Today's Topics

Review

• Sequences
• Lists
• The list Function
• Operators That Work on Objects
• Concatenating Lists
• The Repetition Operator
• Using a for Loop with Lists
• Indexing
• The len Function
• Changing Elements Using Indexes

New Material

• Empty Lists
• Slices
• Leaving Out Indexes in a Slice
• Skipping Elements in a Slice
• The in Operator
• List Methods
• The append Method
• The pop Method
• The index Method
• The insert Method
• The sort Method
• The reverse Method
• The del Statement
• The min and max Functions
• Honesty and Trust
• Fairness

Reading Assignment

You should read Chapter 8, More About Strings, from our textbook, Starting Out with Python, before next week's class.

Homework 11

I have posted homework 11 here.

This is the last homework assignment.

Quiz 8

The answers to Quiz 8 are posted here.

Let's take a look.

Review

Sequences

• Sequences are Python data types that hold many values
• The values are store one right after the other in RAM
• Here are two new sequence data types
  • lists
  • tuples
• Lists are sequences whose values can be changed
• Tuples are sequences that cannot be changed

Lists

• The values in a list are called elements
• You can change any value in the list and change their order
• You can also add and remove items from the list
• We can create a list by placing a series of values inside square brackets
• There must be a comma between each value

  >>> numbers = [5, 8, 2, 9, 7, 6, 3]
  >>> numbers
  [5, 8, 2, 9, 7, 6, 3]

• Here is what this looks like in memory

• This is an example of a list literal
• Lists can contain a value of any type
  • Integers
  • Floats
  • Strings
  • Booleans
• Lists can also contain other lists

The list Function

• list is a conversion function just like int and str
• list turns objects that are collections of things into a list
• Strings are sequences of characters in a specific order
• list will work on strings

  >>> name = "Glenn"
  >>> characters = list(name)
  >>> characters
  ['G', 'l', 'e', 'n', 'n']

Operators That Work on Objects

• Operators are special characters that perform some action
• Every data type has its own set of operators
• For numbers, we have the arithmetic operators
  • +
  • -
  • *
  • /
  • //
  • %
  • *
• Sequences have only two operators
  • +
  • *

Concatenating Lists

• The concatenation operator that works on strings

  >>> name = "Glenn" + " " + "Hoffman"
  >>>  name
  'Glenn Hoffman'

• also works on lists

  >>> n1 = [1,2,3]
  >>> n2 = [4,5,6]
  >>> n1 + n2
  [1, 2, 3, 4, 5, 6]

• That because both strings and lists are sequence data types

The Repetition Operator

• You cannot divide two lists

  >>> n1 / n2
  Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
  TypeError: unsupported operand type(s) for /: 'list' and 'list'

• But you can use the * on lists
• When you do the first operand is a list and the second is an integer
• The result is a new list with multiple copies of the elements of the original list

  >>> zeros = [0] * 5
  >>> zeros
  [0, 0, 0, 0, 0]
  >>> numbers = [1, 2, 3] * 3
  >>> numbers
  [1, 2, 3, 1, 2, 3, 1, 2, 3]

• The repetition operator also works on strings

  >>> "Go " * 3
  'Go Go Go '

Using a for Loop with Lists

• A for loop will work with a list

  >>> numbers = [1, 2, 3, 4, 5]
  >>>for n in numbers:
  ...   print(n)
  ... 
  1
  2
  3
  4
  5

• When we loop loop through a list we are said to iterate over that list
• We can also use a for loop with strings

  >>> team = "Red Sox"
  >>> for char in team:
  ...     print(char)
  ... 
  R
  e
  d
   
  S
  o
  x
  >>>

Indexing

• The elements in a list have a definite order
• Each element's place in line can be given by a number
• This number is called an index
• Unfortunately, index numbers do not start at 1
• Indexes start at 0
• This is called zero-based indexing
• This means that the first element in a list has an index of 0
• The second has an index of 1 and so on
• It also means that the index of the last element is one less than the length of the list

• To get a particular element we use the [ ] operator
• We put this operator right after the name of the list variable
• The index goes inside the square brackets

  >>> even_numbers[0]
  2
  >>> even_numbers[1]
  4
  >>> even_numbers[2]
  6

The len Function

• The built-in function len will return the length of any sequence

  >>> even_numbers = [2, 4, 6, 8, 10]
  >>> len(even_numbers)
  5
  >>> len("foo")

• We can use len with range to iterate through a list

  for i in range(len(even_numbers)):
  ...   print(even_numbers[i])
  ... 
  2
  4
  6
  8
  10

Changing Elements Using Indexes

• Lists are said to be mutable
• That means they can be changed
• This can only be done using indexes
• If we have a list of numbers

  numbers = [1, 4, 6, 8]

• We can change the first number like this

  >>> numbers[0] = 2
  >>> numbers
  [2, 4, 6, 8]

• We can use indexes in a for loop to change every element inside a list

  >>> for i in range(len(numbers)):
  ...   numbers[i] += 1
  ... 
  >>> numbers
  [3, 5, 7, 9]

New Material

Empty Lists

• When calculating a total we created a variable called an accumulator and set its value to 0
• What if we wanted to build a list from scratch?
• We would need to start with an empty list
• Then we could add elements to this list
• We create an empty list using a list literal with nothing between the square brackets

  >>> new_list = []
  >>> new_list
  []

• The empty list serves the same purpose that zero does for numbers
• If we multiply any number by zero we still get zero
• If we use the repetition operator on an empty list we still get an empty list

  >>> new_list * 5
  []

Slices

• Let's say we define the following list

  >>> days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']

• What if I wanted to create a new list with just weekdays?
• That is, all the days except Sunday and Saturday
• Python gives us a easy way to do this using a slice
• A slice is new, smaller list created from another list
• To create a slice you use the following format

  LIST_VARIABLE[FIRST_INDEX:ONE_MORE_THAN_LAST_INDEX]

• The trick to using list is remembering how to get the second index
• The second index is not the index of the last element
• It's the index of the element after the last element you want
• Let's say we wanted to create a new list weekdays
• The first element we want in our slice is "Monday" which has an index of 1
• The last element we want is "Friday" which has an index of 5
• Adding 1 to 5 we get 6
• So we create our new list like this

  >>> weekdays = days[1:6]
  >>> weekdays
  ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']

• Here is another list

  >>> digits = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]

• To get a slice from 2 to 8 we would write

  digits[2:8]
  [3, 4, 5, 6, 7, 8]

• With zero-based indexing the index for 3 is 2
• The index for 8 is 7
• 9 is the element after 8 and its index is 8

Leaving Out Indexes in a Slice

• Python allows you to create a slice using only one index
• If you leave out the first index, Python assumes the value is 0
• In other words, the index of the first element

  >>> days
  ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
  >>> days[:4]
  ['Sunday', 'Monday', 'Tuesday', 'Wednesday']
  >>> digits
  [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]
  >>> digits[:5]
  [1, 2, 3, 4, 5]

• If you leave out the second index Python uses the length of the list
• So the the slice will end with the last element

  >>> days[4:]
  ['Thursday', 'Friday', 'Saturday']
  >>> digits[5:]
  [6, 7, 8, 9, 0]

• You can even leave out both indexes as long as you keep the :
• In this case Python will return a slice that consists of the entire list

  >>> days[:]
  ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']
  >>> digits[:]
  [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]

• This is a great way to make a copy of a list

  >>> daynames = days[:]
  >>> daynames
  ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']

Skipping Elements in a Slice

• You can also skip elements when creating a slice
• It works just like the 3rd argument to the range function
• To use this feature you add a second : followed by a number

  LIST_VARIABLE[FIRST_INDEX:ONE_MORE_THAN_LAST_INDEX:STEP_VALUE]

• The STEP_VALUE works just like the range function
• It is what we add to the index of the last element to get the next one
• It is the difference between the index of any two elements in the original list
• If we wanted to create a slice of all the even digits

  >>> digits = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]
  >>> digits[1:10:2]
  [2, 4, 6, 8, 0]

• Actually, I could leave out the second index

  digits[1::2]
  [2, 4, 6, 8, 0]

The in Operator

• Operators are special characters that perform some action
• The only operator we have seen so far have been symbols
  • +
  • -
  • *
  • /
  • //
  • **
  • %
• But operators can also be words
• in is an operator that works on objects that are a collection of values
• We use it like this

  VALUE in LIST

• The in operator returns True if the LIST contains VALUE
• Otherwise it returns False

  >>> digits
  [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]
  >>> 1 in digits
  True
  >>> 11 in digits
  False

• Is is possible for a list to contain the same value many times

  >>> l = [1, 2, 3, 3, 3, 4, 5, 6]

• in will tell you that value is in a list

  >>> 3 in l
  True

• But it will not tell you it is in there more than once

List Methods

• Lists are objects
• Objects usually have functions that work on the values inside the object
• These functions are called methods
• Here are some of the more useful list methods

  Method	Description
  append(item)	Adds item to the end of the list
  pop(index)	Removes the element at a given index from the list and returns the value. If called with no argument, it returns the last element and deletes it from the list.
  index(item)	Returns the index of the first element whose value is equal to item. A ValueError exception is raised if item is not found in the list.
  insert(index, item)	Inserts item into the list at the specified index. When an item is inserted into a list, the list is expanded in size to accommodate the new item. The item that was previously at the specified index, and all the items after it, are shifted by one position toward the end of the list.
  sort()	Sorts the items in the list so they appear in ascending order (from the lowest value to the highest value)
  reverse()	Reverses the order of the items in the list

The append Method

• The append method adds a value to the end of a list
• It takes one argument, the value you want to add
• Is it probably the most frequently used list method
• You can use the append method to create a list from scratch
• First you create an empty list

  >>> teams = []
  >>> teams
  []

• Then we can call the append method on this list using dot notation

  >>> teams.append('Red Sox')
  >>> teams
  ['Red Sox']

• We can call this method as many times as we like

  >>> teams.append('Orioles')
  >>> teams.append('Blue Jays')
  >>> teams.append('Rays')
  >>> teams.append('Yankees')

• Each new value is added to the end of the list

  >>> teams
  ['Red Sox', 'Orioles', 'Blue Jays', 'Rays', 'Yankees']

The pop Method

• The pop method does two things
  • Removes an element from a list
  • Returns the value of that element
• It's argument is the index of the value to be removed

  >>> numbs = [1, 2, 3, 4, 5]
  >>> n = numbs.pop(0)
  >>> n
  1
  >>> numbs
  [2, 3, 4, 5]

• If you leave out the index argument, pop removes the last element

  >>> n = numbs.pop()
  >>> n
  5
  >>> numbs
  [2, 3, 4]

The index Method

• The in operator will tell us if a list contains a value
• But it won't tell us where that value is inside the list

  >>> 'Red Sox' in teams
  True

• We can use the index method to do that
• We give this method the value we are looking for as an argument
• And it will return the index of that value

  >>> teams.index('Red Sox')
  0
  >>>  teams.index('Blue Jays')
  2

• If the value we are looking for is not in the list we will get a ValueError exception

  teams.index('Mets')
  Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
  ValueError: 'Mets' is not in list

• If the value occurs more than once, the index of the first element is returned

  >>> >>> l = [1, 2, 3, 3, 5]
  >>> l.index(3)
  2

The insert Method

• append always adds to the end of a list
• To insert a value somewhere else we need insert
• The method takes two arguments
  • The index where the element should be inserted
  • The value to be inserted there
• insert puts the value at the index given and moves every element to its right over one position

  >>> l1 = [1, 2, 3, 4, 5]
  >>> l1.insert(2, 7)
  >>> l1
  [1, 2, 7, 3, 4, 5]

The sort Method

• A list is mutable so we can add elements or remove them
• But we can also change the order of the elements
• This can be done with the sort method which takes no argument

  >>> l2 = [9, 1, 0, 2, 8, 6, 7, 4, 5, 3]
  >>> l2
  [9, 1, 0, 2, 8, 6, 7, 4, 5, 3]
  >>>l2.sort()
  >>> l2
  [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

The reverse Method

• The reverse method reverses the order of a list

  >>> l3 = [5, 4, 3, 2, 1]
  >>> l3.reverse()
  >>> l3
  [1, 2, 3, 4, 5]
  >>> l3.reverse()
  >>> l3
  [5, 4, 3, 2, 1]

• If you have a list of unsorted numbers and you want to sort them in descending order you first need to use sort

  >>> l4 = [2, 5, 9, 1, 8, 6, 3, 7, 4]
  >>> l4.sort()
  >>> l4
  [1, 2, 3, 4, 5, 6, 7, 8, 9]

• Then use reverse

  >>> l4.reverse()
  >>> l4
  [9, 8, 7, 6, 5, 4, 3, 2, 1]

The del Statement

• List methods aren't the only things you can use to work with lists
• You can delete elements from a list using the del statement
• The format of a del statement looks like this

  del LIST_VARIABLE[INDEX]

• After the keyword del comes the list variable and the index inside square brackets

• >>> l5 = [1, 2, 3, 4, 5, 6]
  >>> del l5[2]
  >>> l5
  [1, 2, 4, 5, 6]

The min and max Functions

• Two built-in functions can also be used with lists
• They do not change the list but they return information about it
• min returns the smallest value in a list

  >>> l6
  [1, 4, 5, 6]
  >>> min(l6)
  1

• max returns the largest

  max(l6)
  6

Honesty and Trust

• The third of the ACM ethical principles is

  Be honest and trustworthy

• Professionals depend upon their reputation
• Would you go to an accountant who had been accused of embezzlement?
• Or a doctor who was addicted to drugs?
• IT professionals often have access to confidential data
• And trade secrets
• A company would be stupid to hire you if they could not trust you
• Men could learn the address and phone number of attractive women
• Dishonest employees could sell confidential information to competitors
• Integrity is especially important for people working in security

Fairness

• The fourth ACM ethical principle is

  Be fair and take action not to discriminate

• Technical knowledge gives us the power to help people
• We have a moral obligation use this ability fairly
• To do this, we must distinguish between two things
  • Prejudice
  • Unconscious Bias
• Prejudice is "preconceived opinion that is not based on reason or actual experience"
• In other words, coming to a conclusion about something before examining the evidence
• Prejudice toward minorities is illegal in this country and many others
• Most large companies have policies against this
• This is done for both legal and practical reasons
• Companies do not want to violate the law
• And they don't want to alienate potential customers
• Prejudice does occur in professional life
• But unconscious bias is more prevalent
• It is also harder to recognize
• Prejudice is conscious
• Unconscious bias is not
• Unconscious biases are formed through life experiences
• And the cultural context in which we live
• The brain has two decision making systems, one slow and the other fast
• The slow system allows us to think about problems and come to a well thought out decision
• But some dangers come quickly
• This is why we have a faster decision system as this video explains
• This system is fast but not very smart or accurate
• But you can train yourself to learn when this fast system kicks in
• You can learn to stop it from making a biased decision

Attendance

Graded Quiz