Python Session - 3
Escape Sequence
Data Types
Conversion between data types
Operators
Python Numbers
Python List
Python Tuple
Python Strings
Python Set
Python Dictionary
Python is a widely-used and powerful computer programming language that has helped system administrators manage computer networks and problem solve computer systems for decades. Python has also built some popular applications like BitTorrent, Blender, Calibre, Dropbox, and much more. Going further, the “Pi” in Raspberry Pi stands for Python, so learning Python will instill more confidence when working with Raspberry Pi projects. Python is usually the first programming language people learn primarily because it is easy to learn and provides a solid foundation to learn other computer programming languages. In this webinar,
• Learn what Python is and what it is capable of doing.
• Install Python’s IDE for Windows and work in the Python shell.
• Use calculations, variables, strings, lists, and if statements.
• Discover Python’s built-in functions and understand modules.
• Create simple programs to build on later.
The recording is available at https://youtu.be/ThcWmJFf-ho.
The document discusses Python exception handling. It describes three types of errors in Python: compile time errors (syntax errors), runtime errors (exceptions), and logical errors. It explains how to handle exceptions using try, except, and finally blocks. Common built-in exceptions like ZeroDivisionError and NameError are also covered. The document concludes with user-defined exceptions and logging exceptions.
This document provides an overview of the Python programming language. It discusses what Python is, its key features, who uses it, common applications, and how to download and install Python. It then covers Python syntax concepts like identifiers, keywords, multiline statements, docstrings, indentation, comments, and string formatting. The document also introduces Python data types like numbers, strings, lists, tuples, dictionaries, sets and how to work with them. It describes how to convert between number types and access/update strings and lists. Finally, it discusses Python development environments like Anaconda and Spyder.
This document provides an introduction to the Python programming language. It covers Python's background, syntax, types, operators, control flow, functions, classes, tools, and IDEs. Key points include that Python is a multi-purpose, object-oriented language that is interpreted, strongly and dynamically typed. It focuses on readability and has a huge library of modules. Popular Python IDEs include Emacs, Vim, Komodo, PyCharm, and Eclipse.
Abstract: This PDSG workshop introduces the basics of Python libraries used in machine learning. Libraries covered are Numpy, Pandas and MathlibPlot.
Level: Fundamental
Requirements: One should have some knowledge of programming and some statistics.
This document is the preface to the book "Python for Informatics: Remixing an Open Book". It discusses how the book was created by modifying the open source book "Think Python" by Allen B. Downey to have a stronger focus on data analysis and exploring information using Python. Key changes included replacing number examples with data examples, reorganizing topics to get to data analysis quicker, and adding new chapters on data-related Python topics like regular expressions, web scraping, and databases. The goal was to produce a text suitable for a first technology course with an informatics rather than computer science focus.
What is Range Function? | Range in Python Explained | EdurekaEdureka!
YouTube Link: https://youtu.be/0Hp7AThTZhQ
** Python Certification Training: https://www.edureka.co/data-science-python-certification-course **
This Edureka video on 'Range In Python' will help you understand how we can use Range Function in Python with various examples for better understanding. Following are the topics discussed:
What Is Range In Python?
Range Parameters
Range With For Loop
Float Numbers In Range
Reverse Range In Python
Range vs XRange
Range Function Examples
Points To Remember
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Variables & Data Types In Python | EdurekaEdureka!
YouTube Link: https://youtu.be/6yrsX752CWk
(** Python Certification Training: https://www.edureka.co/python **)
This Edureka PPT on 'Variables and Data Types in Python' will help you establish a foothold on Python by helping you learn basic concepts like variables and data types. Below are the topics covered in this PPT:
Introduction To Python
Applications Of Python
Variable Declaration
Variable Data Types
Type Conversion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
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This document provides an introduction to Python programming concepts including data types, operators, control flow statements, functions and modules. It discusses the basic Python data types like integers, floats, booleans, strings, lists, tuples, dictionaries and sets. It also covers Python operators like arithmetic, assignment, comparison, logical and identity operators. Additionally, it describes control flow statements like if/else and for loops. Finally, it touches on functions, modules and input/output statements in Python.
This Edureka Python tutorial will help you in learning various sequences in Python - Lists, Tuples, Strings, Sets, Dictionaries. It will also explain various operations possible on them. Below are the topics covered in this tutorial:
1. Python Sequences
2. Python Lists
3. Python Tuples
4. Python Sets
5. Python Dictionaries
6. Python Strings
The document provides an introduction to Python programming. It discusses key concepts like variables, data types, operators, and sequential data types. Python is presented as an interpreted programming language that uses indentation to indicate blocks of code. Comments and documentation are included to explain the code. Various data types are covered, including numbers, strings, booleans, and lists. Operators for arithmetic, comparison, assignment and more are also summarized.
Basic Python Programming: Part 01 and Part 02Fariz Darari
This document discusses basic Python programming concepts including strings, functions, conditionals, loops, imports and recursion. It begins with examples of printing strings, taking user input, and calculating areas of shapes. It then covers variables and data types, operators, conditional statements, loops, functions, imports, strings, and recursion. Examples are provided throughout to demonstrate each concept.
This document discusses string formatting in Python. It explains that Python uses placeholders like %s and %d to format strings with values. The % operator method of string formatting is deprecated in Python 3 and the str.format() method is recommended instead. The format() method allows accessing formatting arguments by position or name to customize the order and labels of values in formatted strings.
this presentation will walk you through basic introduction to python, major features of python, how python runs on our system and some important commands used in python.
This document discusses strings and string buffers in Java. It defines strings as sequences of characters that are class objects implemented using the String and StringBuffer classes. It provides examples of declaring, initializing, concatenating and using various methods like length(), charAt() etc. on strings. The document also introduces the StringBuffer class for mutable strings and lists some common StringBuffer functions.
This document provides an introduction to the Python programming language. It discusses what Python is, its key features such as being multi-purpose, object oriented, and interpreted. It describes Python's releases and popularity compared to other languages. The document also covers how to run and write Python programs, popular IDEs and code editors, installing packages with pip, categories of public Python packages, and package popularity. It discusses Python modularity with Anaconda and conda versus pip for installation.
This document provides an overview of Python for data analysis using the pandas library. It discusses key pandas concepts like Series and DataFrames for working with one-dimensional and multi-dimensional labeled data structures. It also covers common data analysis tasks in pandas such as data loading, aggregation, grouping, pivoting, filtering, handling time series data, and plotting.
This Presentation Helps for the beginners to understand easily Python Programming Language, because i had given an snapshot of each concepts. Those who are knowing C,C++ and Java they can easily understand my presentation.
The document provides an introduction to Python programming including its features, uses, history, and installation process. Some key points covered include:
- Python is an interpreted, object-oriented programming language that is used for web development, scientific computing, and desktop applications.
- It was created by Guido van Rossum in 1991 and named after the Monty Python comedy group.
- To install Python on Windows, users download the latest version from python.org and run the installer, which also installs the IDLE development environment.
- The document then covers basic Python concepts like variables, data types, operators, and input/output functions.
A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
The document provides an overview of the Python programming language. It discusses that Python is an easy to learn, high-level, open-source programming language. It describes Python's design philosophy of code readability and how it allows programmers to express concepts in fewer lines of code compared to languages like C++ and Java. The document also discusses Python's powerful libraries, wide use across industries, and how to get started with Python programming using the IDLE integrated development environment.
A pointer is a variable that stores the memory address of another variable. Pointers allow functions to modify variables in the caller and are useful for handling arrays and dynamic memory allocation. Pointers contain the address of the memory location they point to. Pointer variables can be declared to hold these memory addresses and can then be used to indirectly access the value at the addressed location.
Python Functions Tutorial | Working With Functions In Python | Python Trainin...Edureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on Python Functions tutorial covers all the important aspects of functions in Python right from the introduction to what functions are, all the way till checking out the major functions and using the code-first approach to understand them better.
Agenda
Why use Functions?
What are the Functions?
Types of Python Functions
Built-in Functions in Python
User-defined Functions in Python
Python Lambda Function
Conclusion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
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Python Tutorial | Python Tutorial for Beginners | Python Training | EdurekaEdureka!
This Edureka Python tutorial will help you in understanding the various fundamentals of Python programming with examples in detail. This Python tutorial helps you to learn following topics:
1. Introduction to Python
2. Who uses Python
3. Features of Python
4. Operators in Python
5. Datatypes in Python
6. Flow Control
7. Functions in Python
8. File Handling in Python
This document provides an overview of Python data types including numeric, string, sequence, mapping, boolean, and set data types. It describes the main classes for each data type such as int, float, complex for numeric types, str for strings, list, tuple, range for sequences, dict for mappings, bool for booleans, and set, frozenset for sets. It includes examples of defining variables of each data type and using functions like type() and isinstance() to check the data type. It also summarizes key aspects of each data type like how they can be indexed, sliced, concatenated, and repeated.
This document provides an introduction to Python programming concepts including data types, operators, control flow statements, functions and modules. It discusses the basic Python data types like integers, floats, booleans, strings, lists, tuples, dictionaries and sets. It also covers Python operators like arithmetic, assignment, comparison, logical and identity operators. Additionally, it describes control flow statements like if/else and for loops. Finally, it touches on functions, modules and input/output statements in Python.
This Edureka Python tutorial will help you in learning various sequences in Python - Lists, Tuples, Strings, Sets, Dictionaries. It will also explain various operations possible on them. Below are the topics covered in this tutorial:
1. Python Sequences
2. Python Lists
3. Python Tuples
4. Python Sets
5. Python Dictionaries
6. Python Strings
The document provides an introduction to Python programming. It discusses key concepts like variables, data types, operators, and sequential data types. Python is presented as an interpreted programming language that uses indentation to indicate blocks of code. Comments and documentation are included to explain the code. Various data types are covered, including numbers, strings, booleans, and lists. Operators for arithmetic, comparison, assignment and more are also summarized.
Basic Python Programming: Part 01 and Part 02Fariz Darari
This document discusses basic Python programming concepts including strings, functions, conditionals, loops, imports and recursion. It begins with examples of printing strings, taking user input, and calculating areas of shapes. It then covers variables and data types, operators, conditional statements, loops, functions, imports, strings, and recursion. Examples are provided throughout to demonstrate each concept.
This document discusses string formatting in Python. It explains that Python uses placeholders like %s and %d to format strings with values. The % operator method of string formatting is deprecated in Python 3 and the str.format() method is recommended instead. The format() method allows accessing formatting arguments by position or name to customize the order and labels of values in formatted strings.
this presentation will walk you through basic introduction to python, major features of python, how python runs on our system and some important commands used in python.
This document discusses strings and string buffers in Java. It defines strings as sequences of characters that are class objects implemented using the String and StringBuffer classes. It provides examples of declaring, initializing, concatenating and using various methods like length(), charAt() etc. on strings. The document also introduces the StringBuffer class for mutable strings and lists some common StringBuffer functions.
This document provides an introduction to the Python programming language. It discusses what Python is, its key features such as being multi-purpose, object oriented, and interpreted. It describes Python's releases and popularity compared to other languages. The document also covers how to run and write Python programs, popular IDEs and code editors, installing packages with pip, categories of public Python packages, and package popularity. It discusses Python modularity with Anaconda and conda versus pip for installation.
This document provides an overview of Python for data analysis using the pandas library. It discusses key pandas concepts like Series and DataFrames for working with one-dimensional and multi-dimensional labeled data structures. It also covers common data analysis tasks in pandas such as data loading, aggregation, grouping, pivoting, filtering, handling time series data, and plotting.
This Presentation Helps for the beginners to understand easily Python Programming Language, because i had given an snapshot of each concepts. Those who are knowing C,C++ and Java they can easily understand my presentation.
The document provides an introduction to Python programming including its features, uses, history, and installation process. Some key points covered include:
- Python is an interpreted, object-oriented programming language that is used for web development, scientific computing, and desktop applications.
- It was created by Guido van Rossum in 1991 and named after the Monty Python comedy group.
- To install Python on Windows, users download the latest version from python.org and run the installer, which also installs the IDLE development environment.
- The document then covers basic Python concepts like variables, data types, operators, and input/output functions.
A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
The document provides an overview of the Python programming language. It discusses that Python is an easy to learn, high-level, open-source programming language. It describes Python's design philosophy of code readability and how it allows programmers to express concepts in fewer lines of code compared to languages like C++ and Java. The document also discusses Python's powerful libraries, wide use across industries, and how to get started with Python programming using the IDLE integrated development environment.
A pointer is a variable that stores the memory address of another variable. Pointers allow functions to modify variables in the caller and are useful for handling arrays and dynamic memory allocation. Pointers contain the address of the memory location they point to. Pointer variables can be declared to hold these memory addresses and can then be used to indirectly access the value at the addressed location.
Python Functions Tutorial | Working With Functions In Python | Python Trainin...Edureka!
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on Python Functions tutorial covers all the important aspects of functions in Python right from the introduction to what functions are, all the way till checking out the major functions and using the code-first approach to understand them better.
Agenda
Why use Functions?
What are the Functions?
Types of Python Functions
Built-in Functions in Python
User-defined Functions in Python
Python Lambda Function
Conclusion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
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Python Tutorial | Python Tutorial for Beginners | Python Training | EdurekaEdureka!
This Edureka Python tutorial will help you in understanding the various fundamentals of Python programming with examples in detail. This Python tutorial helps you to learn following topics:
1. Introduction to Python
2. Who uses Python
3. Features of Python
4. Operators in Python
5. Datatypes in Python
6. Flow Control
7. Functions in Python
8. File Handling in Python
This document provides an overview of Python data types including numeric, string, sequence, mapping, boolean, and set data types. It describes the main classes for each data type such as int, float, complex for numeric types, str for strings, list, tuple, range for sequences, dict for mappings, bool for booleans, and set, frozenset for sets. It includes examples of defining variables of each data type and using functions like type() and isinstance() to check the data type. It also summarizes key aspects of each data type like how they can be indexed, sliced, concatenated, and repeated.
This document discusses Python data types. It introduces common data types like integers, floats, strings, lists, tuples, dictionaries, booleans and sets. For each data type, it provides examples of how to define variables of that type, check the type, perform operations like slicing, concatenation and repetition. Standard data types like numbers, sequences, booleans, sets and dictionaries are covered in detail with examples showing how to create and manipulate variables of each type.
Python supports several data types including numbers, strings, and lists. Numbers can be integer, float, or complex types. Strings are collections of characters that can be indexed, sliced, and manipulated using various string methods and operators. Lists are mutable sequences that can contain elements of different data types and support operations like indexing, slicing, sorting, and joining. Common list methods include append(), insert(), remove(), pop(), clear(), and sort(). Tuples are similar to lists but are immutable.
Python supports several numeric and non-numeric data types including integers, floats, complex numbers, strings, lists, and tuples. Numbers can be integers, floats, or complex, and support common operations. Strings are immutable sequences of characters that can be indexed, sliced, formatted, and concatenated. Lists are mutable sequences that can contain mixed data types, and support common operations like indexing, slicing, sorting, and joining. Tuples are similar to lists but are immutable.
The document discusses various C data types including primary, derived, and user defined data types. It describes integer, floating point, character, array, structure, and enum data types. Integer types store whole numbers, floating point types store decimal numbers, and character types store single characters. Arrays allow storing multiple values of the same type, structures group different data types together, and enums define a new data type with named integer constants. Multidimensional arrays and accessing structure members are also explained with code examples.
The document provides a revision table comparing the key properties and functions of strings, lists, tuples and dictionaries in Python.
It defines each data type and provides examples of their initialization and use. It also summarizes common operations like indexing, slicing, membership testing, comparison operators and various functions that can be performed on each data type like joining, traversing, modifying and retrieving values. Finally, it lists some practice questions focusing on operations related to these fundamental Python data types.
Python is a high-level, general-purpose programming language that was created by Guido van Rossum in 1985. It is an interpreted, interactive, object-oriented language with features like dynamic typing and memory management. This document provides an overview of Python 3 and its basic syntax, data types, operators, decision making structures like if/else statements, and loops. It covers topics like variables, numbers, strings, lists, tuples, dictionaries, and type conversion between data types.
The document discusses various Python datatypes. It explains that Python supports built-in and user-defined datatypes. The main built-in datatypes are None, numeric, sequence, set and mapping types. Numeric types include int, float and complex. Common sequence types are str, bytes, list, tuple and range. Sets can be created using set and frozenset datatypes. Mapping types represent a group of key-value pairs like dictionaries.
This document discusses basic data types in Python, including numeric, sequence, boolean, and dictionary types. It provides examples and explanations of integer, float, complex, string, list, tuple, set, and dictionary data types. Numeric types represent numeric values, sequence types organize ordered sequences, boolean represents True or False, and dictionary stores key-value pairs. Python assigns data types dynamically based on values and allows flexible conversion between types.
The document discusses arrays in C programming language. It defines arrays as fixed-sized sequenced collections of elements of the same data type that share a common name. One-dimensional arrays represent lists, while two-dimensional arrays represent tables with rows and columns. Arrays must be declared before use with the size specified. Elements can be accessed using indices and initialized. Common operations like input, output, sorting and searching of array elements are demonstrated through examples.
This document summarizes Python's standard data types including numbers, strings, lists, tuples, and dictionaries. It describes that in Python, data types are classes and variables are objects of those classes. It provides examples of how to define number variables and delete number object references. It also explains that strings can be defined using single or double quotes and how string slicing and concatenation works using indexes and operators.
The Datatypes Concept in Core Python.pptxKavitha713564
This document summarizes the different datatypes in Python. There are numeric, set, boolean, none, sequence, and mapping datatypes. Numeric datatypes represent values with numbers and can be integer, float, or complex. Sequence datatypes maintain order and include strings, bytes, bytearrays, lists, tuples, and ranges. Mapping datatypes like dictionaries are unordered key-value pairs. The document provides examples and definitions of each datatype.
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Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
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Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
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Illustrator is a widely used and recognized software in the graphic design industry.
Creative Freedom:
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Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search.
Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.
How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers
Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach.
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AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
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Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
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3. Escape Sequence
escape sequences in string and bytes literals are interpreted according to rules similar to
those used by Standard C. The recognized escape sequences are:
4. Data types in Python
Python Numbers
Python List
Python Tuple
Python Strings
Python Set
Python Dictionary
Every value in Python has a datatype. Since everything is an object in Python programming,
data types are actually classes and variables are instance (object) of these classes.
5. Python Numbers (Data Types)
Integers, floating point numbers and complex numbers falls under Python numbers
category. They are defined as int, float and complex class in Python.
Integers can be of any length, it is only limited by the memory available.
A floating point number is accurate up to 15 decimal places. Integer and floating points
are separated by decimal points. 1 is integer, 1.0 is floating point number.
Complex numbers are written in the form, x + yj, where x is the real part and y is the
imaginary part
6. We can use the type() function to know which class a variable or a value belongs to and
the isinstance() function to check if an object belongs to a particular class.
a = 5
print(a, "is of type", type(a))
a = 2.0
print(a, "is of type", type(a))
a = 1+2j
print(a, "is complex number?", isinstance(1+2j,complex))
Python Numbers (Data Types)
7. Python List (Data Types)
List is an ordered sequence of items. It is one of the most used datatype in Python and is
very flexible. All the items in a list do not need to be of the same type.Lists are mutable,
meaning, value of elements of a list can be altered.
Declaring a list is pretty straight forward. Items separated by commas are enclosed within
brackets [ ]. a = [1, 2.2, 'python']
We can use the slicing operator [ ] to extract an item or a range of items from a list. Index
starts form 0 in Python.
a = [5,10,15,20,25,30,35,40]
# a[2] = 15
print("a[2] = ", a[2])
# a[0:3] = [5, 10, 15]
print("a[0:3] = ", a[0:3])
# a[5:] = [30, 35, 40]
print("a[5:] = ", a[5:])
8. Python Tuple (Data Types)
Tuple is an ordered sequence of items same as list.The only difference is that tuples are
immutable. Tuples once created cannot be modified.
Tuples are used to write-protect data and are usually faster than list as it cannot change
dynamically.
It is defined within parentheses () where items are separated by commas.
t = (5,'program', 1+3j)
We can use the slicing operator [] to extract items but we cannot change its value.
t = (5,'program', 1+3j)
# t[1] = 'program'
print("t[1] = ", t[1])
# t[0:3] = (5, 'program', (1+3j))
print("t[0:3] = ", t[0:3])
# Generates error
# Tuples are immutable
t[0] = 10
9. Python Strings (Data Types)
String is sequence of Unicode characters. We can use single quotes or double quotes to
represent strings. Multi-line strings can be denoted using triple quotes, ''' or """.
s = "This is a string"
s = '''a multiline
Like list and tuple, slicing operator [ ] can be used with string. Strings are immutable.
s = 'Hello world!'
# s[4] = 'o'
print("s[4] = ", s[4])
# s[6:11] = 'world'
print("s[6:11] = ", s[6:11])
# Generates error
# Strings are immutable in Python
s[5] ='d'
10. Set is an unordered collection of unique items. Set is defined by values separated by
comma inside braces { }. Items in a set are not ordered.
We can perform set operations like union, intersection on two sets. Set have unique values.
They eliminate duplicates.
Since, set are unordered collection, indexing has no meaning. Hence the slicing operator []
does not work.
Python Set (Data Types)
a = {5,2,3,1,4}
# printing set variable
print("a = ", a)
# data type of variable a
print(type(a))
11. Python Dictionary (Data Types)
Dictionary is an unordered collection of key-value pairs.
It is generally used when we have a huge amount of data. Dictionaries are optimized for
retrieving data. We must know the key to retrieve the value.
In Python, dictionaries are defined within braces {} with each item being a pair in the form
key:value. Key and value can be of any type.
d = {1:'value','key':2}
print(type(d))
print("d[1] = ", d[1]);
print("d['key'] = ", d['key']);
# Generates error
print("d[2] = ", d[2]);
12. Conversion between data types
We can convert between different data types by using different type conversion functions
like int(), float(), str() etc.
>>> set([1,2,3])
{1, 2, 3}
>>> tuple({5,6,7})
(5, 6, 7)
>>> list('hello')
['h', 'e', 'l', 'l', 'o']
>>> dict([[1,2],[3,4]])
{1: 2, 3: 4}
>>> dict([(3,26),(4,44)])
{3: 26, 4: 44}
13. Operators in python
Operators are special symbols in Python that carry out arithmetic or logical computation.
The value that the operator operates on is called the operand.
1) Arithmetic operators
2) Comparison operators
3) Logical operators
4) Assignment operators
5) Bitwise operators
6) Identity operators
7) Membership operators Special operators
18. Bitwise operators
Bitwise operators act on operands as if they were string of binary digits. It operates bit by
bit, hence the name.
For example,In the table below: Let x = 10 (0000 1010 in binary) and y = 4 (0000 0100 in
binary)