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Book - 5.3) Python - Lists and Dictionaries

We have seen graphical descriptions of two fundamental ways of organizing data: lists and dictionaries. We will now see how these basic data structures are written in Python. 

List

A list can also be represented textually in Python as shown in the examples below. In the text representation the values are separated by commas and the entire list is delimited by square brackets. In the first example shown below the list has been set as the value of the property temperature. The other examples are similar except that they show that the values in different list scan be of different types. The value of the property magnitudes is a list all of whose elements are numbers with decimal points (type float) while the value of the property cities is a list all of whose elements are characters (type string). These examples shows that lists can contain any number of elements of the same type and that different lists can have different lengths and types.

temperatures = [45, 33, 20, 11, -7, 15, 3]
magnitudes = [2.1, 1.1, 3.7, 4.2, 2.0, 1.7 ]
cities = [ 'Blacksburg, VA', 'New York, NY', 'Seattle, WA' ]

We have already seen how to access the elements of the list using iteration. The following code shows again the use of iteration. In this code all of the elements of the magnitudes list are printed.

for magnitude in magnitudes: 
    print(magnitude)

At each step in the iteration the property magnitude has as its value the next item in the list.

It is also possible to access individual elements of the list by position. This form of access is shown in the following example that continues the text representation begun above. The notation property[position] is used to denote the position element in the list that is the value of property. The first example sets the property tomorrow to the value that is in first position of the list that is the value of the property temperature. As a convenience we will often just write “the first element of the temperature list” to mean “the first element of the list that is the value of the property temperature”. Using this more convenient language, the example also shows that the value of the property future is set to the last element of the temperature list. The other examples are similar.

tomorrow = temperatures[0]
future = temperatures[6]
biggest = magnitude[3]
big_city_name = cities[2]

The construction aspect for a list means that when we are building a list (for example, in the transform pattern of iteration) the list is built by adding new elements to the end of the list. Starting with an empty list the first value appended becomes the first element in the list, the second value appended to that list becomes the second value in the list, etc. There is no restriction on the number of elements that are in the list. These operations are shown in the code below.

magnitudes = [ ]             # this makes the value of the property be an empty list
magnitudes.append(2.1)       # the list is now [2.1]
magnitudes.append(1.1)       # the list is now [2.1, 1.1]
magnitudes.append(3.7)       # the list is now [2.1, 1.1, 3.7]

 

In this example, note that each element is added at the end of the list because a list is an ordered collection of values.

Dictionaries

The syntax for representing a dictionary is shown in the example below. Recall that a dictionary is an unordered collection of key-value pairs. In Python, the key and value pairs of a dictionary are written with a colon between the key and value: key : value. In the simple example of a book shown below, the pair ‘pages’ : 320 would mean that the int value 320 is associated with the key ‘pages' to express the fact that a given book as 320 pages. The pair ‘price’ : 7.48 would mean that the value 7.48 of float type is associated with the key ‘price’ to express the cost of the book. The ‘author’ key would be associated with a value of a string type to denote the book’s author. In the textual representation, a dictionary consists of some number of comma separated key:value pairs:

aBook = { 'pages' : 320, 'price' : 7.48, 'author' : 'J.K. Rowlings' ,
               'title' : 'Harry Potter #1', 'paperback' : True }

The curly brackets delimit the beginning and the end of the dictionary. In this case the value assigned to the property “aBook” is the entire dictionary.

As noted earlier, a dictionary is unordered because the key:value pairs can be written in any order without changing the meaning of what is represented. For example, the book described above could be written:

aBook = { 'author' : 'J.K. Rowlings',  'pages' : 320, 'price' : 7.48 ,
               'paperback' : True, 'title' : 'Harry Potter #1'}

The unordered nature of a dictionary is also reflected in the fact that these two sentences are the same

  • “The book Harry Potter #1 was written by J.K. Rowlings.”
  • “J.K. Rowlings wrote the book Harry Potter #1.”

The meaning of these sentences is the same because the order in which we state the properties of the book does not change the description of the book.

The dictionary’s access property means that a value is retrieved from the dictionary by specifying the key associated with that value. To find the length of the book in the above example the key ‘pages’ would be used to access the value 320. Accessing the value associated with a key can be written as:

length = aBook['pages']
how_much = aBook['price']

to mean that the property length should be set to the value associated with the key ‘pages’ in the dictionary aBook and that the property how_much should be set to the value associated with the key ‘price’ in the dictionary aBook.

A dictionary can be updated by specifying a new value that should be associated with a given key in the dictionary. For example, reducing the price of the example book from its current value of 7.48 to 6.50 is done by:

aBook['price'] = 6.50   # the key price now has the value 6.50

The construction property of a dictionary means that we add a new element to the dictionary simply by specifying a new key-value pair for the dictionary. In Python, to add a weight to the above book dictionary we could write:

book['weight'] = 2.7

to mean that the book dictionary now contains the key-value pair ‘weight’ : 2.7 in addition to all key-value pairs already in the dictionary. Of course, the new key, weight in this example, must be different from any key currently in the dictionary.

Notice that the update and the construction operations are written similarly in Python. The difference between them is that with the update the specified key already exists in the dictionary and the value associated with this key is being changes while with the construction operation the specified key does not exist in the dictionary and a new key-value is added to the dictionary.