In my previous blog on 30 Sep 2016, I had just discovered the plotly package and was blown away by how easy it was to use plotly to make ggplot2 plots reactive to the user’s mouse.

Well I’ve just stumbled across another package to achieve this called ggiraph, and I ggiraph like even more!!

In my opinion ggiraph integrates with ggolot2 in a nicer way than plotly to achieve basic reactivity to the user’s mouse.

Below is some code to make same fake data as I used in my last blog post, but this time I use ggiraph to turn the static ggplot2 plot from my last blog post into a plot with user reactivity.

The code below uses functions from the “ggplot2”, “stringr”, “dplyr”, “knitr” and “ggiraph” packages.

Use the same fake revenue data as my last blog post, but this time add a column for State Total Revenue ($) per year:

#Make up some fake data
df<-data_frame(state=rep(c("New South Wales", 
                 "Western Australia",
                 "South Australia",
                 "Tasmania"), 36)) %>%
    group_by(state) %>%
    mutate(year=c(rep(2012, 9), rep(2013,9),rep(2014, 9),rep(2015, 9))) %>%
    group_by(state, year) %>%
    mutate(`store ID` = str_c("shop_#",as.character(seq_along(state)))) %>%
    group_by(state, year, `store ID`) %>%
    mutate(`Revenue ($)` =  ifelse(state=="New South Wales", sample(x=c(100000:900000), 1),
                            ifelse(state=="Victoria", sample(x=c(100000:700000), 1),
                            ifelse(state=="Queensland", sample(x=c(100000:500000), 1),
                            ifelse(state=="Western Australia",sample(x=c(10000:200000), 1),
                            ifelse(state=="South Australia",sample(x=c(10000:90000), 1),       
                            ifelse(state=="Tasmania", sample(x=c(10000:200000), 1), NA))))))) %>%
    group_by(state, year) %>%
    mutate(`State Total Revenue ($)` = sum(`Revenue ($)`))

Peak at the first 6 rows of the fake revenue data:

state year store ID Revenue ($) State Total Revenue ($)
New South Wales 2012 shop_#1 271022 3885088
Victoria 2012 shop_#1 207434 4209586
Queensland 2012 shop_#1 236501 3018283
Western Australia 2012 shop_#1 35100 1168335
South Australia 2012 shop_#1 15847 344081
Tasmania 2012 shop_#1 50989 1012868

Get the same ggplot from my last blog most, but this time, add user reactivity using ggiraph…

by replacing ‘geom_boxplot’ and ‘geom_point’ (from the plot in my last blog post) with ‘geom_boxplot_interactive’ and ‘geom_point_interactive’ from the ggiraph package, and then using ggiraph() to print the plot:

#Create the text you want displayed in the tooltop for geom_point_interactive
  df$tooltip_point <- paste0(
    "<b>", df$`store ID`, "</b>",
    "<br>(", df$state, ")",
    "<br>$", df$`Revenue ($)`,

#Create the text you want displayed in the tooltop for geom_boxplot_interactive
  df$tooltip_boxplot <- paste0(
    "<b>", df$state, "</b>",
    "<br>State Total Revenue:",
    "<br>$", df$`State Total Revenue ($)`,

#Make plot reactive to user's mouse with 
#'geom_boxplot_interactive' and 'geom_point_interactive'
point_interactive_plot <- ggplot(df, aes(state, `Revenue ($)`)) +
        geom_boxplot_interactive(aes(colour=state, tooltip=tooltip_boxplot, data_id=tooltip_boxplot)) +
        geom_point_interactive(aes(colour=state, tooltip=tooltip_point, data_id=tooltip_point)) +
        theme(axis.title.x =  element_blank(),
              axis.text.x  =  element_blank(), 
              axis.title.y = element_text(face="bold", size=12),
              axis.text.y  = element_text(angle=0, vjust=0.5, size=11),
              legend.title = element_text(size=12, face="bold"),
              legend.text = element_text(size = 12, face = "bold"),
              plot.title = element_text(face="bold", size=14)) + 
        ggtitle("Store Revenue per State from 2012 to 2015") +

# htmlwidget call
ggiraph(code = {print(point_interactive_plot)}, zoom_max = 5,
        tooltip_offx = 20, tooltip_offy = -10, 
        hover_css = "fill:red;",
        tooltip_opacity = 0.7,
        pointsize = 12)