dashdash: dashdash
In wzb-ipi/dashdash: Make simple dashboards for live data display

Make a .html dashboard. Key required inputs are datasets with 1. data 2. variable interpretations, labels and details 3. other text to be passed as arguments

dashdash(
  output_file,
  my_vars,
  my_data,
  my_args,
  my_blog = NULL,
  title = NULL,
  group = NULL,
  subtitle = NULL,
  author = NULL,
  trend = list("daily"),
  add_maps = NULL,
  map_path = NULL,
  map_region = NULL,
  map_layer = NULL,
  scale_vars = NULL,
  pd_width = 0.1,
  switch = NULL,
  ft_plot = NULL,
  country_code = NULL,
  ...
)

`output_file`	Path to where ouutput should be written, e.g. "docs/index.html"
`my_vars`	dataframe with mapping from variable names to variable families and labels. One row per variable.
`my_data`	dataframe with data on variables listed in 'my_vars'. Should contain a 'id' variable that connects with units in map files and a 'date' variable.
`my_args`	dataframe with arguments to customize a dashboard.
`my_blog`	data frame with blog entries.
`title`	Dashboard title
`subtitle`	Dashboard subtitle
`author`	String, names of authors.
`trend`	List. "daily" for high-frequency daily plots or "moving_average" for 3 day moving average.
`add_maps`	Option to add a map tab
`map_path`	String, path to map shapefiles.
`map_region`	String, map region.
`map_layer`	String, map layer.
`scale_vars`	Logical. Whether to scale_vars variabels before map plotting.
`pd_width`	position dodge argument for graphing aesthetics
`switch`	ggplot2 argument: By default, the labels are displayed on the top and right of the plot. If "x", the top labels will be displayed to the bottom. If "y", the right-hand side labels will be displayed to the left. Can also be set to "both".
`ft_plot`	Add a Financial Times type plot
`country_code`	three letter country code used for Financial Times plot

library(dplyr)

my_data <-
  expand_grid(id = c("Bo", "Bombali", "Bonthe"), date = as.Date(c("2020-04-18", "2020-04-19", "2020-04-20"))) %>%
  data.frame(stringsAsFactors = FALSE) %>%
    mutate(n = 3) %>%
    uncount(n) %>%
    dplyr::mutate(
    market_open	 = rbinom(n(), 1, .5),
    price_rice	 = rbinom(n(), 1, .5),
    aware	 = rbinom(n(), 1, .5),
    water	 = rbinom(n(), 1, .5))

my_vars <- data.frame(
  variable = c("market_open", "price_rice", "aware", "water"),
  family = c("Markets", "Markets", "Actions", "Actions"),
  short_label = c("Is market open?", "Price of a rice", "Aware of Covid19", "Access to water"),
  description = c("details on market open", "Price of a cup of rice", "Details on aware of Covid19", "Details on access to water"),
  stringsAsFactors = FALSE
)

my_args <- data.frame(
  para = "Intro text",
  datanote = "Study specific note about data source",
  map_path = "c:/temp/shapefiles",
  map_layer = "SLE_adm3",
  map_region =  "NAME_2",
  switch = "y",
  stringsAsFactors = FALSE
  )

dashdash(output_file = "dashtest.html",
         title = "title2",
         subtitle = "subtitle here",
         my_data = my_data,
         my_vars = my_vars,
         my_args = my_args)