Module 2: Python Data Structures

About Lists and Tuples

A basic data structure and the methods commonly used in Python.

Tuples

An ordered sequence and immutable (fixed pair of data values).

tup = ("Code", 10, 2.4)
tup_2 = ("Python", 2)
 
print(tup + tup_2) # Output: ('Code', 10, 2.4, 'Python', 2)
print(tup[1:3]) # Output: (10, 2.4)
 
 
# Nested tuple
tup = (12, 23, 36, 20, 51, 40, (200, 240, 100))
 
print(tup[6][0]) # Output: 200

Lists

Essentially used in python data structures and they are mutable.

# Append method
lt = ["Code", 10, 2.4]
lt.append(["Python", 2]) # adding to the list as a single element
 
print(lt) # Output: ['Code', 10, 2.4, ['Python', 2]]
 
# Extend method
lt = ["Code", 10, 2.4]
lt.extend(["Python", 2]) # adding to the list one or multiple elements
 
print(lt) # Output: ['Code', 10, 2.4, 'Python', 2]
 
 
## Modifying Lists
lt = ["Code", 10, 2.4]
 
lt[0] = "Python" # Output: ["Python", 10, 2.4]
del(lt[2]) # Output: ["Python", 10]
 
## Converting string to list
data_seq = "Mike,12,2000"
list_seq = data_seq.split(',')
 
print(list_seq) # Output: ['Mike', '12', '2000']

Methods used in Python Data Structure

strip()

It used to remove leading and trailing characters from a string.

my_string = "--Hello World--"
 
print(my_string.strip("-")) # Output: Hello World

copy()

A method used to create a shallow copy of a list.

my_list = [1, 2, 3, 4, 5]
new_list = my_list.copy() print(new_list)
 
# Output: [1, 2, 3, 4, 5]

insert()

Inserting an element in specific order.

my_list = [1, 2, 3, 4, 5]
my_list.insert(2, 6)
 
# Output: [1, 2, 6, 3, 4, 5]

pop()

A method used to remove the element at the specified index.

my_list = [10, 20, 30, 40, 50]
removed_element = my_list.pop() # Removes and returns the last element
print(removed_element)
# Output: 50
 
print(my_list) # Output: [10, 20, 30, 40]

remove()

A method used to removes the specified value in the list.

my_list = [10, 20, 30, 40, 50]
my_list.remove(30) # Removes the element 30
 
print(my_list) # Output: [10, 20, 40, 50]

reverse()

A method used to reverse the order of elements in a list.

my_list = [1, 2, 3, 4, 5]
my_list.reverse()
 
print(my_list) # Output: [5, 4, 3, 2, 1]

sort()

A method used to sort elements in the list.

my_list = [5, 2, 8, 1, 9]
my_list.sort(reverse=True)
 
print(my_list) # Output: [9, 8, 5, 2, 1]

Dictionaries

A dictionary consists of keys and values. It is helpful to compare a dictionary to a list. Instead of being indexed numerically like a list, dictionaries have keys. These keys are the keys that are used to access values within a dictionary.

Example

The best example of a dictionary can be accessing person’s detais using the social security number.
Here the social security number which is a unique number will be the key and the details of the people will be the values associated with it.

Dictionaries in Python are an unordered, mutable, and indexed collection where each key is unique and maps to a value. Keys can only be strings, numbers, or tuples, but values can be any data type.

Creating a Dictionary

Dict = {"key1": 1, "key2": "2", "key3": [3, 3], "key4": (4, 4), ('key5'): 5}

Modification:

Dict.update({key: value}) # Add another key-value pair
 
Dict.clear() # Removing all key-value pairs
 
# Removing specific key-value pair
Dict.pop({key})
del Dict[key]

Retrieving:

Dict.keys() # Get all the keys in dictionary
Dict.values() # Get all the values in dictionary
 
list(Dict.keys()) # Dictionary as a list
Dict.copy() # Create a shallow copy
 
# Retrieves all key-value pairs as tuples and converts them into a list of tuples.
items_list

Verifying

# Verify the key is in the dictionary
if 1 in Dict.values():
	...
 
if "Key1" in Dict.keys():
	...

Sets

A set is an unordered collection of unique elements.

set1 = {1,2,3,4,5,6,8,7,6,5,3,2,1,1}
print(set1) # Output: {1, 2, 3, 4, 5, 6, 7, 8}
 
set1.add(1) # Output still the same
set1.remove(1) # Output: {2, 3, 4, 5, 6, 7, 8}
 
# Verify an element in the set
1 in set1 # True

Set logic operations:

set1 = {1,2,3,4,5}
set2 = {4,5,6,7,8}
 
intersection = set1.intersection(set2) # Output: {4,5}
difference = set1.difference(set2) # Output: {1,2,3}
union = set1.union(set2) # Output: {1,2,3,4,5,6,7,8}

superset and subset:

set1 = {1,2,3,4,5}
set2 = {4,5}
 
issupertset = set1.issuperset(set2) # Output: True
issubset = set2.subset(set1) # Output: True