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

library(knitr)
knit_engines$set(asis = function(options) {
  if (options$echo && options$eval) knit_child(text = options$code)
})
my_subset <- filter(my_vars, family == families[k] & !is.na(variable))

if (!is.null(my_blog)){
  blog_aggregate <- filter(my_blog, family == families[k] & !is.na(entry_aggregates))
  blog_disaggregate <- filter(my_blog, family == families[k] & !is.na(entry_disaggregates))
}else {
  blog_aggregate <- NULL
  blog_disaggregate <- NULL
}

`r gsub("_", " ", families[k])` {.tabset .tabset-pills}

Time trends

daily <- (isTRUE("daily" %in% trend) & !isTRUE("moving_average"%in% trend))
mov_average <- (!isTRUE("daily" %in% trend) & isTRUE("moving_average"%in% trend))
both <- (isTRUE("daily" %in% trend) & isTRUE("moving_average"%in% trend))
bar <- (isTRUE("bar" %in% trend))

National aggregates

```{asis, echo = TRUE, eval= !is.null(blog_aggregate) && nrow(blog_aggregate)!=0, code=blog_aggregate$entry_aggregates}

```r
plot_aggregates(my_data, my_subset, pd = pd, switch = switch)

plot_mov_avg(my_data, my_subset, pd = pd, switch = switch)

if("together" %in% colnames(my_subset))
{  
  together_vars <- filter(my_subset, !is.na(together))
  t <- together_plot(my_data, together_vars)
  t

  all_bar_vars <- filter(my_vars, is.na(together))
  all_bar_plot(my_data, all_bar_vars, nrow=4)
}

if(!isTRUE("together" %in% colnames(my_subset)))
{  
  all_bar_plot(my_data, my_subset, nrow=4)
}

Broken down by `r group`

```{asis, echo = TRUE, eval= !is.null(blog_disaggregate) && nrow(blog_disaggregate)!=0, code=blog_disaggregate$entry_disaggregates}

```r
plot_disaggregates(my_data, my_subset, pd = pd, switch = switch)

plot_d_mov_avg(my_data, my_subset, pd = pd, switch = switch)

dashdash:::all_bar_plot(my_data, my_subset, nrow=4)

Current averages

current_means <- get_current_means(my_data, my_subset, recent = 1)


kable(current_means, caption = paste("Mean responses in each ", group, " (most recent date)"), 
        col.names = c(group, "Date", my_subset$short_label), 
        digits = 2)

Definitions of measures

if("min" %in% colnames(my_subset) & "max" %in% colnames(my_subset))
{
  my_subset %>% mutate(range = paste(as.character(min), "-", as.character(max))) %>%
    select(short_label, description, range) %>% 
   kable(caption = "Data definitions", col.names = c("Measure", "Definition", "Range"))
}else {
  my_subset %>% select(short_label, description) %>% 
  kable(caption = "Data definitions", col.names = c("Measure", "Definition"))
  }