Python Fundamentals: Lists and Dictionaries PDF

Fundamentals of Python: First Programs Second Edition Chapter 5 Lists and Dictionaries © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, excep...

Fundamentals of Python: First Programs Second Edition Chapter 5 Lists and Dictionaries © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 1  Objectives (1 of 2) 5.1 Construct lists and access items in those lists 5.2 Use methods to manipulate lists 5.3 Perform traversals of lists to process items in the lists 5.4 Define simple functions that expect parameters and return values © 2018 Cengage. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use.  Objectives (2 of 2) 5.5 Construct dictionaries and access entries in those dictionaries 5.6 Use methods to manipulate dictionaries 5.7 Determine whether a list or a dictionary is an appropriate data structure for a given application © 2018 Cengage. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use.  Introduction A list allows the programmer to manipulate a sequence of data values of any types A dictionary organizes data values by association with other data values rather than by sequential position Lists and dictionaries provide powerful ways to organize data in useful and interesting applications © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 4  Lists List: Sequence of data values (items or elements) Some examples: Shopping list for the grocery store To-do list Roster for an athletic team Guest list for a wedding Recipe, which is a list of instructions Text document, which is a list of lines Names in a phone book Each item in a list has a unique index that specifies its position (from 0 to length – 1) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 5  List Literals and Basic Operators (1 of 4) Some examples: [‘apples’, ‘oranges’, ‘cherries’] [[5, 9], [541, 78]] When an element is an expression, its value is included in the list: >>> import math >>> x = 2 >>> [x, math.sqrt(x)] [2, 1.4142135623730951] >>> [x + 1] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 6  List Literals and Basic Operators (2 of 4) Lists of integers can be built using range: >>> first = [1, 2, 3, 4] >>> second = list(range(1, 5)) >>> first [1, 2, 3, 4] >>> second [1, 2, 3, 4] The list function can build a list from any iterable sequence of elements: >>> third = list(“Hi there!”) >>> third [‘H’, ‘I’, ‘ ’ , ‘t’, ‘h’, ‘e’, ‘r’, ‘e’, ‘!’] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 7  List Literals and Basic Operators (3 of 4) len, [], +, and == work on lists as expected: >>> len(first) 4 >>> first 1 >>> first[2:4] [3, 4] Concatenation (+) and equality (==) also work as expected for lists: >>> first + [5, 6] [1, 2, 3, 4, 5, 6] >>> first == second True © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 8  List Literals and Basic Operators (4 of 4) To print the contents of a list: >>> print(“1234”) 1234 >>> print([1, 2, 3, 4]) [1, 2, 3, 4] in detects the presence of an element: >>> 3 in [1, 2, 3] True >>> 0 in [1, 2, 3] False © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 9  Replacing an Element in a List (1 of 2) A list is mutable Elements can be inserted, removed, or replaced The list itself maintains its identity, but its state—its length and its contents—can change Subscript operator is used to replace an element: >>> example = [1, 2, 3, 4] >>> example [1, 2, 3, 4] >>> example = 0 >>> example [1, 2, 3, 0] Subscript is used to reference the target of the assignment, which is not the list but an element’s position within it © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 10  Replacing an Element in a List (2 of 2) The first session shows how to replace each number in a list with >>> its square: numbers = [2, 3, 4, 5] >>> numbers [2, 3, 4, 5] >>> for index in range(len(numbers)): numbers[index] = numbers[index] ** 2 >>> numbers [4, 9, 16, 25] Next session uses the string method split to extract a list of words: >>> sentence = “This example has five words. ” >>> words = sentence.split() >>> words [‘This’, ‘example’, ‘has’, ‘five’, ‘words.’] >>> for index in range(len(words)): words[index] = words[index].upper() >>> words [‘THIS’, ‘EXAMPLE’, ‘HAS’, ‘FIVE’, ‘WORDS.’] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 11  List Methods for Inserting and Removing Elements (1 of 4) The list type includes several methods for inserting and removing elements List Method What It Does L..append(element) Adds element to the end of L L.extend(aList) Adds the elements of aList to the end of L L..insert(index, element) Inserts element at index if index is less than the length of L. Otherwise, inserts element at the end of L. L.pop() Removes and returns the element at the end of L. L.pop(index) Removes and returns the element at index © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 12  List Methods for Inserting and Removing Elements (2 of 4) The method insert expects an integer index and the new element as arguments >>> example = [1, 2] >>> example [1, 2] >>> example.insert(1, 10) >>> example [1, 10, 2] >>> example.insert(3, 25) >>> example [1, 10, 2, 25] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 13  List Methods for Inserting and Removing Elements (3 of 4) The method append expects just the new element as an argument and adds the new element to the end of the list The method extend performs a similar operation, but adds the elements of its list argument to the end of the list >>> example = [1, 2] >>> example [1, 2] >>> example.append(3) >>> example [1, 2, 3] >>> example.extend([11, 12, 13]) >>> example [1, 2, 3, 11, 12, 13] >>> example + [14, 15] [1, 2, 3, 11, 12, 13, 14, 15] >>> example [1, 2, 3, 11, 12, 13] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 14  List Methods for Inserting and Removing Elements (4 of 4) The method pop is used to remove an element at a given position >>> example [1, 2, 10, 11, 12, 13] >>> example.pop() # Remove the last element 13 >>> example [1, 2, 10, 11, 12] >>> example.pop(0) # Remove the first element 1 >>> example [2, 10, 11, 12] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 15  Searching a List in determines an element’s presence or absence, but does not return position of element (if found) Use method index to locate an element’s position in a list Raises an error when the target element is not found aList = [34, 45, 67] target = 45 if target in aList: print(aList.index(target)) else: print(−l) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 16  Sorting a List A list’s elements are always ordered by position, but you can impose a natural ordering on them For example, in alphabetical order When the elements can be related by comparing them , and ==, they can be sorted The method sort mutates a list by arranging its elements in ascending >>> order example = [4, 2, 10, 8] >>> example [4, 2, 10, 8] >>> example.sort() >>> example [2, 4, 8, 10] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 17  Mutator Methods and the Value None All of the functions and methods examined in previous chapters return a value that the caller can then use to complete its work Mutator methods (e.g., insert, append,extend,pop,and sort) usually return no value of interest to caller Python automatically returns the special value None >>> aList = aList.sort() >>> print(aList) None © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 18  Aliasing and Side Effects (1 of 2) Mutable property of lists leads to interesting phenomena: >>> first = [10, 20, 30] >>> second = first >>> first [10, 20, 30] >>> second [10, 20, 30] >>> first = 99 >>> first [10, 99, 30] >>> second [10, 99, 30] First and second are aliases They refer to the exact same list object © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 19  Aliasing and Side Effects (2 of 2) To prevent aliasing, create a new object and copy contents of original: >>> third = [] >>> for element in first: third.append(elemen t) >>> first [10, 99, 30] >>> third [10, 99, 30] >>> first[l] = 100 >>> first [10, 100, 30] >>> third [10, 99, 30] © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 20  Equality: Object Identity and Structural Equivalence (1 of 2) Programmers might need to see whether two variables refer to the exact same object or to different objects Example, you might want to determine whether one variable is an alias for another The == operator returns True if the variables are aliases for the same object. Unfortunately, == also returns True if the contents of two different objects are the same The first relation is called object identity The second relation is called structural equivalence. The == operator has no way of distinguishing between these two types of relations. © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 21  Equality: Object Identity and Structural Equivalence (2 of 2) Python’s is operator can be used to test for object identity >>> first = [20, 30, 40] >>> second = first >>> third = list(first) # Or first[:] >>> first == second True >>> first == third True >>> first is second True >>> first is third False © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 22  Example: Using a List to Find the Median of a Set of Numbers To find the median of a set of numbers: “““ File: median.py Prints the median of a set of numbers in a file. ””” fileName = input(“Enter the filename: ”) f = open(fileName, ‘r’) # Input the text, convert it to numbers, and # add the numbers to a list numbers = [] for line in f: words = line.split() for word in words: numbers.append(float(word)) # Sort the list and print the number at its midpoint numbers.sort() midpoint = len(numbers) // 2 print(“The median is’’, end = “ ”) if len(numbers) % 2 == 1: print(numbers[midpoint]) else: print((numbers[midpoint] + numbers[midpoint − 1]) / 2) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 23  Tuples A tuple resembles a list, but is immutable Indicate by enclosing its elements in () >>> fruits = (“apple”, “banana”) >>> fruits (‘apple’, ‘banana’) >>> meats = (“fish”, “poultry”) >>> meats (‘fish’, ‘poultry’) >>> food = meats + fruits >>> food (‘fish’, ‘poultry’, ‘apple’, ‘banana’) >>> veggies = [“celery”, “beans”] >>> tuple(veggies) (‘celery’, ‘beans’) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 24  Defining Simple Functions Defining our own functions allows us to organize our code in existing scripts more effectively This section provides a brief overview of how to do this © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 25  The Syntax of Simple Function Definitions Definition of a function consists of header and body def square(x): “““Returns the square of x.””” return x * x Docstring contains information about what the function does; to display, enter help(square) A function can be defined in a Python shell, but it is more convenient to define it in an I DLE window Syntax of a function definition: def (,..., ): © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 26  Parameters and Arguments A parameter is the name used in the function definition for an argument that is passed to the function when it is called For now, the number and positions of arguments of a function call should match the number and positions of the parameters in the definition Some functions expect no arguments They are defined with no parameters © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 27  The Return Statement Place a return statement at each exit point of a function when function should explicitly return a value Syntax: return If a function contains no return statement, Python transfers control to the caller after the last statement in the function’s body is executed The special value None is automatically returned © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 28  Boolean Functions A Boolean function usually tests its argument for the presence or absence of some property Returns True if property is present; False otherwise Example: >>> odd(5) True >>> odd(6) False def odd(x): “““ Returns True if x is odd or False otherwise.””” if x % 2 == 1: return True else: return False © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 29  Defining a Main Function (1 of 2) main serves as the entry point for a script Usually expects no arguments and returns no value Definition of main and other functions can appear in no particular order in the script As long as main is called at the end of the script Script can be run from IDLE, imported into the shell, or run from a terminal command prompt © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 30  Defining a Main Function (2 of 2) Example: “““ File: computesquare.py Illustrates the definition of a main function. ””” def main(): “““ The main function for this script.””” number = float(input(“Enter a number: ”)) result = square(number) print(“The square of”, number, “is”, result) def square(x): “““Returns the square of x.””” return x * x # The entry point for program execution if __name__ == “__main:”__ main() © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 31  Dictionaries A dictionary organizes information by association, not position Example: When you use a dictionary to look up the definition of “mammal,” you don’t start at page 1; instead, you turn to the words beginning with “M” Data structures organized by association are also called tables or association lists In Python, a dictionary associates a set of keys with data values © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 32  Dictionary Literals A Python dictionary is written as a sequence of key/value pairs separated by commas Pairs are sometimes called entries Enclosed in curly braces ({ and }) A colon (:) separates a key and its value Examples: A phone book: {‘Savannah’:‘476-3321’, ‘Nathaniel’:‘351-7743’} Personal information: {‘Name’:‘Molly’, ‘Age’:18} Keys in a dictionary An empty can be data of any immutable types, dictionary: {} including other data structures They are normally strings or integers © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 33  Adding Keys and Replacing Values Add a new key/value pair to a dictionary using []: [] = Example: >>> info = {} >>> info[“name”] = “Sandy” >>> info[“occupation”] = “hacker” >>> info {‘name’:‘Sandy’, ‘occupation’:‘hacker’} Use [] also to replace a value at an existing key: >>> info[“occupation”] = “manager” >>> info {‘name’:‘Sandy’, ‘occupation’: ‘manager’} © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 34  Accessing Values (1 of 2) Use [] to obtain the value associated with a key If key is not present in dictionary, an error is raised >>> info[“name”] ‘Sandy’ >>> info[“job”] Traceback (most recent call last): File “”, line 1, in info[“job”] KeyError: ‘job’ © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 35  Accessing Values (2 of 2) If the existence of a key is uncertain, test for it using the dictionary method has_key Easier strategy is to use the method get >>> if “job” in info: print(info [“job”]) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 36  Removing Keys To delete an entry from a dictionary, remove its key using the method pop pop expects a key and an optional default value as arguments >>> print(info.pop(“job”, None)) None >>> print(info.pop(“occupation”)) manager >>> info {‘name’:‘Sandy’} © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 37  Traversing a Dictionary (1 of 3) To print all of the keys and their values: for key in info: print(key, info[key]) Alternative: Use the dictionary method items() >>> grades = {90:‘A’, 80:‘B’, 70:‘C’} >>> list(grades.items()) [(80, ‘B’), (90,‘A’), (70,‘C’)] Entries are represented as tuples within the list for (key, value) in grades.items(): print(key, value) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 38  Traversing a Dictionary (2 of 3) You can sort the list first then traverse it to print the entries of the dictionary in alphabetical order: theKeys = list(info.keys()) theKeys.sort() for key in theKeys: print(key, info[key]) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 39 Traversing a Dictionary (3 of 3) Dictionary Operation What It Does len(d) Returns the number of entries in d d[key] Used for inserting a new key, replacing a value, or obtaining a value at an existing key d.get(key [, default]) Returns the value if the key exists or returns the default if the key does not exist d.pop(key [, default]) Removes the key and returns the value if the key exists or returns the default if the key does not exist list(d.keys()) Returns a list of the keys list(d.values()) Returns a list of the values list(d.items()) Returns a list of tuples containing the keys and values for each entry d.clear() Removes all the keys for key in d: key is bound to each key in d in an unspecified order © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 40  Chapter Summary (1 of 2) A list is a sequence of zero or more elements Can be manipulated with the subscript, concatenation, comparison, and in operators Mutable data structure index returns position of target element in a list Elements can be arranged in order using sort Mutator methods are called to change the state of an object; usually return the value None Assignment of a variable to another one causes both to refer to the same data object (aliasing) © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 41  Chapter Summary (2 of 2) A tuple is similar to a list, but is immutable A function definition consists of header and body return returns a value from a function definition The number and positions of arguments in a function call must match the number and positions of required parameters specified in the function’s definition A dictionary associates a set of keys with values [] is used to add a new key/value pair to a dictionary or to replace a value associated with an existing key dict type includes methods to access and remove data in a dictionary Testing can be bottom-up, top-down, or you can use a mix of both © 2018 Cengage. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website for classroom use. 42