complete the programming assignment in Canvas, which is to complete any one of the ten problems at the end of Chapter 4. Pay attention -- some of the problems that seem simple are actually more com
An Introduction to Computer Science with Java, Python and C++ Community College of Philadelphia edition Copyright 201 8 by C. W. Herbert , all rights reserved. Last edited January 21 , 201 9 by C. W. Herbert This document is a draft of a chapter from An Introduction to Computer Science with Java, Python and C++ , written by Charles Herbert . It is available free of charge for students in Computer Science courses at Community College of Philadelphia during the Spring 201 9 semeste r. It may not be reproduced or distributed for any other purposes without proper prior permission. Please report any typos, other errors, or suggestions for improving the text to [email protected] Chapter 4 – Loops and Lists in Python Chapter 4 – Loops and Lists in Python ................................ ................................ ................................ .......... 1 Chapter 4 – Loops and Lists in Python ................................ ................................ ................................ .......... 2 Chapter 4 Learning Outcomes ................................ ................................ ................................ ...................... 2 Repetition in Algorithms ................................ ................................ ................................ ... 3 Loop Control Variables ................................ ................................ ................................ .......................... 4 Lesson 4.2 P re-Test Loops and Post -Test Loops ................................ ................................ ....................... 6 Pre -Test Loops ................................ ................................ ................................ ................................ ....... 6 Post -Test Loops ................................ ................................ ................................ ................................ ..... 7 While Loops in Python - Sentinel Loops and Count Controlled Loops .............................. 8 Sentinel Loops ................................ ................................ ................................ ................................ ....... 8 Count -controlled Loops ................................ ................................ ................................ ...................... 11 Random numbers in Python ................................ ................................ ........................... 12 Using the randrange() function ................................ ................................ ................................ ........... 14 In Class Exercise ................................ ................................ ................................ ................................ ...... 16 Python lists ................................ ................................ ................................ ...................... 17 Using for statements with Python lists ................................ ................................ ............................... 17 Exercise ................................ ................................ ................................ ................................ ............... 18 Python list operations ................................ ................................ ................................ ......................... 19 Chapter Exercises ................................ ................................ ................................ ................................ .... 20 Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 2 C hapter 4 – Loops and Lists in Python This chapter examines repetition in alg orithms and in Python programming. Repetition i n an algorithm or computer program is also known as looping , because part of an instruction set is repeated, forming a loop in the program logic. The difference between pre -test loops with the test for repetition at the beginning of the loop and post -test loops with the test for repetition at the end of the loop is discussed. The difference between loops that are count -controlled and loops that are not count -controlled is also discussed. The concept s of a list in Python and iterating a list are also discussed. Chapter 4 Learning Outcomes Upon completion of this chapter students should be able to: • describe the concept of repetition in an algorithm; • describe the difference between a pre -test loop and a post -test loop and why a pre -test loop is often preferred; • list and describe the four major components of a pre -test loop in a computer program; • des cribe the difference between a count -controlled loop and a sentinel loop, and the three pieces of information needed for the counter in a count - controlled loop; • create Python code that includes pre -test loops, post -test loops, count - controlled loops, senti nel loops, and nested loops. • describe the concept of a list in Python and how to create a list of data items. • Create code that iterates a list using the Python for statement, and which processes the data items in the list with each iteration. Note: This chapter refers to the Python 3 programming language and assumes that you have th e Python 3 language ready to use on your computer. Appendix A describes downloading and installing Python. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 3 Repetition in Algorithms Repetition occurs wh enever part of an algorithm is repeated, forming a loop in the algorithm. The loop is a repetition sequence . In Chapter 3 we saw conditional execution – algorithms that branched into different paths based on some condition in the form of a Bo olean expression. A loop is created when an algorithm branches backward following such a condition, as shown by the pseudocode and flowchart below. The Boolean condition in this algorithm is (x <= 10). The condition appears following the word while instead of the word if that is used in binary branching. In pseudo -code, as in many programming languages, the word while indicates that the path of the a lgorithm returns to the conditional expression when the block of code following the while statement is finished being executed , forming a loop. This use of the word while originated in the Algol language, so it is common in Algol -derived languages such as C, C++ , Java , and Swing . A while statement forms a test to see if a loop should be executed. Each time the Boolean condition in the while statement is true, the computer will execute the block of code, then go back to the condition again. When the condition is no longer true, the block of code will be ignored , and the computer will move on to whatever comes next in the algorithm. It is possible that the while condition could be false the first time it is encountered, which means t he loop will not be executed in this run through the algorithm. It is also possible that the while condition will always be true, which means the loop will always be executed, forming an infinite loop. A small round circle or dot is used on a flowchart t o show where the path that forms the loop rejoins the previously executed part of the algorithm. This symbol is called a connector and is only used to show where separate paths of logic in an algorithm come together. Figure 1 – a loop in an algorithm Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 4 The algorithm illustrated above prints the numbers from 1 to 10. Before the loop starts, x is set to 1. If the condition ( x ≤ 10 ) is true , the value of x is printed, x is incremented by 1, then the condition is checked again. This continues until the co ndition is false – until x is no longer less than or equal to 10. The last time through the loop, 10 will be printed, then x is set to 11. When the condition is checked this time around, the loop terminates because the condition is now false, 11 is not less than or equal to 10. A while statement is not the only statement used for branching. Just as there are several different kinds of branching routines, there are several different kinds of loops. The loop shown in Figure 1 on the previous page is an ex ample of a count -controlled pre -test loop. Loops are either count -controlled loops or sentinel loops. They are either post -test loops or pre -test loops. We will examine these differences in this chapter. Loop Control Variables As we just saw, a condition i s tested each time through a loop to determine whether to repeat the loop again or terminate the loop and move on. The condition should be either a boolean expression or a function that returns a Boolean value. The condition should include at least one loo p control variable. A loop control variable is a variable used in a boolean expression to determine if a loop should be repeated. Sometimes the acronym LCV is used to refer to a loop control varia ble . Any type of variable may be used in a loop control variable, as long as the overall expression evaluates to a Boolean value, as in the condition from above, (X<=10). Here are some examples of while statements with Boolean expressions containing loop control variables using Python syntax: • while count < 10 : # count is number . • while !(name == “END”) : # name is a string. • while age >= 18 and age <= 65 : # age is a number . This checks for a range of values. • while citizen : # citizen is a Boolean variable. • while angle == math. pi: # angle is a number . This is a troublesome condition. • while (abs(angle – math. pi) < .001) # angle is a number . This works better. Why is angle == math.pi troublesome? Tests for equality of variable s can be troublesome because floating point value s could be rounded off differently, so two floating point values may not be exactly equal. This is especially true for irrational numbers, which cannot be expressed as a ratio of integers -- a fraction with an integer numerator and an integer denominator. 3.14159 does not equal 3.14159 2. Instead of testing for equality, we can test to see if two values are really close to one another, by seeing if the difference between them is less than a given small value , as in the last condition above: (abs(angle – math. pi) < .001) The absolute value function is used in the condition to see if the magnitude of the difference between angle and π is less than .001. It tests to see if angle is really close to π. We can make this test as accurate as needed. In general, this is a good way to compare floating point values that may be irrational or that may be rounded off for some other reason. A loop may have more than one loop control variable, such as in the following wh ile statement: while (all the doors are not painted AND we still have paint left) Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 5 In programming terms, the statement might look more like this: while ( (unpaintedDoorCount > 0) and (amountOfPaint > 0) ): Both unpaintedDoorCount and amountOfPaint are loop control variables. The loop will only repeat if both parts of the condition are true. Here is an example using an OR condition: while ( at least 12 years old OR at least 60 inches tall ) In programming terms, the statement might loo k more like this: while (age >= 12 ) or (height >= 60) : Both age and height are loop control variables. In this case, the loop will repeat if either of the two parts of the condition is true. In the next few sections we will look at the different kinds of loops and how to implement them in Python . While Loops in Other Languages While loops in the Java, C, C++ , Microsoft C# , and the Apple Swift programming languages are almo st identical to while loop s in Python . Here are some examples of a while loop to print the numbers from one to ten in several programming languages. Almost all use syntax derived from ALGOL 68. Notice that Python uses indenting to indicate the body of a loop, where many other languages use braces { }, or word pairs, such as do and end . Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 6 Lesson 4.2 Pre -Test Loops and Post -Test Loops The test to determine if part of an algorithm should be repeated could occur at the beginning of a loop or at the end of a loop. If the test occurs at the beginning of a loop, the loop is known as a pre -test loop . If the test occurs at the end of the loop, the loop is known as a post -test loop. In this section we will look at the structure of pre -test loops and post -test loops. Pre -Test Loops A pre -test loop is a loop in which the test to determine whether or not to go through the loop comes before the process that is to be executed within the loop. There are four parts to every pre -test loop: • Loop Initialization : set the first value of the loop control variable • Loop Test : test the loop control variable to see if the loop should be executed • Loop Processing : instructions defining the part of the algorithm to be repeated • Loop Update : change the value of at the loop control variable The body of a loop includes all of the instructions in the loop’s block of code – the processing and the update . The four parts of the loop are identified in the following pseudocod e: The update in a pre -test loop usually occurs at the end of the body of the loop, after the processing. This is a convention adopted by many programmers to make the logic in an algorithm easier to understand. It’s a good idea to do things this way to avo id confusion, but it is not absolutely necessary to do so. count = 1 while count ≤ 10:print (count) count += 1 •The initialization happens before the loop starts. All of a loop’s control variables should be initialized before a loop starts. The loop shown here has only one control variable, count . •The test is the condition in the while statement. This loop’s condition tests to see if count is less than or equal to 10. •The processing in this example is just one instruction. It could be many instructions or even a call to run a different method or function, which we will see in later chapters. •The update is the part of the algorithm where the value of at least one control v ariable is changed. If the values of all of a loop’s control variables remain the same each time through the loop, then we have an infinite loop. The loop’s update is the statement +=1, which increments count. Figure 2 – structure of a pre -test loop Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 7 Post -Test Loops A post -test loop is a loop in which the test to determine whether or not to repeat the loop comes after the body of the loop. Here is our one to ten algorithm with a post -test loop: start x = 1 do print x increment x while (x <= 10) stop This post -test algorithm produces the same results as the pre -test algorithm we saw earlier. A do…while structure establishes a post -test loop, with do at the beginning of the loo p and the while condition at the end of the loop. We migh t see this in pseudocode, and in languages such as Java and C++ , but there is no do. ..while structure, nor any other structure for post -test loops, in Python. This was a conscious decision by Guido van Rossum based on principles of computer science. Many computer scientists believe that post -test loops are dangerous and can lead to software with undesired side effects. Here is an example: Imagine a method that erases hard drives , which are numbered starting with zero. If this is a pre -test loop, as in the e xample on the left, the program first asks if we want to erase a hard drive, then does so if we say yes . In the post -test loop algorithm on the right it erase s a drive first , then asks if we want to erase another. What happens if someone tries the p rogram on the left to see what it does? …the program on the right? What could go wrong with a post -test loop used to control nuclear weapons? Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 8 Of course, not all programmers agree, and there is a way to implement post -test loops in Python, even though they are discouraged. We will s ee more about this later in the course . While Loops in Python - Sentinel Loops and Count Controlled Loops Python has a while statement that can be used to implement pre -test loops. The Python while statement is simila r to an if statement, with a condition, followed by a colon, then an instruction or block of code indented to form the body of the loop. It looks very much like the pseudocode in the last section. Both sentinel loops and count -controlled loops can be impl emented with the while statement. We will look at sentinel loops first, then count controlled loops. Sentinel Loops a sentinel is a marker that signals when a loop should be terminated. The sentinel could be a value or a terminating condition. A sentin el loop continues until it encounters a sentinel. The sentinel could be input from a user, a marker at the end of a data file, or any other condition that the software can determine, such as a printer running out of paper. The concept of a sentinel is impo rtant in reading data files. Usually there is a special value at the end of a file called an end of file marker . We can write a loop to read data in from a data file until the end of file marker is encountered. Here is a pseudocode examples of such a l oop. We will see more about this when we study data files later in the semeste r. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 9 read the first data item from a file while not(end of file): print (data item) read next data item The loop above will continue to read data from the file, one it em at a time, until the sentinel condition is met – the data is the end -of-file marker. The EOF marker is a sentinel value. The condition is a sentinel condition. In older computers that used punched cards, data would be read in from a deck of cards, with one record on each card. The last card in the deck, called a trailer card, marked the end of the deck. Sentinel values are sometimes still referred to as trailer values. These images from a British university circa 1970 show a deck of cards, students creating decks of cards with keypunch machines, and an operator loading a deck of cards into a card reader. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 10 Python while statements can be used for sentinel loops. Here is an example with user input: The loop reads a string value from the keyboard each time it is executed. The input to initialize the loop control variable before the while command is called a priming read . The loop will continue until the user inputs the string "done". Notice that the input is a string. if it is not the string "done", then it should be a value entered by the user. The loop converts the input string to an integer before proceeding. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 11 Count -controlled Loops It could be argued that every loop is a sentinel loop, checking for a sentinel in a data set or looking for a condition that ends a loop and thus acts like a sentinel. However, if the condition that controls repetition is based o n counting , then we have a count -controlled loop. A count -controlled loop is a loop in which the loop control variable is an iterated numeric variable. An iterated numeric variable changes in discrete steps from one value to another. When we count to ten , we are changing a value from one to ten in steps of one. The pre -test and post -test loops we saw at the beginning of this chapter were count -controlled loops. The loop control variable in a count -controlled loop is a called a counter . There are three t hings we need to know about the counter to set up a loop control variable: • the initial value • the final value • the increment In the one to ten loops we saw, the initial value is 1, the final value is 10, and the increment is 1. We could have a negative increment, also called a decrement, but only if the final value is less than the starting value. For example, we could have an initial value of 10, a final value of 1, and an increment of -1, which would cause our loop to go from 10 down to 1. Be careful – if the initial value and the final value don’t match the increment – for example if the initial value is 1 the final value is 10 and the increment is -1 ( negative one ) – then we could end up with an infinite loop. The values of the counter would start at 1, then be 0, then -1, then -2, and theoretically never reach 10. However, the program will eventually stop on most computers. One of three things will happen: • the computer will timeout automatically if the program continues to run for a certain amount of time . Some operating systems have a built -in mechanism for this. • The computer will run out of memory. Of course, this only applies if more memory is used each time through a loop. • the loop control variable will go out of bounds. Each data type has an acceptable range of values. Eventually the value of the loop control variable will be out of bounds -- out of the acceptable range for that data type. In Python, one of these three things will eventually happen, but it cou ld take a while to go out of bounds – integer numeric values often have a range of values from -2,147,483,648 to + 2,147,483,647 . The following Python 3 code will tell you the largest integer available on the platform you are using: import sys print(sys.ma xsize) The increment for a counter in a count -controlled loop does not need to be 1 or -1. It could be almost any number. Here are some examples. Can you identify the output from each one? Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 12 Example A x = 1 while ( x < 10) : print (x) x = x + 1 Example B x = 10 while ( x ≥ 1) : print (x) x = x -1 Example C x = 1 while ( x ≤ 100) : print (x) x = x + 2 Example D x = 2 while ( x ≤ 100) : print (x) x = x + 2 Example E x = 0 .0 while ( x ≤ 10 .0): print (x) x = x + 0.5 The Python += operator can be used to increment a value. x += 1 is equivalent to x = x + 1. This is known as the augmented assignment operator for addition. There are augmented assignment operators in Python for each of the mathematical operator s: +, -, /, //, * , and ** have augmented assignment operator += , -=, /= , //= , *=, and **= . x -= 2 is the same as x = x - 2, and so on. Random numbers in Python Python has a module named random that can be used to generate pseudo -random numbers. A pseudo - random number is a number that appears to be random, but which really follows a pattern that can be duplicated. Unlike true random numbers, pseudo -random numbers are predictable. The Python ran dom module contains a function named random() that will generate and print a random floating point number between 0 and 1, including 0 but not including 1. 0.0 <= random() < 1.0. To use the random() function, or any of the functions in the random module , it must be imported into your Python programs. import random #declare variables rand = 0.0 # a randomly generated number # generate and print a random number using the random() function rand = random.random() print(rand, " is a randomly generated numb er") Under identical circumstances, a Python program will generate the same pattern of random numbers every time. This can be useful when doing a statistical experiment or a simulation in which we would like to use the same set of random number each time we repeat the experiment, but is not desirable for things like games that should be random, not pseudo -random. To control pseudo -random numbers, and to make them harder to predict, Python has a seed( n) function that can be used to seed its random number ge nerator. To seed a random number generator is to place the generator in a state to pick a specific number. In Python, n can be any number. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 13 # seed the random number generator rand = random.seed(1) # generate and print a random number using the random() function rand = random.random() print(rand, " is a randomly generated number using seed(1). \n") If we use the seed( ) function with no parameter, python will initialize the random number generator using the system clock. Since the system clock is accurate to billionths of a second, this mimics a truly random number for most purposes. However, keep in mind that a progr am could still be written allowing someone to access the system and predict the numbers generated. # seed the random number generator using the system clock rand = random.seed() # generate and print a random number using the random() function rand = rando m.random() print(rand, " is a randomly generated number using the system clock. \n") Almost any value can be used as seed for the random number generator, including strings. Python uses a formula to turn the value of n in seed(n) into a number that can seed the random number generator. # seed the random number generator with a string rand = random.seed("Hello") # generate and print a random number using the random() function rand = random.random() print(rand, " is a randomly generated number using 'Hello'. \n") The value returned by random.random () is in the range 0.0 ≤ n < 1.0. What if we want to pick an integer from 1 to 10, including 1 and 10? We start by multiplying by the number 10. 0 times 10 is 0. 1 times 10 is 10. If 0.0 ≤ n < 1.0, and we multiply n by 10, then 0.0 ≤ n < 10.0. But we still don’t have an integer, and notice the range is < 10, so ten is not included in the possible values yet. Our next step is to type cast the result into an integer. Remember, y = (int) x; turns y into an integer by truncating x. It does not round off x, it chops off the decimal. If 0.0 ≤ n < 10.0, and we truncate the value, we get 0 ≤ n < 10. The number will be an integer in the set {0, 1, 2, 3,… 9} . Next we just add 1 to the value and now it is in the set {1,2,3…,10} which is what we want. So, to generate an integer in the range from 1 to 10, including 1 and 10 with Math.random() use: x= 1+ int( random .random() * 10) This does exactly what we want – picks a number in the range 0.0 ≤ n < 1.0, multiply by 10, truncate it to be an integer, then add 1. So, to set a variable x equal to a random integer between 1 and b, including 1 and b , the assignment statement should be: Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 14 x= 1 + int( random .random() * b) where b is the high endpoint of the range of values. The following examples show how to generate random integers for specific ranges of values. Generating random floating point numbers is similar, but we do not typecast the values to integers. pick a do or – 1, 2, or 3 door = 1 + int( random .random() * 3) simulate rolling a pair of dice, each between 1 and 6 d1 = 1 + int (random .random() * 6) d2 = 1 + int (random .random() * 6) total = d1 +d2; pick a card from a deck of cards suit = 1 + int (random .random() * 4); # if 1 print “hearts”, if 2 print “clubs”, etc. rank = 1 + int (random .random() * 13 ); # 1 is an “ace”, 11 is a “jack”, 12 is a “queen”, 13 is a “king” Using the randrange () function Python has a randrange() function that will generate a random number within a given range of values, which is a shortcut to using the mathematical methods discu ssed above. It can be used in several ways. With a single parameter, randrange(n) will generate an integer from zero up to but not including n. With two parameters, randrange(n1, n2) will generate an integer from n1 up to but not including n2 . The Python program randomDemo.py demonstrates the random functions discussed above. # randomDemo.py # program to demonstrate generating random numbers # last edited Oct. 8, 2018 by C. Herbert for CSCI 111 import random #decl are variables rand = 0.0 # a randomly generated number count = 0.0 # a loop counter # generate and print a random number using the random() function rand = random.random() print(rand, " is a randomly generated number. \n") # seed the random number ge nerator rand = random.seed(1) # generate and print a random number using the random() function rand = random.random() Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 15 print(rand, " is a randomly generated number using seed(1). \n") # seed the random number generator using the system clock rand = random.seed() # generate and print a random number using the random() function rand = random.random() print(rand, " is a randomly generated number using the system clock. \n") # generate and print a set of random numbers using the randrange(n) func tion print("Here is a set of random numbers between zero and ten.") count = 1 while count <= 5 : rand = random.randrange(11) print(" \t", rand) count +=1 # end while print(" \n") # generate and print a set of random numbers using the rand range(n1,n2) function print("Here is a set of random numbers between 10 and 20") count = 1 while count <= 5 : rand = random.randrange(10,21) print(" \t", rand) count +=1 # end while .
Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 16 In Class Exercise The following pseudocode is from the example of a guessing game found in Chapter 3, starting on page 19. Create a Python program to implement this design. start int pick # the number the computer picks int guess = 0 # the user’s guess, initialized to zero int count = 0 # the number of guesses pick = a random number between 1 and 100 print “I am thinking of a nu mber between 1 and 100.” print ”Try to guess what it is.” print” Your guess?” user inputs guess # ge t value of guess from the keyboard input while (guess ≠ pick) # set up a loop to repeat until the user guesses the number { increment count # keep track of how many guesses if (guess < pick) # in the loop guess cannot equal pick: it will be low or high print “Too low. Try again.” else print “too high. Try again.” print ”Your guess?” user inputs guess # get value of guess from the keyboard input } #end while (guess ≠ pick) , the loop ends when guess = pick print “Correct. The number is ” + pick print “It took you ” + count + “ guesses” stop Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 17 Python lists In addition to simple data types such as integer and string , Python has several compound data types that can be used to store more than one value. The most commonly used among these is the Python list . A list in Python is a linear, sequential, indexed set of values that can be represented by a single variable. Values in the list are separated by commas, with the entire list enclosed in square brac kets. Here is an example of a Python list defined by an assignment statement. seventiesMovies = ["The Godfather", "Chinatown", "Taxi Driver", "Rocky "] An individual value in a Python list can be accessed using the name of the list followed by its index number in square brackets , which is an integer starting at zero for the first item and following in sequence for each additional item. in the list above, seventiesMovies[0] is "Godfather", seventiesMovies[1] is " Chinatown", and so on. Notice that the highest index value will be one less than the number of items in the list because we started counting at zero. If the list has n item, then the highest index will be n-1. Many programming languages have a built -in linear, sequential, indexed data structure called an array . Python does not have arrays, but Python lists are very similar to arrays. The values in a Python list can be any valid Python data type. Python's loose binding of variable names to their locations and data types allows values of different data types to be used in the same list, although all values in a Python list are often the same data type for practical reasons. Lists can be printed using the print() function, just as with other data ty pes. Using for statements with Python lists A python for statement can be used to iterate a list, as in the following: for movie in seventiesMovies: print(movie) The name of a variable follows the word for , with the name of the list following the word in. The for loop will be executed once for each value in the list, with the variable referring to each value from the list in turn. In this example, the variable movie will refer to seventiesMovies[0] for the first iteration of the loop, seventiesMovies[1 ] for the second iteration of the loop, and so on, up to seventiesMovies[ 3}. Individual values in Python lists can be assigned with assignment statements, such as: seventiesMovies[2] = "Star Wars" This only works if the list item already exists. In the cas e above, " Star Wars " replaces " Taxi Driver " in the list. The following will not work, because our list does not have 5 items, so there is no seventiesMovies[ 4]: seventiesMovies[4] = "Annie Hall" Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 18 The if…in statement can be used to test for membership in a Python list: if "Godfather" in seventiesMovies : print("Yes, Godfather is in the list.") Exercise The Python statements shown as examples in the section above are listed below. Try them in order in the Python shell to see the results. for and if statements can be entered on a single line, but your may need tp press enter twice at the end of the line. (The statements can also each be cut and pasted from this text.) seventiesMovies = ["The Godfather", "Chinatown", "Taxi Driver", "Rocky"] for movie in seventiesMovies: print(movie) seventiesMovies[2] = "Star Wars" for movie in seventiesMovies: print(movie) seventiesMovies[4] = "Annie Hall" if "The Godfather" in seventiesMovies: print("Yes, Godfather is in the list.") Your results should be similar to those shown below: Notice that the error message generated by seventiesMovie s[4] = "Annie Hall" tells us that the " list assignment index is out of range. " This is because we attempted to assign a value using index 4 and the list only contains 4 items with index values 0 through 3. As mentioned above, the highest index in a list with n items in n-1. The length of a Python list can be changed; in other words, Python lists are dynamically sized . This is one of the operations that can be formed by Python's list methods . Some commonly used list operations, functions , and methods are described below. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 19 Python list operations Several operations can be performed on Python lists. The two most common operations are list concatenation and list repetition . Two Python lists can be concatenated to combine one longer list, as in t he following: newList = ["A", "B", "C"] + ["D", "E", "F"] This can also be done with list variables. List repetition can be used to create a list with repeated items: Hello = ["Hello, world!"] * 3 This can also be done with lists that have more than one item: dataset = ["city", "state", "zip"] * 12 Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 20 Chapter Exercises 1. Multiplication Table A set of nested loops can be used to print a multiplication table using formatted print statements. 1 2 3 4 5 6 7 8 9 1 1 2 3 4 5 6 7 8 9 2 2 4 6 8 10 12 14 16 18 3 3 6 9 12 15 18 21 24 27 4 4 8 12 16 20 24 28 32 36 5 5 10 15 20 25 30 35 40 45 6 6 12 18 24 30 36 42 48 54 7 7 14 21 28 35 42 49 56 63 8 8 16 24 32 40 48 56 64 72 9 9 18 27 36 45 54 63 72 81 Write a program to print such a multiplication table. 2. Celsius to Fahrenheit Table Write a program to print a Celsius to Fahrenheit conversion table that a traveler could use to look up temperatures while traveling. The formula is F = ( 9 5 C) + 32. The table should include integer Celsi us degrees from 0 to 40. Your program does not need to use integers, but the table should display the Celsius temperature, then the Fahrenheit accurate to one - tenth of a degree. The first four entries from the table could look like this : Celsius Fahrenhei t 0 32.0 1 33.8 2 35.6 3 37.4 4 39.2 3. Guessing Game The guessing game that asks a user to pick a number from 1 to 100 is described in Chapter 3, starting on on pages 19 with pseudocode, sample output, and a flowchart. It uses branching, repetition, and the generation of random numbers. Your task is to create the game in Python . You should submit the game along with your programming lab report as described in Chapter 3. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 21 4. Printing Patterns Nested for loops can print patterns of stars, such as the example below: for i in range(1,6): for j in range(1,11): print("*", end =" ") print("") Output from this program: ********** ********** ********** ********** ********** Your task is to write similar Python code using nested loops to print each the following patterns : * ** *** **** ***** * ** *** **** ***** * *** ***** ****** * *** ***** ******* * *** ***** ******* *** *** *** Consider the numeric relationship between the row number and the number of starts in that row, as well as the relationship between the row number and the number of blank spaces to be pri nted before the stars are printed. 5. International Gymnas tics Scoring We wish to write a program to quickly calculate gymnastics scores for an international competition. The program should have a loop to ask the user for the scores from each of the six judges, numbered 1 through 6 for anonymity. Your program sho uld add each score to a sum inside the loop, then calculate and display the average score after the loop is finished. Scores are in the range 0 to 10 with one decimal place, such as 8.5. The average should be displayed with two decimal places. Here is a s ample of the output: Score for Judge 1: 8.5 Score for Judge 2: 8.7 Score for Judge 3: 8.4 Score for Judge 4: 9.1 Score for Judge 5: 8.9 Score for Judge 6: 9.0 The average score is: 8.77 6. Write a program similar to number 5, above, but in this case it should work no matter how many judges there are. The user will enter a -1.0 as the score to signal that there are no more judges. Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 22 7. Fibonacci Numbers The Fibonacci sequence is one of the most commonly found patterns in nature. It starts with 0 and 1, then each term in the sequence is generated by adding the previous two terms. The first few terms are 0, 1, 1, 2, 3, 5, 8, 13, 21, and 34. Numbers that appear in the sequence are called Fibonacci numbers. Write a program that uses a loop to generate and display the first 20 Fibonacci numbers. Your program can start by printing 0 and 1, then work from there for the next 18 Fibonacci numbers. 8. Trigonometric Table Write a program to print the sine and cosine for angles between 0 degrees and 90 degrees in increments of 10 degrees. Your program should use the functions in the Math library – Math.sin() and Math.cos(). The trigonometric functions work in radians, so for each angle, your program will n eed to convert degrees to radians, then find and print the sine and cosine. Fo r example, y = math.sin( math.radians(x)) # calculates the sin of x degrees angle sin Cos 10 0.174 0.985 20 0.342 0.940 30 0.500 0.866 40 0.643 0.766 50 0.766 0.643 60 0.866 0.500 70 0.940 0.342 80 0.985 0.174 90 1.000 0.000 9. Test for Divisibility If the remainder from dividing A by B is zero, then A is a multiple of B ( A is evenly divisible by B). For example, the remainder from dividing 6, 9, or 12 by 3 is 0, which means 6, 9, and 12 are all multiples of 3. Write a program to print the numbers from 1 to 25, and on the line next to each number, print messages if the numb er is a multiple of 2, 3, or 5. Here is a sample of the output: 1 2 multiple of 2 3 multiple of 3 4 multiple of 2 5 multiple of 5 6 multiple of 2 multiple of 3 7 8 multiple of 2 9 multiple of 3 10 multiple of 2 multiple of 5 Intro to CSCI with Java, Python, and C++ Chapter 4 – Loops and Lists in Python page 23 10. Estimate of a Definite Integral A loop in a computer program can be used to approximate the value of a definite integral. We can break the integral into rectangles, find the area of each rectangle then add the areas together to get the total area, as sho wn in the accompanying diagram. In practice, we could make the width of the rectangles progressively smaller, then run the loop again, until we achieved the desired accuracy. As the width of the rectangles gets progressively s maller, their total area gets closer to the total area under the curve. This is an old method that predates Calculus. Both Leibnitz and Newton used this method, eventually developing calculus from the concept of infinitesimals, which, in the case of our rectangles, would amount to asking, what would the total area be if we had very many rectangles with very small width? This was tedious by hand, but we now have computers. We can set the width of the rectangle. The height of the rectangle is the y value at point x. So for example, if we need to solve: ∫ 9− 2 −3 +3 The starting point is -3, the ending point is +3, and the height of the rectangle at each value of x in between the two is 9− 2 where y at each x is the height of the rectangle at that x. We can start with a width of 0.1, and write a loop like this: totalArea = 0 for x in range( -3, +3 .1, 0.1 ): # x is -3.00, then -2.9, then -2.8, etc. y = 9- x**x # the height is the y value at each x area = y * 0. 1 # the width is the increment, in this case 0.1 totalArea = totalArea + area # end for When the loop is finished, totalArea is the total area of the rectangles, which is an approximation of the area under the curve. Your task is to write a Python program that implements this algorithm for the definite integral used in this example. Run the loop several times, each time with a smaller increment, until your result does not change by more than .01 from the previous run of the program. — End of Chapter 4 — y = 9-x2 area under the curveestimated by rectangles
