Data Visualization with R and ggplot2

Master the grammar of graphics and the ggplot2 library, building plots with seven layers: data, aesthetics, geometries, facets, statistics, coordinates, and theme.

Learn how aesthetics map data variables to graph properties in ggplot2, mapping x and y, and use color, size, shape, fill, and transparency while avoiding visual noise.

Explore how to tailor non-data elements in ggplot2 with the theme function and theme sets, override defaults, and adjust axis text, titles, margins, and facet strips for polished visuals.

Prepare tidy data for visualization by mastering data wrangling and cleaning with essential functions from deep layer and tyler, including long from wide and wide to long transformations.

Learn to summarize and group data in R using summarize and group_by, performing mean, standard deviation, and median per group to create concise summary tables.

Explore pivoting between wide and long data formats using tidyr's pivot_longer and pivot_wider, and reshape data for modeling and visualization.

Explore the diamonds dataset in R using ggplot2, inspect variables such as carat, price, cut, color, clarity, and dimensions, and create smaller samples to visualize distributions and outliers.

Explore visualizing continuous bivariate data in R with ggplot2 using heat maps, two-dimensional densities, and hex bin maps; map price vs length in the diamonds data, adjusting bins and colors.

Explains how a boxplot compares one discrete and one continuous variable, visualizing median, quartiles, IQR, and outliers across diamond cuts with prices.

Explore matrix plots that compare all pairs of variables in a data frame, with diagonal distributions and visualizations such as histograms, density plots, and the correlation coefficient.

Watch an assignment walkthrough on data visualization with R and ggplot2. Build and customize plots, map aesthetics to car attributes, and run, train, and compare predictive models with train-test splits.

Create the price prediction models section by building models, selecting a target price, and evaluating accuracy with RMSE. Present results in a report with tables using kableExtra.

Learn to customize html output for data visualization reports by creating and applying css templates, adjusting fonts, margins, and table of contents, and integrating markdown and templates for polished reports.

Learn to build markdown reports, create plots, and develop price prediction models using the diamonds dataset and cars dataset, with a guided markdown report walkthrough of assignments.

Walk through an assignment in r, using markdown templates to explore the diamonds and cars datasets, create single and multiple-variable plots, and build a highway consumption model.

Explore a range of plots in data visualization with R and ggplot2, from pie and doughnut charts to time-series, heat maps, parallel coordinates, and coronavirus data maps.

Learn how to build a donut chart in R using ggplot2, including data frame setup, calculating percentages, customizing labels, colors, and polar coordinates for a polished visualization.

Visualize time series with a line chart in ggplot2 using economics data to plot unemployment and indicators, format date axis, reshape to long format, and apply a log scale.

Explore creating a mosaic plot in R to visualize relationships among discrete variables, using Titanic data to compare class, sex, age, and survival with the mosaic package.

Learn to create world maps with ggplot2 using the maps package and a world database, plotting infected, killed, and recovered counts with borders, longitude–latitude coordinates, and facets.

Design and apply custom themes in ggplot2 by building from built-in themes, testing with multiple color schemes, and adjusting margins, titles, and axis text.

Learn to annotate and label ggplot2 visuals by generating two normal distributions, mapping x and y, and adding mean labels and decade annotations for unemployment data.

Apply gghighlight to histograms of the diamonds data to emphasize subsets such as carat greater than 3 or 2.5 with price over 15000, using optional labels and facets.

Learn to build and customize ggplot2 visualizations in R, covering data preparation, long-to-wide transformations, and plotting multiple assets—including cryptocurrency prices and corona data set—with themes, labels, and a logarithmic scale.

Reproduce FiveThirtyEight-style visualizations in R with ggplot2, including a congress-age line chart by party and a state bar plot of speeding collisions, using the 538 data package.

Load the fiveThirtyEight congress age data, compute average age by party over term start years, and render a ggplot2 split line chart with custom labels, colors, and theme.

Explore reproducing a 538 figure about four Tarantino movies using R and ggplot2, including profanity counts and deaths, with guidance on subplots and labeling.

Create and prepare a data frame of movie events, then build a ggplot2 visualization with profanity and death events by minute, using subplots and custom scales.