Learn how to use ggplot2, a powerful R package for data visualization, to create and customize bar charts with categorical data.

R is a widely used language for statistical analysis and data visualization. It has many packages that enable creating interactive charts, such as plotly, ggplot2, shiny, and leaflet. For example ...

Contribute to giahy2507/visreflect-examples development by creating an account on GitHub.

<p>Reordering groups in a <code>ggplot2</code> chart can be a struggle. This is due to the fact that ggplot2 takes into account the order of the <code>factor</code> levels, not the order you observe ...

Create R data visualizations easily with a few lines of simple code using the ggcharts R package. Plus, the resulting charts and graphs are customizable ggplot objects. ggplot2 is an enormously ...

Here are a dozen great ggplot2 extensions you should know, along with example code and graphics. As a bonus, I’ve included a list of additional packages worth exploring at the end of the article.

An example of a relative filepath would be: /charts/line_chart.png. width_pixels: this is set to 640px by default, so only call this argument and specify the width you want your chart to be.

Scraping Pro-Football Data and Interactive Charts using rCharts, ggplot2, and shiny. This is a highly useful example of beginning-to-end data analysis with R.