Interactive Web Based Data Visualization With R Plotly And Shiny
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Interactive Web Based Data Visualization With R Plotly And Shiny
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Author : Carson Sievert
language : en
Publisher: CRC Press
Release Date : 2020-01-30
Interactive Web Based Data Visualization With R Plotly And Shiny written by Carson Sievert and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Business & Economics categories.
The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more. Key Features: Convert static ggplot2 graphics to an interactive web-based form Link, animate, and arrange multiple plots in standalone HTML from R Embed, modify, and respond to plotly graphics in a shiny app Learn best practices for visualizing continuous, discrete, and multivariate data Learn numerous ways to visualize geo-spatial data This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics.
Interactive Visualization With R
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Author : Royal Statistical Society
language : en
Publisher:
Release Date : 2017
Interactive Visualization With R written by Royal Statistical Society and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Learn the techniques and tools for presenting data in visually attractive and interactive ways using the R programming language. This course is perfect for social scientists who are looking to use and develop their existing R skills to communicate their research in a new and engaging way. Not familiar with R? Try our Introduction to R course first. By the end of this course you will be able to: Understand the need for interactive visualizations and reports, and the associated workflows Produce a range of visualizations relevant to the available data Produce and publish a report that contains appropriate interactive visualizations to tell a story about the data.
Data Visualization In R And Python
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Author : Marco Cremonini
language : en
Publisher: John Wiley & Sons
Release Date : 2024-12-03
Data Visualization In R And Python written by Marco Cremonini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
Communicate the data that is powering our changing world with this essential text The advent of machine learning and neural networks in recent years, along with other technologies under the broader umbrella of ‘artificial intelligence,’ has produced an explosion in Data Science research and applications. Data Visualization, which combines the technical knowledge of how to work with data and the visual and communication skills required to present it, is an integral part of this subject. The expansion of Data Science is already leading to greater demand for new approaches to Data Visualization, a process that promises only to grow. Data Visualization in R and Python offers a thorough overview of the key dimensions of this subject. Beginning with the fundamentals of data visualization with Python and R, two key environments for data science, the book proceeds to lay out a range of tools for data visualization and their applications in web dashboards, data science environments, graphics, maps, and more. With an eye towards remarkable recent progress in open-source systems and tools, this book offers a cutting-edge introduction to this rapidly growing area of research and technological development. Data Visualization in R and Python readers will also find: Coverage suitable for anyone with a foundational knowledge of R and Python Detailed treatment of tools including the Ggplot2, Seaborn, and Altair libraries, Plotly/Dash, Shiny, and others Case studies accompanying each chapter, with full explanations for data operations and logic for each, based on Open Data from many different sources and of different formats Data Visualization in R and Python is ideal for any student or professional looking to understand the working principles of this key field.
R Data Visualization Recipes
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Author : Vitor Bianchi Lanzetta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-22
R Data Visualization Recipes written by Vitor Bianchi Lanzetta 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 2017-11-22 with Computers categories.
Translate your data into info-graphics using popular packages in R About This Book Use R's popular packages—such as ggplot2, ggvis, ggforce, and more—to create custom, interactive visualization solutions. Create, design, and build interactive dashboards using Shiny A highly practical guide to help you get to grips with the basics of data visualization techniques, and how you can implement them using R Who This Book Is For If you are looking to create custom data visualization solutions using the R programming language and are stuck somewhere in the process, this book will come to your rescue. Prior exposure to packages such as ggplot2 would be useful but not necessary. However, some R programming knowledge is required. What You Will Learn Get to know various data visualization libraries available in R to represent data Generate elegant codes to craft graphics using ggplot2, ggvis and plotly Add elements, text, animation, and colors to your plot to make sense of data Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2 Build interactive dashboards using Shiny. Color specific map regions based on the values of a variable in your data frame Create high-quality journal-publishable scatterplots Create and design various three-dimensional and multivariate plots In Detail R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions. This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using Shiny By the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision. Style and approach This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization with R. You will learn to leverage the power of R and ggplot2 to create highly customizable data visualizations of varying complexities. The readers will then learn how to create, design, and build interactive dashboards using Shiny.
Interactive Dashboards And Data Apps With Plotly And Dash
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Author : Elias Dabbas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-05-21
Interactive Dashboards And Data Apps With Plotly And Dash written by Elias Dabbas 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 2021-05-21 with Computers categories.
Build web-based, mobile-friendly analytic apps and interactive dashboards with Python Key Features Develop data apps and dashboards without any knowledge of JavaScript Map different types of data such as integers, floats, and dates to bar charts, scatter plots, and more Create controls and visual elements with multiple inputs and outputs and add functionality to the app as per your requirements Book DescriptionPlotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways. Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.What you will learn Find out how to run a fully interactive and easy-to-use app Convert your charts to various formats including images and HTML files Use Plotly Express and the grammar of graphics for easily mapping data to various visual attributes Create different chart types, such as bar charts, scatter plots, histograms, maps, and more Expand your app by creating dynamic pages that generate content based on URLs Implement new callbacks to manage charts based on URLs and vice versa Who this book is for This Plotly Dash book is for data professionals and data analysts who want to gain a better understanding of their data with the help of different visualizations and dashboards – and without having to use JS. Basic knowledge of the Python programming language and HTML will help you to grasp the concepts covered in this book more effectively, but it’s not a prerequisite.
Data Visualization With Python And Javascript
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Author : Kyran Dale
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-06-30
Data Visualization With Python And Javascript written by Kyran Dale and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-30 with Computers categories.
Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library
The Complete Guide To Data Visualization With Python
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Author : Greyson Chesterfield
language : en
Publisher: Independently Published
Release Date : 2024-12-09
The Complete Guide To Data Visualization With Python written by Greyson Chesterfield and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-09 with Computers categories.
Unlock the power of data visualization with The Complete Guide to Data Visualization with Python: Master Data Presentation with Matplotlib, Seaborn, and Plotly. Whether you're a data scientist, analyst, or aspiring Python programmer, this comprehensive guide will teach you how to effectively present your data using the most popular Python libraries: Matplotlib, Seaborn, and Plotly. In today's world of big data, the ability to visualize complex datasets is essential for making informed decisions. This book will show you how to create compelling, insightful, and interactive visualizations that transform raw data into meaningful stories. With practical examples and clear explanations, you'll gain hands-on experience and the skills needed to present data in ways that are both engaging and easy to understand. What's Inside: Introduction to Data Visualization: Understand the importance of data visualization and how it can help you communicate your insights effectively. Getting Started with Matplotlib: Learn the basics of Matplotlib, the foundational library for creating static plots and charts. Create line graphs, bar charts, histograms, and more. Enhancing Visuals with Seaborn: Dive into Seaborn, built on top of Matplotlib, and discover how to create beautiful, statistical visualizations like heatmaps, violin plots, and pair plots. Interactive Plots with Plotly: Explore Plotly for creating interactive, web-based visualizations. Learn how to make dashboards, 3D plots, and dynamic charts that enhance data exploration. Advanced Visualization Techniques: Learn how to create more advanced visualizations, such as geographical maps, network graphs, and animated plots. Customizing Plots: Master the art of customizing visualizations with colors, styles, labels, and annotations to make your charts both informative and visually appealing. Data Exploration and Visualization Best Practices: Learn best practices for visualizing data, including how to choose the right type of chart, interpret visualized data, and design for clarity and impact. Visualizing Real-World Datasets: Work with real-world datasets to create visualizations that provide meaningful insights in various domains like business, finance, healthcare, and more. Optimizing Visualizations for Reports and Presentations: Learn how to prepare and export visualizations for presentations, reports, and web use, ensuring they look professional and are easy to understand. By the end of this book, you'll be equipped with the skills to create a wide range of stunning, insightful, and interactive data visualizations using Python. Whether you're working with small datasets or big data, you'll have the knowledge to communicate complex data clearly and effectively. Take your data visualization skills to the next level and start building impactful visualizations with The Complete Guide to Data Visualization with Python today!
Creating Interactive Presentations With Shiny And R
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Author : Charlie Joey Hadley
language : en
Publisher:
Release Date : 2016
Creating Interactive Presentations With Shiny And R written by Charlie Joey Hadley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Analyzing big data is great, but not if you can't share your results. In this course, Martin Hadley shows how to create interactive presentations of large data sets with R, RStudio, and Shiny, an R-based tool for producing interactive, web-ready data visualizations. Learn why these tools are important to data scientists, how to configure and install them, and how to use them to make your findings more clear and engaging. Discover the different types of presentations you can make right out of the box with R Markdown templates (built right into RStudio) and how to customize the templates with CSS. Find out how to register for RPubs to deploy RStudio presentations for sharing, and then go beyond the basics with Shiny-adding interactivity and creating embeddable dashboards without the need for HTML or JavaScript. This is an exciting course for analysts who want to increase the relevance and visibility of their work. Make sure to watch the knowledge checks at the end of each chapter to test your new skills.
Creating Interactive Presentations With Shiny And R
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Author :
language : en
Publisher:
Release Date : 2016
Creating Interactive Presentations With Shiny And R written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Analyzing big data is great, but not if you can't share your results. In this course, Martin Hadley shows how to create interactive presentations of large data sets with R, RStudio, and Shiny, an R-based tool for producing interactive, web-ready data visualizations. Learn why these tools are important to data scientists, how to configure and install them, and how to use them to make your findings more clear and engaging. Discover the different types of presentations you can make right out of the box with R Markdown templates (built right into RStudio) and how to customize the templates with CSS. Find out how to register for RPubs to deploy RStudio presentations for sharing, and then go beyond the basics with Shiny-adding interactivity and creating embeddable dashboards without the need for HTML or JavaScript. This is an exciting course for analysts who want to increase the relevance and visibility of their work. Make sure to watch the knowledge checks at the end of each chapter to test your new skills.
Learn Rstudio Ide
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Author : Matthew Campbell
language : en
Publisher: Apress
Release Date : 2019-04-17
Learn Rstudio Ide written by Matthew Campbell and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-17 with Computers categories.
Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data from diverse sources such as SAS files, CSV files, and JSON. You will map out the features in RStudio so that you will be able to customize RStudio to fit your own style of coding. Finally, you will see how to save a ton of time by adopting best practices and using packages to extend RStudio. Learn RStudio IDE is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects. What YouWill Learn Quickly, effectively, and productively use RStudio IDE for building data science applications Install RStudio and program your first Hello World application Adopt the RStudio workflow Make your code reusable using RStudio Use RStudio and Shiny for data visualization projects Debug your code with RStudio Import CSV, SPSS, SAS, JSON, and other data Who This Book Is For Programmers who want to start doing data science, but don’t know what tools to focus on to get up to speed quickly.