Adding layers

Interactive Data Visualization with plotly in R

Adam Loy

Statistician, Carleton College

Wine data

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...
$ Ash             <dbl> 2.43, 2.14, 2.67, 2.50, 2.87, 2.45, 2.45, 2.61...
$ Alcalinity      <dbl> 15.6, 11.2, 18.6, 16.8, 21.0, 15.2, 14.6, 17.6...
...
$ Color           <dbl> 5.64, 4.38, 5.68, 7.80, 4.32, 6.75, 5.25, 5.05...
$ 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,...

Adding a smoother

m <- loess(Alcohol ~ Flavanoids, data = wine, span = 1.5)

wine %>%
  plot_ly(x = ~Flavanoids, y = ~Alcohol) %>%
  add_markers() %>%

  add_lines(y = ~fitted(m)) %>%

  layout(showlegend = FALSE)

Adding a second smoother

m2 <- lm(Alcohol ~ poly(Flavanoids, 2), data = wine)

wine %>%
  plot_ly(x = ~Flavanoids, y = ~Alcohol) %>%
  add_markers(showlegend = FALSE) %>%
  add_lines(y = ~fitted(m), name = "LOESS") %>%
  add_lines(y = ~fitted(m2), name = "Polynomial")

Layering densities

d1 <- filter(wine, Type == 1)
d2 <- filter(wine, Type == 2)
d3 <- filter(wine, Type == 3)

density1 <- density(d1$Flavanoids)
density2 <- density(d2$Flavanoids)
density3 <- density(d3$Flavanoids)

plot_ly(opacity = 0.5) %>%
  add_lines(x = ~density1$x, y = ~density1$y, name = "Type 1") %>%
  add_lines(x = ~density2$x, y = ~density2$y, name = "Type 2") %>%
  add_lines(x = ~density3$x, y = ~density3$y, name = "Type 3") %>%
  layout(xaxis = list(title = 'Flavonoids'),
         yaxis = list(title = 'Density'))

Let's practice!

Interactive Data Visualization with plotly in R