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.

Methods	Description
append()	Adds an element at the end of the list
clear()	Removes all the elements from the list
copy()	Returns a copy of the list
count()	Returns the number of elements with the specified value
extend()	Add the elements of a list (or any iterable), to the end of the current list
index()	Returns the index of the first element with the specified value
insert()	Adds an element at the specified position
pop()	Removes the element at the specified position
remove()	Removes the first item with the specified value
reverse()	Reverses the order of the list
sort()	Sorts the list

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.

Operator
The + operator returns a tuple containing all the elements of the first and the second tuple object.

Example

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

Operator
The * operator Concatenates multiple copies of the same tuple.

Example

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

Operator
The [] operator Returns the item at the given index. A negative index counts the position from the right side.

Example

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

Operator
The [:] operator returns the items in the range specified by two index operands separated by the : symbol.
If the first operand is omitted, the range starts from zero. If the second operand is omitted, the range goes up to the end of the tuple.

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

Operator
The in operator returns true if an item exists in the given tuple.

Example

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

Operator
The not in operator returns true if an item does not exist in the given tuple.

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

Method	Description
clear()	Removes all the elements from the dictionary

Example

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

Output:
{}

Method	Description
copy()	Returns a copy of the dictionary

Example

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

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

Method	Description
fromkeys()	Returns a dictionary with the specified keys and value.Can be used to make dictionary with the same values

Example

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

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

Method	Description
get()	Returns the value of the specified key

Example

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

Output:
Mustafa

Method	Description
items()	Returns a list containing a tuple for each key value pair.The view object contains the key-value pairs of the dictionary, as tuples in a list.

Example

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

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

Method	Description
keys()	Returns a list containing the dictionary's keys.The view object contains the keys of the dictionary, as a list.

Example

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

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

Method	Description
pop()	Removes the element with the specified key

Example

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

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

Method	Description
popitem()	Removes the last inserted key-value pair

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'}

Method	Description
setdefault()	Returns the value of the specified key. If the key does not exist: insert the key, with the specified value

Example

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

Method	Description
update()	Updates the dictionary with the specified key-value pairs.The specified items can be a dictionary, or an iterable object with key value pairs.

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'}

Method	Description
values()	Returns a list of all the values in the dictionary.The view object contains the values of the dictionary, as a list.The view object will reflect any changes done to the dictionary

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

Method	Description
add()	Adds an element to the set

Example

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

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

Method	Description
clear()	Removes all the elements from the set

Example

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

Output:
set()

Method	Description
copy()	Returns a copy of the set

Example

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

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

Method	Description
difference()	Returns a set containing the difference between two or more sets

Method	Description
difference_update()	Removes the items in this set that are also included in another, specified set

Method	Description
discard()	Remove the specified item

Method	Description
intersection()	Returns a set, that is the intersection of two other sets

Method	Description
intersection_update()	Removes the items in this set that are not present in other, specified set(s)

Method	Description
isdisjoint()	Returns whether two sets have a intersection or not

Method	Description
issubset()	Returns whether another set contains this set or not

Method	Description
issuperset()	Returns whether this set contains another set or not

Method	Description
pop()	Removes an element from the set randomly

Example

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

Output:
{'instagram','whatsapp'}

Method	Description
remove()	Removes the specified element

Example

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

Output:
{'instagram','whatsapp'}

Method	Description
symmetric_difference()	Returns a set with the symmetric differences of two sets

Example

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

x.symmetric_difference(y)
print(x)

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

Method	Description
symmetric_difference_update()	inserts the symmetric differences from this set and another

Example

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

x.symmetric_difference_update(y)
print(x)

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

Method	Description
union()	Return a set containing the union of sets

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'}

Method	Description
update()	Update the set with the union of this set and others

Example

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

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