ezimms99 / 608-mod3

Notes and exercises for Module 3

608-mod3

Notes and exercises for Module 3

Chapter 4 Notes:

Defining functions:

• Custom functions that you create yourself.
• Function definition - begins with def keyword followed by function name, set of paranetheses and a colon. This shows you the parameter list, comma separated representing the data that the function needs to perform its task.
• Can add a Docstring after colon that explains functions purpose.
• Finally, after executing the return line returns the answer to the user.
• To access a functions docstring, write functionname? or functionname?? to include source code.

Functions with multiple parameters:

• Take in specified values through a comma-separated list.

Random-Number Generation:

• Random module - import random
• randrange function generates an integer from the first argument up to but not including second argument.
• randrange generate pseudorandom numbers, based on an internal calculation that begins with a numeric value known as a seed.
• You can use random.seed to generate a seed number and test for logic errors.
• Tuple = an immutable sequence of values.

Python Standard Library:

• Package groups related modules.
• List of common used mmodules on page 132

Math Module Functions:

• Math module defines functions for performing various common mathematical calculations.
• Functions within this module are on page 133

Using Ipython tab completion for discovery:

• Tab completion - a discovery feature that speeds your codind and learning process.
• Can view math identifiers by using math.
• Uses CamelCase.

Default Parameter Values:

• You can specify that a parameter has a default parameter value. It will automatically insert if inputs aren't taken in.
• If multiple inputs are asked for and only one is given, input will take first parameters slot, and autofill other parameters.

Keyword Arguments:

• Use keyword arguments to pass arguments in any order.
• IE: def rectangle_area(length, width): uses two keyword arguments.

Arbitrary Argument lists

• Functions with arbitrary argument lists, can recieve any number of arguments
• Min and max for example.
• Using *args allows you to recieve any number of arguments.
• The * operator, when applied to an iterable argument in a function, upacks the elements in a list.

Methods: Functions that Belong to Objects

• A Method is a function that you call on an object using the form object_name.method_name(arguments)

Scope Rules:

• Each identifier has a scope that determines where you can use it in your program.
• A Local Variable's identifier has local scope ie only used within the function.
• Identifiers defined outside of a function have global scope - functions, variables, and classes.
• can use global statement to declare a variable as global.

import: Deeper look

• Can import multiple modules using comma separated list.
• Can import all identifiers defined in a module with a wildcard import of the form: from modulename import*
• You can use as to simplify a modules name import statistics as stats

Passing Arguments to Functions: Deeper Look

• pass_by_value: the called function recieves a copy of the arguments value and works exclusively with that copy
• pass_by_reference: the called function can access the arguments value in the caller directly and modify the value if it's mutable.
• can use id function to obtain a unique int value identifying that object.
• the is operator returns true if it's two operands have the same identity.

Function-Call Stack:

• Stacks are known as last-in, first-out data structures - that last item pushed onto the stack is the first item popped out from the stack.
• The function call stack supports the function call/return mechanism.
• For each function call, the interpreter pushes an entry called a stack frame that contains the return location.
• If a function-call stack runs out of memory it creates a fatal error known as stack overflow.
• Principle of least privelege: says that code should be granted only the amount of privelege and access that it needs to accomplish its designated task, and no more.

Functional-Style Programming:

• Pure functions: result depends only on the argument you pass to it.

Intro to Data Science: Measures of Dispersion

• Variance: Squaring the difference of each value helps to identify outliers. Used as statistics.pvariance
• Standard Deviation: Square root of the variance. Used as statistics.pstdev
  • The smaller the variance and standard deviation, the closer the data values are to the mean and the less overall dispersion.