Interactive timeline plots with hc

1. Basic example

library(vistime)
timeline_data <- data.frame(event = c("Event 1", "Event 2"), 
                            start = c("2020-06-06", "2020-10-01"), 
                            end = c("2020-10-01", "2020-12-31"), 
                            group = "My Events")

hc_vistime(timeline_data)

2. Installation

To install vistime package from CRAN, type the following in your R console:

install.packages("vistime")

For interactive hc_vistime() plots, you need to install the highcharter package. This package is free for non-commercial and non-governmental use:

install.packages("highcharter")

3. Usage and default arguments

The simplest way to create a timeline is by providing a data frame with event and start columns. If your columns are named otherwise, you need to tell the function. You can also tweak the y positions, title and label visibility.

hc_vistime(data,
           col.event = "event",
           col.start = "start",
           col.end = "end", 
           col.group = "group", 
           col.color = "color", 
           optimize_y = TRUE,
           title = NULL, 
           show_labels = TRUE)

4. Arguments

parameter	optional?	data type	explanation
data	mandatory	data.frame	data.frame that contains the data to be visualized
col.event	optional	character	the column name in data that contains event names. Default: event
col.start	optional	character	the column name in data that contains start dates. Default: start
col.end	optional	character	the column name in data that contains end dates. Default: end
col.group	optional	character	the column name in data to be used for grouping. Default: group
col.color	optional	character	the column name in data that contains colors for events. Default: color, if not present, colors are chosen via RColorBrewer.
col.tooltip	optional	character	the column name in data that contains the mouseover tooltips for the events. Default: tooltip, if not present, then tooltips are build from event name and date. Basic HTML is allowed.
optimize_y	optional	logical	distribute events on y-axis by smart heuristic (default) or use order of input data.
title	optional	character	the title to be shown on top of the timeline. Default: empty.
show_labels	optional	logical	choose whether or not event labels shall be visible. Default: `TRUE`.

5. Value

hc_vistime returns an object of class highchart and htmlwidget

6. Examples

Ex. 1: Presidents

pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'))
                  
hc_vistime(pres, 
           col.event = "Position", 
           col.group = "Name", 
           title = "Presidents of the USA") %>% 
  hc_size(width = 700, height = 300)

Ex. 2: Project Planning

data <- read.csv(text="event,group,start,end,color
                       Phase 1,Project,2016-12-22,2016-12-23,#c8e6c9
                       Phase 2,Project,2016-12-23,2016-12-29,#a5d6a7
                       Phase 3,Project,2016-12-29,2017-01-06,#fb8c00
                       Phase 4,Project,2017-01-06,2017-02-02,#DD4B39
                       Room 334,Team 1,2016-12-22,2016-12-28,#DEEBF7
                       Room 335,Team 1,2016-12-28,2017-01-05,#C6DBEF
                       Room 335,Team 1,2017-01-05,2017-01-23,#9ECAE1
                       Group 1,Team 2,2016-12-22,2016-12-28,#E5F5E0
                       Group 2,Team 2,2016-12-28,2017-01-23,#C7E9C0
                       3-200,category 1,2016-12-25,2016-12-25,#1565c0
                       3-330,category 1,2016-12-25,2016-12-25,#1565c0
                       3-223,category 1,2016-12-28,2016-12-28,#1565c0
                       3-225,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2017-01-19,2017-01-19,#1565c0
                       3-330,category 1,2017-01-19,2017-01-19,#1565c0
                       1-217.0,category 2,2016-12-27,2016-12-27,#90caf9
                       4-399.7,moon rising,2017-01-13,2017-01-13,#f44336
                       8-831.0,sundowner drink,2017-01-17,2017-01-17,#8d6e63
                       9-984.1,birthday party,2016-12-22,2016-12-22,#90a4ae
                       F01.9,Meetings,2016-12-26,2016-12-26,#e8a735
                       Z71,Meetings,2017-01-12,2017-01-12,#e8a735
                       B95.7,Meetings,2017-01-15,2017-01-15,#e8a735
                       T82.7,Meetings,2017-01-15,2017-01-15,#e8a735")
                           
hc_vistime(data)

Ex. 3: Gantt Charts

The argument optimize_y can be used to change the look of the timeline. TRUE (the default) will find a nice heuristic to save y-space, distributing the events:

data <- read.csv(text="event,start,end
                       Phase 1,2020-12-15,2020-12-24
                       Phase 2,2020-12-23,2020-12-29
                       Phase 3,2020-12-28,2021-01-06
                       Phase 4,2021-01-06,2021-02-02")
        
hc_vistime(data, optimize_y = TRUE)

FALSE will plot events as-is, not saving any space:

hc_vistime(data, optimize_y = FALSE)

8. Usage in Shiny apps

hc_vistime() objects can be integrated into Shiny via highchartOutput() and renderHighchart()

library(vistime)

pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'))

shinyApp(
  ui = highcharter::highchartOutput("myVistime"),
  server = function(input, output) {
    output$myVistime <- highcharter::renderHighchart({
      vistime(pres, col.event = "Position", col.group = "Name")
    })
  }
)

9. Customization

Since every hc_vistime() output is a highchart object, you can customize and override literally everything using its functions. See ?hc_xAxis, ?hc_chart etc. and the official Highcharts API reference for details.

library(highcharter)

p3 <- hc_vistime(data,
                 optimize_y = T, 
                 col.group = "event",
                 title = "Highcharts customization example")

p3 %>% hc_title(style = list(fontSize = 30)) %>% 
       hc_yAxis(labels = list(style = list(fontSize=30, color="violet"))) %>% 
       hc_xAxis(labels = list(style = list(fontSize=30, color="red"), rotation=30)) %>% 
       hc_chart(backgroundColor = "lightgreen") %>% 
  hc_size(width = 700, height = 300)

Interactive timeline plots with hc_vistime()