Dataframe Structures And Manipulation
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Dataframe Structures And Manipulation
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-24
Dataframe Structures And Manipulation written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
"DataFrame Structures and Manipulation" "DataFrame Structures and Manipulation" offers an exhaustive exploration of the conceptual foundations, practical implementations, and emerging frontiers of DataFrame technology in modern data science and engineering. Beginning with a historical evolution of tabular data structures, the book guides readers through core abstractions, formal underpinnings in relational algebra, robust schema enforcement, and advanced metadata models. The text carefully examines the impact of memory and storage choices, equipping learners to understand the trade-offs behind popular DataFrame libraries such as pandas, Apache Spark, and polars. Delving into essential operational competencies, the book explores data parsing from diverse sources, validation, and strategies for dealing with incomplete or corrupted data. Comprehensive coverage of transformation and cleaning operations—ranging from deduplication and type normalization to sophisticated feature engineering—ensures the reader can prepare data for robust analysis. Advanced topics, such as hierarchical indexing, custom user-defined functions, window and rolling computations, and optimization for large-scale and distributed workloads, prepare practitioners to tackle both performance and scalability demands. True to its forward-looking approach, the book addresses the integration of DataFrames into cloud-native, distributed, and real-time analytical ecosystems. Readers gain insight into best practices for ecosystem interfacing—machine learning pipelines, ETL bridges, visualization, and cross-language bindings—along with critical considerations for governance, security, and privacy in the age of data regulation. Closing chapters explore declarative interfaces, hardware acceleration, semantics enrichment, edge computing, and vital ethical dimensions, making "DataFrame Structures and Manipulation" an indispensable reference for both practitioners and researchers seeking to master the present and shape the future of DataFrame systems.
Mastertech Pandas For Data Manipulation
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2024-12-15
Mastertech Pandas For Data Manipulation written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-15 with Business & Economics categories.
WELCOME TO "MASTERTECH: PANDAS FOR DATA MANIPULATION," THE DEFINITIVE GUIDE TO REVOLUTIONIZE THE WAY YOU ANALYZE AND TRANSFORM INFORMATION. WRITTEN WITH EXPERTISE AND UNMATCHED SKILL, DIEGO RODRIGUES, AN INTERNATIONAL AUTHOR WITH OVER 180 TITLES PUBLISHED IN SIX LANGUAGES, DELIVERS AN ESSENTIAL RESOURCE FOR STUDENTS AND PROFESSIONALS AIMING FOR EXCELLENCE IN DATA ANALYSIS. EXPLORE A COMPREHENSIVE APPROACH THAT COVERS EVERYTHING FROM BASIC SETUP TO THE MOST ADVANCED TECHNIQUES. DIVE INTO A JOURNEY THAT ADDRESSES DATA CLEANING AND TRANSFORMATION, POWERFUL VISUALIZATIONS, AND PERFORMANCE OPTIMIZATION. WITH A PRACTICAL AND STRUCTURED FOCUS, THIS BOOK FILLS CRUCIAL GAPS IN TECHNICAL LITERATURE, PROVIDING A UNIQUE LEARNING EXPERIENCE. MASTER STRUCTURES LIKE DATAFRAMES AND SERIES, AND ENHANCE YOUR WORK WITH COMPLEX DATA THROUGH TOOLS SUCH AS MERGE, JOIN, AND CONCATENATE. EXPLORE THE USE OF PANDAS IN BIG DATA, MACHINE LEARNING, AND REAL-TIME ANALYSIS. THE CONTENT IS DEVELOPED WITH EXEMPLARY DIDACTICS, ENABLING YOU TO TRANSFORM RAW DATA INTO STRATEGIC DECISIONS. IN ADDITION TO OFFERING PRACTICAL EXERCISES AND REAL-WORLD APPLICATIONS, THIS GUIDE ALSO PRESENTS FUTURE TRENDS AND INNOVATIONS IN PANDAS, PREPARING YOU FOR THE FUTURE OF TECHNOLOGY. WHETHER IN INDUSTRY, SCIENCE, OR TECHNOLOGY, THIS BOOK IS THE ESSENTIAL RESOURCE FOR THOSE WHO WANT TO STAND OUT IN AN INCREASINGLY COMPETITIVE MARKET. "MASTERTECH: PANDAS FOR DATA MANIPULATION" IS YOUR PASSPORT TO MASTERING DATA ANALYSIS AND AN INDISPENSABLE REFERENCE FOR ANYONE SEEKING TO DOMINATE ONE OF THE MOST RELEVANT LIBRARIES IN THE MARKET. TRANSFORM THE WAY YOU WORK WITH DATA AND ESTABLISH YOURSELF AS A STANDOUT PROFESSIONAL! TAGS: Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals careers cybersecurity expertise library cybersecurity training Linux operating systems tools ethical hacking tools security testing penetration test cycle concepts mobile security cybersecurity fundamentals cybersecurity techniques skills cybersecurity industry global trends Kali Linux tools education innovation penetration test tools best practices global companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle consulting cybersecurity framework network security courses cybersecurity tutorials Linux security challenges landscape cloud threats compliance research technology React Native Flutter Ionic Xamarin HTML CSS JavaScript Java Kotlin Swift Objective-C Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Angular Vue.js Bitrise GitHub Actions Material Design Cupertino Fastlane Appium Selenium Jest CodePush Firebase Expo Visual Studio C# .NET Azure Google Play App Store CodePush IoT AR VR GITHUB BIG DATA JENKINS
Machine Learning Hero
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-01-16
Machine Learning Hero written by Cuantum Technologies LLC and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-16 with Computers categories.
Learn machine learning through hands-on Python projects, covering core concepts, essential libraries, and real-world applications for aspiring data scientists. Key Features Comprehensive coverage of machine learning fundamentals and advanced topics Real-world projects to apply skills in practical scenarios Integration of Python libraries for data science and AI development Book DescriptionThis book takes you on a journey through the world of machine learning, beginning with foundational concepts such as supervised and unsupervised learning, and progressing to advanced topics like feature engineering, hyperparameter tuning, and dimensionality reduction. Each chapter blends theory with practical exercises to ensure a deep understanding of the material. The book emphasizes Python, introducing essential libraries like NumPy, Pandas, Matplotlib, and Scikit-learn, along with deep learning frameworks like TensorFlow and PyTorch. You’ll learn to preprocess data, visualize insights, and build models capable of tackling complex datasets. Hands-on coding examples and exercises reinforce concepts and help bridge the gap between knowledge and application. In the final chapters, you'll work on real-world projects like predictive analytics, clustering, and regression. These projects are designed to provide a practical context for the techniques learned and equip you with actionable skills for data science and AI roles. By the end, you'll be prepared to apply machine learning principles to solve real-world challenges with confidence.What you will learn Build machine learning models using Python libraries Apply feature engineering and preprocessing techniques Visualize datasets with Matplotlib and Seaborn Optimize machine learning models with hyperparameter tuning Implement clustering and dimensionality reduction methods Work on real-world projects for practical experience Who this book is for Aspiring data scientists, software developers, and tech enthusiasts seeking to master machine learning concepts and Python libraries. Basic Python knowledge is recommended but not required, as foundational topics are covered.
Data Analysis Foundations With Python
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-12
Data Analysis Foundations With Python written by Cuantum Technologies LLC and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-12 with Computers categories.
Dive into data analysis with Python, starting from the basics to advanced techniques. This course covers Python programming, data manipulation with Pandas, data visualization, exploratory data analysis, and machine learning. Key Features From Python basics to advanced data analysis techniques. Apply your skills to practical scenarios through real-world case studies. Detailed projects and quizzes to help gain the necessary skills. Book DescriptionEmbark on a comprehensive journey through data analysis with Python. Begin with an introduction to data analysis and Python, setting a strong foundation before delving into Python programming basics. Learn to set up your data analysis environment, ensuring you have the necessary tools and libraries at your fingertips. As you progress, gain proficiency in NumPy for numerical operations and Pandas for data manipulation, mastering the skills to handle and transform data efficiently. Proceed to data visualization with Matplotlib and Seaborn, where you'll create insightful visualizations to uncover patterns and trends. Understand the core principles of exploratory data analysis (EDA) and data preprocessing, preparing your data for robust analysis. Explore probability theory and hypothesis testing to make data-driven conclusions and get introduced to the fundamentals of machine learning. Delve into supervised and unsupervised learning techniques, laying the groundwork for predictive modeling. To solidify your knowledge, engage with two practical case studies: sales data analysis and social media sentiment analysis. These real-world applications will demonstrate best practices and provide valuable tips for your data analysis projects.What you will learn Develop a strong foundation in Python for data analysis. Manipulate and analyze data using NumPy and Pandas. Create insightful data visualizations with Matplotlib and Seaborn. Understand and apply probability theory and hypothesis testing. Implement supervised and unsupervised machine learning algorithms. Execute real-world data analysis projects with confidence. Who this book is for This course adopts a hands-on approach, seamlessly blending theoretical lessons with practical exercises and real-world case studies. Practical exercises are designed to apply theoretical knowledge, providing learners with the opportunity to experiment and learn through doing. Real-world applications and examples are integrated throughout the course to contextualize concepts, making the learning process engaging, relevant, and effective. By the end of the course, students will have a thorough understanding of the subject matter and the ability to apply their knowledge in practical scenarios.
Python Data Science Essentials
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Author : MARK JOHN LADO
language : en
Publisher: Amazon Digital Services LLC - Kdp
Release Date : 2024-03-18
Python Data Science Essentials written by MARK JOHN LADO and has been published by Amazon Digital Services LLC - Kdp this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-18 with Computers categories.
The field of data science has emerged as a critical component in extracting actionable insights and making informed decisions from vast amounts of data. This comprehensive guide explores the fundamentals of data science using the Python language, a versatile toolset widely adopted in the industry. The journey begins with an introduction to data science, outlining its principles, methodologies, and real-world applications. Next, the basics of Python programming are covered, providing a solid foundation for data manipulation and analysis. Data types and structures in Python are then explored, followed by an in-depth look at essential libraries such as NumPy and Pandas, which facilitate efficient data handling and manipulation. The importance of data visualization is emphasized through tutorials on Matplotlib and Seaborn, enabling effective communication of insights and trends. Data cleaning and preprocessing techniques are discussed, addressing common challenges in data quality and preparation. Statistical analysis is introduced as a fundamental aspect of data science, showcasing its applications in hypothesis testing, correlation analysis, and regression modeling using Python. Machine learning concepts are then explored, covering both supervised and unsupervised learning algorithms, including linear regression, decision trees, clustering, and dimensionality reduction. Model evaluation and validation techniques are essential for assessing model performance and generalization ability, ensuring robust and reliable predictions. Additionally, an introduction to deep learning with Python provides insights into advanced neural network architectures and their applications in solving complex problems. Handling big data is a critical aspect of modern data science, and this guide provides an overview of using Python and Spark for scalable and distributed data processing. Real-world case studies across various domains illustrate the practical applications of data science techniques, from e-commerce recommendation systems to healthcare analytics. Finally, best practices and tips for data science projects are discussed, highlighting key considerations for project success, including data exploration, feature engineering, model selection, and collaboration. By mastering these fundamentals, aspiring data scientists can embark on their journey with confidence, equipped to tackle real-world challenges and drive impactful insights from data.
Euromicro Symposium On Microprocessing And Microprogramming
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Author :
language : en
Publisher:
Release Date : 1988
Euromicro Symposium On Microprocessing And Microprogramming written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computer architecture categories.
Python For Programmers
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Author : Paul Deitel
language : en
Publisher: Prentice Hall
Release Date : 2019-03-15
Python For Programmers written by Paul Deitel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.
The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.
Transparent Measurement And Manipulation Of Internet Protocols
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Author : Gerald Robert Malan
language : en
Publisher:
Release Date : 2000
Transparent Measurement And Manipulation Of Internet Protocols written by Gerald Robert Malan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Ultimate Pandas For Data Manipulation And Visualization
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Author : Tahera Firdose
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-06-10
Ultimate Pandas For Data Manipulation And Visualization written by Tahera Firdose and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-10 with Computers categories.
TAGLINE Unlock the power of Data Manipulation with Pandas. KEY FEATURES ● Master Pandas from basics to advanced and its data manipulation techniques. ● Visualize data effectively with Matplotlib and explore data efficiently. ● Learn through hands-on examples and practical real-world use cases. DESCRIPTION Unlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. WHAT WILL YOU LEARN ● Wrangle data efficiently using Pandas' cleaning, filtering, and transformation techniques. ● Unlock hidden patterns with advanced grouping, joining, and merging operations. ● Master time series analysis with Pandas to extract valuable insights from your data. ● Apply Pandas to real-world scenarios like customer churn analysis and financial modeling. ● Unleash the power of data visualization with Matplotlib and craft compelling charts and graphs. ● Enhance your workflow with essential Pandas optimizations and performance tips. WHO IS THIS BOOK FOR? This book is ideal for aspiring data scientists, analysts, and Python enthusiasts looking to enhance their data manipulation skills using Pandas. Familiarity with Python programming basics and a basic understanding of data structures will greatly benefit readers as they delve into the concepts presented in this book. TABLE OF CONTENTS 1. Introduction to Pandas and Data Analysis 2. Pandas Series 3. Pandas DataFrame 4. Data Cleaning with Pandas 5. Data Filtering with Pandas 6. Grouping and Aggregating Data 7. Reshaping and Pivoting in Pandas 8. Joining and Merging Data in Pandas 9. Introduction to Time Series Analysis in Pandas 10. Visualization Using Matplotlib 11. Analyzing Bank Customer Churn Using Pandas Index
Proceedings Of The International Symposium On Remote Sensing Of Environment
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Author :
language : en
Publisher:
Release Date : 2003
Proceedings Of The International Symposium On Remote Sensing Of Environment written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Geophysics categories.