How to use Data Structures in Python

Learn Python Data Structures in Detail with Real Examples
Written by Paayi Tech |03-May-2019 | 0 Comments | 1314 Views

In computer science, the data structure is one of the most important phenomena. It has more importance than classes. The data structure is a way of organizing the data in a proper format which make easy to access and to modify the data at the time of need. More precisely we can say data structure is a way of organizing data and making a relationship between them.

There are lots of data structures, but basic data structures are divided into two categories. The first one is linear data structures and the second one is the nonlinear data structure.

The linear data structures contain:

  • Arrays
  • Link List
  • Stack
  • Queues

Also, nonlinear contains:

  • Tree
  • Graph

Data Structures in Python



In python there is no built-in array data structure; alternatively, we can use a list for that function. However, at a higher level we can see how to use arrays in python.

In addition to the data mentioned above, structure python provides other data structures too like sets and tuples.

Today we see how to use sets and tuples in python.



Set is a type of data structures in python. It is similar to the mathematics set. There is no repetition of an element in a set. Unlike list and arrays where the elements are stored in order, there is no order in sets. The position of sets element is random. We can apply all the functionality of set as we have studied in math in python too. We can add or remove the element from the set. We can apply union, intersection, etc. in sets. Any immutable can be inserted to the sets. For example, we can set a tuple as an element, but the list cannot be inserted into a set.


How to define Sets:

In python, sets can be defined by the set () function or by substituting the values within the curly braces. Following are the method to initiate the sets in python.

  • Method 1:
    >> set("Python")
  • Method 2:
    >> set_variable = {"p","y","t","h","o","n"}


Order of Set:

The order of an element is not essential in sets. The elements positions are changed when the sets are executed as follows:


Orders of Sets Figure 2

In figure 2 above the order of an element is changed as we can see.


Non-Repetition of Elements:

Inset no element is repeated. The repeated element is removed from the set. Figure 3 shows this phenomenon:


Non Repetition of Elements



Add element:

Inset we can add element by calling the add function. Following method is used to add the element.

set1 = {1,2,3,4}
set1.add (5)






Removing an Element:

To remove the element there are two methods one is by calling remove function, and other is by calling discard function. Both take one argument, and that is the value of the element that is to be removed. Following code can be used to remove elements

set1 = {1,2,3,4,5,6,7}
set1.pop ()


{1, 2, 3, 4, 5, 6}

{1, 2, 3, 4, 5}

{2, 3, 4, 5}



Operation on Set:

  • Union Operation:
    Union operation is done to merge all elements of two set and combined to make it one set. Following is the method of union operation in python:

a = {1,2,3,4,5}
b = {6,7,8}





  • Intersection Operation:
    It returns the common element of both set “A” and B. Following is the code of intersection:

a = {1,2,3,4,5}
b = {5,6,7,8}




  • Symmetric Difference:
    It returns the element that either belongs to A or B but not from both. Following code can be used:

a = {1,2,3,4,5,6}
b = {1,2,3,4,5,7}






  • Subset:
    To check if set A is a subset of set B, it can be verified by (A <= B). It returns true if it is subset otherwise false
  • Superset:

To check if A is a superset of B, it can be verified by (A >= B). It returns true if it is superset; otherwise, it returns false.


A tuple is another type of data structure. It is similar to the list, but it is immutable. By immutable we mean that tuple cannot be changed. Once the values are assigned to the tuple no more value can be added or deleted from the tuple. Tuple uses parentheses whereas in list square brackets are used.

Tuples are an essential data structure. Mostly it is used where the data should not be changed just like a constant variable.


How to initialize tuple:

Tuple can be created by two methods one is by the keyword method and the second one is by initializing the variable. Following methods is used to create the tuple.


tuple1 = (1,2,3,4,5)
tuple2 = tuple("Python")


(1, 2, 3, 4, 5)

('P', 'y', 't', 'h', 'o', 'n')


Assigning the value of a variable in a tuple:

We can assign multiple variables in one line by using the tuple. This allows the code to be more compact and written in less line of code which ultimately makes the code cleaner. Following is the example of creating multiple variables in one line as follows:

string1, integer1, float1 = ("Python", 100, 3.47)
print (string1)
print (integer1)
print (float1)






Comma Separated Value:

If the variable is initiated without parentheses separated by coma’s, python convert it into tuples. This tuple can be used then. The above example can be modified without parentheses as follows:

a = "Python",100,3.47
string1, integer1, float1 = a
print (string1)
print (integer1)
print (float1)





As we can see, there is no difference in the output.


Changing in the tuple:

As we discussed earlier tuple values are immutable; they are not changeable. If we try to change or update the value of tuple python compiler can generate an error.

tuple1 = ("Python",100,3.47)
tuple1[0] = "Programming"



Traceback (most recent call last):

  File "/home/lalatoofani/", line 3, in

    tuple1[0] = "Programming"

TypeError: 'tuple' object does not support item assignment


As the error indicates, tuple doesn’t allow any changes which make it immutable.

 As we see earlier that we cannot change the tuple and its value. This is valid only for the data types like string, integer or float but what happens if a tuple contains mutable data type as a list in it. In such scenario value of list can be changed within a tuple. Let us take a look at how we can change the value of mutable data type within a no mutable tuple:

tuple1 = ("Python",100,3.47, [1,2,3,4,5,6])
tuple1[3][2] ="New Value"


In the above code, we first initialize a tuple which has 4 value. At index 3 we have a list that contains multiple values. Now by accessing the 3rd index and then accessing its 2nd index, we change the value of the list from three to new value. The program can be run to check its output:



('Python', 100, 3.47, [1, 2, 'New Value', 4, 5, 6])


As we can see from the above line the value has been changed from 3 to New Value.


Built-in Function of tuples:

  1. max (): max function returns the maximum value of the tuple
  2. min (): min function returns the minimum value of the tuple
  3. Len (): len function returns the length of a tuple.
  4. tuple (): tuple function converts any list or string into tuples.
  5. sorted (): returns the sorted tuple


Checking Existence:

Generally in other languages to check if the value is present in a data structure or not, we have to iterate to all of the value and match from our desired value. However, no in the case of python. Python allows the user to check value existence in just one line as follows:

tuple1 = ("Python",100,3.47, [1,2,3,4,5,6])
print ("Python" in tuple1)
print (100 not in tuple1)


The output of the above program is True and then False as “Python” is in the tuple and the second statement we say 100 not present in tuple which is false as 100 is in the tuple


Accessing tuple:

The following methods can access the value of tuple:

  1. Looping
  2. Indexing
  3. Negative Indexing



In the looping technique, we loop over each element of the tuple to get the value. Following are the ways to loop over the tuple:

tuple1 = ("Python",100,3.47, [1,2,3,4,5,6])
for e in tuple1:
for i in range(len(tuple1)):

Both these loops can perform the same action.



By the method of indexing, we have to provide the index to access the value. Following are the method of indexing:

tuple1 = ("Python",100,3.47, [1,2,3,4,5,6])

Output 3.47


Output ("Python",100,3.47)



Negative Indexing:

Negative indexing is the opposite of indexing. As indexing starts from the start negative indexing starts from last as follows:

tuple1 = ("Python",100,3.47, [1,2,3,4,5,6])





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