Interactive Plotting Libraries in R

dataset

library(dplyr)

package ‘dplyr’ was built under R version 3.2.5
Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

head(mtcars)

ggiraph

Github: https://github.com/davidgohel/ggiraph

tooltip

Display the value of gear variable when mouse over a point:

suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(ggiraph))
gg <- ggplot(data = mtcars,
             aes(x = mpg, y = wt, color = factor(cyl))) 
gg1 <-  gg + geom_point_interactive(aes(tooltip = gear), size = 5) 
ggiraph(code = print(gg1))

hover

Fill the point with orange color when mouse over a point:

gg2 <- gg + geom_point_interactive(aes(data_id = gear,
                                       tooltip = gear), size = 5) 
ggiraph(code = print(gg2))

Change the fill color of hover:

gg3 <- gg + geom_point_interactive(aes(data_id = gear,
                                       tooltip = gear), size = 5) 
ggiraph(code = {print(gg3)}, hover_css = "fill:black;" )

click actions

# Add a new variable: vehicle model
mtcars2 <- data.frame(model = rownames(mtcars), mtcars)
# create an 'onclick' column
mtcars2$onclick <- sprintf("window.open(\"%s%s\")",
  "http://www.google.com/images?q=", as.character(mtcars2$model) )
gg4 <- ggplot(data = mtcars2,
             aes(x = mpg, y = wt, color = factor(cyl)))  + 
  geom_point_interactive(
    aes( data_id = model, tooltip = model, onclick = onclick ), size = 5 ) +
  theme_bw()
ggiraph(code = print(gg4),
        hover_css = "fill-opacity:.3;cursor:pointer;")

zoom

ggiraph(code = print(gg4), zoom_max = 7)

plotly

Webpage: https://plot.ly/ggplot2/

Just mouse over the points to see tooltips. You can also zoom, save and lasso select by default:

suppressPackageStartupMessages(library(plotly))

package ‘plotly’ was built under R version 3.2.5

ggplotly(gg + geom_point())

multiple plots

You can also combine multiple plots:

df <- mtcars
df$lab1 <- 'mpg vs cyl'
df$lab2 <- 'disp vs cyl'
mt_mpg <- ggplot(df)+
  geom_boxplot(aes(x = as.factor(cyl), y = mpg))+
  facet_wrap(~lab1)
mt_disp <- ggplot(df)+
  geom_boxplot(aes(x = as.factor(cyl), y = disp))+
  facet_wrap(~lab2)
subplot(mt_mpg, mt_disp)

is.na() applied to non-(list or vector) of type 'NULL'is.na() applied to non-(list or vector) of type 'NULL'

rbokeh

Webpage: http://hafen.github.io/rbokeh/#plot_attributes

You can add tooltips, select and zoom, and also save the plot using buttons:

suppressPackageStartupMessages(library(rbokeh))

package ‘rbokeh’ was built under R version 3.2.5

bb1 <- figure() %>%
  ly_points(mpg, wt, data = mtcars, color = factor(cyl), size = 25, glyph = factor(cyl),
            hover = "This car has @cyl cylinders") %>%
  tool_box_select() %>%
  tool_lasso_select()
bb1