continuum Analytics- Confidential & Proprietary
Open Data Science is …
an inclusive movement
that makes open source...
© 2015 Continuum Analytics- Confidential & Proprietary
Open Source ecosystems for Data Science
7
NumPy SciPy
Pandas Scikit...
ANACONDA
Introduction to
© 2015 Continuum Analytics- Confidential & Proprietary 9
is….
the leading Open Data Science platform
powered by Python the...
10
Why Anaconda?
• Easy to install on all platforms
• Trusted by industry leaders: e.g.
Microsoft Azure ML
• Large user ba...
11
Anaconda Glossary
PYTHON
NumPy, SciPy, Pandas, Scikit-learn, Jupyter /
IPython, Numba, Matplotlib, Spyder, Numexpr,
Cyt...
PACKAGE AND ENVIRONMENT
MANAGEMENT FOR R
13
From http://www.slideshare.net/RevolutionAnalytics/r-at-microsoft
An R Reproducibility Problem
14
Reproducibility
• Programming language (R, Python, Scala…)
• Packages (OSS libraries or internally developed)
• Data or...
15
Reproducibility solutions
Bare metal
Virtual Machines
Docker containers
Conda environments
Your Analysis
or Application...
16
Conda Environments
• Programming language (R, Python, Scala…)
• Packages (OSS libraries or internally developed)
• Data...
17
lightweight isolated sandbox to manage your dependencies
and allow reproducibility of your project
environment.yml
$ co...
18
Where packages, notebooks, and environments are shared.
Powerful collaboration and package management for open source a...
19
Anaconda for R
https://www.continuum.io/blog/developer/jupyter-and-conda-r
• R-Essentials: A conda
metapackage with 80+...
20
• Package and environment manager
• Language angnostic (Python, R, Java…)
• Cross-platform (Windows, OS X, Linux)
$ con...
21
name: myenv
channels:
- chdoig
- r
- foo
dependecies:
- python=2.7
- r
- r-ldavis
- pandas
- mongodb
- spark=1.5
- pip
...
22
FAQ
• R-Essentials has too many / too few / not the packages I
want, how can I create my own “R-Essentials”?
• I need a...
23
Anaconda: Navigator
• Launch applications and easily
manage conda packages,
environments and channels.
• No need of usi...
24
Anaconda Repository
• Centralized internal repository
to share package, environments
and notebooks.
• Control user or t...
DATA SCIENCE COLLABORATION
WITH R
© 2015 Continuum Analytics- Confidential & Proprietary
Data Science Development Environments
26
PyCharm Spyder
Text Editor...
27
http://jupyter.org/
https://try.jupyter.org/
The Jupyter Notebook is a web application that allows you to create
and sh...
28
IPython IPython
notebook
nbviewer tmpnb binderJupyter
https://try.jupyter.org/
http://mybinder.org/
Jupyter
29
Jupyter: IRkernel
https://www.continuum.io/blog/developer/jupyter-and-conda-r
conda config --add channels r
conda insta...
30
To start jupyter notebooks, simply run the following command:
$ jupyter notebook
http://nbviewer.ipython.org/github/chd...
31
Jupyter
32
Jupyter
33
$ jupyter nbconvert my_r_notebook.ipynb --to slides --post serve
Jupyter
DEMO 1:
ENVIRONMENTS & REPOSITORY
35
Moving your team to collaborate with each other
with Anaconda Enterprise Notebooks
Data Scientist
Interactive notebooks...
36
Anaconda Enterprise Notebooks
• Collaborate with your team on
the same project
• Notebooks enterprise
extensions: diff,...
DEMO 2: NOTEBOOKS AND AEN
SCALING R
39
Scalability
Data Scientists want:
• Easy cluster setup and provisioning ->
Anaconda for cluster management
• Distribute...
40
Anaconda for cluster management
• Dynamically manage conda environments
across a cluster
• Works with enterprise Hadoop...
41
Anaconda for cluster management
Before Anaconda
for cluster management
Head Node
1. Manually install Python,
packages &...
42
SparkR
• Distributed framework for large
scale processing
• Provides an R interface through
SparkR
DEMO 3: ANACONDA FOR CLUSTER
MANAGEMENT AND SPARKR
44
https://www.continuum.io/anaconda-subscriptions
45https://www.continuum.io/anaconda-subscriptions
46
• Need a centralized repository to publish and share notebooks,
environments and packages (OSS and private)? Get Anacon...
47
• Download Anaconda: https://www.continuum.io/downloads
• Sign up for Anaconda cloud: https://anaconda.org
• Contact sa...
48
Email: sales@continuum.io
Twitter: @ContinuumIO
Christine Doig
Twitter: @ch_doig
Thank you!
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Open Data Science with R and Anaconda

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Make Life Easier & More Powerful with Anaconda
Easily Manage, Collaborate & Scale Out Your Data Science on Hadoop

R is a powerful Open Data Science language, adored by statisticians, analysts and data scientists across the globe.

But managing packages and dependencies in R is frustrating. Making other people's R code work is a time-consuming challenge that prevents you and your colleagues from collaborating. Most importantly, these challenges stop your organization from reproducing and benefiting from the insights your analysis has uncovered.

We're here to help. Anaconda makes package, dependency and environment management with R, as well as other Open Data Science languages, easy. Now your code works on everyone's machine, and Anaconda Enterprise Notebooks make team collaboration effortless while giving both data scientists and analysts a powerful interface to share the entire data science narrative, including analysis and interactive visualizations.

Once your analysis is complete and you're ready to scale out, Anaconda for Cluster Management makes installation and ongoing package management on your Hadoop cluster simple and as easy as working locally, while your analysis benefits from the scalability of distributed computing.

On April 27th, Continuum Analytics Senior Data Scientist Christine Doig will host a webinar on using Anaconda with R.

You'll learn to:
-Manage R packages, dependencies and environments with ease using conda and R-Essentials
-Collaborate across your data science team with Enterprise Notebooks for R
-Scale out across hundreds of nodes with Anaconda for Cluster Management and SparkR

Published in: Data & Analytics
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Open Data Science with R and Anaconda

  1. 1. OPEN DATA SCIENCE WITH R Make Life Easier & More Powerful with Anaconda Christine Doig, Senior Data Scientist
  2. 2. 2 Christine Doig is a Senior Data Scientist at Continuum Analytics, where she worked on MEMEX, a DARPA-funded project helping stop human trafficking. She has 5+ years of experience in analytics, operations research, and machine learning in a variety of industries, including energy, manufacturing, and banking. Christine holds a M.S. in Industrial Engineering from the Polytechnic University of Catalonia in Barcelona. She is an open source advocate and has spoken at many conferences, including PyData, EuroPython, SciPy and PyCon. About me Christine Doig
 Senior Data Scientist Continuum Analytics
  3. 3. 3 • Introduction to Open Data Science • Introduction to Anaconda, the leading Open Data Science platform • Package and environment management for R – conda, R-Essentials and MRO • Data Science Collaboration in R – Jupyter notebooks for R and Anaconda Enterprise Notebooks • Scaling R – Anaconda for cluster management and SparkR Agenda - Open Data Science with R
  4. 4. OPEN DATA SCIENCE Introduction to
  5. 5. “ ” © 2015 Continuum Analytics- Confidential & Proprietary 5 An interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms Wikipedia Data Science is …
  6. 6. © 2015 Continuum Analytics- Confidential & Proprietary Open Data Science is … an inclusive movement that makes open source tools of data science - data, analytics, & computation - easily work together as a connected ecosystem 6
  7. 7. © 2015 Continuum Analytics- Confidential & Proprietary Open Source ecosystems for Data Science 7 NumPy SciPy Pandas Scikit-learn Jupyter/IPython dplyr shiny tidyr ggplot Spark tidyr
  8. 8. ANACONDA Introduction to
  9. 9. © 2015 Continuum Analytics- Confidential & Proprietary 9 is…. the leading Open Data Science platform powered by Python the fastest growing Open Data Science language • Accelerate Time-to-Value • Connect Data, Analytics, & Compute • Empower Data Science Teams
  10. 10. 10 Why Anaconda? • Easy to install on all platforms • Trusted by industry leaders: e.g. Microsoft Azure ML • Large user base: 3M+ downloads • BSD license • Extensible - easily build, share and install proprietary libraries with Anaconda Cloud • Language agnostic - Python, R, Scala… • Allows isolated custom sandboxes with different versions of packages Why Anaconda?
  11. 11. 11 Anaconda Glossary PYTHON NumPy, SciPy, Pandas, Scikit-learn, Jupyter / IPython, Numba, Matplotlib, Spyder, Numexpr, Cython, Theano, Scikit-image, NLTK, NetworkX and 150+ packages conda PYTHON cond conda • Anaconda distribution: Python distribution that includes 150+ packages for data science • conda: Cross-platform and language agnostic package and environment manager • Miniconda: Lightweight version of Anaconda, with just Python and conda. • Anaconda Cloud: Cloud service to host and share public and private packages, environments and notebooks • conda environments: custom isolated sandboxes to easily reproduce and share data science projects
  12. 12. PACKAGE AND ENVIRONMENT MANAGEMENT FOR R
  13. 13. 13 From http://www.slideshare.net/RevolutionAnalytics/r-at-microsoft An R Reproducibility Problem
  14. 14. 14 Reproducibility • Programming language (R, Python, Scala…) • Packages (OSS libraries or internally developed) • Data or Access to data • Configuration of Services: DBs, keys… • Your Analysis - Script, Notebook
  15. 15. 15 Reproducibility solutions Bare metal Virtual Machines Docker containers Conda environments Your Analysis or Application Your laptop, server, EC2 instance Env 1 Env 2 Env 3 Analysis 1 Analysis 2 Analysis 3
  16. 16. 16 Conda Environments • Programming language (R, Python, Scala…) • Packages (OSS libraries or internally developed) • Data or Access to data • Configuration of Services: DBs, keys… • Your Analysis - Script, Notebook
  17. 17. 17 lightweight isolated sandbox to manage your dependencies and allow reproducibility of your project environment.yml $ conda env create $ source activate ENV_NAME Conda Environments
  18. 18. 18 Where packages, notebooks, and environments are shared. Powerful collaboration and package management for open source and private projects. Public projects and notebooks are always free. REGISTER TODAY! ANACONDA.ORG
  19. 19. 19 Anaconda for R https://www.continuum.io/blog/developer/jupyter-and-conda-r • R-Essentials: A conda metapackage with 80+ R packages for data science • MRO: Microsoft R Open distribution with MKL conda config --add channels r conda install r-essentials conda config --add channels mro conda install r
  20. 20. 20 • Package and environment manager • Language angnostic (Python, R, Java…) • Cross-platform (Windows, OS X, Linux) $ conda install python=2.7 $ conda install pandas $ conda install -c r r $ conda install mongodb Conda
  21. 21. 21 name: myenv channels: - chdoig - r - foo dependecies: - python=2.7 - r - r-ldavis - pandas - mongodb - spark=1.5 - pip - pip: - flask-migrate - bar=1.4 environment.yml $ conda env create $ source activate myenv $ conda env export -n freeze.yml Create and activate Freeze versions Upload to anaconda.org $ conda server upload my_foo_env.yml $ conda env create chdoig/my_foo_env.yml Conda environments flow example
  22. 22. 22 FAQ • R-Essentials has too many / too few / not the packages I want, how can I create my own “R-Essentials”? • I need an R package that is not on R-Essentials or the R channel, but is available through CRAN, how do I get it? $ conda skeleton cran ldavis $ conda build r-ldavis/ $ conda server upload r-ldavis $ conda install -c chdoig r-ldavis $ conda metapackage custom-r-bundle 0.1.0 --dependencies r-irkernel jupyter r-ggplot2 r-dplyr --summary "My custom R bundle”
  23. 23. 23 Anaconda: Navigator • Launch applications and easily manage conda packages, environments and channels. • No need of using the command line. •Available for Windows, OS X and Linux. • Anaconda Navigator has replaced Launcher. • Integration with Anaconda Cloud. A desktop graphical user interface included in Anaconda
  24. 24. 24 Anaconda Repository • Centralized internal repository to share package, environments and notebooks. • Control user or team access to packages, environments and notebooks • Blacklist packages in your organization (e.g. GPL licenses) • Internal mirror Anaconda • Build and easily share internal developed software
  25. 25. DATA SCIENCE COLLABORATION WITH R
  26. 26. © 2015 Continuum Analytics- Confidential & Proprietary Data Science Development Environments 26 PyCharm Spyder Text Editors: Sublime, vim, emacs… RStudio Eclipse
  27. 27. 27 http://jupyter.org/ https://try.jupyter.org/ The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Jupyter
  28. 28. 28 IPython IPython notebook nbviewer tmpnb binderJupyter https://try.jupyter.org/ http://mybinder.org/ Jupyter
  29. 29. 29 Jupyter: IRkernel https://www.continuum.io/blog/developer/jupyter-and-conda-r conda config --add channels r conda install r-essentials jupyter notebooks Trivial to get started writing R notebooks the same way you write Python ones.
  30. 30. 30 To start jupyter notebooks, simply run the following command: $ jupyter notebook http://nbviewer.ipython.org/github/chdoig/conda-jupyter-irkernel/blob/master/Jupyter%20and%20conda%20for%20R.ipynb Jupyter
  31. 31. 31 Jupyter
  32. 32. 32 Jupyter
  33. 33. 33 $ jupyter nbconvert my_r_notebook.ipynb --to slides --post serve Jupyter
  34. 34. DEMO 1: ENVIRONMENTS & REPOSITORY
  35. 35. 35 Moving your team to collaborate with each other with Anaconda Enterprise Notebooks Data Scientist Interactive notebooks Models Data apps & visualizations Data Scientist Data Scientist
  36. 36. 36 Anaconda Enterprise Notebooks • Collaborate with your team on the same project • Notebooks enterprise extensions: diff, collaborative locking • Manage collaborators and access to projects • Search and tag notebooks
  37. 37. DEMO 2: NOTEBOOKS AND AEN
  38. 38. SCALING R
  39. 39. 39 Scalability Data Scientists want: • Easy cluster setup and provisioning -> Anaconda for cluster management • Distributed framework to scale analysis -> SparkR
  40. 40. 40 Anaconda for cluster management • Dynamically manage conda environments across a cluster • Works with enterprise Hadoop distributions and HPC clusters • Integrates with on-premises Anaconda repository • Cluster management features are available with Anaconda subscriptions Client Machine Compute Node Compute Node Compute Node Head Node
  41. 41. 41 Anaconda for cluster management Before Anaconda for cluster management Head Node 1. Manually install Python, packages & dependencies 2. Manually install R, packages & dependencies After Anaconda for cluster management Compute Nodes 1. Manually install Python, packages & dependencies 2. Manually install R, packages & dependencies Compute Nodes Head Node Easily install conda environments and packages (including Python and R) across cluster nodes • Empower IT with scalable and supported Anaconda deployments • Fast, secure and scalable Python & R package management on tens or thousands of nodes • Backed by an enterprise configuration management system • Scalable Anaconda deployments tested in enterprise Hadoop and HPC environments
  42. 42. 42 SparkR • Distributed framework for large scale processing • Provides an R interface through SparkR
  43. 43. DEMO 3: ANACONDA FOR CLUSTER MANAGEMENT AND SPARKR
  44. 44. 44 https://www.continuum.io/anaconda-subscriptions
  45. 45. 45https://www.continuum.io/anaconda-subscriptions
  46. 46. 46 • Need a centralized repository to publish and share notebooks, environments and packages (OSS and private)? Get Anaconda Repository! (Available in Anaconda Workgroups and Enterprise) • Need a centralized server to help your data science team interactively collaborate on projects? Get Anaconda Enterprise Notebooks! (Available Enterprise) • Need a “data scientist friendly” cluster manager? Get Anaconda for cluster management! (Available in Anaconda Workgroups and Enterprise) Enterprise Product Solutions
  47. 47. 47 • Download Anaconda: https://www.continuum.io/downloads • Sign up for Anaconda cloud: https://anaconda.org • Contact sales@continuum.io for more information about
 Anaconda subscriptions, consulting, or training Contact Information and Additional Details
  48. 48. 48 Email: sales@continuum.io Twitter: @ContinuumIO Christine Doig Twitter: @ch_doig Thank you!

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