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#' Manual classification of observations
#' 
#' \code{classify} launches a Shiny app to manually classify a subset of observations.
#'
#' @param x A character vector.
#' @param btn_labels A character vector of length 2 corresponding to 0 and 1.
#' @return A vector of 0/1 for each element in \code{x}.
#' @export
#' @examples \dontrun{
#'  foo <- sprintf('%s (%.2f miles per gallon)', rownames(mtcars), mtcars$mpg)

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<script language="JavaScript">
$(function() {
  /* Lets the user click on the images to view them in full resolution. */
  $("div.figure img").wrap(function() {
    var link = $('<a/>');
    link.attr('href', $(this).attr('src'));
    link.attr('title', $(this).attr('alt'));
    link.attr('target', '_blank');
    return link;
  });

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# daily_stats has 5 columns used by this code: date, time_spent_10/25/50/75/90

ggplot(daily_stats) +
    geom_segment(aes(x = date, xend = date, y = time_spent_10, yend = time_spent_90),
                 size = 1, color = "#00af89") +
    geom_segment(aes(x = date, xend = date, y = time_spent_25, yend = time_spent_75),
                 size = 2, color = "#14866d") +
    # geom_ribbon(aes(x = date, ymin = time_spent_lower, ymax = time_spent_upper), alpha = 0.3) +
    # geom_line(aes(x = date, y = time_spent_middle)) +
    geom_label(

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{
  "type": "index_hadoop",
  "spec": {
    "ioConfig": {
      "type": "hadoop",
      "inputSpec": {
        "paths": "hdfs://analytics-hadoop/tmp/gsc-all.csv.gz",
        "type": "static"
      }
    },

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---
title: "Printing chunk engine via hook"
output: github_document
---

```{r setup, include=FALSE}
library(knitr)
opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)

print_engine_hook <- function(before, options, envir) {

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---
title: "Sympy Engine"
output: html_notebook
editor_options: 
  chunk_output_type: inline
---

Assuming the "sympy" knitr engine has been registered:

```{sympy, results='asis'}

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