Time module — time_ui • epishiny

Visualise data over time with an interactive 'epicurve'.

Usage

time_ui(
  id,
  date_vars,
  count_vars = NULL,
  group_vars = NULL,
  title = "Time",
  icon = bsicons::bs_icon("bar-chart-line-fill"),
  tooltip = NULL,
  opts_btn_lab = "options",
  date_lab = "Date axis",
  date_int_lab = "Date interval",
  date_intervals = c(Day = "day", Week = "week", Month = "month"),
  count_vars_lab = "Indicator",
  groups_lab = "Group data by",
  no_grouping_lab = "No grouping",
  bar_stacking_lab = "Bar stacking",
  cumul_data_lab = "Show cumulative data?",
  ratio_line_lab = "Show ratio line?",
  full_screen = TRUE
)

time_server(
  id,
  df,
  date_vars,
  count_vars = NULL,
  group_vars = NULL,
  show_ratio = FALSE,
  ratio_var = NULL,
  ratio_lab = NULL,
  ratio_numer = NULL,
  ratio_denom = NULL,
  place_filter = shiny::reactiveVal(),
  filter_info = shiny::reactiveVal(),
  filter_reset = shiny::reactiveVal()
)

Arguments

id: Module id. Must be the same in both the UI and server function to link the two.
date_vars: Character vector of date variable(s) for the date axis. If named, names are used as variable labels.
count_vars: If data is aggregated, variable name(s) of count variable(s) in data. If more than one variable provided, a select input will appear in the options dropdown. If named, names are used as variable labels.
group_vars: Character vector of categorical variable names. If provided, a select input will appear in the options dropdown allowing for data groups to be visualised as stacked bars on the epicurve. If named, names are used as variable labels.
title: Header title for the card.
icon: The icon to display next to the title.
tooltip: additional title hover text information
opts_btn_lab: text label for the dropdown menu button.
date_lab: text label for the date variable input.
date_int_lab: text label for the date interval input.
date_intervals: Character vector with choices for date aggregation intervals passed to the unit argument of lubridate::floor_date. If named, names are used as labels. Default is c('day', 'week', 'year').
count_vars_lab: text label for the aggregate count variables input.
groups_lab: text label for the grouping variable input.
no_grouping_lab: text label for the no grouping option in the grouping input.
bar_stacking_lab: text label for bar stacking option.
cumul_data_lab: text label for cumulative data option.
ratio_line_lab: text label for the ratio line input. This input will only be visable if show_ratio is TRUE in time_server
full_screen: Add button to card to with the option to enter full screen mode?
df: Data frame or tibble of patient level or aggregated data. Can be either a shiny reactive or static dataset.
show_ratio: Display a ratio line on the epicurve?
ratio_var: For patient level data, character string of variable name to use for ratio calculation.
ratio_lab: The label to describe the computed ratio i.e. 'CFR' for case fatality ratio.
ratio_numer: For patient level data, Value(s) in ratio_var to be used for the ratio numerator i.e. 'Death'. For aggregated data, character string of numeric count column to use of ratio numerator i.e. 'deaths'.
ratio_denom: For patient level data, values in ratio_var to be used for the ratio denominator i.e. c('Death', 'Recovery'). For aggregated data, character string of numeric count column to use of ratio denominator i.e. 'cases'.
place_filter: supply the output of place_server() wrapped in a shiny::reactive() here to filter the data by click events on the place module map (clicking a polygon will filter the data to the clicked region)
filter_info: If contained within an app using filter_server(), supply the filter_info object returned by that function here wrapped in a shiny::reactive() to add filter information to chart exports.
filter_reset: If contained within an app using filter_server(), supply the filter_reset object returned by that function here wrapped in a shiny::reactive() to reset any click event filters that have been set from by module.

Value

the module server function returns any point click event data of the highchart. see highcharter::hc_add_event_point for details.