This document discusses functions in Python. It begins by recapping functions from the previous lecture, noting that functions allow for code reuse and organization. It then provides examples of defining functions using def, including functions with positional and keyword arguments. It discusses the local and global namespaces of functions, and how variables are handled depending on whether they are defined inside or outside of a function. The document also demonstrates returning multiple values from functions using tuples and dictionaries. Finally, it introduces the concept of writing more generic reusable functions.
This document provides a summary of a lecture on built-in capabilities of Python related to data structures like sets, lists, dictionaries, and their comprehensions. It discusses how sets, lists, and dictionaries are created in Python and some common operations on them like union, intersection, addition, removal. It also explains list, set, and dictionary comprehensions which provide a concise way to create and transform collections in Python using a single line of code instead of multiple lines using loops and conditional logic. Examples of nested comprehensions and their use cases in data processing are also presented.
(download for flawless quality) A brief introduction to unison, the exciting and innovative new functional programming language.
Wholly based on a talk by Paul Chiusano.
download for better quality - Learn how to use an Applicative Functor to handle multiple independent effectful values through the work of Sergei Winitzki, Runar Bjarnason, Paul Chiusano, Debasish Ghosh and Adelbert Chang
Monad as functor with pair of natural transformationsPhilip Schwarz
Explains why a Monad is a functor with a pair of natural transformations (plus associativity and identity laws). It then explores this by looking at an example, with code in Scala.
Inspired and based on videos/publications by Bartosz Milewski, Rúnar Bjarnason and Rob Norris.
Download for better quality.
Download for better quality - Learn about the composition of effectful functions through the work of Bartosz Milewski, Rob Norris, Rúnar Bjarnason and Debasish Ghosh.
Functions allow for code reusability and modularization. A function is defined using the def keyword followed by the function name and parameters. Functions can take in arguments as inputs and return a value. Variables declared inside a function have local scope while those outside have global scope. Default parameter values can be specified in the function definition.
Functions allow programmers to organize and reuse code. Defining a function involves using the def keyword followed by the function name and parameters. Functions create a new local scope, and variables are searched in local, then global, then built-in scopes. Arguments passed to functions are assigned to parameter variables in the local scope. Functions can return values, and mutable objects like lists can be modified in-place by functions. Python also supports anonymous lambda functions defined with a single expression.
This document provides a summary of a lecture on built-in capabilities of Python related to data structures like sets, lists, dictionaries, and their comprehensions. It discusses how sets, lists, and dictionaries are created in Python and some common operations on them like union, intersection, addition, removal. It also explains list, set, and dictionary comprehensions which provide a concise way to create and transform collections in Python using a single line of code instead of multiple lines using loops and conditional logic. Examples of nested comprehensions and their use cases in data processing are also presented.
(download for flawless quality) A brief introduction to unison, the exciting and innovative new functional programming language.
Wholly based on a talk by Paul Chiusano.
download for better quality - Learn how to use an Applicative Functor to handle multiple independent effectful values through the work of Sergei Winitzki, Runar Bjarnason, Paul Chiusano, Debasish Ghosh and Adelbert Chang
Monad as functor with pair of natural transformationsPhilip Schwarz
Explains why a Monad is a functor with a pair of natural transformations (plus associativity and identity laws). It then explores this by looking at an example, with code in Scala.
Inspired and based on videos/publications by Bartosz Milewski, Rúnar Bjarnason and Rob Norris.
Download for better quality.
Download for better quality - Learn about the composition of effectful functions through the work of Bartosz Milewski, Rob Norris, Rúnar Bjarnason and Debasish Ghosh.
Functions allow for code reusability and modularization. A function is defined using the def keyword followed by the function name and parameters. Functions can take in arguments as inputs and return a value. Variables declared inside a function have local scope while those outside have global scope. Default parameter values can be specified in the function definition.
Functions allow programmers to organize and reuse code. Defining a function involves using the def keyword followed by the function name and parameters. Functions create a new local scope, and variables are searched in local, then global, then built-in scopes. Arguments passed to functions are assigned to parameter variables in the local scope. Functions can return values, and mutable objects like lists can be modified in-place by functions. Python also supports anonymous lambda functions defined with a single expression.
This document discusses PHP functions and how to define, call, and use them. It covers defining functions, arguments and parameters, default argument values, variable scope, and including library files. Functions allow reusable blocks of code and avoid duplicating code. Arguments are values passed into a function, while parameters are variable names used inside the function. Default arguments can be set so functions still work if not all arguments are passed. Variable scope determines where variables can be accessed. Library files allow storing functions in one place and including them elsewhere.
This document discusses recursion and recursive functions. It begins by defining recursive definitions as those that relate a term back to itself. It notes that recursive functions have base cases and recursive cases. The base cases provide the initial values, while the recursive cases compute new values by applying the function to other inputs that get closer to the base cases.
It then explains that computer programs implement function calls using a call stack, where each function call pushes a new frame onto the stack containing the function arguments and return location. For recursive functions, multiple frames for the same function may exist on the stack. Some recursive functions can be optimized by reusing frames if the recursive call is in tail position. Overall, recursion allows problems to be broken down into
Functions allow programmers to organize and reuse code. They take in parameters and return values. Parameters act as variables that represent the information passed into a function. Arguments are the actual values passed into the function call. Functions can have default parameter values. Functions can return values using the return statement. Python passes arguments by reference, so changes made to parameters inside functions will persist outside the function as well. Functions can also take in arbitrary or keyword arguments. Recursion is when a function calls itself within its own definition. It breaks problems down into sub-problems until a base case is reached. The main types of recursion are direct, indirect, and tail recursion. Recursion can make code more elegant but uses more memory than iteration.
The document provides an introduction to functions in Python. It begins by explaining that a function is a block of code that runs when called. It then discusses how functions can take in parameters and return values. The document walks through examples of creating, calling, and writing functions. It also covers topics like default parameter values, arbitrary arguments, and using a main function.
A book for learning puppet by real example and by building code. Second chapters takes you through all basics of Puppet and enough ruby to work with Puppet.
A function provides a convenient way of packaging a computational recipe, so that it can be used as often as required. A function definition consists of two parts: interface and body. The interface of a function (also called its prototype) specifies how it may be used. It consists of three entities:
The function name. This is simply a unique identifier.
The function parameters (also called its signature). This is a set of zero or more typed identifiers used for passing values to and from the function.
The function return type. This specifies the type of value the function returns. A function which returns nothing should have the return type void.
The body of a function contains the computational steps (statements) that comprise the function.
Understand the expression problem
See Haskell and Scala code illustrating the problem
Learn how FP typeclasses can be used to solve the problem
See the Haskell solution to the problem and a translation into Scala
Part 2
A pointer can point to an object by holding the object's address value. This is known as a "this pointer". A derived class inherits properties from its base class. A pointer to the base class can point to a derived class object, allowing access to both base and derived class members. Virtual functions ensure the correct overridden function is called at runtime based on the actual object type, rather than the pointer type. They are declared with the virtual keyword in the base class.
LESSON 4: INTRODUCING FUNCTIONS AND MODULAR DESIGN
Learn about Functions in Python. Advantages and disadvantages of functions. Introduction to Modular design. Local and Global Variables and their use. Passing parameters. What are arguments? Big questions: Evolution vs Intelligent design in light of functions (and modular design). A closer look at Robotics and advances in this field. Challenges and tasks including with solutions. Suggested research/HW and YouTube video recommendations. A note on Python’s built in functions.
Functional programming is the most extreme programmingsamthemonad
Functional Programming is the most Extreme form of Programming according to the document. It introduces Functional Programming concepts and compares them to Object Oriented Programming. It argues that FP is better aligned with Extreme Programming principles like YAGNI and KISS. OOP can introduce unnecessary complexity and tight coupling between components, whereas FP avoids this through purity and avoiding side effects and mutable state.
Static variables in C++ allow values to persist between function calls. They are declared with the static keyword inside a function. Static variables only initialize once and retain their value each time the function is called. This allows a function to "remember" or maintain state between invocations. Regular automatic variables declared inside a function without static are created and destroyed each time the function runs. Static variables provide a way to maintain state without using global variables, which exist throughout program execution.
Arriving at monads by going from pure-function composition to effectful-funct...Philip Schwarz
This document discusses functional programming principles and how to deal with effects like mutability, exceptions, and logging in a pure functional style. It introduces the idea of effects, distinguishing them from side effects. Six common effects are discussed: partiality, nondeterminism, dependency injection, logging, mutability, and exceptions. The document explains how the Kleisli category and monads can be used to define functions with effects and allow their composition while preserving referential transparency. This provides techniques for handling effects normally found in imperative programs using functional programming.
The document discusses JavaScript functions as first-class objects that can be passed as arguments, returned from other functions, and stored in variables. It explains that functions can be defined using function declarations or function expressions. Function declarations are hoisted to the top of their scope, while function expressions must be assigned to variables. Immediately invoked function expressions (IIFEs) allow defining anonymous functions that execute right away, protecting private variables from polluting the global scope.
New Concepts: Representative Expressions and Manifestation Statements (Transc...ALAeLearningSolutions
The document discusses new concepts in RDA related to representative expressions and manifestation statements. It provides an overview of representative expressions, which allow attributes typically associated with expressions, such as language and intended audience, to be recorded at the work level when describing a work. Representative expressions are deemed essential for characterizing a work and are taken from a representative expression of the work. This helps address the problem that catalogers want to record such expression-level details when describing works, which RDA previously did not allow. The document discusses issues with identifying a single representative expression for some works and explains how RDA's implementation allows for multiple representative expressions to be linked to a work.
The document discusses different ways to declare variables in JavaScript. There are three main keywords: var, let, and const. Var declares variables with function scope, let declares block-scoped variables, and const declares block-scoped variables that cannot be reassigned.
Javascripts hidden treasures BY - https://geekyants.com/Geekyants
Closures and hoisting are hidden features in JavaScript that can cause confusion. Closures allow functions to access variables from outer scopes even after they have returned. Hoisting refers to variables and functions being declared at the top of their scope before code execution. Understanding closures and hoisting can help explain unexpected behavior, such as functions running before they are defined or variables printing undefined values.
This document is an introductory tutorial on PHP web development. It begins by explaining what PHP is and its role in server-side programming. It then covers PHP basics like variables, arrays, functions, loops and conditional statements. Examples are provided for each concept to demonstrate how it works in PHP code. The document concludes by providing a full program example that combines these elements to check names in an array against a condition using a loop and function.
The Ring programming language version 1.5.4 book - Part 74 of 185Mahmoud Samir Fayed
This document discusses syntax flexibility in Ring, including:
1. The ability to change language keywords and operators using the ChangeRingKeyword and ChangeRingOperator commands, and examples of how to do so.
2. The LoadSyntax command, which allows loading syntax files containing ChangeRingKeyword and ChangeRingOperator commands to apply sets of syntax changes across multiple source files.
3. Optional use of parentheses around function parameters.
Anton Kasyanov, Introduction to Python, Lecture2Anton Kasyanov
This document provides an introduction and overview of key concepts in Python, including variables, types, functions, and conditional statements. It discusses how variables store and reference values, Python's dynamic typing, and how functions are defined with the def keyword. Conditionals like if/else statements are explained, with the general form being an if conditional block followed by optional elif and else blocks. Homework involves implementing functions for logical operations, distance calculation, and percent calculation.
This chapter introduces the key concepts of international human resource management (IHRM). It defines IHRM and differentiates it from domestic HRM, noting IHRM involves more complex activities and broader external influences. The chapter outlines five variables that moderate the differences between domestic and international HRM: cultural environment, industry type, reliance on the home country labor market, and senior management attitudes. It provides frameworks for analyzing IHRM strategically and how the context continues to change.
The document describes countdown timers that can be used in PowerPoint presentations. It provides instructions for copying and pasting the timers into slides. The timers include buttons counting down from 60 seconds to 10 seconds, bar timers for 1-2 minutes, sand timers, and digital clocks for 1-2 minutes. The timers are free to use for educational and non-profit purposes but cannot be modified without permission.
This document discusses PHP functions and how to define, call, and use them. It covers defining functions, arguments and parameters, default argument values, variable scope, and including library files. Functions allow reusable blocks of code and avoid duplicating code. Arguments are values passed into a function, while parameters are variable names used inside the function. Default arguments can be set so functions still work if not all arguments are passed. Variable scope determines where variables can be accessed. Library files allow storing functions in one place and including them elsewhere.
This document discusses recursion and recursive functions. It begins by defining recursive definitions as those that relate a term back to itself. It notes that recursive functions have base cases and recursive cases. The base cases provide the initial values, while the recursive cases compute new values by applying the function to other inputs that get closer to the base cases.
It then explains that computer programs implement function calls using a call stack, where each function call pushes a new frame onto the stack containing the function arguments and return location. For recursive functions, multiple frames for the same function may exist on the stack. Some recursive functions can be optimized by reusing frames if the recursive call is in tail position. Overall, recursion allows problems to be broken down into
Functions allow programmers to organize and reuse code. They take in parameters and return values. Parameters act as variables that represent the information passed into a function. Arguments are the actual values passed into the function call. Functions can have default parameter values. Functions can return values using the return statement. Python passes arguments by reference, so changes made to parameters inside functions will persist outside the function as well. Functions can also take in arbitrary or keyword arguments. Recursion is when a function calls itself within its own definition. It breaks problems down into sub-problems until a base case is reached. The main types of recursion are direct, indirect, and tail recursion. Recursion can make code more elegant but uses more memory than iteration.
The document provides an introduction to functions in Python. It begins by explaining that a function is a block of code that runs when called. It then discusses how functions can take in parameters and return values. The document walks through examples of creating, calling, and writing functions. It also covers topics like default parameter values, arbitrary arguments, and using a main function.
A book for learning puppet by real example and by building code. Second chapters takes you through all basics of Puppet and enough ruby to work with Puppet.
A function provides a convenient way of packaging a computational recipe, so that it can be used as often as required. A function definition consists of two parts: interface and body. The interface of a function (also called its prototype) specifies how it may be used. It consists of three entities:
The function name. This is simply a unique identifier.
The function parameters (also called its signature). This is a set of zero or more typed identifiers used for passing values to and from the function.
The function return type. This specifies the type of value the function returns. A function which returns nothing should have the return type void.
The body of a function contains the computational steps (statements) that comprise the function.
Understand the expression problem
See Haskell and Scala code illustrating the problem
Learn how FP typeclasses can be used to solve the problem
See the Haskell solution to the problem and a translation into Scala
Part 2
A pointer can point to an object by holding the object's address value. This is known as a "this pointer". A derived class inherits properties from its base class. A pointer to the base class can point to a derived class object, allowing access to both base and derived class members. Virtual functions ensure the correct overridden function is called at runtime based on the actual object type, rather than the pointer type. They are declared with the virtual keyword in the base class.
LESSON 4: INTRODUCING FUNCTIONS AND MODULAR DESIGN
Learn about Functions in Python. Advantages and disadvantages of functions. Introduction to Modular design. Local and Global Variables and their use. Passing parameters. What are arguments? Big questions: Evolution vs Intelligent design in light of functions (and modular design). A closer look at Robotics and advances in this field. Challenges and tasks including with solutions. Suggested research/HW and YouTube video recommendations. A note on Python’s built in functions.
Functional programming is the most extreme programmingsamthemonad
Functional Programming is the most Extreme form of Programming according to the document. It introduces Functional Programming concepts and compares them to Object Oriented Programming. It argues that FP is better aligned with Extreme Programming principles like YAGNI and KISS. OOP can introduce unnecessary complexity and tight coupling between components, whereas FP avoids this through purity and avoiding side effects and mutable state.
Static variables in C++ allow values to persist between function calls. They are declared with the static keyword inside a function. Static variables only initialize once and retain their value each time the function is called. This allows a function to "remember" or maintain state between invocations. Regular automatic variables declared inside a function without static are created and destroyed each time the function runs. Static variables provide a way to maintain state without using global variables, which exist throughout program execution.
Arriving at monads by going from pure-function composition to effectful-funct...Philip Schwarz
This document discusses functional programming principles and how to deal with effects like mutability, exceptions, and logging in a pure functional style. It introduces the idea of effects, distinguishing them from side effects. Six common effects are discussed: partiality, nondeterminism, dependency injection, logging, mutability, and exceptions. The document explains how the Kleisli category and monads can be used to define functions with effects and allow their composition while preserving referential transparency. This provides techniques for handling effects normally found in imperative programs using functional programming.
The document discusses JavaScript functions as first-class objects that can be passed as arguments, returned from other functions, and stored in variables. It explains that functions can be defined using function declarations or function expressions. Function declarations are hoisted to the top of their scope, while function expressions must be assigned to variables. Immediately invoked function expressions (IIFEs) allow defining anonymous functions that execute right away, protecting private variables from polluting the global scope.
New Concepts: Representative Expressions and Manifestation Statements (Transc...ALAeLearningSolutions
The document discusses new concepts in RDA related to representative expressions and manifestation statements. It provides an overview of representative expressions, which allow attributes typically associated with expressions, such as language and intended audience, to be recorded at the work level when describing a work. Representative expressions are deemed essential for characterizing a work and are taken from a representative expression of the work. This helps address the problem that catalogers want to record such expression-level details when describing works, which RDA previously did not allow. The document discusses issues with identifying a single representative expression for some works and explains how RDA's implementation allows for multiple representative expressions to be linked to a work.
The document discusses different ways to declare variables in JavaScript. There are three main keywords: var, let, and const. Var declares variables with function scope, let declares block-scoped variables, and const declares block-scoped variables that cannot be reassigned.
Javascripts hidden treasures BY - https://geekyants.com/Geekyants
Closures and hoisting are hidden features in JavaScript that can cause confusion. Closures allow functions to access variables from outer scopes even after they have returned. Hoisting refers to variables and functions being declared at the top of their scope before code execution. Understanding closures and hoisting can help explain unexpected behavior, such as functions running before they are defined or variables printing undefined values.
This document is an introductory tutorial on PHP web development. It begins by explaining what PHP is and its role in server-side programming. It then covers PHP basics like variables, arrays, functions, loops and conditional statements. Examples are provided for each concept to demonstrate how it works in PHP code. The document concludes by providing a full program example that combines these elements to check names in an array against a condition using a loop and function.
The Ring programming language version 1.5.4 book - Part 74 of 185Mahmoud Samir Fayed
This document discusses syntax flexibility in Ring, including:
1. The ability to change language keywords and operators using the ChangeRingKeyword and ChangeRingOperator commands, and examples of how to do so.
2. The LoadSyntax command, which allows loading syntax files containing ChangeRingKeyword and ChangeRingOperator commands to apply sets of syntax changes across multiple source files.
3. Optional use of parentheses around function parameters.
Anton Kasyanov, Introduction to Python, Lecture2Anton Kasyanov
This document provides an introduction and overview of key concepts in Python, including variables, types, functions, and conditional statements. It discusses how variables store and reference values, Python's dynamic typing, and how functions are defined with the def keyword. Conditionals like if/else statements are explained, with the general form being an if conditional block followed by optional elif and else blocks. Homework involves implementing functions for logical operations, distance calculation, and percent calculation.
This chapter introduces the key concepts of international human resource management (IHRM). It defines IHRM and differentiates it from domestic HRM, noting IHRM involves more complex activities and broader external influences. The chapter outlines five variables that moderate the differences between domestic and international HRM: cultural environment, industry type, reliance on the home country labor market, and senior management attitudes. It provides frameworks for analyzing IHRM strategically and how the context continues to change.
The document describes countdown timers that can be used in PowerPoint presentations. It provides instructions for copying and pasting the timers into slides. The timers include buttons counting down from 60 seconds to 10 seconds, bar timers for 1-2 minutes, sand timers, and digital clocks for 1-2 minutes. The timers are free to use for educational and non-profit purposes but cannot be modified without permission.
The document discusses the Memorandum and Articles of Association, which are the two main constitutional documents of a company. The Memorandum of Association sets out the constitution of the company and specifies its objectives and share capital. It contains clauses related to the company's name, registered office, objectives, shareholder liability, share capital, and original subscribers. The Articles of Association contain the internal rules and regulations regarding the company's management and operations. It covers topics like directors' powers and duties, shareholder rights, meetings, financial matters, and winding up procedures. The document also explains the doctrines of ultra vires and indoor management.
The Consumer Protection Act, 2019 proposes the establishment of a new regulatory authority called the Central Consumer Protection Authority (CCPA) to protect consumer rights. The CCPA will have investigation powers and can file class action suits. It also increases the pecuniary jurisdiction of consumer commissions, allows electronic filing of complaints, and introduces alternate dispute resolution. The Act aims to provide better redressal of consumer grievances through this 3-tier consumer commission structure at the district, state and national levels.
This document provides an overview of the Indian Contract Act 1872. It discusses key concepts related to contracts such as the definition of a contract, essential elements of a valid contract (offer, acceptance, consideration), capacity to contract, free consent, lawful object and discharge of a contract. It also covers types of contracts, formation of contracts and performance and breach of contracts. The document aims to teach legal and ethical aspects of business by explaining India's main contract law through concepts, principles and examples.
Case Studies on GST - CA KAMAL GARG (1).pdfprojectseasy
This document contains a series of multiple choice questions related to case studies on the Goods and Services Tax (GST) in India. It begins with 14 questions testing understanding of key concepts related to the taxable event and scope of supply under GST. Another set of 12 questions covers the topic of charge of GST, including the person liable to pay GST and eligibility for composition scheme. A final section has 11 questions on exemptions from GST and place of supply under the law. The document serves as a practice assessment for students and professionals to evaluate their working knowledge of important GST concepts and provisions.
This document discusses the formation of contracts, including offers, acceptance, and related concepts:
[1] An offer is a proposal made with the intent of obtaining consent from another party to enter a legally binding agreement. It must express a willingness to act or refrain from acting. [2] The essentials of a valid offer include being made to another person with the objective of their assent. [3] An offer can be express, implied, specific, or general.
The document then examines the lapse and revocation of offers, acceptance of offers, cases related to offers and acceptance, and differences between offers and invitations to offer.
There are several remedies available for a breach of contract, including rescission of the contract, suits for damages, and specific performance. Damages awarded can include ordinary damages to compensate for natural and direct losses, special damages for unusual losses contemplated by the parties, and in rare cases exemplary damages to punish particularly egregious breaches. Other remedies are suits on quantum meruit if a contract is only partially performed, injunctions to prevent future breaches, and restitution to return benefits received under a void contract.
There are several remedies available for a breach of contract, including rescission of the contract, suits for damages, and specific performance. Damages awarded for breach of contract aim to compensate the injured party for losses directly resulting from the breach, and can include ordinary, special, nominal, or exemplary damages depending on the circumstances. The injured party may also sue for specific performance to enforce the contract, seek an injunction preventing further breach, or pursue restitution of benefits received under a void contract.
This document discusses the formation of contracts, including offers, acceptance, and related concepts:
[1] It defines an offer as a proposal made with the intention of obtaining another's consent to enter a legally binding agreement. [2] It outlines the essential elements of a valid offer and different types of offers. [3] It discusses when an offer can end or lapse, such as through revocation, rejection, or non-fulfillment of conditions. The document provides examples to illustrate these contract law concepts.
This document provides an overview of the course "Legal and Ethical Aspects of Business" taught by Dr. A.K. Subramani. The course objectives are to create knowledge of the legal perspective and practices to improve business and provide a strong foundation in principles, contemporary issues, and practical examples. The outcomes are that students will have a better understanding of legal aspects in the business environment and be able to apply legal insights appropriately in changing situations. The document outlines the syllabus, including units on the Indian Contract Act, Sale of Goods Act, Company Law, tax laws, and consumer protection and intellectual property laws. Suggested readings are also provided.
The document discusses understanding factors that influence organic food purchases in China. It summarizes previous research that identified beliefs like organic food being healthier, environmentally friendly, and safer. It aims to obtain a deeper understanding by confirming additional beliefs in China, specifically that organic food is seen as a luxury, upscale, or subject to marketing hype. It also examines how subjective norms, identity expressiveness, trust, and income impact purchase intention and behavior. Findings could provide insights for marketing organic food in China.
The impact of_age_on_the_customers_buying_behaviourprojectseasy
This document discusses factors that influence consumer buying behavior, with a focus on the impact of age. It provides background on theories of consumer behavior and defines it as the process by which individuals select, purchase, use, and dispose of products. The document reviews literature showing that psychological and demographic characteristics like age significantly shape consumer preferences and decisions. It aims to examine how age influences a customer's perception of price, an important consideration in the purchasing process.
This document provides an overview of industrial relations, including:
1. It defines industrial relations and outlines its key areas such as collective bargaining, the roles of management, unions, and government, and mechanisms for resolving disputes.
2. It discusses the importance of industrial relations for increased productivity and ethical treatment of workers.
3. It describes three main approaches to industrial relations: the unitary approach which emphasizes cooperation; the pluralistic approach which sees competing interests; and the Marxist approach which views conflicts as a result of capitalism.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
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For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
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Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
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Liberal Approach to the Study of Indian Politics.pdf
lec15 (1).pdf
1. Business Analytics And Text Mining Modeling Using Python
Prof. Gaurav Dixit
Department of Management Studies
Indian Institute of Technology-Roorkee
Lecture-15
Built-in Capabilities of Python-VII
Welcome to the course business analytics and text mining modeling using python. So, in
previous few lectures we have been covering python language you know mainly in the context
how you know, basics and how you know it could be really useful in the analytics context. So,
from the analytics perspective we have been covering python. Now in the previous lecture we
started our discussion on functions.
So, let us pick up from there. So, we talked about functions. So, functions are just any other
type of python objects. However, as we discussed that they are going on the most important
mechanisms in terms of code organization and reuse. Because many times a certain piece of
code we would like to you know execute again and again for certain computations certain you
know, other processing that we require.
So, it is better to have them you know in the functional form, so, we can use these functional
objects by functional python object. So, in a sense, we will be able to reuse that part of the code
and our core organization will also improve. So, for any programming languages function play
an important role. Now, as far as python is concerned you know in terms of defining you know,
function objects.
(Refer Slide Time: 01:46)
2. We declare them with you know, using a def keyword and, you know typically them they might
have more than 1, you know, a return statement. So, you know, as you can see here that in kind
of statements. So, as we have discussed in the previous lecture that your flow of execution you
know, can go to any of the multiple paths that could be there, and in each of parts that are
possible, we are supposed to have return statement.
So that we are able to end the you know, a code of execution in the functional scope and able to
return to the parent scope. So for that we need those returning statements to indicate the same
and in case no return a statement is encountered, none is returned automatically. So, this is
about how we are supposed to structure our function objects in python.
(Refer Slide Time: 01:56)
Now, as we have discussed in the previous lecture, they can have positional arguments as well
as keyword arguments. And, you know, for obvious reason, keyword arguments must follow
the positional arguments, because the positional arguments, they are to be accessed by their
positions, however you know keyword argument, they can also be accessed by their names, the
keywords, so, therefore, first positional arguments and then, you know, keyword arguments will
follow them.
3. (Refer Slide Time: 05:34)
.
(Video Starts: 03:08)
So, that is the typical structure one example that you can see here. This part of the code, you
can see, we have you know, default we are defining a function f and 3 arguments are there x y
and z and the first 2 arguments are positional argument, third argument is the keyword
argument, where we have given a value also. So, typically, as we have discussed before as well,
keyword arguments they are typically used when we would like to have a default value.
So, and the nature of keyword argument also facilitates so different, you know, ways of calling
that particular function. So, we will you know go through this, so, in the code block of this
functional object, but we have we have conditional logic here, if else blocks here so z greater
than 1 then will return this expression and otherwise else will return this expression, z you
know, divided by x+y if z rather than 1 then z*x+y. Now, we can call, you know, in many ways
we can call this function in many ways.
So, first one first example that we're taking here is f first argument is 1, second argument is 2
and the third argument z=0.3, remember it the third argument is the keyword argument is also
having it you know default value as well. So, if I run this so, you can see, we obtain a value
here. And then similarly, second we are calling would be, you know, just be just pass the
values.
(Refer Slide Time: 08:21)
4. So, f then 3, 4.5, 1.3, so if I run this I will get a value, then another way of calling is that we are
just passing values first 2 arguments and the third argument is in a sense optional argument,
because we have already indicated the default value in the definition itself. So, if we want, we
do not need to specify that. So, therefore we can call this function using just 2 arguments. So, if
I run this will get a value.
Now, this must we have discussed in the previous lecture, as well. So, now, let us move
forward. Now, let us talk about some more aspects about functions, name spaces scope and
local functions. So, functions can access variables in 2 different scopes, 1 is global, 1 is local.
So, if variable scope, you know, whether it is global or local, it is also referred as a name is
space in python terminology.
So, local name is space within a function, it is typically created when a function is called and it
is destroyed, after the function is finish when we are in functional environment, when we are
executing the code within function, then a local namespace for that functional, that functionality
scope is created. And once the call to you know, that function is finished, then that local
namespace is destroyed.
5. So all the variables that would be created inside the functional scope inside that local
namespace, they would be destroyed once the execution comes out of the functional scope, the
local namespace. So let us understand this through few examples. So here in the first example
of what I have done is I have created available outside the functional scope V5 and it is an
empty list here.
And then I am defining a function called f1. And in that I have this you know, just a for loop
there for I in range 5, and V5 got append i. So we would be appending these elements one by
one, as we run the loop into the list empty list that we have created. So let us run this. And what
is the function is defined, you can see let us call this function f1. So in this fashion f1 and the
parentheses because this function does not require any argument.
(Refer Slide Time: 12:10)
So just empty parentheses here and we have called the function, now we check the value of V5.
So, we would see that even though the we have added elements in this p5 list inside the
functional scope, but since V5 was no defined in the global namespace, therefore, the values
have been added to this variable. And you would see in the output that 0 1 2 3 4, all the
elements that we have added inside the functional scope, inside the local namespace of the
function.
6. They can be access, they can be seen in the global name is space as well, because the variable
was you know, define and created in the global namespace. So, it would not be destroyed once
we come out of the functional local name space of the function. So, that is one aspect. Now, let
us remove this variable. So, we can use the del command here and del V5. So, let us remove
this one.
Now, we are defining another function here to again, you know, understand the name space and
the scope aspects. So, here in this function, the V5 variable is defined in the functional scope
itself in the local namespace of the function itself. So, def f2, and the first line is the one where
we are you know, defining this variable creating this variable V5 empty list, and then we are
running the loop for i in range 5.
And you can see them we are appending the element, you know, to this particular sequence this
program list. So, in this case, this variable V5 this list object, V5 has been, you know, created in
the functional scope or local namespace of the function. So, therefore, once the call to that
function is, you know, finished, then this particular variable is going to be destroyed. So, if you
try to access this protocol variable, or its elements, we would not be able to do so.
So, let us run this, let us define the function f2, let us call this function and once we are able to
call this function and let us try to access variable V5. So, you can see name V5 is not defined.
So, because the ones we call the function that local namespace gets destroyed, so along with
that, any variable any other objects that are part of that local name space they would also get
destroyed.
(Refer Slide Time: 18:40)
7. So, V5 is destroyed in that sense and therefore, we cannot see the elements of V5, we are not
able to access because as far as global namespace is concerned, the global scope is concerned or
the parent scope is concerned, this variable does not exist, this variable is not defined. Now, let
us understand few more aspects about a scope local and global scope. Now, sometimes, you
know, we might like to create a variable within the function.
But the global scope. So, that is also possible for that we can use global keyword. So, what we
can do is you can see in this example here, we are defining a new function f3 here with no
arguments. So, to define a variable inside the body of the function, but with global scope, we
need to use global keyword. So, the variable we are defining global V5, once we have you
know, define the type of the scope of this variable, then we you know, again, you know,
initialize it as an empty list V5 as an empty list.
And then we run the loop. So, because you have used the global keyword or we have you know,
in a sense define this variable in the global namespace or the parent scope. So, therefore, if we
call this function and in the code block of the function, you know, elements are being added.
So, we will be able to access even the you know once the call to the function is finished.
8. So, if I run this, the function will be defined. Now, if I call this function f3 here, so, call has
happened. Now if I try to access this variable V5, you can see 0 1 2 3 4 now, because the
function was defined using global keywords, so, therefore, it is in the global part of the global
namespace. So, therefore, even though we added the elements inside the local name space of
the function, we are able to access this particular element because it is in the global namespace.
So, this is about the you know a local and global scope and the name is space aspects in the
python language. Now let us move forward, now let us talk about some you know different
aspects about functions. So, some of these things we have touched upon before as well, for
example, returning multiple values. So, this aspect also we have discussed before. So, let us do
one more exercise here, while we are discussing, you know functions in more detail.
(Refer Slide Time: 25:18)
So, I am defining another function, def f4, parentheses, no arguments here. And in the body of
the function, I am creating these variables a=5, b=6, c=7, and I am returning you know, a,b,c.
So, you can see, when we return in this fashion, in a sense, we are returning a tuple here. So
using the tuple data centre that we have in python language, we are able to return all these
values in one go.
9. And you can see in the next line of this, you know, code block, I am recording this return value
from f4 by calling f4 and storing in the this tuple a b c outside the you know functional name
space. So, if I run this, so here you can see first thing that you should notice that a b c that were
created inside the you know functionally scope in the local name space of the function, they
will be destroyed you know, the a b c that will access they are the new a b c that we have
created in the you know, global namespace by you know, recording the return value of the
function f4.
So, if I try to access the value individual element of this tuple. So if I try to access if I run this b
you can see we got the value 6. So, you can see in this fashion, we can return multiple values,
and, you know, then, you know, access them in the, you know, global namespace as well. Now,
another way to do the same thing is I can you know, record the variable instead of you know
tuple with you know instead of mentioning each element of the tuple, I can just, you know,
record this value, store this value in a valuable V6.
So, it is now stored, now if I access this variable V6 you can see we got a tuple here 5 6 7. So,
this is another way to perform the same thing. Now, instead of maintaining the element of the
tuple you can have the you know tuple variable and whenever you want to access will get the
tuple as the output. Now, the same kind of thing, you know, we can also do with the dict data
structure.
So, let us do the same exercise again once more. So, again, we are defining another function def
f4 and you can see again 3 variables a=5, b=6, c=7. Now, we are returning in the dict format.
So, the dict format is about key value pair combination. So, you can see a is the key and then
colon a then b colon b, colon c and in this format, we will be returning, you know, the value
that we have, you know, created in the functional, you know, scope.
10. (Refer Slide Time: 26:45)
So, then I am recording the return value for by calling this function f4 in a valuable V7. So, if I
run this part of the code, and if I access this value, V7 this variable, you can see we have got a
dict object here. Now with the values of those elements, you know, value part of you know
those key value pairs as well in that dict object, if I look at the type of f4 because we have
discussed that functions in python are also objects so if I look at the type of output.
So you can see function is the output. So, here these are function type of these objects is
function here. Now, let us move forward. Now, we would like to discuss a particular scenario
you know, so, we can all the time as we discussed, you know, writing lines of code, which
could be repeated later on. So, we as we discussed, we can use functions to make them you
know, to organize that part of the code and use that part of the code.
So, that is one thing what another aspect is writing functional in such a way that they are more
generic and more useful. So, the same function, you know, we can write in a fashion that it can
be, used in only one particular situation, but the same function, the same lines of code, same
code block, we can, you know, reorganize that code of law into more than one functions or in
some fashion.
11. So, that it can be used in more than one scenarios. So, there can be those situation where the
same code block can be run in the form of function can be used in very few scenarios, and the
same code block can be written in the form of one or more functions and can be used in many
scenarios. So, that aspect also, you know, I would like to emphasize here. So, this is about
writing more reusable and generic functions.
So one example that we are taking here is data cleaning on a list of strings. So when we talk
about data cleaning, it is about you know, stripping, wide spaces, removing punctuation, and
proper capitalization, you know consistent, you know, capitalization that we might require
typically in the analytics context. So, let us just talk about the first approach, which is not that
much usual and generic.
But nevertheless, we are using function here itself, take the second approach, which is slightly
more usable and more generic in nature. So, let us start. So, in this first of all, we are using
building string methods along with the re standard library module for regular expression. So, in
this we have this example, we have this messy strings. So, this is a list, this is a sequence.
This is a list object and having a string elements and strings if you see Alabama it has the wide
space before it and the wide space after the characters that are part of Alabama and Georgia, we
have extra exclamation marks and you know capitalization is also not consistent, we have
Georgia multiple times with different variations and Florida, South Carolina with extra you
know has characters there.
So, this is the kind of a string that we have. So, this is the messy string that we have, we would
like to clean this particular data, clean this particular you know, sequence of a string values. So
for that we would like to because this is something that you know, cleaning or particular string
we might require quite often. So, why not write a function to perform this task, because that
would be to better code organized and better, you know, reuse of the code.
So, we are importing this module because we will be using certain functions, which are part of
this module re. And then we are you know, writing a function called clean_strings. So, what
12. objective is to deal with such kind of strings to be able to strip them of wide spaces, punctuation
symbols and capitalization, we would like to have consistent capitalization.
So, in this code block of the function, we are first defining the result the empty list that is there
and because in this empty list, we would like to return the clean destroying once we have
performed all our cleaning operation, we would like to return that clean the strings using this
results object result variable. So, we are running a loop here. So for x in strings, so, this is
strings is you know, list of you know, a string element.
So, what each of the string, we would like to run the loop and we would like to perform certain
operation in each of the string element here. So, first thing we are doing is we are calling this
function x dot for each string will call this strip function. So, what it will do is it will remove all
the you know wise spaces that are part of a particular you know string. So, all the wide spaces
trailing or otherwise they would be stripped off, then the next line of code we are calling this
function as part of this module V re.sub.
So, this will again you know, substitute if there are any punctuation mark or any characters,
they would be substituted. So, you can see in the first argument that we are using here we have
you know, these within the you know, this list that we have you know exclamation has question
mark, so these are some of the punctuation marks are some special characters. So, we would
like to substitute them with the, you know, this character, you know non character here.
So, this is something that we would like to perform to get rid of the punctuation symbols, then
next thing is x.title, we are calling this you know, title method here. So, in this all the strings
that we have, they will be converted into the title format. So, in a sense, they would be in the
consistent with the capitalizes would be consistent, and as per the title format. So, let us define
this, how the function is created.
Now, let us look at the messy string that we have now, to run this. So, you can see, you know,
this list messy string that we have, and you can see the problem with the string values and the
13. cleaning that might be required now, will call the function cleaning string, string that we have
just defined here, if I call this function can see clean string I am passing this string in this as an
argument and you can see the whole string has been cleaned.
I can see Alabama, Georgia, Georgia and Georgia all the string elements that we have only the
first letter is capitalized for all of them, and any extra spaces that we had, they are gone, and the
any punctuation symbols or special characters that we had, they are also gone. So, in this first
approach, but we had done in we had we have defined a function and in the code of that
function, we have you know, done certain number of operations in one go in a you know, for a
particular list of strings.
So, this is one approach, now, can we make, can we write a function in slightly more reusable,
and slightly, you know, more organized way, so, that it is more generic. So, it could be, you
know, used in multiple scenarios. So, let us, you know, focus on the second approach. So, what
we are doing here is, what we are trying to achieve here is here will apply a list of the
operations on list of strings.
So, instead of, you know, in the first approach, in the function, we just kept applying
operations, here, we are trying to, you know, if further identify another structure, like we have a
list of operations that we want to perform on a list of strings. So, in that sense, we will create a
list of operation that we would like to do, and you would like to apply that on the list of strings.
So, we will create, you know, 2 different functions here. So, first function is about remove
punctuation. So, in this, we are just using that the re.sub function here, and any punctuation
mark or a specific character they would be removed by calling this function. Now, we are
focusing on the list of function based operations to be applied. So, it could be user defined or
built in. So, in this, we have created a list of operations, list of function based operations.
So, you can see first one is string.str.string and then second one is removed punctuation, which
we have already defined, and then str.title. So, you know, we would like to perform, you know,
these, you know, 3 function based operations and in a sense we upgraded more structure, where
14. we are listing all the functional operation that we want to perform. Now, what is left in the
cleanest strings function.
So, in this function, again we are creating an empty list. And we are running a loop just like
before, and now for f in ops. So, now, we have 2 you know, for loops, first for loop is to rate
over the you know strings. So, you know, for each string would like to operate something, we
would like to perform something, then second loop each operation in the ops, we would like to
know, the list of operation we have created.
So, we would like to iterate over that list. And then we are just going to applying those
operations you can see, for each element x, we are calling that function fx. So, in a iterative
fashion, we are calling each of those functions. And this is more useful, more structures. So this
is more scalable in the sand more generic kind of function. In some other scenario, we would
like to, we would be required to perform another cleaning function, another cleaning you know
operation, then we would just have to add that particular functional object in the clean ops 1list.
And you can see the cleanest string function, we would not have to make any change. However,
in the first approach that we have the in the clean string functions, we would have to make
changes. However in this, we would have to just add that particular function in the list of
functions that we would like to form. So this is slightly more usable, slightly more generic way
of writing the same code block.
So let us run this. And now let us again have a look at the messy string that we had. Now you
can see we are calling the clean string functions. First argument is the messy string. The second
argument is clean ops that means list of functions that we would like to apply to clean the string
that we have in the first argument.
(Video Ends: 26:52)
So if I run this, the same, you know, result is achieved as you can see. So you can clearly notice
the differences in the sense the same function, same code lines, you know, more or less similar
thing. But just the way we organize the code you know, the second approach made it more
15. usable, more generic in that sense. So with that, we would like to stop here, and we will
continue our discussion on functions in the next lecture, thank you.
Keywords: Punctuation, Cleaning operation, Block operation, Execution.