Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language.
Make use of the PPT to have a better understanding of Python.
This document discusses data visualization tools in Python. It introduces Matplotlib as the first and still standard Python visualization tool. It also covers Seaborn which builds on Matplotlib, Bokeh for interactive visualizations, HoloViews as a higher-level wrapper for Bokeh, and Datashader for big data visualization. Additional tools discussed include Folium for maps, and yt for volumetric data visualization. The document concludes that Python is well-suited for data science and visualization with many options available.
Presentation on application of numerical method in our lifeManish Kumar Singh
This document discusses the application of numerical methods in real-life problems. It provides examples of using the bisection method to find the root of equations related to estimating ocean currents, modeling combustion flow, airflow patterns, and other applications. Specifically, it shows the steps to use the bisection method to estimate the depth at which a floating ball with given properties would be submerged. Over three iterations, it computes the estimated root, error, and number of significant digits estimated.
Introduction to Python Pandas for Data AnalyticsPhoenix
Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Python with Pandas is used in a wide range of fields including academic and commercial domains including finance, economics, Statistics, analytics, medical...
The document provides an overview of key Python concepts including variables, data types, operators, formatting numbers, and taking user input. It explains that variables store values in memory and have naming rules. The main data types are int, float, and string, and operators allow mathematical and logical operations. User input is taken with input() and formatted for output using format specifiers like .2f.
Operators in Python perform operations on operands. There are unary, binary, and ternary operators. The document discusses arithmetic, assignment, relational, logical, boolean, and bitwise operators in Python. Arithmetic operators include addition, subtraction, multiplication, division, modulus, exponent, and integer division. Assignment operators assign values to variables like +=, -=, *=, /=, %=, **=, and //= . Relational, logical, boolean, and bitwise operators are also discussed.
1. The document discusses the history and concepts of set theory, including how it was founded by Georg Cantor and how work by Zermelo and Fraenkel led to the commonly used ZFC set of axioms.
2. Various concepts in set theory are defined, such as empty sets, singleton sets, finite and infinite sets, unions, intersections, differences, and subsets.
3. The document also discusses applications of set theory and related fields like fuzzy logic, rough set theory, and how fuzzy set theory has been applied in rock engineering characterization.
This document discusses data visualization tools in Python. It introduces Matplotlib as the first and still standard Python visualization tool. It also covers Seaborn which builds on Matplotlib, Bokeh for interactive visualizations, HoloViews as a higher-level wrapper for Bokeh, and Datashader for big data visualization. Additional tools discussed include Folium for maps, and yt for volumetric data visualization. The document concludes that Python is well-suited for data science and visualization with many options available.
Presentation on application of numerical method in our lifeManish Kumar Singh
This document discusses the application of numerical methods in real-life problems. It provides examples of using the bisection method to find the root of equations related to estimating ocean currents, modeling combustion flow, airflow patterns, and other applications. Specifically, it shows the steps to use the bisection method to estimate the depth at which a floating ball with given properties would be submerged. Over three iterations, it computes the estimated root, error, and number of significant digits estimated.
Introduction to Python Pandas for Data AnalyticsPhoenix
Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Python with Pandas is used in a wide range of fields including academic and commercial domains including finance, economics, Statistics, analytics, medical...
The document provides an overview of key Python concepts including variables, data types, operators, formatting numbers, and taking user input. It explains that variables store values in memory and have naming rules. The main data types are int, float, and string, and operators allow mathematical and logical operations. User input is taken with input() and formatted for output using format specifiers like .2f.
Operators in Python perform operations on operands. There are unary, binary, and ternary operators. The document discusses arithmetic, assignment, relational, logical, boolean, and bitwise operators in Python. Arithmetic operators include addition, subtraction, multiplication, division, modulus, exponent, and integer division. Assignment operators assign values to variables like +=, -=, *=, /=, %=, **=, and //= . Relational, logical, boolean, and bitwise operators are also discussed.
1. The document discusses the history and concepts of set theory, including how it was founded by Georg Cantor and how work by Zermelo and Fraenkel led to the commonly used ZFC set of axioms.
2. Various concepts in set theory are defined, such as empty sets, singleton sets, finite and infinite sets, unions, intersections, differences, and subsets.
3. The document also discusses applications of set theory and related fields like fuzzy logic, rough set theory, and how fuzzy set theory has been applied in rock engineering characterization.
Python is a general purpose programming language created by Guido van Rossum in 1991. It is widely used by companies like Google, Facebook, and Dropbox for tasks like web development, data analysis, and machine learning. Python code is easy to read and write for beginners due to its simple syntax and readability. It supports features like object oriented programming, procedural programming, and functional programming.
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
Pandas is an open source Python library that provides data structures and data analysis tools for working with tabular data. It allows users to easily perform operations on different types of data such as tabular, time series, and matrix data. Pandas provides data structures like Series for 1D data and DataFrame for 2D data. It has tools for data cleaning, transformation, manipulation, and visualization of data.
Thermodynamics is the study of energy and its transformations. It helps predict the feasibility and extent of chemical reactions based on temperature and pressure conditions. A system exchanges energy and matter with its surroundings. Thermodynamic processes include isothermal, isochoric, isobaric, and adiabatic processes. The first law of thermodynamics states that energy is conserved and the change in internal energy of a system equals heat supplied plus work done. Enthalpy is a state function that is the sum of a system's internal energy and pressure-volume work, and its change is a measure of heat absorbed or released at constant pressure.
This chapter discusses multivariable calculus topics including functions of several variables, partial derivatives, applications of partial derivatives, implicit partial differentiation, higher-order partial derivatives, the chain rule, and finding maxima and minima for functions of two variables. It provides examples of computing partial derivatives, finding marginal costs and productivity, implicit partial differentiation, and using the chain rule. The objectives are to develop concepts and techniques for multivariable calculus including computing derivatives of functions with multiple variables.
This document discusses Python variables and data types. It defines what a Python variable is and explains variable naming rules. The main Python data types are numbers, strings, lists, tuples, dictionaries, booleans, and sets. Numbers can be integer, float or complex values. Strings are sequences of characters. Lists are mutable sequences that can hold elements of different data types. Tuples are immutable sequences. Dictionaries contain key-value pairs with unique keys. Booleans represent True and False values. Sets are unordered collections of unique elements. Examples are provided to demonstrate how to declare variables and use each of the different data types in Python.
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.
Getters and setters are used to effectively protect data in classes. Getters return the value of a variable while setters set the value. They follow a standard naming convention starting with get/set followed by the variable name capitalized. Constructors initialize objects and can provide initial values. They have the same name as the class and no return type. Value types like int store values directly while reference types store references to objects. The Math class provides predefined math methods that can be accessed without creating an object.
Rodixon K.R. presented on operations research techniques. Some important techniques discussed include allocation models that optimize resource allocation under constraints using linear and non-linear programming, sequencing models that determine optimal ordering of items for service, and waiting line/queuing theory models that aim to minimize costs of servicing and waiting in interrupt-prone systems. Other techniques covered are inventory models, competitive strategy models, decision theory, network analysis, simulation, search models, and replacement theory.
After the end of lesson you will be able to learn Python basics-What Python is? Its releases. Where we can use Python? Python Features. Tokens, comments variables etc... In out next PPT you will learn how to input and get output in Python
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document discusses Python iteration, comprehensions, generators, functional programming idioms, and provides examples of each. It covers that iterators and iterables are defined by implementing certain methods, comprehensions can create lists, sets, dicts or generators from iterables, generators are lazily evaluated and both iterable and iterators, and functional programming idioms like map and filter can often provide more readable solutions than comprehensions. Examples show common idioms for enumerating lists, finding the first occurrence, and collating data from multiple lists.
The document discusses Python regular expressions (RegEx). It covers importing the re module, using common RegEx functions like search(), findall(), split(), and sub(). It also covers RegEx patterns like metacharacters, special sequences, and match objects. Named groups are introduced as a way to make RegEx matches more readable by labeling parts of the pattern instead of using numbers.
This document discusses plotting data with Python and Pylab. It begins by describing a sample data table and the problem of reading and plotting the data. It then reviews options for plotting in Python like Pylab, Enthought, RPy, and Sage. The remainder of the document demonstrates how to use Pylab to read CSV data, and create bar charts, pie charts, line plots, and histograms of the sample data.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then tells the processor to execute the program. Functions allow code to be reused by defining operations that take in arguments and return values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
Python is a general purpose programming language created by Guido van Rossum in 1991. It is widely used by companies like Google, Facebook, and Dropbox for tasks like web development, data analysis, and machine learning. Python code is easy to read and write for beginners due to its simple syntax and readability. It supports features like object oriented programming, procedural programming, and functional programming.
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
Pandas is an open source Python library that provides data structures and data analysis tools for working with tabular data. It allows users to easily perform operations on different types of data such as tabular, time series, and matrix data. Pandas provides data structures like Series for 1D data and DataFrame for 2D data. It has tools for data cleaning, transformation, manipulation, and visualization of data.
Thermodynamics is the study of energy and its transformations. It helps predict the feasibility and extent of chemical reactions based on temperature and pressure conditions. A system exchanges energy and matter with its surroundings. Thermodynamic processes include isothermal, isochoric, isobaric, and adiabatic processes. The first law of thermodynamics states that energy is conserved and the change in internal energy of a system equals heat supplied plus work done. Enthalpy is a state function that is the sum of a system's internal energy and pressure-volume work, and its change is a measure of heat absorbed or released at constant pressure.
This chapter discusses multivariable calculus topics including functions of several variables, partial derivatives, applications of partial derivatives, implicit partial differentiation, higher-order partial derivatives, the chain rule, and finding maxima and minima for functions of two variables. It provides examples of computing partial derivatives, finding marginal costs and productivity, implicit partial differentiation, and using the chain rule. The objectives are to develop concepts and techniques for multivariable calculus including computing derivatives of functions with multiple variables.
This document discusses Python variables and data types. It defines what a Python variable is and explains variable naming rules. The main Python data types are numbers, strings, lists, tuples, dictionaries, booleans, and sets. Numbers can be integer, float or complex values. Strings are sequences of characters. Lists are mutable sequences that can hold elements of different data types. Tuples are immutable sequences. Dictionaries contain key-value pairs with unique keys. Booleans represent True and False values. Sets are unordered collections of unique elements. Examples are provided to demonstrate how to declare variables and use each of the different data types in Python.
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.
Getters and setters are used to effectively protect data in classes. Getters return the value of a variable while setters set the value. They follow a standard naming convention starting with get/set followed by the variable name capitalized. Constructors initialize objects and can provide initial values. They have the same name as the class and no return type. Value types like int store values directly while reference types store references to objects. The Math class provides predefined math methods that can be accessed without creating an object.
Rodixon K.R. presented on operations research techniques. Some important techniques discussed include allocation models that optimize resource allocation under constraints using linear and non-linear programming, sequencing models that determine optimal ordering of items for service, and waiting line/queuing theory models that aim to minimize costs of servicing and waiting in interrupt-prone systems. Other techniques covered are inventory models, competitive strategy models, decision theory, network analysis, simulation, search models, and replacement theory.
After the end of lesson you will be able to learn Python basics-What Python is? Its releases. Where we can use Python? Python Features. Tokens, comments variables etc... In out next PPT you will learn how to input and get output in Python
Python is a versatile, object-oriented programming language that can be used for web development, data analysis, and more. It has a simple syntax and is easy to read and learn. Key features include being interpreted, dynamically typed, supporting functional and object-oriented programming. Common data types include numbers, strings, lists, dictionaries, tuples, and files. Functions and classes can be defined to organize and reuse code. Regular expressions provide powerful string manipulation. Python has a large standard library and is used widely in areas like GUIs, web scripting, AI, and scientific computing.
This document discusses Python iteration, comprehensions, generators, functional programming idioms, and provides examples of each. It covers that iterators and iterables are defined by implementing certain methods, comprehensions can create lists, sets, dicts or generators from iterables, generators are lazily evaluated and both iterable and iterators, and functional programming idioms like map and filter can often provide more readable solutions than comprehensions. Examples show common idioms for enumerating lists, finding the first occurrence, and collating data from multiple lists.
The document discusses Python regular expressions (RegEx). It covers importing the re module, using common RegEx functions like search(), findall(), split(), and sub(). It also covers RegEx patterns like metacharacters, special sequences, and match objects. Named groups are introduced as a way to make RegEx matches more readable by labeling parts of the pattern instead of using numbers.
This document discusses plotting data with Python and Pylab. It begins by describing a sample data table and the problem of reading and plotting the data. It then reviews options for plotting in Python like Pylab, Enthought, RPy, and Sage. The remainder of the document demonstrates how to use Pylab to read CSV data, and create bar charts, pie charts, line plots, and histograms of the sample data.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and optionally returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then tells the processor to execute the program. Functions allow code to be reused by defining operations that take in arguments and return values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be manipulated using indexes and methods. Common string methods include upper() and concatenation using +.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
A program is a sequence of instructions that are run by the processor. To run a program, it must be compiled into binary code and given to the operating system. The OS then gives the code to the processor to execute. Functions allow code to be reused by defining operations and returning values. Strings are sequences of characters that can be accessed by index and manipulated with methods like upper() that return new strings.
The document provides an overview of the Python programming language. It discusses what Python is, its history and naming, features like being dynamically typed and interpreted, popular applications like web development, machine learning, and its architecture. It also covers Python constructs like variables, data types, operators, and strings. The document compares Python to other languages and provides examples of common Python concepts.
This document provides an overview of Python basics including statements, expressions, loops, strings, functions, and more. It discusses what a program is and how it runs. It explains how to get input from the user, import modules like math, use assignment statements, and print output. It also covers syntax, side effects vs returns, whitespace, operators, loops, range function, strings, indexes, basic string operations, len function, and functions. The document is from a Python training institute in Bangalore and is intended to teach Python fundamentals.
Python Workshop - Learn Python the Hard WayUtkarsh Sengar
This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.
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.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and commonly used string and list methods.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and assigning values to variables.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and commonly used string and list methods.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and assigning values to variables.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to the Python programming language. It discusses installing Python and interacting with it through command line and IDLE modes. It covers basic Python data types like numbers, strings, lists, and booleans. It demonstrates how to perform operations and call functions on these data types. It also discusses Python modules, getting input from users, and assigning values to variables.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
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.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Physiology and chemistry of skin and pigmentation, hairs, scalp, lips and nail, Cleansing cream, Lotions, Face powders, Face packs, Lipsticks, Bath products, soaps and baby product,
Preparation and standardization of the following : Tonic, Bleaches, Dentifrices and Mouth washes & Tooth Pastes, Cosmetics for Nails.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
Python.pdf
1. Basic Math using Python
Dr. Shivakumar B. N.
Assistant Professor
Department of Mathematics
CMR Institute of Technology
Bengaluru
2.
3. History of Python
▪ It is a general-purpose interpreted, interactive,
object-oriented, and high-level programming
language.
▪ It was created by Guido van Rossum (Dutch
Programmer) during the period 1985- 1990.
▪ Python 3.9.2 is current version
Guido van Rossum
Inventor of Python
4. Interesting facts about Python Programming
1. Python was a hobby project
2. Why it was called Python [The language’s name isn’t about snakes, but
about the popular British comedy troupe Monty Python]
3. Flavors of Python
Python ships in various flavors:
• CPython- Written in C, most common implementation of Python
• Jython- Written in Java, compiles to bytecode
• IronPython- Implemented in C#, an extensibility layer to frameworks
written in .NET
• Brython- Browser Python, runs in the browser
• RubyPython- Bridge between Python and Ruby interpreters
• PyPy- Implemented in Python
• MicroPython- Runs on a microcontroller
5.
6. Scope of learning Python in the field of Mathematics:
▪ Data Analytics
▪ Big Data
▪ Data Mining
7. ▪ https://solarianprogrammer.com/2017/02/25/install-numpy-scipy-matplotlib-python-3 ( To install packages)
▪ windows/https://www.w3schools.com/python/default.asp
▪ https://www.tutorialspoint.com/python/python_environment.htm
▪ https://www.udemy.com/course/math-with-python/ (Cover picture)
▪ https://data-flair.training/blogs/python-career-opportunities/ (companies using python picture)
▪ https://geek-university.com/python/add-python-to-the-windows-path/ (To set path)
▪ https://www.programiz.com/python-programming/if-elif-else
12. Basic Python Learning
Exercise 1: To print a message using Python IDE
Syntax: print ( “ Your Message”)
Example code:
print (“Hello, I like Python coding”)# Displays the message
in next line
# Comments
13. Variables
13
▪ Variables are nothing but reserved memory locations to store values.
▪ We are declaring a variable means some memory space is being reserved.
▪ In Python there is no need of declaring variables explicitly, if we assign a value it , automatically gets
declared.
Example:
counter = 100 # An integer assignment
miles =1000.0 # A floating point
name =(“John”) # A string
print counter
print miles
print name
14. Rules to Name Variables
▪ Variable name must always start with a letter or underscore symbol i.e, _
▪ It may consist only letters, numbers or underscore but never special symbols like @, $,%,^,* etc..
▪ Each variable name is case sensitive
Good Practice : file file123 file_name _file
Bad Practice : file.name 12file #filename
16. Operators Precedence Rule
Operator
Symbol
Operator Name
( ) Parenthesis
** Exponentiation (raise to the power)
* / % Multiplication , Division and
Modulus(Remainder)
+ - Addition and Subtraction
<< >> Left to Right
17. Let a = 10 and b = 20
Python Arithmetic Operators
21. CONDITIONAL STATEMENTS
One-Way Decisions
Syntax:
if expression:
statement(s)
Program:
a = 33
b = 35
if b > a:
print("b is greater than a")
Indentation
Python relies on indentation (whitespace at
the beginning of a line) to define scope in the
code. Other programming languages often use
curly-brackets for this purpose.
23. Multi-way if
Syntax:
if expression1:
statement(s)
if expression2:
statement(s)
elif expression3:
statement(s)
elif expression4:
statement(s)
else:
statement(s)
else:
statement(s)
Program:
a = 200
b = 33
if b > a:
print("b is greater than a")
elif a == b:
print("a and b are equal")
else:
print("a is greater than b")
24. LOOPS AND ITERATION
Repeated Steps
Syntax:
While expression:
Body of while
Program:
count = 0
while (count < 3):
count = count + 1
print("Hello all")
25. For Loop
Syntax:
for val in sequence:
Body of for
Program:
fruits = ["apple", "banana", "cherry"]
for x in fruits:
print(x)
Looking at in:
• The iteration variable "iterates through the sequence (ordered
set)
• The block (body) of code is executed once for each value in the
sequence
• The iteration variable moves through all the values in the sequence
26. The range() function
The range() function returns a sequence of numbers, starting from 0 by
default, and increments by 1 (by default), and ends at a specied number.
Program 1:
x = range(6)
for n in x:
print(n)
Program 2:
x = range(2,6)
for n in x:
print(n)
Program 3:
x = range(2,20,4)
for n in x:
print(n)
27. Quick Overview of Plotting in Python
https://matplotlib.org/
Use the command prompt to install the following:
✓ py -m pip install
✓ py -m pip install matplotlib
pip is a package management system used to install and manage software
packages written in Python.
28. import matplotlib.pyplot as plt
# line 1 points
x1 = [1,2,3]
y1 = [2,4,1]
# plotting the line 1 points
plt.plot(x1, y1, label = "line 1")
# line 2 points
x2 = [1,2,3]
y2 = [4,1,3]
# plotting the line 2 points
plt.plot(x2, y2, label = "line 2")
# naming the x axis
plt.xlabel('x - axis')
# naming the y axis
plt.ylabel('y - axis')
# giving a title to my graph
plt.title('Two lines on same graph!')
# show a legend on the plot
plt.legend()
# function to show the plot
plt.show()
Plotting two or more lines on same plot
29. import matplotlib.pyplot as plt
# x-coordinates of left sides of bars
left = [1, 2, 3, 4, 5]
# heights of bars
height = [10, 24, 36, 40, 5]
# labels for bars
tick_label = ['one', 'two', 'three', 'four', 'five']
# plotting a bar chart
plt.bar(left, height, tick_label = tick_label,
width = 0.8, color = ['red', 'green'])
# naming the x-axis
plt.xlabel('x - axis')
# naming the y-axis
plt.ylabel('y - axis')
# plot title
plt.title('My bar chart!')
# function to show the plot
plt.show()
Bar Chart
30. import matplotlib.pyplot as plt
# defining labels
activities = ['eat', 'sleep', 'work', 'play']
# portion covered by each label
slices = [3, 7, 8, 6]
# color for each label
colors = ['r', 'y', 'g', 'b']
# plotting the pie chart
plt.pie(slices, labels = activities, colors=colors,
startangle=90, shadow = True, explode = (0, 0, 0.1, 0),
radius = 1.2, autopct = '%1.1f%%')
# plotting legend
plt.legend()
# showing the plot
plt.show()
Pie-chart
31. # importing the required modules
import matplotlib.pyplot as plt
import numpy as np
# setting the x - coordinates
x = np.arange(0, 2*(np.pi), 0.1)
# setting the corresponding y - coordinates
y = np.sin(x)
# potting the points
plt.plot(x, y)
# function to show the plot
plt.show()
Plotting curves of given equation: 𝑺𝒊𝒏 𝒙