tidyjson: Tidy Complex 'JSON'

#' Issue data for the dplyr repo from github API
#'
#' @docType data
#' @name issues
#' @usage issues
#' @format JSON
#' @examples
#'
#' library(dplyr)
#'
#' # issues is a long character string
#' nchar(issues)
#'
#' # Let's make it a tbl_json object
#' issues %>% as.tbl_json
#'
#' # It begins as an array, so let's gather that
#' issues %>% gather_array
#'
#' # Now let's spread all the top level values
#' issues %>% gather_array %>% spread_all %>% glimpse
#'
#' # Are there any top level objects or arrays?
#' issues %>% gather_array %>% gather_object %>% json_types %>%
#'   count(name, type) %>%
#'   filter(type %in% c("array", "object"))
#'
#' # Count issues labels by name
#' labels <- issues %>%
#'   gather_array %>%                    # stack issues as "issue.num"
#'   spread_values(id = jnumber(id)) %>% # capture just issue id
#'   enter_object(labels) %>%            # filter just those with labels
#'   gather_array("label.index") %>%     # stack labels
#'   spread_all
#' labels %>% glimpse
#'
#' # Count number of distinct issues each label appears in
#' labels %>%
#'   group_by(name) %>%
#'   summarize(num.issues = n_distinct(id))
NULL