Data Visualization for Social and Policy Research: A Step-by-Step Approach Using R and Python, Jose Manuel Magallanes Reyes
Автор: Magallanes Reyes, Jose Manuel (pontificia Universidad Catolica Del Peru) Название: Data visualization for social and policy research ISBN: 1108714382 ISBN-13(EAN): 9781108714389 Издательство: Cambridge Academ Рейтинг: Цена: 4750.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book teaches basic techniques for produce visualizations of tables, time series, maps, text, and networks that communicate data and analyses creatively and effectively. The step by step presentation helps readers learn coding in R and Python while simultaneously becoming familiar with the advantages and disadvantages of each visual.
Автор: Molin Stefanie Название: Hands-On Data Analysis with Pandas ISBN: 1789615321 ISBN-13(EAN): 9781789615326 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will be a handy guide to quickly learn pandas and understand how it can empower you in the exciting world of data manipulation, analysis, and data science. You will learn how to use pandas to perform numeric and statistical analysis using real-world examples. You will also visualize statistical data and apply pandas to different domains.
Описание: If you want to learn more about Data Analysis or how to master it with the Python Programming Language, then keep reading.
Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future.
Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.
With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
Pandas, Jupyter and PyTorch
The 7 Python libraries that make Python one of the best choices for Data Analysis
Neural Network
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Some of the main industries that are using data to improve their business with 14 real-world applications
And Much More
While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics.
Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, and the most important real-world applications.
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Автор: by Laura Po; Nikos Bikakis; Federico Desimoni Название: Linked Data Visualization ISBN: 1681737256 ISBN-13(EAN): 9781681737256 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 8039.00 р. Наличие на складе: Нет в наличии.
Описание: Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains.
The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens.
This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios.
The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.
Описание: Are you looking for a Python for Data Science crash course and want to come up easily with your first project from scratch in no time?Are you constantly looking for information on social networks (like FB groups) and you don't know where to start with Python programming? If so, then read on
Python is often used in data science today because it is a mature programming language that has excellent properties for beginning programmers. Some of the most notable of these properties are the easy-to-read password, suppression of optional delimiters, dynamic writing, and the use of dynamic memory.
Data science uses science strategies to process data and separate information from it. It moves away from an idea similar to Big Data and Data Mining. It requires innovative equipment along with useful calculation and programming to deal with data problems or process data to gain substantial learning from them.
The improvement and highly useful research in the world of Computing and Technology have increased the importance of its most basic and essential concepts in a thousand aspects. This notion of principle is what we continuously refer to as data, and that data is the only thing that opens the way for everything in the world. The world's largest organizations and companies have built their creation and their philosophies and determine a unique portion of their pay through data. The value and importance of data can be understood with the simple certainty that a legitimate data storage/distribution center is a million times more profitable than the pure gold mine in the advanced world.
However, learning all the required skills to master data science and machine learning could certainly be challenging.
BUT DON'T WORRY In this complete Guide we have condensed all the knowledge you need in a simple and practical way. Through his revolutionary and systematic approach, you will skyrocket your skills, regardless of your previous experience, with the best techniques to manipulate and process datasets, learn in deep the principles of Python programming, and their real-world applications.
In this book you are ready to discover:
How to move your first steps in the world of "Python". I will explain you, with easy to follow visuals, how to exactly install Python on the Mac OS X, Windows and Linux systems.
How to easily setting up your first Data Science project from scratch with Python in less than 7 days.
Practical codes and exercises to use Python. I will explain you the step-by-step process to create games like: "magic 8 ball" and "hangman game".
How works the regression algorithms used in data science and what are the best tips and tricks to work with them.
How Scikit-Learn library is used in the development of a machine learning algorithm.
And much more
Even if you're still a beginner struggling on how to start projects with Python, this book will surely give you the right information to skyrocket your programming skills to the next level.
Keep in mind: "Real progress happens only when advantages of a new technology become available to everybody" (H. Ford).
Описание: Ideal for anyone who is just getting started with machine learning, this hands-on data science book will give you experience building predictive models using industry-standard tools and techniques. It will help you develop the skills and understanding to generate valuable insights and make data-driven business decisions.
Автор: Dцbler Mario, GroЯmann Tim Название: The Data Visualization Workshop, Second Edition ISBN: 1838981489 ISBN-13(EAN): 9781838981488 Издательство: Неизвестно Рейтинг: Цена: 4827.00 р. Наличие на складе: Нет в наличии.
Описание: Cut through the noise and get real results with a step-by-step approach to learning data visualization with Python
Описание: Knowing how to work with data to extract insights generates significant value. This book will help you to develop data analysis skills using a hands-on approach and real-world data. You`ll get up to speed with pandas 1.x in no time and build some software engineering skills in the process, vastly expanding your data science toolbox.
Автор: Keller Benjamin Название: Mastering Matplotlib 2.x ISBN: 1789617693 ISBN-13(EAN): 9781789617696 Издательство: Неизвестно Рейтинг: Цена: 6068.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mastering Matplotlib covers the use cases and encounter unusual cases that requires more powerful tools. With the easy to follow examples and high end components of matplotlib, this book will enable to develop advanced and interactive plots using Python scripting and Matplotlib
Описание: Statistics and Data Visualization Using R: The Art and Practice of Data Analysis teaches students statistics visually, focusing on interpreting graphs and charts to learn statistical concepts, from the mean through regression.
Описание: To start with you will cover the basics of graph analytics, Cypher querying language, components of graph architecture, and more. You will implement Neo4j techniques to understand various graph analytics methods to reveal complex relationships in data. You will understand how machine learning can be used to perform smarter graph analytics.
Автор: Decaria Alex, Petty Grant W. Название: Python Programming and Visualization for Scientists ISBN: 0972903356 ISBN-13(EAN): 9780972903356 Издательство: Неизвестно Рейтинг: Цена: 10483.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Python continues to gain dominance as a language of choice for analyzing and visualizing scientific data. Although it has concise, intuitive syntax, learning how to plot and visualize data requires scouring the internet for documentation and examples. This book was written from the perspective of "What book would the authors want to have had when they were transitioning to Python?"
A second edition of the book was made necessary by the transition to Python 3, which did not maintain full backward compatibility with earlier versions of the language. The second edition has been completely revised to ensure that all code examples work in Python 3. Additional chapters on the Pandas library and Cartopy have been included, as well as an appendix on Jupyter notebooks, which have become an important tool for developing and communicating code in both the research and educational settings.
The 90 figures are mostly in color, and color syntax highlighting is used with all code samples throughout the text to facilitate visual recognition of program structure.
The first edition of the book has proven useful not only as a classroom text but also as a guide and reference for students, educators, and researchers who already have programming experience and want to start creating plots and analyzing data using Python. The second edition will serve the same role. It is not meant for the person who is completely new to programming, nor is it an introductory computer science textbook. The authors' assumptions are that the reader has some experience programming with a language other than Python.
Although the new Python programmer may wish to read the book cover to cover, the book is organized such that an experienced programmer can readily jump to the appropriate chapter. An extensive index aids in searching for functions and methods useful for data visualization and analysis.
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