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,
...
)data.frame that contains the data to be visualized
(optional, character) the column name in data that contains event
names. Default: event.
(optional, character) the column name in data that contains start
dates. Default: start.
(optional, character) the column name in data that contains end dates.
Default: end.
(optional, character) the column name in data to be used for
grouping. Default: group.
(optional, character) the column name in data that contains colors
for events. Default: color, if not present, colors are chosen via
RColorBrewer.
(optional, character) the column name in data that contains the
font color for event labels. Default: fontcolor, if not present,
color will be black.
(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.
(optional, logical) distribute events on y-axis by smart heuristic (default), otherwise use order of input data.
(optional, numeric) the linewidth (in pixel) for the events (typically used for large amount of parallel events). Default: heuristic value.
(optional, character) the title to be shown on top of the timeline.
Default: NULL.
(optional, boolean) choose whether or not event labels shall be
visible. Default: TRUE.
(optional, integer) the number of vertical lines to draw in the background to demonstrate structure (default: 10). Less means more memory-efficient plot.
(optional, character) event source label (see plotly::plot_ly())
(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, ...)
vistime returns an object of class plotly and htmlwidget.
Functions ?hc_vistime and ?gg_vistime for different charting engines (Highcharts and ggplot2).
# 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) {
# 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
}