Built-in Data Structures In Python

Introduction

Python has always been classified as a general-purpose programming language due to it's versatility, from web dev to data science.
However, data has become a lifestyle and has to be considered during systems design. All the data collected needs to be store and accessed efficiently. To attain this , data structures come in hand.

1. What's a Data structure ?

A data structure is a specialized format for organizing, processing, retrieving and storing data.

Types of Data Structures

1. Built-in

As the name suggest, Built-in data structures are predefined data structures that come along with python.Can be accessed from any python environment.
a.Lists
They are used to store data of different data types in a sequential manner.Every member of the list are assigned unique address called index.The first member of a list is assigned number 0. Members of the list can accessed in two ways; Positive indexing(the most common method) and Negative indexing.All this will be demonstrated in examples.
List are created by assigning square rackets to a variable and add a values accordingly.
Implementation

#creating empty values
cars = []
print(cars)
#adding elements to a list
cars = ["Audi",3.2,"Subaru",5,"Romeo",432.789]
print(cars)

Output:
[]
["Audi",3.2,"Subaru",5,"Romeo",432.789]

List Methods

These are built-in operations for manipulating lists. We shall explore them with examples.

Example

cars = ["Audi",3.2,"Subaru",5,"Romeo",432.789]
print(cars)
# append 
cars.append("Toyota")
print(cars)
#copy
cars_1 = cars.copy()
print(cars_1)
# clear
cars_1.clear()
print(cars_1)
# count
print(cars.count("Audi"))
# Extend
fruit = ["kiwi","cherry","grapes"]
city = ["morotro","iraq","texas","qalit"]
fruit.extend(city)
print(fruit)
# index
cars = ["Audi",3.2,"Subaru",5,"Toyota","Romeo",432.789]
print(cars.index("Toyota"))
#insert
fruits = ['apple', 'banana', 'cherry']
fruits.insert(1, "orange")
print(fruits)
#pop
fruits = ['apple', 'banana', 'cherry']
fruits.pop(1)
print(fruits)

output:
["Audi",3.2,"Subaru",5,"Romeo",432.789]
["Audi",3.2,"Subaru",5,"Romeo",432.789,"Toyota"]
["Audi",3.2,"Subaru",5,"Romeo",432.789]
[]
1
["kiwi","cherry","grapes","morotro","iraq","texas","qalit"]
4
['apple','orange','banana', 'cherry']

['apple','cherry']

b.Tuples

These are data structure that store an ordered sequence of values. Tuples are immutable. This means you cannot change the values in a tuple. Tuples are defined with parenthesis.

NOTE

• Tuples allow duplicate values
• it is not necessary to enclose the tuple elements in parentheses
• Tuples allow use of heterogeneous data

Implementation

realk = ("Texas","Estonia","Monaco")
print(realk)
# duplicate values
realk1 = ("Texas","Estonia","Monaco","Texas")
print(realk1)
# No parentheses
realk = 'Texas','Estonia','Monaco'
print(realk)
# Heterogeneous data
employee=(1, 'Steve', True, 25, 12000)
print(employee)

output:
('Texas','Estonia','Monaco')
('Texas','Estonia','Monaco','Texas')
('Texas','Estonia','Monaco')
(1, 'Steve', True, 25, 12000)

Tuples Operations

Tuple is unchangeable. So, once a tuple is created, any operation that seeks to change its contents is not allowed. For instance, trying to modify or delete an element of any tuple will result in an error.

Example

t1=(1,2,3)
t2=(4,5,6)         
t1+t2              
(1, 2, 3, 4, 5, 6) 
t2+(7,)            
(4, 5, 6, 7)

Example

>>> t1=(1,2,3)
>>> t1*4                             
(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3)

Example

>>> t1=(1,2,3,4,5,6)     
>>> t1[3]                
4                        
>>> t1[-2]               
5

>>> t1=(1,2,3,4,5,6) 
>>> t1[1:3]              
(2, 3)                   
>>> t1[3:]               
(4, 5, 6)                
>>> t1[:3]               
(1, 2, 3)

Example

>>> t1=(1,2,3,4,5,6) 
>>> 5 in t1
True                
>>> 10 in t1 
False

Example

>>> t1=(1,2,3,4,5,6) 
>>> 4 not in t1 
False                    
>>> 10 not in t1
True

c.Dictionary

Dictionaries are used to store data values in key:value pairs.

Characteristics of Dictionaries

• They are ordered:The items have a defined order, and that order will not change.
• They are Changeable: that we can change, add or remove items after the dictionary has been created.
• They do not allow duplicates: cannot have two items with the same key
• The values of a dictionaries can be of any data type.

NB: As of Python version 3.7, dictionaries are ordered. In Python 3.6 and earlier, dictionaries are unordered.

Dictionary methods

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
members.clear()
print(members)

Output:
{}

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
copy_members = members.copy()
print(copy_members)

Output:
{'sales':'Rhorda','Accounts':'Mustafa','Technical':'Naliaka'}

Example

departmet = ("account","IT","Engineering")
members = ("Tityo")
dict_1 = dict.fromkeys(departmet,members)
print(dict_1)

Output:
{'account': 'Tityo', 'IT': 'Tityo', 'Engineering': 'Tityo'}

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Acc_1 = members.get("Accounts")
print(Acc_1)

Output:
Mustafa

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Acc_1 = members.items()
print(Acc_1)

Output:
dict_items([('sales', 'Rhorda'), ('Accounts', 'Mustafa'), ('Technical', 'Naliaka')])

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Acc_1 = members.keys()
print(Acc_1)

Output:
dict_items(['sales','Accounts','Technical'])

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Remove_member = members.pop("sales")
print(Remove_member)

Output:
{'Accounts':'Mustafa','Technical':'Naliaka'}

NB:Before Python 3.7, the popitem() method removes a random item.
Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Remove_member = members.popitem()
print(Remove_member)

Output:
{'Accounts':'Mustafa','Accounts': 'Mustafa'}

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
Remove_member = members.setdefault("sales","phagra")
print(Remove_member)
Output:
Rhorda

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
New_member = members.update({"Engineering":"phagra"})
print(New_member)
Output:
{'sales':'Rhorda','Accounts':'Mustafa','Technical':'Naliaka','Engineering':'phagra'}

Example

members = {
  "sales": "Rhorda",
  "Accounts": "Mustafa",
  "Technical": "Naliaka"
          }
member_values = members.values()
print(member_values)
Output:
dict_values(['Rhorda','Mustafa','Naliaka'])

d.Sets
A set is an unordered collection of items.

Characteristics of Sets

• Every set element is unique (no duplicates)
• They must be unchangeable.
• It is created by placing all the items (elements) inside curly braces {}, separated by comma, or by using the built-in set() function.

Set Methods

Example

x = {"facebook", "instagram", "whatsapp"}
x.add("twitter")
print(x)

Output:
{'facebook', 'instagram', 'whatsapp','twitter'}

Example

x = {"facebook", "instagram", "whatsapp"}
x.clear()
print(x)

Output:
set()

Example

x = {"facebook", "instagram", "whatsapp"}
y = x.copy()
print(y)

Output:
{'facebook','instagram', 'whatsapp'}

Example

x = {"facebook", "instagram", "whatsapp"}
x.pop()
print(x)

Output:
{'instagram','whatsapp'}

Example

x = {"facebook", "instagram", "whatsapp"}
x.remove("facebook")
print(x)

Output:
{'instagram','whatsapp'}

Example

x = {"facebook", "instagram", "whatsapp"}
y = {"google", "microsoft", "facebook"}

x.symmetric_difference(y)
print(x)

Output:
{'instagram','whatsapp','google','microsoft'}

Example

x = {"facebook", "instagram", "whatsapp"}
y = {"google", "microsoft", "facebook"}

x.symmetric_difference_update(y)
print(x)

Output:
{'instagram','whatsapp','google','microsoft'}

NB:You can specify as many sets you want, separated by commas.
It does not have to be a set, it can be any iterable object.
If an item is present in more than one set, the result will contain only one appearance of this item.

Example

x = {"facebook", "instagram", "whatsapp"}
y = {"google", "microsoft", "apple"}
w = {"google","twitch","whatsapp"}
x.union(y,w)
print(x)

Output:
{'facebook','instagram','microsoft','apple','whatsapp','google','twitch'}

Example

x = {"facebook", "instagram", "whatsapp"}
y = {"google", "microsoft", "apple"}
x.update(y)
print(x)

Output:
{'facebook','instagram','whatsapp','google','microsoft','apple'}

In my next article, I will be discussing User-defined Data Structures in python. Stay tuned by following me.
Your comment is highly-valued

RESOURCES

• https://www.programiz.com/python-programming/set
• https://www.w3schools.com/python/ref_dictionary_values.asp