Set Operations in Python

Set Operations in Python

In this blog, we will learn set operations. We will see add(), remove(), update(), union(), intersection(), difference() and many more functions with examples.

What is set?

A set object is an unordered collection of distinct hashable objects. Common uses include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

Like other collections, sets support x in set, len(set), and for x in set. Being an unordered collection, sets do not record element position or order of insertion. Accordingly, sets do not support indexing, slicing, or other sequence-like behavior. Set items can appear in a different order every time you use them, and cannot be referred to by index or key.

There are currently two built-in set types, set and frozenset.

The set type is mutable — the contents can be changed using methods like add() and remove(). Since it is mutable, it has no hash value and cannot be used as either a dictionary key or as an element of another set.

The frozenset type is immutable and hashable — its contents cannot be altered after it is created; it can therefore be used as a dictionary key or as an element of another set.

The constructors for both classes work the same:

class set([iterable]) class frozenset([iterable])

Return a new set or frozenset object whose elements are taken from iterable.

Instances of set and frozenset provide the following operations:

len(s)

x in s

x not in s

isdisjoint(other)

issubset(other)

issuperset(other)

union(*others)

intersection(*others)

difference(*others)

symmetric_difference(other)

copy()

Create sets

In [1]:
A = {1, 2, 3, 4, 5}
B = {10, 3, 5, 9, 8}
In [2]:
A
Out[2]:
{1, 2, 3, 4, 5}
In [3]:
B
Out[3]:
{3, 5, 8, 9, 10}

Check the len of set A

In [4]:
len(A)
Out[4]:
5

Test x for membership in set.

In [5]:
2 in A
Out[5]:
True
In [6]:
2 in B
Out[6]:
False

Test x for non-membership in set.

In [7]:
20 not in A
Out[7]:
True
In [8]:
5 not in B
Out[8]:
False

isdisjoint

isdisjoint(other)

Return True if the set has no elements in common with other. Sets are disjoint if and only if their intersection is the empty set. Means returns whether two sets have a intersection or not
In [9]:
A.isdisjoint(B)
Out[9]:
False

issubset(other)

set <= other

Test whether every element in the set is in other.
In [10]:
A.issubset(B)
Out[10]:
False

issuperset(other)

set >= other

Test whether every element in other is in the set.

set > other

Test whether the set is a proper superset of other, that is, set >= other and set != other.
In [11]:
A.issuperset(B)
Out[11]:
False

Add item in set A

In [12]:
A = {1, 2, 3, 4, 5}
B = {10, 3, 5, 9, 8}
print(A)
print(B)

{1, 2, 3, 4, 5}
{3, 5, 8, 9, 10}
In [13]:
A.add(12)
In [14]:
A
Out[14]:
{1, 2, 3, 4, 5, 12}
In [15]:
B
Out[15]:
{3, 5, 8, 9, 10}

remove(elem)

Remove element elem from the set. Raises KeyError if elem is not contained in the set.
In [16]:
A.remove(5)
In [17]:
A
Out[17]:
{1, 2, 3, 4, 12}

pop()

Remove and return an arbitrary element from the set. Raises KeyError if the set is empty.
In [18]:
A.pop()
Out[18]:
1
In [19]:
A
Out[19]:
{2, 3, 4, 12}

discard(elem)

Remove element elem from the set if it is present.
In [20]:
A.discard(4)
In [21]:
A
Out[21]:
{2, 3, 12}

Set Union

union(s): Union of A and B is a set of all elements from both sets. Using the operator '|' between 2 existing sets is the same as writing My_Set1.union(My_Set2)..

In [22]:
A|B
Out[22]:
{2, 3, 5, 8, 9, 10, 12}
In [23]:
A.union(B)
Out[23]:
{2, 3, 5, 8, 9, 10, 12}

use union function on B

In [24]:
B.union(A)
Out[24]:
{2, 3, 5, 8, 9, 10, 12}

Set Intersection

intersection(*others)

set & other & ...

Return a new set with elements common to the set and all others.

Intersection of A and B is a set of elements that are common in both the sets.

In [25]:
A & B
Out[25]:
{3}
In [26]:
A.intersection(B)
Out[26]:
{3}
In [27]:
B.intersection(A)
Out[27]:
{3}

Set Difference

difference(*others)

set - other - ...

Return a new set with elements in the set that are not in the others.
In [28]:
A
Out[28]:
{2, 3, 12}
In [29]:
B
Out[29]:
{3, 5, 8, 9, 10}

Difference of the set B from set A(A - B) is a set of elements that are only in A but not in B.

In [30]:
A - B
Out[30]:
{2, 12}
In [31]:
A.difference(B)
Out[31]:
{2, 12}

B - A is a set of elements in B but not in A.

In [32]:
B - A
Out[32]:
{5, 8, 9, 10}
In [33]:
B.difference(A)
Out[33]:
{5, 8, 9, 10}

Symmetric Difference

set ^ other

Return a new set with elements in either the set or other but not both.

The symmetric difference between two sets is the set of all the elements that are either in the first set or the second set but not in both.

In [34]:
A ^ B
Out[34]:
{2, 5, 8, 9, 10, 12}
In [35]:
A.symmetric_difference(B)
Out[35]:
{2, 5, 8, 9, 10, 12}
In [36]:
B.symmetric_difference(A)
Out[36]:
{2, 5, 8, 9, 10, 12}

update(*others)

set |= other | ...

Update the set, adding elements from all others.
In [37]:
A.update(B)
In [38]:
A
Out[38]:
{2, 3, 5, 8, 9, 10, 12}

intersection_update(*others)

set &= other & ...

Update the set, keeping only elements found in it and all others.
In [39]:
A
Out[39]:
{2, 3, 5, 8, 9, 10, 12}
In [40]:
B
Out[40]:
{3, 5, 8, 9, 10}
In [41]:
A.intersection_update(B)
In [42]:
A
Out[42]:
{3, 5, 8, 9, 10}

difference_update(*others)

set -= other | ...

Update the set, removing elements found in others.
In [43]:
A.difference_update(B)
In [44]:
A
Out[44]:
set()

clear()

Remove all elements from the set.
In [45]:
A = {1, 2, 3, 4, 5}
A
Out[45]:
{1, 2, 3, 4, 5}
In [46]:
A.clear()
In [47]:
A
Out[47]:
set()

copy()

Return a shallow copy of the set.
In [48]:
C = B.copy()
In [49]:
C
Out[49]:
{3, 5, 8, 9, 10}

Create another example

In this example, we will create two sets of papa's and mummy's family. We will see which are common members in both the family. If new member comes in one family, how we will add new member. If one member is not there, how we will remove that member. How to get difference between both the family.

In [50]:
papa_family = {'dada', 'dadi', 'papa', 'mummy', 'john', 'priyanka', 'uncle', 'aunty', 'sara'}
mummy_family = {'nana', 'nani', 'mama', 'mami', 'papa', 'mummy', 'john', 'priyanka', 'ratna'}
In [51]:
print(papa_family)
print(mummy_family)

{'dadi', 'john', 'mummy', 'priyanka', 'uncle', 'aunty', 'sara', 'dada', 'papa'}
{'nana', 'john', 'mama', 'mami', 'mummy', 'priyanka', 'nani', 'papa', 'ratna'}

All members in papa's and mummy's family

In [52]:
full_family_members = papa_family | mummy_family
print(full_family_members)

{'nana', 'dadi', 'john', 'mama', 'mummy', 'mami', 'priyanka', 'uncle', 'aunty', 'sara', 'dada', 'nani', 'papa', 'ratna'}

Common members in papa and mammy's family

In [53]:
common_members = papa_family & mummy_family
print(common_members)

{'papa', 'john', 'mummy', 'priyanka'}

Aunty got a new baby boy 'Aarav'. Add new member in papa's family.

In [54]:
new_member = 'aarav'
papa_family.add(new_member)
In [55]:
print(papa_family)

{'dadi', 'john', 'aarav', 'mummy', 'priyanka', 'uncle', 'aunty', 'sara', 'dada', 'papa'}

My nana was suffering from chronic disease. He is no more now.

In [56]:
mummy_family.remove('nana')

After removing nana from mummy's family.

In [57]:
print(mummy_family)

{'john', 'mama', 'mami', 'mummy', 'priyanka', 'nani', 'papa', 'ratna'}

What is difference in papa's family

We have remove commom items,which is present in mummy's family

In [58]:
#papa_family - mummy_family
#or
papa_family.difference(mummy_family)
Out[58]:
{'aarav', 'aunty', 'dada', 'dadi', 'sara', 'uncle'}

Difference in mummy's family

In [59]:
#mummy_family - papa_family
#or
mummy_family.difference(papa_family)
Out[59]:
{'mama', 'mami', 'nani', 'ratna'}

All the members that are either in the papa's family or in the mummy's family but not in both.

In [60]:
#papa_family ^ mummy_family
#or
papa_family.symmetric_difference(mummy_family)
Out[60]:
{'aarav',
 'aunty',
 'dada',
 'dadi',
 'mama',
 'mami',
 'nani',
 'ratna',
 'sara',
 'uncle'}

That's it, in this blog. Thanks for reading.

In [ ]:

kindergarten

  1. Arithmetic
  2. Identify Pictures
  3. Learn Words

Python for kids

  1. How We Teach Exponents and Powers to Kids
  2. Plotting points
  3. Learning shapes, size and color
  4. Learning Coordinate Geometry
  5. Draw Shapes With Points Using Matplotlib Module
  6. Learn Coordinate Geometry With Intuitive Way - Part 1
  7. Teaching Geometry to Grade 3 Kids
  8. Plotting Simple Line, Bar And Pie Chart
  9. Draw Dream House Using Python Matplotlib Module
  10. Draw Circle - Diameter, Radius, Arc and Segment Using Python Matplotlib Module
  11. Draw Badminton Court Using Python Matplotlib Module
  12. Let Us Play With Carrom Board in Python
  13. Draw Some Interesting Pattern With Numpy & Matplotlib Module
  14. Step by Step Draw Boy Using Matplotlib Module
  15. Make Shapes With SystemOfBobies
  16. Draw Cartoon
  17. Draw Two Cartoons Inside House
  18. 3Dimension Plotting in Python
  19. Solar System
  20. Plot World, Continent and Cities
  21. Text Data Handling
  22. Draw Properties of Triangle Using the Python Matplotlib Module

Fourier series

  1. Plotting fourier series

Linear Equations

  1. Linear Equations

Geometry

  1. Cone geometry
  2. Cube geometry
  3. Cylinder geometry
  4. Disk geometry
  5. Open top box geometry
  6. Rectangle geometry
  7. Ring geometry
  8. Saturn geometry
  9. Sphere geometry

Laplace

  1. Laplace transfomation plotting in 3D

Vectors

  1. Reference frames 3d
  2. Vector implimentation 2 vectors
  3. Vector with numpy and sympy

Differential equations

  1. First order differential equations

Functions

  1. Function plotting in 3D
  2. Function plotting in 2D

Jacobian

  1. Jacobian

Lagrangian

  1. Lagrange multipliers
  2. Lagrange example

Waves

  1. Plot electromagnectic waves

Electromagnetism

  1. Field plot
  2. Electric fields
  3. Fields
  4. Charges on Equilateral Triangle

Optics

  1. Lens optics geometry
  2. Mirror optics geometry

Quantum mechanics concepts

  1. Dirac notation and photon polarisation
  2. Photon polarisation
  3. Electron spin
  4. Position momentum and heisenberg
  5. The EPR paradox explanation
  6. Energy operators the hamiltonian and schrodinger
  7. The harmonic oscillator
  8. Schrodinger equation a simple derivation

Theory of relativity

  1. Derivation of time dilation
  2. Gamma factor
  3. Spacetime reference frames equations

Kinematics

  1. Circular motion

Thermodynamics

  1. Entropy and the second law of thermodynamics
  2. Introductory chemical engineering thermodynamics

Formulae

  1. Formulae

A level physics

  1. Classical mechanics

Chemistry

  1. ChemCalcManager
  2. ChemistryFormulaManager
  3. ElementGroupManager
  4. ElementsManager
  5. EnvironmentManager
  6. MolarManager
  7. MoleculesManager
  8. PeriodicTableManager
  9. ReactivityManager
  10. SmilesManager
  11. VisualizationManager

English

  1. Book Manager
  2. Word Manager
  3. Grammar Manager
  4. Tense Manager
  5. Vocabulary Manager
  6. Learn Language Manager
  7. I sat with cat - Poem by Ishwarya
  8. There was a bug - Poem by Ishwarya
  9. The dog was doing a jog - Poem by Ishwarya

Geography

  1. Solar System
  2. Plot World, Continent and Cities

Animation

  1. Animate Circle With SVG
  2. Animate Stars in Different Directions Kids
  3. Move Box in HTML

Plotting

  1. Matplotlib Introduction
  2. Single Line Plots
  3. Bar Plots
  4. Histograms Plots
  5. Types of Plotting
  6. Seaborn Introduction
  7. Seaborn Scatterplot
  8. Seaborn Barplot
  9. Seaborn Boxplot
  10. Seaborn Pairplot
  11. Seaborn Heatmap
  12. Seaborn Seaborn Pandas
  13. Seaborn Plot a Simple Linear Relationship Between Two Variables
  14. Seaborn Displot
  15. Seaborn Palette
  16. Three-Dimensional Plotting in Matplotlib
  17. Interactive Visualizations With Bokeh Part 1
  18. Data Visualization With Seaborn - Part 1
  19. Draw Concrete Jungle In Matplotlib
  20. Draw Beautiful Eyes in Python Using the Matplotlib Module
  21. Celebrate Valentine With Your Partner and Python

SVG

  1. SVG Shapes
  2. SVG Shapes Advanced
  3. Animate Circle With SVG
  4. SVG Animation
  5. SVG Text
  6. Can We Write Alphabets With Help of SVG?

Python

  1. Searching Text in Multiple Files in Python
  2. Working With MongoDB & Python Using PyMongo and Pandas
  3. Capture Date, Phone and Email From Text With Regular Expression in Python
  4. Set Operations in Python
  5. Extract Table Data From Wikipedia Using Web Scraping With Python
  6. Word Cloud for a Website
  7. Sqlite Relational Database Management With Python
  8. How to Import Data From a MySql Database Into Pandas Data Frame
  9. Python Object Serialization and Deserialization With Pickle
  10. Regular Expression Operations in Python
  11. Creating and Writing to Different Type of Files in Python
  12. Convert Word file to PDF, HTML and PDF to JPG, PNG in Python

Machine Learning

  1. Deal Banking Marketing Campaign Dataset With Machine Learning

TensorFlow

  1. Difference Between Scalar, Vector, Matrix and Tensor
  2. TensorFlow Deep Learning Model With IRIS Dataset
  3. Sequence to Sequence Learning With Neural Networks To Perform Number Addition
  4. Image Classification Model MobileNet V2 from TensorFlow Hub
  5. Step by Step Intent Recognition With BERT
  6. Sentiment Analysis for Hotel Reviews With NLTK and Keras
  7. Simple Sequence Prediction With LSTM
  8. Image Classification With ResNet50 Model
  9. Predict Amazon Inc Stock Price with Machine Learning
  10. Predict Diabetes With Machine Learning Algorithms
  11. TensorFlow Build Custom Convolutional Neural Network With MNIST Dataset
  12. Deal Banking Marketing Campaign Dataset With Machine Learning

PySpark

  1. How to Parallelize and Distribute Collection in PySpark
  2. Role of StringIndexer and Pipelines in PySpark ML Feature - Part 1
  3. Role of OneHotEncoder and Pipelines in PySpark ML Feature - Part 2
  4. Feature Transformer VectorAssembler in PySpark ML Feature - Part 3
  5. Logistic Regression in PySpark (ML Feature) with Breast Cancer Data Set

PyTorch

  1. Build the Neural Network with PyTorch
  2. Image Classification with PyTorch
  3. Twitter Sentiment Classification In PyTorch
  4. Training an Image Classifier in Pytorch

Natural Language Processing

  1. Spelling Correction Of The Text Data In Natural Language Processing
  2. Handling Text For Machine Learning
  3. Extracting Text From PDF File in Python Using PyPDF2
  4. How to Collect Data Using Twitter API V2 For Natural Language Processing
  5. Converting Text to Features in Natural Language Processing
  6. Extract A Noun Phrase For A Sentence In Natural Language Processing

Others

  1. test-nutan
  2. QuestionManager.ipynb
  3. ActivityManager.ipynb
  4. Why us?
  5. How to Setup Wordpress Website Step by Step in Ubuntu VPS
  6. Setup Plesk Panel and Deploy Wordpress Website in Ubuntu VPS - Part 1
  7. Deploy a New Server With Plesk Control Panel - Part 2
  8. Setup Plesk Control Panel For Wordpress Website - Part 3
  9. Deploy Wordpress Website In Plesk Control Panel - Part 4
  10. HTML Basic Example
  11. Install MongoDB Community Server in Windows10
  12. How to Setup SAP BTP Trial Account and Create SAP HANA Cloud Database
  13. Connect SAP Hana Cloud Database Through Python
  14. How To Create a Self-Signed SSL Certificate for Apache in Ubuntu Virtual Cloud Server
  15. Consume Rest API in Django Web Application
  16. Setup GIT Repository in Ubuntu VPS
▲