Difference between revisions of "Using R to improve data analyses Python workflows"

From Gridkaschool
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You can also setup the software environment on your own computer.
  
You can also setup the software environment on your own computer.
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=== Minimum Requirement ===
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* Current web browser, such as Firefox, Chrome or Safari.
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** You will receive a server address and password at the start of the course.
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=== Running the Course on your own Computer ===
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'''We have only tested the course on Linux and OSX! Installation on Windows may differ!'''
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=== Required Software ===
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* Python3 (>= 3.4) - A sufficiently recent release of Python
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** Commonly available via package managers such as <code>apt-get install python3</code> or <code>brew install python3</code>.
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** Also available from the [https://www.python.org/downloads/ Python Homepage]
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* Python3 pip - Python Package Manager
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** Several package managers do not install the python package manger
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** It will be available as a separate package in this case, e.g. <code>apt-get install python3-pip</code>.
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* Jupyter - Evaluates and renders the notebooks
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** Available via pip: <code>pip3 install jupyter</code>
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* RISE ('''optional''') - provides the interactive presentation view
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** Consult the [https://github.com/damianavila/RISE/blob/master/README.md RISE Readme]
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** Available via pip: <code>pip3 install RISE && jupyter-nbextension install rise --py --sys-prefix && jupyter-nbextension enable rise --py --sys-prefix</code>
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==== Setting up the Environment ====
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* Check out the exercise repositories <code>https://bitbucket.org/teamkseta/gks_2016_pyr.git</code> and <code>https://bitbucket.org/teamkseta/gks_2016_python.git</code>.
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* Set PYTHONPATH to include the <code>gks_2016_pyr</code> directory.
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* Change to the <code> gks_2016_python</code> directory and run the notebook server.
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<code>
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GKSDIR='~/gks2016' # change me
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git clone https://bitbucket.org/teamkseta/gks_2016_pyr.git $GKSDIR/gks_lib
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git clone https://bitbucket.org/teamkseta/gks_2016_python.git $GKSDIR/gks_2016_python
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export PYTHONPATH="$GKSDIR/gks_lib:$PYTHONPATH"
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jupyter-notebook
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</code>

Revision as of 07:07, 29 August 2016

Using R to improve data analyses Python workflows

Software Environment

The courses are implemented as Jupyter/IPython notebooks, running Python and R. We provide a VM with preconfigured Jupyter Notebook Server for each student.

You can also setup the software environment on your own computer.

Minimum Requirement

  • Current web browser, such as Firefox, Chrome or Safari.
    • You will receive a server address and password at the start of the course.

Running the Course on your own Computer

We have only tested the course on Linux and OSX! Installation on Windows may differ!

Required Software

  • Python3 (>= 3.4) - A sufficiently recent release of Python
    • Commonly available via package managers such as apt-get install python3 or brew install python3.
    • Also available from the Python Homepage
  • Python3 pip - Python Package Manager
    • Several package managers do not install the python package manger
    • It will be available as a separate package in this case, e.g. apt-get install python3-pip.
  • Jupyter - Evaluates and renders the notebooks
    • Available via pip: pip3 install jupyter
  • RISE (optional) - provides the interactive presentation view
    • Consult the RISE Readme
    • Available via pip: pip3 install RISE && jupyter-nbextension install rise --py --sys-prefix && jupyter-nbextension enable rise --py --sys-prefix

Setting up the Environment

GKSDIR='~/gks2016' # change me

git clone https://bitbucket.org/teamkseta/gks_2016_pyr.git $GKSDIR/gks_lib

git clone https://bitbucket.org/teamkseta/gks_2016_python.git $GKSDIR/gks_2016_python

export PYTHONPATH="$GKSDIR/gks_lib:$PYTHONPATH"

jupyter-notebook

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