Python Lab Proteomics Informatics, Spring 2014 Week 1 28 th Jan, 2014 Himanshu Grover

Slides:



Advertisements
Similar presentations
Guy Griffiths. General purpose interpreted programming language Widely used by scientists and programmers of all stripes Supported by many 3 rd -party.
Advertisements

Python Lab: Fundamentals Proteomics Informatics, Spring 2014 Week 3 11 th Feb, 2014
Introduction to Java Lab CS110A – Lab Section 004 Instructor: Duo Wei.
CS-2852 Data Structures LECTURE 1A Andrew J. Wozniewicz Image copyright © 2010 andyjphoto.com.
1 Programming Concepts Module Code : CMV6107 Class Contact Hours: 45 hours (Lecture 15 hours) (Laboratory/Tutorial 30 hours) Module Value: 1 Textbook:
Fall AboutMichael Fung, CS&E, The Chinese University of HK1 CSC1030 Hands-on Introduction to JAVA Dept of Computer Science and Engineering The.
A one day crash course on Python
Python Lab Pandas Library - II Proteomics Informatics, Spring 2014 Week 8 18 th Mar, 2014
EECE 310 Software Engineering Lecture 0: Course Orientation.
Python Lab: Control Statements Conditionals, Loops, Iterations Proteomics Informatics, Spring 2014 Week 4 18 th Feb, 2014
MaterialsHub - A hub for computational materials science and tools.  MaterialsHub aims to provide an online platform for computational materials science.
Scientific Computing Beyond Matlab Nov 19, 2012 Jason Su.
Python Lab Summary and Resources Proteomics Informatics, Spring 2014 Week nd Apr, 2014
Python – Part 1 Python Programming Language 1. What is Python? High-level language Interpreted – easy to test and use interactively Object-oriented Open-source.
Introduction to Information and Computer Science Computer Programming Lecture b This material (Comp4_Unit5b), was developed by Oregon Health and Science.
Pattern Recognition Software CS855 Week 1. Matlab Commercial Very fast matrix operations Many open source functions Portability limited Free Interpreted.
Integrating Open Source Statistical Packages with ArcGIS Mark V. Janikas Liang-Huan (Leo) Chin.
Python Lab Functions Proteomics Informatics, Spring 2014 Week 6 04 th Mar, 2014
Computer Science 101 Spring 2000 Section E8TBA Registration Code 1693 Dr. Christopher Vickery.
 Instructor: Dr. Jason Nichols –  Office Hours: – 9:30-10:30 M/W/F or by appointment – Business Building.
Python for: Data Science. Python  Python is an open source scripting language.  Developed by Guido Van Rossum in late 1980s  Named after Monty Python.
DATA MINING Pandas. Python Data Analysis Library A library for data analysis of (mostly) tabular data Gives capabilities similar to Excel and SQL but.
Useful Python Libraries Ghislain Prince. This presentation - Standard libraries - “batteries included” - 3 rd party libs.
Python – May 16 Recap lab Simple string tokenizing Random numbers Tomorrow: –multidimensional array (list of list) –Exceptions.
COMP 4332 Tutorial 1 Feb 16 WANG YUE Tutorial Overview & Learning Python.
Exploring Spyder: An IDE for scientific computing
COP2800 – Computer Programming Using JAVA University of Florida Department of CISE Spring 2013 Lecture 39 – Command Line Args & Recursion Webpage:
CS 161 Introduction to Computer Science I Winter, 2014: 112 Spring, 2014: 131 Summer, 2014: 132.
Dr. Sajib Datta Jan 15,  Instructor: Sajib Datta ◦ Office Location: ERB 336 ◦ Address: ◦ Web Site:
Installing CUDA, PyCUDA on Ubuntu
Python Lab Matplotlib - I Proteomics Informatics, Spring 2014 Week 9 25 th Mar, 2014
Programming 2 Intro to Java Machine code Assembly languages Fortran Basic Pascal Scheme CC++ Java LISP Smalltalk Smalltalk-80.
Extending ArcGIS with Python Clinton Dow – Geoprocessing Product Esri.
S5.40. Module Structure 30% practical tests / 70% written exam 3h lectures / week (except reading week) 3 x 2h of computer labs (solving problems practicing.
CS140 – Computer Programming 1 Course Overview First Semester – Fall /1438 – 2016/2017 CS140 - Computer Programming 11.
How to Get Started With Python
Examples Data Driven, Event Driven Typical Architecture Building Ogre
PH2150 Scientific Computing Skills
Python for data analysis Prakhar Amlathe Utah State University
CSC 222: Object-Oriented Programming
MET4750 Techniques for Earth System Modeling
Introduction to Eclipse
CSC 458– Predictive Analytics I, Fall 2017, Intro. To Python
PH2150 Scientific Computing Skills
Mark V. Janikas Marjean Pobuda
1. Open any Office 2016 app, such as Word, and create a new document.
DATA MINING Python.
MaterialsHub - A hub for computational materials science and tools.
Python for Quant Finance
LEARN WHY COMPUTERS ARE REVOLUTIONIZING BIOLOGY!
Prepared by Kimberly Sayre and Jinbo Bi
Network Visualization
EECE 310 Software Engineering
Brief Intro to Python for Statistics
CSC 458– Predictive Analytics I, Fall 2018, Intro. To Python
Segurança e auditoria de sistemas
Computer Programming 1 introduction to JAVA Lecture 1 Instructor: Ruba A. Salamah Islamic University of Gaza.
Option One Install Python via installing Anaconda:
Tutorial 1: Python, Numpy, and AWS Tutorial
Python/TensorFlow Installation
Python Crash Course CSC 576: Data Science.
Recitation #1 Tel Aviv University 2017/2018 Slava Novgorodov
Recitation #1 Tel Aviv University 2016/2017 Slava Novgorodov
University of Washington CSE 416 Spring 2019 Hongjun Wu
Matplotlib and Pandas
LING/C SC 581: Advanced Computational Linguistics
Installations for Course
Python Modules.
Installations for Course
Introduction to Python
Presentation transcript:

Python Lab Proteomics Informatics, Spring 2014 Week 1 28 th Jan, 2014 Himanshu Grover

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

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

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

Setup Anaconda – – Installs: Python env (including IPython) Several packages Eclipse (pre-requisite: Java) – PyDev (requires Java 7) – Install: – Setup Interpreter

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”

Resources Learning Python, 5 th ed. Python in a Nutshell Python for Data Analysis Official Python/Library documentation – Internet