R: Interactive Visualizations With Html Widgets Assignment Help

Using almost entirely the R programming language, htmlwidgets allows you to create the same interactive maps, charts, and graphs that you see on popular data journalism sites and in BI dashboards. htmlwidget packages allow you to connect R to popular JavaScript libraries such as Plotly and Leaflet. Your interactive visualisations can be used in R Markdown reports and presentations, as well as in rich, responsive Shiny applications. This course will teach you the fundamental skills required to incorporate htmlwidgets into your R workflow.
Begin by learning how to use the tidyverse and the pipe operator to manage packages and structure data for visualisations. Then there’s the big question: which library should you go to? The course covers five well-known options: Leaflet, Plotly, Highchart, visNetwork, and DataTables (DT). Charlie Hadley, the instructor, demonstrates how to use these libraries to create scattergeo, choropleth, and geolines maps; stacked bar charts, scatter charts, bubble charts, and heat maps; treemaps and time series charts; interactive networks and graphs; and responsive, interactive data tables. Learn how to customise your visualisations with legends and tooltips, as well as how to extract click data for Shiny apps.

KEY FEATURE

Client-side filtering and linked brushing between widgets are currently supported. Shiny can be used to create more sophisticated interactions.

R and JavaScript can both prepare data and visualise it on their own. However, when combined, they can create an efficient and impressive pipeline.

Java is a compiled language, whereas JavaScript (similar to R) is a scripting language that can be saved as a text file and run through an interpreter.

There are numerous libraries available for creating visually appealing and fully interactive data visualisations for the web.

R: Interactive Visualizations With Html Widgets Assignment Help

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    Html widgets Assignment Help

    JavaScript is one of the most popular scripting languages for creating interactive websites. The html widgets package provides a framework for binding R commands to existing, interactive JavaScript libraries, such as those that generate data graphs. The framework-created interactive components (“widgets”) can be:
    • used in the R console for data analysis in the same way that traditional R plots are
    • R Markdown documents and Shiny web applications are seamlessly integrated.
    • saved as standalone web pages for on-the-fly sharing via email, Dropbox, and so on
    While you can certainly create your own widget, there are a number of pre-installed widgets that make creating interactive visualisations much easier. Indeed, all of the packages used in the examples in section?? are based on htmlwidgets.
    Check out the htmlwidgets gallery for a comprehensive list. The graphics are rendered locally by the htmlwidgets framework. They run in either your web browser or the R Studio viewer by default. If you use R Markdown, the html pages generated contain the complete JavaScript code, allowing you to deploy them to a standard webserver.

    Topics We Cover Under R: Interactive Visualizations With Html Widgets

    Learn how to create rich, interactive data visualisations quickly using R and htmlwidgets—packages that connect R to popular JavaScript libraries such as Plotly, Leaflet, and DT.

    1. Getting Started with htmlwidgets

    • What are htmlwidgets?
    • Where can you use htmlwidgets?
    • Set up RStudio for htmlwidgets
    • Install htmlwidget libraries
    • Select the best htmlwidget
    • Use the pipe operator (%>%)
    • Prepare data to be tidy

    2. Creating Interactive Maps with Leaflet

    • What is the Leaflet library?
    • Create interactive scattergeo maps
    • Change map styles in Leaflet
    • Prepare data for a choropleth plot
    • Create interactive choropleth maps
    • Create interactive geolines maps
    • Add legends to Leaflet maps
    • Extract click information from Leaflet

    3. Creating Interactive Maps with Leaflet

    • What is the Plotly library?
    • Make ggplot2 interactive using Plotly
    • Create interactive stacked bar charts
    • Interactive scatter, line, and bubble charts with Leaflet
    • Create interactive maps
    • Specify custom colors
    • Customize tooltips
    • Combine multiple charts
    • Extract click information from Plotly

    4. Creating Interactive Charts with Highcharter

    • What is the Highcharter library?
    • Create interactive stacked bar charts
    • Create interactive scatter charts and bubble charts
    • Create interactive time series
    • Create interactive treemaps
    • Create interactive choropleth maps
    • Specify your own colors
    • Modify tooltips in Highcharter
    • Extract click information from Highcharter

    5. Creating Interactive Networks with visNetwork

    • What is the visNetwork library?
    • Create basic network diagrams
    • Style visNetwork graph
    • Use visNetwork with igraph
    • Choose graph layouts and embeddings
    • Cluster nodes in visNetwork using groups
    • Add legends to visNetwork
    • Extract click information from visNetwork

    6. Creating Interactive Tables

    • What is the DT library?
    • Create interactive data tables with DT
    • Format columns and data
    • Design responsive (mobile-ready) tables
    • Allow users to download data
    • Extract click information from data tables

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