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vistime - Pretty Timelines in R

A library for creating time-based charts, like Gantt or timelines. Possible outputs include ggplots, plotly graphs, Highcharts or data.frames. Results can be used in the RStudio viewer pane, in R Markdown documents or in Shiny apps. In the interactive outputs created by vistime() and hc_vistime() you can interact with the plot using mouse hover or zoom. Timelines and their components can afterwards be manipulated using ggplot::theme(), plotly_build() or hc_*functions (for gg_vistime(), vistime() or hc_vistime(), respectively). When choosing the data.frame output, you can use your own plotting engine for visualizing the graph.

If you find vistime useful, please consider supporting its development:

Feedback welcome: sa.ra.online@posteo.de

Table of Contents

1. Installation
2. Main functionality
3. Real-life example
4. Usage and documentation

1. Installation

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

install.packages("vistime")

2. Main functionality

This package vistime provides four main functions, the first three allow you to draw a timeline with Plotly, Highcharts or ggplot2, the last one outputs the pure optimized data frame ready for plotting.

vistime() - interactive Plotly charts

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")
                            
vistime(timeline_data)

hc_vistime() - interactive Highcharts timelines

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)

This is facilitated by the highcharter package, so, this package needs to be installed before attempting to produce any hc_vistime() output.

gg_vistime() - static ggplot2 output

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")
                            
gg_vistime(timeline_data)

vistime_data() - pure data.frame output if you want to draw yourself

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")
                            
vistime_data(timeline_data)

#>     event      start        end     group                                      tooltip      col subplot   y
#> 1 Event 1 2020-06-06 2020-10-01 My Events  from <b>2020-06-06</b> to <b>2020-10-01</b>  #8DD3C7       1   1
#> 2 Event 2 2020-10-01 2020-12-31 My Events  from <b>2020-10-01</b> to <b>2020-12-31</b>  #FFFFB3       1   1

You want to use this for the intelligent y-axis assignment depending on overlapping of events (this can be disabled with optimize_y = FALSE).

3. Real-life example

During COVID-19 2020, @wlhamilton used gg_vistime() for visualizing patient ward movements as timelines in order to investigate possible hospital acquired infections. See his github for the code.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.