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Sumita Arora Informatics Practices Class 12 PDF 686: A Complete Course for CBSE Students



Sumita Arora Informatics Practices Class 12 PDF 686: A Comprehensive Guide for CBSE Students




Introduction




If you are a class 12 student who has opted for informatics practices as one of your subjects, you might be wondering what it is all about and how to prepare for it. Informatics practices is a subject that teaches you how to use computers and software tools to solve real-world problems in various domains such as data science, database management, web development, networking, etc. It also helps you develop your logical thinking, creativity, and problem-solving skills.




sumita arora informatics practices class 12 pdf 686



One of the best books that can help you learn informatics practices is Informatics Practices: A Text Book for Class XII by Sumita Arora. Sumita Arora is a renowned author who has written several books on computer science and informatics practices for CBSE students. She has a rich experience in teaching and writing on these subjects. Her books are written in a simple and lucid language that makes them easy to understand and follow.


Her book on informatics practices for class 12 covers all the topics prescribed by the CBSE syllabus of subject code 065. It also provides ample examples, exercises, projects, and assignments to help you practice and test your knowledge. The book covers four main units: Python Pandas, MySQL, Computer Networks, and Internet and Web. It also covers some important topics on social impacts of informatics practices such as data protection, open source software, cybercrime, etc.


In this article, we will give you a comprehensive guide on what you can learn from Sumita Arora's book on informatics practices for class 12. We will also provide you some tips and resources for further learning and practice. So, let's get started!


Python Pandas




Python is a popular programming language that is widely used for data science, web development, machine learning, etc. Pandas is a Python library that provides powerful tools for data handling and analysis. Pandas stands for PANel DAta Structures.


Pandas allows you to work with different types of data such as tabular data, time series data, text data, etc. It also allows you to perform various operations on data such as cleaning, transforming, filtering, grouping, aggregating, merging, etc. Pandas also integrates well with other Python libraries such as numpy, matplotlib, scipy, etc.


To use pandas in Python, you need to install it first using pip or conda commands. Then you need to import it using import pandas as pd. The main objects that pandas provides are DataFrame and Series. A DataFrame is a two-dimensional table-like structure that can store heterogeneous data in rows and columns. A Series is a one-dimensional array-like structure that can store homogeneous data.


Some of the main concepts and functions that you can learn from Sumita Arora's book on pandas are:


  • Data Frame Creation: You can create a DataFrame from various sources such as lists, dictionaries, arrays, CSV files, SQL databases, etc.



  • Data Frame Indexing: You can access or modify specific rows or columns of a DataFrame using labels or positions.



  • Data Frame Slicing: You can select a subset of rows or columns of a DataFrame using slicing operators or methods.



  • Data Frame Filtering: You can filter out rows or columns of a DataFrame based on some conditions or criteria.



  • Data Frame Grouping: You can group rows or columns of a DataFrame based on some common values or categories.



  • Data Frame Aggregation: You can apply some statistical or mathematical functions on groups or entire DataFrame to get summary results.



  • Data Frame Merging: You can combine two or more DataFrames based on some common values or keys using join or concatenate operations.



  • Data Visualization: You can plot different types of charts or graphs using pandas and matplotlib libraries such as line plot, bar graph, histogram, pie chart, frequency polygon, box plot, scatter plot, etc.



You can find detailed explanations, examples, and exercises on these topics in chapters 1, 2, and 3 of Sumita Arora's book.


MySQL




MySQL is a popular relational database management system (RDBMS) that helps you store, manage, and query structured data using SQL (Structured Query Language). SQL is a standard language that allows you to perform various operations on databases such as creating, inserting, updating, deleting, selecting, joining, etc.


To use MySQL in Python, you need to install it first using pip or conda commands. Then you need to install a connector module such as mysql.connector or pymysql that allows you to communicate with MySQL server from Python. Then you need to import it using import mysql.connector or import pymysql. Then you need to create a connection object that establishes a connection with MySQL server using your username, password, host name, and database name. Then you need to create a cursor object that executes SQL commands on the connection object.


Some of the main concepts and functions that you can learn from Sumita Arora's book on MySQL are:



  • Tables: Tables are the basic units of storage in MySQL that store data in rows and columns.



  • Columns: Columns are the attributes or fields of a table that define the type, name, and constraints of data stored in them.



  • Keys: Keys are the columns or combinations of columns that uniquely identify or relate rows of a table. There are different types of keys such as primary key, foreign key, candidate key, etc.



  • Constraints: Constraints are the rules or conditions that enforce data integrity and validity in a table. There are different types of constraints such as not null, unique, check, default, etc.



  • Data Types: Data types are the categories of data that define the format, range, and storage of values in a column. There are different types of data types such as numeric, string, date, etc.



  • Operators: Operators are the symbols or keywords that perform some arithmetic, logical, comparison, or bitwise operations on values or expressions.



  • Expressions: Expressions are the combinations of values, operators, and functions that produce a result.



  • Clauses: Clauses are the parts of a SQL statement that specify some conditions or parameters for the operation. There are different types of clauses such as where, order by, group by, having, etc.



  • Functions: Functions are the predefined or user-defined routines that perform some specific tasks on values or expressions. There are different types of functions such as aggregate functions, scalar functions, string functions, math functions, etc.



  • Commands: Commands are the SQL statements that perform some actions on databases or tables. There are different types of commands such as DDL (Data Definition Language), DML (Data Manipulation Language), DCL (Data Control Language), TCL (Transaction Control Language), etc.



You can find detailed explanations, examples, and exercises on these topics in chapters 4, 5, 6, and 7 of Sumita Arora's book.


Computer Networks




Computer networks are the systems of interconnected devices that enable communication and data transfer between them. Computer networks can be classified based on various criteria such as size, scope, topology, architecture, protocol, etc. Some of the common types of computer networks are LAN (Local Area Network), WAN (Wide Area Network), MAN (Metropolitan Area Network), PAN (Personal Area Network), etc.


Computer networks use various protocols and models to establish and maintain communication between devices. Protocols are the rules or standards that define how devices exchange information and cooperate with each other. Models are the conceptual frameworks that describe how different layers of protocols work together. Some of the common protocols and models of computer networks are TCP/IP (Transmission Control Protocol/Internet Protocol), OSI (Open Systems Interconnection), HTTP (Hypertext Transfer Protocol), FTP (File Transfer Protocol), SMTP (Simple Mail Transfer Protocol), etc.


To use computer networks in Python, you need to import some modules such as socket, urllib, requests, etc. that provide various functions and classes to create and use network sockets, URLs, requests, responses, etc. You also need to use some network tools such as ping, traceroute, netstat, etc. that help you test and troubleshoot network connectivity and performance.


Some of the main concepts and functions that you can learn from Sumita Arora's book on computer networks are:



  • Sockets: Sockets are the endpoints of communication between devices on a network. They have an address and a port number that identify them uniquely. Sockets can be created using socket module in Python.



  • URLs: URLs (Uniform Resource Locators) are the addresses that identify and locate resources on the internet such as web pages, images, files, etc. URLs have a format that consists of protocol, host name, path, and query string. URLs can be accessed and manipulated using urllib module in Python.



  • Requests and Responses: Requests and responses are the messages that devices exchange on a network to request and provide information or services. Requests and responses have a format that consists of headers and body. Requests and responses can be created and processed using requests module in Python.



  • Ping: Ping is a network tool that tests the reachability and latency of a device on a network by sending and receiving packets of data. Ping can be executed using os module in Python.



  • Traceroute: Traceroute is a network tool that traces the route and hops of packets from one device to another on a network by sending and receiving packets with increasing TTL (Time To Live) values. Traceroute can be executed using os module in Python.



  • Netstat: Netstat is a network tool that displays various information about network connections and statistics such as protocol, local address, remote address, state, etc. Netstat can be executed using os module in Python.




You can find detailed explanations, examples, and exercises on these topics in chapter 8 of Sumita Arora's book.


Internet and Web




Internet and web are two related but different concepts that often confuse people. Internet is the global network of interconnected devices that use TCP/IP protocol to communicate with each other. Web is one of the services or applications that run on the internet that use HTTP protocol to deliver information or resources using URLs. Web consists of web servers that host web pages or files and web browsers that request and display them.


Internet and web provide various features and services to users such as email, web browsing, search engines, social media, e-commerce, etc. Email is a service that allows users to send and receive messages electronically using SMTP protocol. Web browsing is a service that allows users to access and view web pages or files using HTTP protocol. Search engines are services that allow users to find information or resources on the web using keywords or queries. Social media are services that allow users to create and share content or interact with other users online using platforms such as Facebook, Twitter, Instagram, etc. E-commerce are services that allow users to buy or sell goods or services online using platforms such as Amazon, Flipkart, Paytm, etc.


To access and use internet and web resources in Python, you need to use some libraries such as requests, BeautifulSoup, urllib, etc. that provide various functions and classes to create and process requests and responses, parse HTML documents extract data from web pages etc. Some of the main concepts and functions that you can learn from Sumita Arora's book on internet and web are:


  • Email: Email is a service that allows users to send and receive messages electronically using SMTP protocol. Email has a format that consists of sender address recipient address subject body and attachments. Email can be created and sent using smtplib module in Python.



  • Web Browsing: Web browsing is a service that allows users to access and view web pages or files using HTTP protocol. Web browsing involves sending requests to web servers using URLs and receiving responses that contain HTML documents or files. Web browsing can be performed using requests module in Python.



  • Search Engines: Search engines are services that allow users to find information or resources on the web using keywords or queries. Search engines work by crawling indexing and ranking web pages based on their relevance and popularity. Search engines can be accessed using requests module in Python.



  • Social Media: Social media are services that allow users to create and share content or interact with other users online using platforms such as Facebook Twitter Instagram etc. Social media work by storing user profiles posts comments likes etc. in databases and displaying them on web pages or apps. Social media can be accessed using requests module in Python.



  • E-commerce: E-commerce are services that allow users to buy or sell goods or services online using platforms such as Amazon Flipkart Paytm etc. E-commerce work by storing product details customer details order details payment details etc. in databases and processing them using web pages or apps. E-commerce can be accessed using requests module in Python.




You can find detailed explanations examples and exercises on these topics in chapter 9 of Sumita Arora's book.


Social Impacts




Social impacts are the effects or consequences of informatics practices on individuals society and environment. Social impacts can be positive or negative depending on how informatics practices are used or misused. Some of the important topics on social impacts of informatics practices are:


  • Data Protection: Data protection is the process of safeguarding personal or sensitive data from unauthorized access use modification disclosure or destruction. Data protection is important for preserving privacy security confidentiality integrity accountability etc. of data owners. Data protection can be achieved by following some best practices such as encryption hashing authentication authorization backup audit etc. Data protection can also be enforced by some laws or regulations such as GDPR IT Act etc.



  • Open Source Software: that has its source code available for anyone to inspect, modify, or distribute freely. Open source software is important for promoting collaboration, innovation, transparency, quality, security, etc. of software development. Open source software can also benefit users by providing them more choices, flexibility, control, etc. over their software. Some examples of open source software are Linux, Python, MySQL, etc.



  • Cybercrime: Cybercrime is the crime that involves using computers or networks to commit illegal or harmful acts such as hacking, phishing, spamming, identity theft, fraud, cyberbullying, etc. Cybercrime is a serious threat to individuals, organizations, and society as it can cause financial loss, data breach, reputation damage, emotional distress, etc. Cybercrime can be prevented or detected by following some best practices such as using strong passwords, antivirus software, firewall, VPN, etc. Cybercrime can also be prosecuted by some laws or regulations such as IT Act, IPC, etc.



  • Digital Divide: Digital divide is the gap or inequality between individuals or groups in terms of access to or use of information and communication technologies (ICTs) such as computers, internet, mobile phones, etc. Digital divide can be caused by various factors such as income, education, location, gender, age, etc. Digital divide can have negative impacts on social and economic development such as education, health care, employment, empowerment, etc. Digital divide can be bridged or reduced by following some strategies such as providing affordable and accessible ICTs, promoting digital literacy, creating inclusive and relevant content, etc.



  • E-waste Management: E-waste management is the process of disposing or recycling electronic waste such as computers, mobile phones, batteries, etc. that are no longer useful or functional. E-waste management is important for protecting environment, health, and resources from the harmful effects of e-waste such as pollution, toxicity, wastage, etc. E-waste management can be achieved by following some best practices such as reducing, reusing, recycling, donating, etc. e-waste. E-waste management can also be supported by some laws or regulations such as E-Waste Rules, etc.




You can find detailed explanations, examples, and exercises on these topics in chapter 10 of Sumita Arora's book.


Conclusion




In this article, we have given you a comprehensive guide on what you can learn from Sumita Arora's book on informatics practices for class 12. We have covered four main units: Python Pandas, MySQL, Computer Networks, and Internet and Web. We have also covered some important topics on social impacts of informatics practices such as data protection, open source software, cybercrime, digital divide, e-waste management, etc. We hope that this article has helped you understand and appreciate the subject of informatics practices and its applications in various domains.


Here are some tips and resources for further learning and practice of informatics practices:



Tips:


  • - Read the book thoroughly and try to understand the concepts and examples. - Practice the exercises and assignments given in the book and check your answers with the solutions provided. - Try to apply the concepts and skills learned in the book to solve real-world problems or projects of your interest. - Keep yourself updated with the latest trends and developments in informatics practices by reading blogs, articles, newsletters, etc. - Seek feedback and guidance from your teachers, peers, mentors, etc. on your learning and performance.



Resources:


  • - W3Schools: A website that provides tutorials, references, and examples on various web development topics such as HTML, CSS, JavaScript, PHP, SQL, etc. - GeeksforGeeks: A website that provides articles, quizzes, videos, etc. on various computer science and programming topics such as Python, MySQL, Data Structures, Algorithms, etc. - Kaggle: A website that provides datasets, notebooks, competitions, courses, etc. on various data science and machine learning topics such as pandas, numpy, matplotlib, scikit-learn, etc. - Codecademy: A website that provides interactive online courses on various programming languages and technologies such as Python, SQL, HTML, CSS, JavaScript, etc. - Udemy: A website that provides online video courses on various topics such as web development, data science, networking, etc.



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