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Python Lab

Python Lab. Proteomics Informatics, Spring 2014 Week 1 28 th Jan, 2014 Himanshu Grover ( Himanshu.Grover@nyumc.org ). Administrivia. Last 45 mins of each class Ppt and code snippets will be uploaded along with course lectures Open cube office hours

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Python Lab

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  1. Python Lab Proteomics Informatics, Spring 2014 Week 1 28th Jan, 2014 Himanshu Grover (Himanshu.Grover@nyumc.org)

  2. Administrivia • Last 45 mins of each class • Ppt and code snippets will be uploaded along with course lectures • Open cube office hours • discuss doubts, code, projects, whatever remotely pythonic

  3. Goals • Develop core (python) programming skills • Programming best-practices along the way • Hands-on with libraries in the Python data analytics ecosystem • Pandas • Matplotlib • Numpy/Scipy • Other libraries (as needed) • Some “must have” tools in a programmer’s toolbox: • (Integrated) Development environment (Eclipse/Pydev, IPython) • Code debuggers • Package management

  4. Structure • Week 2 & 3: Core Python • Data types and structures • Expressions, Statements, Loops • Functions and modules, file handling • Week 4 – end: • Code examples for computational proteomics • Assignments with skeletal structure

  5. Setup • Anaconda • http://docs.continuum.io/conda/index.html • Installs: • Python env(including IPython) • Several packages • Eclipse (pre-requisite: Java) • http://www.eclipse.org/downloads/ • PyDev (requires Java 7) • Install: http://pydev.org/manual_101_install.html • Setup Interpreter

  6. Checks!! • conda/pip (update) • > ipython; • > conda • > pip -V • Ipython > print “all is well” > import numpy, scipy, matplotlib, pandas • Eclipse • Create a python project • Create a python file • print “all is well”

  7. Resources • http://docs.python.org/2/tutorial/ • Learning Python, 5th ed. • Python in a Nutshell • Python for Data Analysis • Official Python/Library documentation • http://www.python.org/doc/ • Internet 

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