r/lecture1-eventlogs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Applied Process Mining Module\n",
    "\n",
    "This notebook is part of an Applied Process Mining module. The collection of notebooks is a *living document* and subject to change. \n",
    "\n",
    "# Lecture 1 - 'Event Logs and Process Visualization' (R / bupaR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "<img src=\"http://bupar.net/images/logo_text.PNG\" alt=\"bupaR\" style=\"width: 200px;\"/>\n",
    "\n",
    "In this notebook, we are going to need the `tidyverse` and the `bupaR` packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Perform the commented out commands below in a separate R session\n",
    "# install.packages(\"tidyverse\")\n",
    "# install.packages(\"bupaR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for larger and readable plots\n",
    "options(jupyter.plot_scale=1.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "-- \u001b[1mAttaching packages\u001b[22m ----------------------------------------------------------------------------------------------- tidyverse 1.3.1 --\n",
      "\n",
      "\u001b[32mv\u001b[39m \u001b[34mggplot2\u001b[39m 3.3.3     \u001b[32mv\u001b[39m \u001b[34mpurrr  \u001b[39m 0.3.4\n",
      "\u001b[32mv\u001b[39m \u001b[34mtibble \u001b[39m 3.1.0     \u001b[32mv\u001b[39m \u001b[34mdplyr  \u001b[39m 1.0.5\n",
      "\u001b[32mv\u001b[39m \u001b[34mtidyr  \u001b[39m 1.1.3     \u001b[32mv\u001b[39m \u001b[34mstringr\u001b[39m 1.4.0\n",
      "\u001b[32mv\u001b[39m \u001b[34mreadr  \u001b[39m 1.4.0     \u001b[32mv\u001b[39m \u001b[34mforcats\u001b[39m 0.5.1\n",
      "\n",
      "-- \u001b[1mConflicts\u001b[22m -------------------------------------------------------------------------------------------------- tidyverse_conflicts() --\n",
      "\u001b[31mx\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
      "\u001b[31mx\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m    masks \u001b[34mstats\u001b[39m::lag()\n",
      "\n",
      "\n",
      "Attaching package: 'bupaR'\n",
      "\n",
      "\n",
      "The following object is masked from 'package:stats':\n",
      "\n",
      "    filter\n",
      "\n",
      "\n",
      "The following object is masked from 'package:utils':\n",
      "\n",
      "    timestamp\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# the initial execution of these may give you warnings that you can safely ignore\n",
    "library(tidyverse)\n",
    "library(bupaR)\n",
    "library(processanimateR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Event Logs\n",
    "\n",
    "This part introduces event logs and their unique properties that provide the basis for any Process Mining method. Together with `bupaR` several event logs are distributed that can be loaded without further processing. \n",
    "In this lecture we are going to make use of the following datasets:\n",
    "\n",
    "* Patients, a synthetically generated example event log in a hospital setting.\n",
    "* Sepsis, a real-life event log taken from a Dutch hospital. The event log is publicly available here: https://doi.org/10.4121/uuid:915d2bfb-7e84-49ad-a286-dc35f063a460 and has been used in many Process Mining related publications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exploring Event Data\n",
    "\n",
    "Let us first explore the event data without any prior knowledge about event log structure or properties. We convert the `patients` event log below to a standard `tibble` (https://tibble.tidyverse.org/) and inspect the first rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>handling</th><th scope=col>patient</th><th scope=col>employee</th><th scope=col>handling_id</th><th scope=col>registration_type</th><th scope=col>time</th><th scope=col>.order</th></tr>\n",
       "\t<tr><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Registration</td><td>1</td><td>r1</td><td>1</td><td>start</td><td>2017-01-02 11:41:53</td><td>1</td></tr>\n",
       "\t<tr><td>Registration</td><td>2</td><td>r1</td><td>2</td><td>start</td><td>2017-01-02 11:41:53</td><td>2</td></tr>\n",
       "\t<tr><td>Registration</td><td>3</td><td>r1</td><td>3</td><td>start</td><td>2017-01-04 01:34:05</td><td>3</td></tr>\n",
       "\t<tr><td>Registration</td><td>4</td><td>r1</td><td>4</td><td>start</td><td>2017-01-04 01:34:04</td><td>4</td></tr>\n",
       "\t<tr><td>Registration</td><td>5</td><td>r1</td><td>5</td><td>start</td><td>2017-01-04 16:07:47</td><td>5</td></tr>\n",
       "\t<tr><td>Registration</td><td>6</td><td>r1</td><td>6</td><td>start</td><td>2017-01-04 16:07:47</td><td>6</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 7\n",
       "\\begin{tabular}{lllllll}\n",
       " handling & patient & employee & handling\\_id & registration\\_type & time & .order\\\\\n",
       " <fct> & <chr> & <fct> & <chr> & <fct> & <dttm> & <int>\\\\\n",
       "\\hline\n",
       "\t Registration & 1 & r1 & 1 & start & 2017-01-02 11:41:53 & 1\\\\\n",
       "\t Registration & 2 & r1 & 2 & start & 2017-01-02 11:41:53 & 2\\\\\n",
       "\t Registration & 3 & r1 & 3 & start & 2017-01-04 01:34:05 & 3\\\\\n",
       "\t Registration & 4 & r1 & 4 & start & 2017-01-04 01:34:04 & 4\\\\\n",
       "\t Registration & 5 & r1 & 5 & start & 2017-01-04 16:07:47 & 5\\\\\n",
       "\t Registration & 6 & r1 & 6 & start & 2017-01-04 16:07:47 & 6\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 7\n",
       "\n",
       "| handling &lt;fct&gt; | patient &lt;chr&gt; | employee &lt;fct&gt; | handling_id &lt;chr&gt; | registration_type &lt;fct&gt; | time &lt;dttm&gt; | .order &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| Registration | 1 | r1 | 1 | start | 2017-01-02 11:41:53 | 1 |\n",
       "| Registration | 2 | r1 | 2 | start | 2017-01-02 11:41:53 | 2 |\n",
       "| Registration | 3 | r1 | 3 | start | 2017-01-04 01:34:05 | 3 |\n",
       "| Registration | 4 | r1 | 4 | start | 2017-01-04 01:34:04 | 4 |\n",
       "| Registration | 5 | r1 | 5 | start | 2017-01-04 16:07:47 | 5 |\n",
       "| Registration | 6 | r1 | 6 | start | 2017-01-04 16:07:47 | 6 |\n",
       "\n"
      ],
      "text/plain": [
       "  handling     patient employee handling_id registration_type\n",
       "1 Registration 1       r1       1           start            \n",
       "2 Registration 2       r1       2           start            \n",
       "3 Registration 3       r1       3           start            \n",
       "4 Registration 4       r1       4           start            \n",
       "5 Registration 5       r1       5           start            \n",
       "6 Registration 6       r1       6           start            \n",
       "  time                .order\n",
       "1 2017-01-02 11:41:53 1     \n",
       "2 2017-01-02 11:41:53 2     \n",
       "3 2017-01-04 01:34:05 3     \n",
       "4 2017-01-04 01:34:04 4     \n",
       "5 2017-01-04 16:07:47 5     \n",
       "6 2017-01-04 16:07:47 6     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>%\n",
    "    as_tibble() %>%\n",
    "    head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most important ingredient of an event log is the timestamps column `time`. This allows us to establish a sequence of events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tPDcxmXuXTWg0cPbn/rx337mc+87uOX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\nwBUgEnAF/g+CbywkcFjWEwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 672,
       "width": 672
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>% \n",
    "  filter(time < '2017-01-31') %>% \n",
    "  ggplot(aes(time, \"Event\")) + \n",
    "  geom_point() + \n",
    "  theme_bw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 7 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>handling</th></tr>\n",
       "\t<tr><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Registration         </td></tr>\n",
       "\t<tr><td>Triage and Assessment</td></tr>\n",
       "\t<tr><td>Blood test           </td></tr>\n",
       "\t<tr><td>MRI SCAN             </td></tr>\n",
       "\t<tr><td>X-Ray                </td></tr>\n",
       "\t<tr><td>Discuss Results      </td></tr>\n",
       "\t<tr><td>Check-out            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 7 × 1\n",
       "\\begin{tabular}{l}\n",
       " handling\\\\\n",
       " <fct>\\\\\n",
       "\\hline\n",
       "\t Registration         \\\\\n",
       "\t Triage and Assessment\\\\\n",
       "\t Blood test           \\\\\n",
       "\t MRI SCAN             \\\\\n",
       "\t X-Ray                \\\\\n",
       "\t Discuss Results      \\\\\n",
       "\t Check-out            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 7 × 1\n",
       "\n",
       "| handling &lt;fct&gt; |\n",
       "|---|\n",
       "| Registration          |\n",
       "| Triage and Assessment |\n",
       "| Blood test            |\n",
       "| MRI SCAN              |\n",
       "| X-Ray                 |\n",
       "| Discuss Results       |\n",
       "| Check-out             |\n",
       "\n"
      ],
      "text/plain": [
       "  handling             \n",
       "1 Registration         \n",
       "2 Triage and Assessment\n",
       "3 Blood test           \n",
       "4 MRI SCAN             \n",
       "5 X-Ray                \n",
       "6 Discuss Results      \n",
       "7 Check-out            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>%\n",
    "    as_tibble() %>% \n",
    "    distinct(handling)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 6 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>patient</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1</td></tr>\n",
       "\t<tr><td>2</td></tr>\n",
       "\t<tr><td>3</td></tr>\n",
       "\t<tr><td>4</td></tr>\n",
       "\t<tr><td>5</td></tr>\n",
       "\t<tr><td>6</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 1\n",
       "\\begin{tabular}{l}\n",
       " patient\\\\\n",
       " <chr>\\\\\n",
       "\\hline\n",
       "\t 1\\\\\n",
       "\t 2\\\\\n",
       "\t 3\\\\\n",
       "\t 4\\\\\n",
       "\t 5\\\\\n",
       "\t 6\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 1\n",
       "\n",
       "| patient &lt;chr&gt; |\n",
       "|---|\n",
       "| 1 |\n",
       "| 2 |\n",
       "| 3 |\n",
       "| 4 |\n",
       "| 5 |\n",
       "| 6 |\n",
       "\n"
      ],
      "text/plain": [
       "  patient\n",
       "1 1      \n",
       "2 2      \n",
       "3 3      \n",
       "4 4      \n",
       "5 5      \n",
       "6 6      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>%\n",
    "    as_tibble() %>% \n",
    "    distinct(patient)  %>% \n",
    "    head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 6 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>patient</th><th scope=col>n</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1  </td><td>12</td></tr>\n",
       "\t<tr><td>10 </td><td>10</td></tr>\n",
       "\t<tr><td>100</td><td>10</td></tr>\n",
       "\t<tr><td>101</td><td>10</td></tr>\n",
       "\t<tr><td>102</td><td>10</td></tr>\n",
       "\t<tr><td>103</td><td>12</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 2\n",
       "\\begin{tabular}{ll}\n",
       " patient & n\\\\\n",
       " <chr> & <int>\\\\\n",
       "\\hline\n",
       "\t 1   & 12\\\\\n",
       "\t 10  & 10\\\\\n",
       "\t 100 & 10\\\\\n",
       "\t 101 & 10\\\\\n",
       "\t 102 & 10\\\\\n",
       "\t 103 & 12\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 2\n",
       "\n",
       "| patient &lt;chr&gt; | n &lt;int&gt; |\n",
       "|---|---|\n",
       "| 1   | 12 |\n",
       "| 10  | 10 |\n",
       "| 100 | 10 |\n",
       "| 101 | 10 |\n",
       "| 102 | 10 |\n",
       "| 103 | 12 |\n",
       "\n"
      ],
      "text/plain": [
       "  patient n \n",
       "1 1       12\n",
       "2 10      10\n",
       "3 100     10\n",
       "4 101     10\n",
       "5 102     10\n",
       "6 103     12"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>%\n",
    "    as_tibble() %>% \n",
    "    count(patient) %>% \n",
    "    head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CKpQCTCEUmASITbji8XqW/qCq6dOywT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\nAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 672,
       "width": 672
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>% \n",
    "  filter(time < '2017-01-31') %>% \n",
    "  ggplot(aes(time, patient, color = handling)) + \n",
    "  geom_point() + \n",
    "  theme_bw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 6 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>handling</th><th scope=col>patient</th><th scope=col>employee</th><th scope=col>handling_id</th><th scope=col>registration_type</th><th scope=col>time</th><th scope=col>.order</th></tr>\n",
       "\t<tr><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Registration         </td><td>1</td><td>r1</td><td>1   </td><td>start   </td><td>2017-01-02 11:41:53</td><td>   1</td></tr>\n",
       "\t<tr><td>Triage and Assessment</td><td>1</td><td>r2</td><td>501 </td><td>start   </td><td>2017-01-02 12:40:20</td><td> 501</td></tr>\n",
       "\t<tr><td>Registration         </td><td>1</td><td>r1</td><td>1   </td><td>complete</td><td>2017-01-02 12:40:20</td><td>2722</td></tr>\n",
       "\t<tr><td>Triage and Assessment</td><td>1</td><td>r2</td><td>501 </td><td>complete</td><td>2017-01-02 22:32:25</td><td>3222</td></tr>\n",
       "\t<tr><td>Blood test           </td><td>1</td><td>r3</td><td>1001</td><td>start   </td><td>2017-01-05 08:59:04</td><td>1001</td></tr>\n",
       "\t<tr><td>Blood test           </td><td>1</td><td>r3</td><td>1001</td><td>complete</td><td>2017-01-05 14:34:27</td><td>3722</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 7\n",
       "\\begin{tabular}{lllllll}\n",
       " handling & patient & employee & handling\\_id & registration\\_type & time & .order\\\\\n",
       " <fct> & <chr> & <fct> & <chr> & <fct> & <dttm> & <int>\\\\\n",
       "\\hline\n",
       "\t Registration          & 1 & r1 & 1    & start    & 2017-01-02 11:41:53 &    1\\\\\n",
       "\t Triage and Assessment & 1 & r2 & 501  & start    & 2017-01-02 12:40:20 &  501\\\\\n",
       "\t Registration          & 1 & r1 & 1    & complete & 2017-01-02 12:40:20 & 2722\\\\\n",
       "\t Triage and Assessment & 1 & r2 & 501  & complete & 2017-01-02 22:32:25 & 3222\\\\\n",
       "\t Blood test            & 1 & r3 & 1001 & start    & 2017-01-05 08:59:04 & 1001\\\\\n",
       "\t Blood test            & 1 & r3 & 1001 & complete & 2017-01-05 14:34:27 & 3722\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 7\n",
       "\n",
       "| handling &lt;fct&gt; | patient &lt;chr&gt; | employee &lt;fct&gt; | handling_id &lt;chr&gt; | registration_type &lt;fct&gt; | time &lt;dttm&gt; | .order &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| Registration          | 1 | r1 | 1    | start    | 2017-01-02 11:41:53 |    1 |\n",
       "| Triage and Assessment | 1 | r2 | 501  | start    | 2017-01-02 12:40:20 |  501 |\n",
       "| Registration          | 1 | r1 | 1    | complete | 2017-01-02 12:40:20 | 2722 |\n",
       "| Triage and Assessment | 1 | r2 | 501  | complete | 2017-01-02 22:32:25 | 3222 |\n",
       "| Blood test            | 1 | r3 | 1001 | start    | 2017-01-05 08:59:04 | 1001 |\n",
       "| Blood test            | 1 | r3 | 1001 | complete | 2017-01-05 14:34:27 | 3722 |\n",
       "\n"
      ],
      "text/plain": [
       "  handling              patient employee handling_id registration_type\n",
       "1 Registration          1       r1       1           start            \n",
       "2 Triage and Assessment 1       r2       501         start            \n",
       "3 Registration          1       r1       1           complete         \n",
       "4 Triage and Assessment 1       r2       501         complete         \n",
       "5 Blood test            1       r3       1001        start            \n",
       "6 Blood test            1       r3       1001        complete         \n",
       "  time                .order\n",
       "1 2017-01-02 11:41:53    1  \n",
       "2 2017-01-02 12:40:20  501  \n",
       "3 2017-01-02 12:40:20 2722  \n",
       "4 2017-01-02 22:32:25 3222  \n",
       "5 2017-01-05 08:59:04 1001  \n",
       "6 2017-01-05 14:34:27 3722  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patients %>% \n",
    "  as_tibble() %>% \n",
    "  arrange(patient, time) %>% \n",
    "  head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Further resources"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [XES Standard](http://xes-standard.org/)\n",
    "* [Creating event logs from CSV files in bupaR](http://bupar.net/creating_eventlogs.html)\n",
    "* [Changing the case, activity notiions in bupaR](http://bupar.net/mapping.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reflection Questions\n",
    "\n",
    "* What could be the reason a column `.order` is included in this dataset?\n",
    "* How could the column `employee` be used?\n",
    "* What is the use of the column `handling_id` and in which situation is it required?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Process Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set of Traces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>% \n",
    "  trace_explorer(coverage = 1.0, .abbreviate = T) # abbreviated here due to poor Jupyter notebook output scaling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dotted Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>%\n",
    "    filter(time < '2017-01-31') %>% \n",
    "    dotted_chart(add_end_events = T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>%    \n",
    "    dotted_chart(\"relative\", add_end_events = T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also use `plotly` to get an interactive visualization:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>%    \n",
    "    plotly_dotted_chart(\"relative\", add_end_events = T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sepsis %>% \n",
    "    dotted_chart(\"relative_day\",\n",
    "                 sort = \"start_day\", \n",
    "                 units = \"hours\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check out other process visualization options using bupaR:\n",
    "\n",
    "* [Further Dotted Charts](http://bupar.net/dotted_chart.html)\n",
    "* [Exploring Time, Resources, Structuredness](http://bupar.net/exploring.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Process Map Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>% \n",
    "    precedence_matrix() %>% \n",
    "    plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>% \n",
    "    process_map()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>% \n",
    "    process_map(type = performance(units = \"hours\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Challenge 1\n",
    "Use some other attribute to be shown in the `patients` dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#patients %>% \n",
    "#    process_map(type = custom(...))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "patients %>% \n",
    "    animate_process(mode = \"relative\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Challenge 2\n",
    "Reproduce the example shown on the lecture slides by animating some other attribute from the `traffic_fines` dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "traffic_fines %>% \n",
    "  head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "traffic_fines %>% \n",
    "    # WARNING: don't animate the full log in Jupyter (at least not on Firefox - it will really slow down your browser the library does not scale well)\n",
    "    bupaR::sample_n(1000) %>%\n",
    "    edeaR::filter_trace_frequency(percentage=0.95) %>%\n",
    "    animate_process(mode = \"relative\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# traffic_fines %>% "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Real-life Processes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sepsis %>% \n",
    "  precedence_matrix() %>% \n",
    "  plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Challenge 3\n",
    "Draw the `sepsis` process map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sepsis %>%"
   ]
  }
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