6.6 Interative Plot with plotly()

Until now, all the plots we created are all static. In this section, we will introduce a powerful tool named plotly() that can make interactive plots. If you haven’t done so, you need to first install the R package plotly.

install.pacakges("plotly")

Let’s start with a static scatterplot and make it interactive.

library(r02pro)
library(ggplot2)
library(plotly)
#> 
#> Attaching package: 'plotly'
#> The following object is masked from 'package:ggplot2':
#> 
#>     last_plot
#> The following object is masked from 'package:stats':
#> 
#>     filter
#> The following object is masked from 'package:graphics':
#> 
#>     layout
my_plot <- ggplot(data = gm2004) + 
    geom_point(mapping = aes(x = sugar, 
                             y = cholesterol))
ggplotly(my_plot)

Upon a first look, this may look identical to a regular scatterplot. However, you can try to move your cursor to the points which will show the corresponding coordinates. Some other features offered are available via a bar of buttons on the top right of the plot. Some useful features include

  • Download plot as png.
  • Zoom: Zoom a region of the plot.
  • Pan: Move the plot around.

In addition to the vanilla scatterplots, you can use plotly with more complicated plots that involves aesthetics.

my_plot_continent <- ggplot(data = gm2004) + 
    geom_point(mapping = aes(x = sugar, 
                             y = cholesterol,
                             color = continent))
ggplotly(my_plot_continent)

Now, you can easily see the continent in addition to the sugarand cholesterol values for each data point.

Let’s try to use plotly with some other types of plots.

my_box_plot <- ggplot(data = na.omit(sahp), 
            aes(x = house_style, 
                y = sale_price)) +
  scale_x_discrete(limits=c("1Story", "2Story")) + geom_boxplot(mapping = aes(color = oa_qual > 5))
ggplotly(my_box_plot)

For boxplots, we can easily see the values of summary statistics. You are welcome to try out plotly on other types of plots.