In this chapter, you will receive an introduction to basic graphics with plotly. You will create your first interactive graphics, displaying both univariate and bivariate distributions. Additionally, you will discover how to easily convert ggplot2 graphics to interactive plotly graphics. 

What is plotly?

A follow-up on the course intro

Converting a ggplot2 scatterplot

Univariate graphics

Histograms

Bar charts

Bivariate graphics

A first scatterplot

A first stacked bar chart

Boxplots

Introduction to plotly

In this chapter, you will learn how to customize the appearance of your graphics and use opacity, symbol, and color to clarify your message. You will also learn how to transform axes, label your axes, and customize the hover information of your graphs.

Customize your traces

Color and opacity

Alternative color formats

Size and symbol

Thoughtful use of color

Adding a third variable

Beyond color: Symbols

Transforming a color scale

Hover info

Removing a piece of hover info

Adding to hoverinfo

Custom hoverinfo

Customizing your layout

Polishing a scatterplot

Matching a theme

Styling and customizing your graphics

In this chapter, you move past basic plotly charts to explore more-complex relationships and larger datasets. You will learn how to layer traces, create faceted charts and scatterplot matrices, and create binned scatterplots.

Layering traces

Adding a linear smoother

Overlayed density plots

Subplots

Manual faceting

Automated faceting

Plot and axis titles

Polishing axis titles

Scatterplot matrices

Your first SPLOM

Customizing color

Tweaking the appearance

Binned scatterplots

Binning a scatterplot

Advanced charts

In the final chapter, you use your plotly toolkit to explore the results of the 2018 United States midterm elections, learning how to create maps in plotly along the way.

Introduction to the 2018 election data

Did voters turn out?

Adding a reference line

Which state had the highest turnout?

How much was spent on Senate races?

Which candidate spent the most?

Choropleth maps

Mapping change in voter turnout

Mapping Senate winners

Adding points to a map

Geo layout

From polygons to maps

Mapping Senate winners, redux

A county-level choropleth map

Wrap-up

Case Study

Video game sales and ratings dataset

Wine datasets

Midterm election datasets

Interactive graphics allow you to manipulate plotted data to gain further insight. As an example, an interactive graphic would allow you to zoom in on a subset of your data without the need to create a new plot. In this course, you will learn how to create and customize interactive graphics in plotly using the R programming language. Along the way, you will review data visualization best practices and be introduced to new plot types such as scatterplot matrices and binned scatterplots.

<h2>Build Interactive Data Visualizations in plotly </h2>
Interactive graphics allow you to manipulate plotted data to gain further insights. As an example, an interactive graphic would allow you to zoom in on a subset of your data without the need to create a new plot. In this course, you will learn how to create and customize interactive graphics in plotly using R.
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<h2>Get Started Using plotly</h2>
You’ll start the course with an introduction to plotly and a view of different plots you can make using this R package, including histograms, bar charts, bivariate graphics, scatterplots, and boxplots. You’ll also learn how to convert a ggplot2 scatterplot into plotly so that you can enhance your graphics and dashboards. 
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<h2>Explore Creating plotly Plots and Dashes </h2>
The next two chapters of the course show you how you can customize your graphics to build the perfect dashboard, and even add hover-over information to add detail and depth. Then you’ll move on to advanced charts that visualize complex relationships and larger datasets. By completing this course, you’ll be able to create manual and automated faceting, binned scatterplots, and your first scatter plot matrix (SPLOM).
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<h2>Create Visualizations with Real-World Data </h2>
The final chapter of this course uses your new-found plotly skills to visualize the results of the 2018 US elections. You’ll create the first interactive plotly dash in your portfolio and learn how to create maps using this valuable data visualization tool. 

Introduction to the Tidyverse

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling. 

Interactive Data Visualization with plotly in R

Visualisation interactive des données en R

Statistician, Carleton College

Faceting plotly graphics

2016 video game sales

Representing many categories

A single subplot

Two subplots

Legends

Axis labels

Iterate to automate

Let's practice!

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Advanced charts - Subplots

Subplots

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