Introduction to Python Lesson 5: Collections and Functions

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Python Collections

There are four collection data types in the Python programming language:

• List is a collection which is ordered and mutable (can add/delete elements to a list). Duplicate members are allowed.
• Tuple is a collection which is ordered and immutable (can not change once created). Duplicate members are allowed.
• Set is a collection which is unordered and unindexed. It is mutable (can add/delete elements to a set). No duplicate members.
• Dictionary is a collection which is unordered, mutable (can add/delete elements to a dictionary) and indexed. No duplicate members.

Data Type	Ordered?	Mutable ?	Indexed ?	Allow Duplicate Member ?
List	Yes	Yes	Yes	Yes
Tuple	Yes	No	Yes	Yes
Set	No	Yes	No	No
Dictionary	No	Yes	Yes	No

When choosing a collection type, it is useful to understand the properties of that type. Choosing the right type for a particular data set could mean retention of meaning, and, it could mean an increase in efficiency or security.

Python Tuple

Tuple is an ordered sequence of items same as a list. The only difference is that tuples are immutable. Tuples once created cannot be modified. In Python tuples are written with round brackets () where items are separated by commas, for example:

fruits = ("apple", "banana", "orange")
print(fruits)

You can access tuple items by referring to the index number, inside square brackets:

fruits = ("apple", "banana", "orange")

#print out the second item in the tuple
print(fruits[1])

Negative Indexing

In Python, negative indexing means beginning from the end, -1 refers to the last item, -2 refers to the second last item etc. Negative indexing can be used both in List and Tuple, for example:

primes = [2,3,5,7,11,13,17]
#print out the last number in the list
print(primes[-1])

fruits = ("apple", "banana", "orange")

#print out the second last item
print(fruits[-2])

Python Set

Set is an unordered collection of unique items. In Python sets are items written with curly brackets { }. Different from List and Tuple, items in a set are not ordered, that means items in a set can not be accessed by referring to an index.

We can check if a specified variable is present in a set by using the in keyword.

fruits = {'apple', 'banana', 'orange'}

a = 'carrot'
if a in fruits:
    print(a, " is a fruit")
else:
    print(a, " is not a fruit")

We can also iterate through the set items using a for loop, as shown below:

fruits = {'apple', 'banana', 'orange'}

for a in fruits:
   print(a)

Set is mutable, which means we can add/delete items to an existing set, as shown below. Please note that if the item to remove does not exist, remove() will raise an error.

fruits = {'apple', 'banana', 'orange'}

fruits.add('watermelon')
print(fruits)

fruits.remove('banana')
print(fruits)

There are several ways to operate on two or more sets in Python.

| or union() for union.

& or intersection() for intersection.

– or difference() for difference

^ or symmetric_difference() for symmetric difference

You can use the union() method that returns a new set containing all items from both sets, or the update() method that inserts all the items from one set into another. This is written as shown in the example below:

# Program to perform different set operations
# as we do in  mathematics

# sets are define
A = {0, 2, 4}
B = {1, 2, 3}

# union
print("Union :", A | B)
print("Union :", A.union(B))

# intersection
print("Intersection :", A & B)
print("Intersection :", A.intersection(B))

# difference
print("Difference :", A - B)
print("Difference :", A.difference(B))

# symmetric difference
print("Symmetric difference :", A ^ B)
print("Symmetric difference :", A.symmetric_difference(B))

Python Dictionary

In Python, Dictionary is an unordered collection of key-value pairs. Dictionaries are defined within braces {} with each item being a pair in the form key:value. Key and value can be of any type.

# empty dictionary
myDict = {}
print(myDict)

# empty dictionary
myDict = dict()
print(myDict)

# dictionary with integer keys
myDict = {1: 'blue', 2: 'ball'}
print(myDict)

# dictionary with mixed keys
myDict = {'color': 'blue', 1: 'orange'}
print(myDict)

# from list of tuples
myDict = dict([('color','red'), (1,'apple')])
print(myDict)

Python functions

In Python, a function is a group of related statements that performs a specific task. Python function is a reusable block of code. Functions help break our program into smaller and modular chunks. As our program grows larger and larger, functions make it more organized and manageable.
Furthermore, it avoids repetition and makes the code reusable.

Syntax of a Python Function

def function_name(parameters):
	statement
  statement
  ...
  return return_value

A Python Function follows the following rules:

• Keyword def that marks the start of the function header.
• A function name to uniquely identify the function. Function name follows the same rules as variable names in Python.
• Function parameters (arguments) through which we pass values to a function. They are optional.
• A colon (:) to mark the end of the function header.
• The function body consists of one or more valid python statements.
• Statements in the function body must have the same indentation level.
• An optional return statement to return a value from the function.

Example of a Python function:

def hello(name):
    greetString = "Hello, " + name
    return greetString

print(hello('World!'))

Please note that it is possible to define a function with zero arguments:

def hello():
    greetString = "Hello, " + "World!"
    return greetString

print(hello())

It is also possible to define a function with do not return any value.
You can just simple omit the return statement in your function body.

def hello():
    greetString = "Hello, " + "World!"
    print(greetString)

hello()

Calling Functions

Once we have defined a function, we can call it from another function, program or even the Python prompt.
To call a function we simply type the function name with appropriate parameters.

Consider the following code. It creates a variable, text, and then calls a function re.sub10 to substitute all occurrences of the string ‘OI’ with the more informative string ‘Operating Income’. Notice that we passed three arguments to re.sub. The first argument is the search text, the second argument is the replacement text, and the third argument is the text to search.