Provide a data frame with event data to create a visual and interactive timeline plot rendered by Plotly. Simplest drawable dataframe can have columns event and start.

vistime(
  data,
  col.event = "event",
  col.start = "start",
  col.end = "end",
  col.group = "group",
  col.color = "color",
  col.fontcolor = "fontcolor",
  col.tooltip = "tooltip",
  optimize_y = TRUE,
  linewidth = NULL,
  title = NULL,
  show_labels = TRUE,
  background_lines = NULL,
  source = "A",
  customdata = NULL,
  ...
)

Arguments

data

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.fontcolor

(optional, character) the column name in data that contains the font color for event labels. Default: fontcolor, if not present, color will be black.

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 built from event name and date.

optimize_y

(optional, logical) distribute events on y-axis by smart heuristic (default), otherwise use order of input data.

linewidth

(optional, numeric) the linewidth (in pixel) for the events (typically used for large amount of parallel events). Default: heuristic value.

title

(optional, character) the title to be shown on top of the timeline. Default: NULL.

show_labels

(optional, boolean) choose whether or not event labels shall be visible. Default: TRUE.

background_lines

(optional, integer) the number of vertical lines to draw in the background to demonstrate structure (default: 10). Less means more memory-efficient plot.

source

(optional, character) event source label (see plotly::plot_ly())

customdata

(optional, character vector) values to make available to Plotly's event data. Recycled across values in data where possible.

...

for deprecated arguments up to vistime 1.1.0 (like events, colors, ...)

Value

vistime returns an object of class plotly and htmlwidget.

See also

Functions ?hc_vistime and ?gg_vistime for different charting engines (Highcharts and ggplot2).

Examples

# presidents and vice 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"),
  fontcolor = c("black", "white", "black")
)

vistime(pres, col.event = "Position", col.group = "Name", title = "Presidents of the USA")
if (FALSE) { # \dontrun{ # 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") vistime(data, optimize_y = TRUE) # `FALSE` will plot events as-is, not saving any space: vistime(data, optimize_y = FALSE) # more complex and colorful example data <- read.csv(text = "event,group,start,end,color Phase 1,Project,2018-12-22,2018-12-23,#c8e6c9 Phase 2,Project,2018-12-23,2018-12-29,#a5d6a7 Phase 3,Project,2018-12-29,2019-01-06,#fb8c00 Phase 4,Project,2019-01-06,2019-02-02,#DD4B39 Room 334,Team 1,2018-12-22,2018-12-28,#DEEBF7 Room 335,Team 1,2018-12-28,2019-01-05,#C6DBEF Room 335,Team 1,2019-01-05,2019-01-23,#9ECAE1 Group 1,Team 2,2018-12-22,2018-12-28,#E5F5E0 Group 2,Team 2,2018-12-28,2019-01-23,#C7E9C0 3-200,category 1,2018-12-25,2018-12-25,#1565c0 3-330,category 1,2018-12-25,2018-12-25,#1565c0 3-223,category 1,2018-12-28,2018-12-28,#1565c0 3-225,category 1,2018-12-28,2018-12-28,#1565c0 3-226,category 1,2018-12-28,2018-12-28,#1565c0 3-226,category 1,2019-01-19,2019-01-19,#1565c0 3-330,category 1,2019-01-19,2019-01-19,#1565c0 1-217.0,category 2,2018-12-27,2018-12-27,#90caf9 3-399.7,moon rising,2019-01-13,2019-01-13,#f44336 8-831.0,sundowner drink,2019-01-17,2019-01-17,#8d6e63 9-984.1,birthday party,2018-12-22,2018-12-22,#90a4ae F01.9,Meetings,2018-12-26,2018-12-26,#e8a735 Z71,Meetings,2019-01-12,2019-01-12,#e8a735 B95.7,Meetings,2019-01-15,2019-01-15,#e8a735 T82.7,Meetings,2019-01-15,2019-01-15,#e8a735") vistime(data) # ------ It is possible to change all attributes of the timeline using plotly_build(), # ------ which generates a list which can be inspected using str p <- vistime(data.frame(event = 1:4, start = c("2019-01-01", "2019-01-10"))) pp <- plotly_build(p) # transform into a list # Example 1: change x axis font size: pp$x$layout$xaxis$tickfont <- list(size = 28) pp # Example 2: change y axis font size: pp$x$layout[["yaxis"]]$tickfont <- list(size = 28) pp # Example 3: Changing events font size for (i in 1:length(pp$x$data)) { if (pp$x$data[[i]]$mode == "text") pp$x$data[[i]]$textfont$size <- 28 } pp # or, using purrr: text_idx <- which(purrr::map_chr(pp$x$data, "mode") == "text") for(i in text_idx) pp$x$data[[i]]$textfont$size <- 28 pp # Example 4: change marker size # loop over pp$x$data, and change the marker size of all text elements to 50px for (i in 1:length(pp$x$data)) { if (pp$x$data[[i]]$mode == "markers") pp$x$data[[i]]$marker$size <- 40 } pp # or, using purrr: marker_idx <- which(purrr::map_chr(pp$x$data, "mode") == "markers") for(i in marker_idx) pp$x$data[[i]]$marker$size <- 40 pp } # }