Learn Advance Data Visualization with R

Explore the Plotrix package in R to quickly create diverse charts with easy customization, without specialized syntax, including pie charts.

Create a 3d pie chart using a graphics package to visualize a dataset of states, mapping regions, population, income, and murder rate into colored, labeled sectors.

Learn to add tables to a plot by incorporating x and y coordinates into a data table, and use headings and red, green, and blue colors to organize the visualization.

discover radial plots in R, a two-dimensional chart that uses angle and radius to compare multiple data series, with labeled values and customizable plot options.

Learn to build a multi bar chart in R to compare age and sex distributions, using a 32-observation dataset, and apply subset and customization steps.

Learn to build interactive charts in R using the high charts package, visualize a 237-observation dataset with 12 variables, and explore x and y relationships, groupings, and chart views.

Explore how to create a scatterplot chart in R to detect groupings and patterns between two variables, using the charts package with sample data to build and interpret the visualization.

Learn to build an X chart in R by preparing data, renaming fields to category, grouping values, and exporting the chart with a function.

Explore combination charts in R to compare values across categories using bars and lines, visualizing sales, expenses, and profit across dates with a Google visualization package.

Learn to create gauge charts in R that visualize a single metric with a speedometer-style display, using green and yellow colors and a city popularity dataset.

Explore interactive Google Maps in R by using a map function with latitude and longitude data. Configure map types (normal, satellite, hybrid), enable scroll, and show location descriptions.

Explore how to create and interpret a timeline chart in R, visualizing how resources and events unfold over time using a dedicated package.

Demonstrates a treemap built with a Google package to visualize hierarchical data, using size and color to represent attributes across 55 regions and four variables.

Explore how to create a calendar chart in R using a Google library, visualizing date and temperature data from Cairo for 2002–2004 and noting how missing values affect the chart.

Learn to create and customize area charts in R, using colors, textures, and hatchings to emphasize data regions while building datasets by passing values to a function.

Learn to create heat maps that encode data values with color, and configure axes and color palettes using a dataset with 32 observations and 11 variables.

Explore how venn diagrams illustrate all logical relationships between sets, and learn to create, render, customize, and save such diagrams in R using set A and B examples.

Demonstrate building a word cloud in r by loading a text corpus, preprocessing with stopword and number removal and case normalization, and visualizing word frequencies.

Create a three-dimensional bar chart in R with population as the dependent variable across region and income, using color scales and axis settings to interpret the data.

Explore three-dimensional scatterplots in R to visualize relationships among variables, using a three-column dataset with dependent and independent variables, and customize points, colors, and planes interactively.

Discover how the shiny package enables interactive web apps in R, with a two-part UI and server architecture, using controls like radio buttons and dropdowns.

Create a Shiny application in RStudio and learn to install the Shiny package, start a new Shiny project, and build interactive visuals with a histogram and adjustable bins.

Explore how to define HTML headings in a Shiny web app using the page function and title argument. Structure layouts with sidebarLayout, sidebarPanel, and mainPanel to organize headings.

Explore how to add images in a Shiny app, render images within a panel-based layout, and reference non-Latin images with a responsive UI.

Learn the basics of standard shiny widgets and control widgets in shiny applications, including file input and text input, and see how user input updates values in real time.

Explore building a shiny app that uses text input and radio buttons within a side bar layout to capture unstructured text and display results in the main panel.

Learn to add a file upload widget to a Shiny app using a sidebar layout, with fileInput, labels, and controls, plus server logic to read and display data.

Learn to implement the slider input widget in shiny apps using the shiny package, defining input IDs, labels, and min, max, and value settings within a sidebar layout.

Create an interactive box plot in R using shiny, exploring a dataset with measurements in centimeters by species and color coding by species to compare distributions.

Explore advanced data visualization with R by building a pie chart and related bar and area visuals from a multi-variable dataset of 11 variables.

Learn to build a shiny app that connects to a MySQL database, retrieves table data, and visualizes it with bar and pie charts using R.

Learn how the shiny package creates reactive outputs in a shiny app by connecting ui and server logic, using inputs like sliders, checkboxes, and select lists to drive scatter plots.