Why Python?

• It’s free, well-documented, and runs almost everywhere
• Large (and growing) user base among researchers and scientists
• Simple, readable, flexible, powerful language and easier for beginners to grasp
• Goal is to teach basic programming concepts that can be applied to other programming languages

Why Python?

• Part of the winning formula for productivity, software quality, and maintainability at many institutions and companies across the world
• Largely being used across various application domains:
  • Scientific (Bioinformatics, Biology, Computational chemistry, Data visualisation, Scientific programming etc..)
  • Engineering
  • Software development
  • Arts, business, education and government sectors

Why Python?

• Used for development on the web and the client
• Increased productivity:
  • Debugging Python programs is easy: a bad input or bug will show a meaningful error message.

Python is up and coming!

• Based on Southampton PhD students software usage survey conducted by SSI’s Policy researchers:

We’ll be teaching Python3

• Python is currently transitioning from version 2 to 3
• Teaching will be in 3.4
• Lots of new features of Python3
  • Advanced unpacking
  • Matrix multiplication
  • Chained exceptions
  • Everything is an iterator …

Learning objectives

• how to assign values to variables and perform simple operations: python basics
• how to repeat actions with loops
• how to correctly evaluate expressions: making choices using conditionals
• why we should divide programs into small, single-purpose blocks of code: creating functions
• how to build a program, step by step, to do basic analysis on some climate data
• how to read and analyse patient data using libraries
• how to visualise data using libraries

Turning on Python Interpreter

• The interpreter provides an interactive environment to play with the language
• Open a terminal window and type python3.4
  
• If on windows open Git Bash (covered in Shell session)
• At the prompt type ‘hello world!’

Python Overview

From Learning Python:

• Programs are composed of modules
• Modules contain statements
• Statements contain expressions
• Expressions create and process objects

Basics: Variables, Objects, types and Data Structures

• Introduction to Python variables
• Creating and assigning values to variables
• Everything in Python is really an object
• Types: Built-in types and type handling
  • Built-in: String, integers, boolean and floating point
  • type(val) returns the type of a variable (also classes)
    
  • int(val[,base]) converts to an integer (of base base)
  • float(val): Corresponding to floats
  • str(val): Corresponding to strings (classes allow this automatically)

Python Control Flow

• Real power of programs come from:
  • Repetition
  • Selection

Control Flow: Repeating actions with loops

• What a loop does?
• Writing loops to repeat simple calculations
  • Indexing/ Counting starts from 0
• Track changes to a loop variable as the loop runs
• Track changes to other variables as they are updated by a for loop

Why indentation?

• Studies show that’s what people actually pay attention to
  • Every textbook on C or Java has examples where indentation and bracing don’t match
• Doesn’t matter how much indentation you use, but the whole block must be consistent
  
• Python Style Guide (PEP 8) recommends 4 spaces
• And no tab characters

Lists in Python

• Lists as arrays
• Indexing
  • Indexing some single value or even a whole set of values from a given list.
  • Indexing for retrieving single elements works as usual in python and indexing by negative numbers starts counting from the end.
• Slicing
  • Subset of a list, called a Slice, by specifying two indices. The return value is a new list containing all the elements of the list, in order, starting with the first slice index, up to but not including the second slice index.
  • Difference between upper and lower bound is the number of values in the slice.

Indexing and Slicing a List Example

Using Python libraries

• This introduction to Python is built around an end to end scientific example: data analysis
• What is a library (module) and its usage
• Reading data from a file

NumPy Arrays

• NumPy arrays and operations on arrays of data

NumPy arrays: Indexing and Slicing

• Ways of selecting individual values and subsets of data
• One-dimensional arrays are simple; on the surface they act similarly to Python lists.

Indexing in a NumPy 2D array

• The indices are (row, column) instead of (column, row).
• Example Patient inflammation data who were given treatment for arthritis:
  • Rows: Hold information for a single patient
  • Columns: Represent successive days

Cont..

Data visualisation using libraries

The purpose of computing is insight, not numbers, Richard Hamming.

• Best way to develop insight is often to visualise data.
• Plotting data using matplotlib library

Control Flow: Making choices

• Write conditional statements including if, elif and else
• A few things to note about the syntax:
  • Each if/ else statement must close with a colon (:)
  • Code to be executed as part of any if/else statement must be indented by four spaces.
  • Although not explicitly required, every if statement must also include an else statement - it just makes for a better program.
• Evaluate expressions containing and and or

Creating Functions

• Defining a function, the parameters that it takes, return value
• Test and debug a function
• Scope of variables
• Set default values for function parameters
• Divide programs into small, single-purpose functions

Command-line Programs

• Using values of command-line arguments in a program
• Handling flags and files separately in a command-line program
• Reading data from standard input in a program

Wrap-up Challenge: Connecting the dots

Write a python script (function) for Fahrenheit to Celsius temperature conversion and stores the output in a file.

• Hint (Tools to be used):
  • Unix pipes and filters
  • Python functions
  • Command-line programs
  • Using Fahr_to_kelvin() and Kelvin_to_celsius() functions

Thank You!