An Introduction to plotly

Interactive Data Visualization with plotly in R

Adam Loy

Statistician, Carleton College

plotly

Visualization library for interactive and dynamic web-based graphics
Plots work in multiple formats
- viewer windows
- R Markdown documents
- shiny apps
Active development + supportive community

Static vs. Interactive graphics

Wine data

library(dplyr)
glimpse(wine)

Rows: 178
Columns: 14
$ Type            <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1...
$ Alcohol         <dbl> 14.23, 13.20, 13.16, 14.37, 13.24, 14.20, 14.3...
$ Malic           <dbl> 1.71, 1.78, 2.36, 1.95, 2.59, 1.76, 1.87, 2.15...
...
$ Hue             <dbl> 1.04, 1.05, 1.03, 0.86, 1.04, 1.05, 1.02, 1.06...
$ Dilution        <dbl> 3.92, 3.40, 3.17, 3.45, 2.93, 2.85, 3.58, 3.58...
$ Proline         <int> 1065, 1050, 1185, 1480, 735, 1450, 1290, 1295,...

ggplot2 scatterplot

library(ggplot2)
static <- wine %>%
  ggplot(aes(x = Flavanoids, y = Proline, color = Type)) +
  geom_point()

Dataset, wine
Aesthetics, aes()
Add a layer, geom_point()

ggplotly()

library(plotly)

ggplotly(static)

Remarks

Interactive ? Good
- Bad design = bad interactive graphic
- Follow data-viz best practices
ggplotly() is only the beginning

Let's practice!

Interactive Data Visualization with plotly in R