University:
Boston University
Course:
MET CS 201 | Introduction to Programming
Academic year:

2024
Views:

148

Pages:

22
Author:

Akli97uo

Introduction to Python Part 2 Tutorial Outline – Part 2       Lists Tuples and dictionaries Modules numpy and matplotlib modules Script setup Development notes Lists  A Python list is a general purpose 1-dimensional container for variables.  i.e. it is a row, column, or vector of things  Lots of things in Python act like lists or use list-style notation.  Variables in a list can be of any type at any location, including other lists.  Lists can change in size: elements can be added or removed Making a list and checking it twice…  Make a list with [ ] brackets.  Append with the append() function  Create a list with some initial elements  Create a list with N repeated elements Try these out yourself! Edit the file in Spyder and run it. Add some print() calls to see the lists. List functions  Try dir(list_1)  Like strings, lists have a number of built-in functions  Let’s try out a few…  Also try the len() function to see how many things are in the list: len(list_1) List Indexing  Elements in a list are accessed by an index number.  Index #’s start at 0.  List:     x=['a', 'b', 'c', 'd' ,'e'] First element: Nth element: Last element: Next-to-last: x[0]  x[2]  x[-1] x[-2] 'a' 'c' 'e' 'd' x=['a', 'b', 'c', 'd' ,'e'] x[0:1]  ['a'] x[0:2]  ['a','b'] x[-3:]  ['c', 'd', 'e'] # Third from the end to the end x[2:5:2]  ['c', 'e'] List Slicing  Slice syntax:      x[start:end:step] The start value is inclusive, the end value is exclusive. Start is optional and defaults to 0. Step is optional and defaults to 1. Leaving out the end value means “go to the end” Slicing always returns a new list copied from the existing list List assignments and deletions  Lists can have their elements overwritten or deleted (with the del) command. x=['a', 'b', 'c', 'd' ,'e'] x[0] = -3.14  x is now [-3.14, 'b', 'c', 'd', 'e'] del x[-1]  x is now [-3.14, 'b', 'c', 'd'] • • • • DIY Lists Go to the menu FileNew File Enter your list commands there Give the file a name when you save it Use print() to print out results  In the Spyder editor try the following things:  Assign some lists to some variables. a = [1,2,3] b = 3*[‘xyz’]  Try an empty list, repeated elements, initial set of elements  Add two lists: a + b What happens?  Try list indexing, deletion, functions from dir(my_list)  Try assigning the result of a list slice to a new variable More on Lists and Variables  Open the sample file list_variables.py but don’t run it yet!  What do you think will be printed? Variables and Memory Locations  Variables refer to a value stored in memory.  y = x does not mean “make a copy of the list x and assign it to y” it means “make a copy of the memory location in x and assign it to y”  x is not the list it’s just a reference to it.  This is how all objects in Python are handled. x y Copying Lists  How to copy (2 ways…there are more!):  y = x[:] or y=list(x)  In list_variables.py uncomment the code at the bottom and run it. While Loops  While loops have a condition and a code block.  the indentation indicates what’s in the while loop.  The loop runs until the condition is false.  The break keyword will stop a while loop running.  In the Spyder edit enter in some loops like these. Save and run them one at a time. What happens with the 1st loop? For loops  for loops are a little different. They loop through a collection of things.  The for loop syntax has a collection and a code block.  Each element in the collection is accessed in order by a reference variable  Each element can be used in the code block.  The break keyword can be used in for loops too. collection In-loop reference variable for each collection element The code block Processing lists element-by-element  A for loop is a convenient way to process every element in a list.  There are several ways:     Loop over the list elements Loop over a list of index values and access the list by index Do both at the same time Use a shorthand syntax called a list comprehension  Open the file looping_lists.py  Let’s look at code samples for each of these. The range() function  The range() function auto-generates sequences of numbers that can be used for indexing into lists.  Syntax: range(start, exclusive end, increment)  range(0,4)  produces the sequence of numbers 0,1,2,3  range(-3,15,3)  -3,0,3,6,9,12  range(4,-3,2)  4,2,0,-2  Try this: print(range(4)) numbers.txt Lists With Loops  Open the file read_a_file.py  This is an example of reading a file into a list. The file is shown to the right, numbers.txt  We want to read the lines in the file into a list of strings (1 string for each line), then extract separate lists of the odd and even numbers. 38,83,37,21,98 50,53,55,37,97 39,7,81,87,82 18,83,66,82,47 56,64,9,39,83 …etc… • Let’s walk through this line-byline using Spyder • read_a_file_low_mem.py is a modification that uses less memory. Tutorial Outline – Part 2       Lists Tuples and dictionaries Modules numpy and matplotlib modules Script setup Development notes Tuples  Tuples are lists whose elements can’t be changed.  Like strings they are immutable  Indexing (including slice notation) is the same as with lists. Return multiple values from a function  Tuples are more useful than they might seem at first glance.  They can be easily used to return multiple values from a function.  Python syntax can automatically unpack a tuple return value. Dictionaries  Dictionaries are another basic Python data type that are tremendously useful.  Create a dictionary with a pair of curly braces: x = {}  Dictionaries store values and are indexed with keys  Create a dictionary with some initial values: x = {'a_key':55, 100:'a_value', 4.1:[5,6,7]} Dictionaries  Values can be any Python thing  Keys can be primitive types (numbers), strings, tuples, and some custom data types  Basically, any data type that is immutable  Lists and dictionaries cannot be keys but they can stored as values.  Index dictionaries via keys: x['a_key']  55 x[100]  'a_value'