├── data
    └── .gitkeep
├── images
    └── .gitkeep
├── template-live-webinar.Rproj
├── README.md
├── .gitignore
├── _r
    └── notebook.ipynb
├── _python
    └── notebook.ipynb
├── webinar.yml
└── _sql
    └── notebook.ipynb


/data/.gitkeep:
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1 | 


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/images/.gitkeep:
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1 | 


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/template-live-webinar.Rproj:
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 1 | Version: 1.0
 2 | 
 3 | RestoreWorkspace: Default
 4 | SaveWorkspace: Default
 5 | AlwaysSaveHistory: Default
 6 | 
 7 | EnableCodeIndexing: Yes
 8 | UseSpacesForTab: Yes
 9 | NumSpacesForTab: 2
10 | Encoding: UTF-8
11 | 
12 | RnwWeave: Sweave
13 | LaTeX: pdfLaTeX
14 | 


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/README.md:
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1 | # Live Training Session
2 | 
3 | Thank you for signing up to conduct a live training session! Please make sure
4 | you have read the detailed instructions in this [document](https://docs.google.com/document/d/1dYZhQVib4-jQwoj_LLmPItXmdEfeyVE0ylEjjU4vrIs/edit) before getting started.
5 | 
6 | This template has been designed to help you create your code in notebooks, that
7 | can be easily run by students on [Google Colab](https://colab.research.google.com/).
8 | 
9 | 


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/.gitignore:
--------------------------------------------------------------------------------
 1 | # History files
 2 | .Rhistory
 3 | .Rapp.history
 4 | 
 5 | # Session Data files
 6 | .RData
 7 | 
 8 | # User-specific files
 9 | .Ruserdata
10 | 
11 | # Example code in package build process
12 | *-Ex.R
13 | 
14 | # Output files from R CMD build
15 | /*.tar.gz
16 | 
17 | # Output files from R CMD check
18 | /*.Rcheck/
19 | 
20 | # RStudio files
21 | .Rproj.user/
22 | 
23 | # produced vignettes
24 | vignettes/*.html
25 | vignettes/*.pdf
26 | 
27 | # OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
28 | .httr-oauth
29 | 
30 | # knitr and R markdown default cache directories
31 | *_cache/
32 | /cache/
33 | 
34 | # Temporary files created by R markdown
35 | *.utf8.md
36 | *.knit.md
37 | 
38 | # R Environment Variables
39 | .Renviron
40 | 
41 | # Mac OS
42 | .DS_Store
43 | 
44 | 


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/_r/notebook.ipynb:
--------------------------------------------------------------------------------
 1 | {
 2 |   "nbformat": 4,
 3 |   "nbformat_minor": 0,
 4 |   "metadata": {
 5 |     "colab": {
 6 |       "name": "student_notebook.ipynb",
 7 |       "provenance": []
 8 |     },
 9 |     "kernelspec": {
10 |       "name": "ir",
11 |       "display_name": "R"
12 |     }
13 |   },
14 |   "cells": [
15 |     {
16 |       "cell_type": "markdown",
17 |       "metadata": {
18 |         "id": "OJYbvo8eV-Rd",
19 |         "colab_type": "text"
20 |       },
21 |       "source": [
22 |         "<p align=\"center\">\n",
23 |         "<img src=\"https://cdn.datacamp.com/main-app/assets/brand/datacamp-horizontal-rgb-b641f95b7bdd7560b554c761a0b4910f9619907dd823c0e41244ed72078723bf.svg\" alt = \"DataCamp icon\" width=\"50%\">\n",
24 |         "</p>\n",
25 |         "<br><br>\n",
26 |         "\n",
27 |         "Please run the code below to install additional packages required for this webinar!"
28 |       ]
29 |     },
30 |     {
31 |       "cell_type": "code",
32 |       "metadata": {
33 |         "id": "KUKG6fNMV_zf",
34 |         "colab_type": "code",
35 |         "colab": {},
36 |         "cellView": "form"
37 |       },
38 |       "source": [
39 |         "#@title Install packages\n"
40 |       ],
41 |       "execution_count": 0,
42 |       "outputs": []
43 |     }
44 |   ]
45 | }


--------------------------------------------------------------------------------
/_python/notebook.ipynb:
--------------------------------------------------------------------------------
 1 | {
 2 |   "nbformat": 4,
 3 |   "nbformat_minor": 0,
 4 |   "metadata": {
 5 |     "colab": {
 6 |       "name": "Untitled5.ipynb",
 7 |       "provenance": []
 8 |     },
 9 |     "kernelspec": {
10 |       "name": "python3",
11 |       "display_name": "Python 3"
12 |     }
13 |   },
14 |   "cells": [
15 |     {
16 |       "cell_type": "markdown",
17 |       "metadata": {
18 |         "id": "tRQcWN1Edm0p",
19 |         "colab_type": "text"
20 |       },
21 |       "source": [
22 |         "<p align=\"center\">\n",
23 |         "<img src=\"https://cdn.datacamp.com/main-app/assets/brand/datacamp-horizontal-rgb-b641f95b7bdd7560b554c761a0b4910f9619907dd823c0e41244ed72078723bf.svg\" alt = \"DataCamp icon\" width=\"50%\">\n",
24 |         "</p>\n",
25 |         "<br><br>\n",
26 |         "\n",
27 |         "Please run the code below to install additional packages required for this webinar!"
28 |       ]
29 |     },
30 |     {
31 |       "cell_type": "code",
32 |       "metadata": {
33 |         "id": "0dpufov7dnk4",
34 |         "colab_type": "code",
35 |         "colab": {},
36 |         "cellView": "form"
37 |       },
38 |       "source": [
39 |         "#@title Install packages\n"
40 |       ],
41 |       "execution_count": 0,
42 |       "outputs": []
43 |     }
44 |   ]
45 | }


--------------------------------------------------------------------------------
/webinar.yml:
--------------------------------------------------------------------------------
 1 | # A catch and descriptive title for the webinar.
 2 | title: Building Web Apps with Shiny
 3 | # The technology used [r / python/ sql]
 4 | technology: r
 5 | # The url slug to be used for the webinar
 6 | slug: building-web-apps-withs-shiny
 7 | # The registration link on GotoWebinar
 8 | registerLink: https://attendee.gotowebinar.com/register/
 9 | # The date and time for the webinar in the same format
10 | time: 'Wednesday 15 April, 11 AM EST, 4 PM BST'
11 | # A description of the webinar
12 | description: >
13 |   Join us for this live, hands-on training where you will learn how to apply
14 |   the power of shiny to build web applications with R. This session will run 
15 |   for three hours, allowing you time to really immerse yourself in the subject, 
16 |   and includes short breaks and opportunities to ask the expert questions 
17 |   throughout the training.
18 | # A list of key learning objectives
19 | whatWillILearn:
20 |   - Apply your DataCamp knowledge to new data
21 |   - Identify and transform data to create common graphics with ggplot2
22 |   - Create and use plots to answer common data questions
23 |   - Share visualizations to answer business questions
24 | # A description of how to prepare for the webinar
25 | whatShouldIPrepare: >
26 |   You can join the webinar from your web browser following the instructions
27 |   you receive in your registration email. All required data/resources will be
28 |   provided in the training.
29 | # A description of who should attend the webinar and what courses are prereqs.
30 | whoShouldAttend:
31 |   text: >
32 |     This course is open to all DataCamp Premium learners, looking to improve
33 |     their data visualization skills. We recommend that you have taken at least
34 |     one of the following courses before attending:
35 |   courses:
36 |     - title: Introduction to Data Visualization with ggplot2
37 |       path: /courses/introduction-to-data-visualization-with-ggplot2
38 |     - title: Data Visualization with ggplot2 (part 1)
39 |       path: /courses/data-visualization-with-ggplot2-1
40 |     - title: Introduction to the Tidyverse
41 |       path: /courses/introduction-to-the-tidyverse
42 | # Some details about the instructor
43 | instructor:
44 |   name: Ramnath Vaidyanathan
45 |   title: VP of Product Research
46 |   image: 
47 |   description: >
48 |     Ramnath is the VP of Product Research at DataCamp, where he helps drive
49 |     product innovation and data-driven development. Ramnath has a PhD in
50 |     Operations Management from the Wharton School, and has worked as an
51 |     Assistant Professor at the Desautels Faculty of Management, McGill
52 |     University
53 |   linkedIn: https://www.linkedin.com/in/ramnathv
54 | 


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/_sql/notebook.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |   "nbformat": 4,
  3 |   "nbformat_minor": 0,
  4 |   "metadata": {
  5 |     "colab": {
  6 |       "name": "Untitled5.ipynb",
  7 |       "provenance": []
  8 |     },
  9 |     "kernelspec": {
 10 |       "name": "python3",
 11 |       "display_name": "Python 3"
 12 |     }
 13 |   },
 14 |   "cells": [
 15 |     {
 16 |       "cell_type": "markdown",
 17 |       "metadata": {
 18 |         "id": "tRQcWN1Edm0p",
 19 |         "colab_type": "text"
 20 |       },
 21 |       "source": [
 22 |         "<p align=\"center\">\n",
 23 |         "<img src=\"https://cdn.datacamp.com/main-app/assets/brand/datacamp-horizontal-rgb-b641f95b7bdd7560b554c761a0b4910f9619907dd823c0e41244ed72078723bf.svg\" alt = \"DataCamp icon\" width=\"50%\">\n",
 24 |         "</p>\n",
 25 |         "<br><br>\n",
 26 |         "\n"
 27 |       ]
 28 |     },
 29 |     {
 30 |       "cell_type": "markdown",
 31 |       "metadata": {
 32 |         "id": "GUV6DZ6Qfz6h",
 33 |         "colab_type": "text"
 34 |       },
 35 |       "source": [
 36 |         "# Setup\n",
 37 |         "\n",
 38 |         "Before we get started, we need to do some initial setup. Please run the cells below to install postgress, start the server, load sql extensions, download data, and create the required database tables. This will take a few minutes on the first run."
 39 |       ]
 40 |     },
 41 |     {
 42 |       "cell_type": "code",
 43 |       "metadata": {
 44 |         "id": "0dpufov7dnk4",
 45 |         "colab_type": "code",
 46 |         "colab": {},
 47 |         "cellView": "both"
 48 |       },
 49 |       "source": [
 50 |         "#@title Install postgres and start server\n",
 51 |         "%%capture\n",
 52 |         "!wget -qO- https://www.postgresql.org/media/keys/ACCC4CF8.asc | apt-key add -\n",
 53 |         "!echo \"deb http://apt.postgresql.org/pub/repos/apt/ bionic-pgdg main\" >/etc/apt/sources.list.d/pgdg.list\n",
 54 |         "!apt -qq update\n",
 55 |         "!apt -yq install postgresql-12 postgresql-client-12\n",
 56 |         "!service postgresql start\n",
 57 |         "# make calling psql shorter\n",
 58 |         "!sudo -u postgres psql -c \"CREATE USER root WITH SUPERUSER\"  \n",
 59 |         "!psql postgres -c \"CREATE DATABASE root\"  # now just !psql -c \"...\"\n",
 60 |         "# load SQL extensions\n",
 61 |         "%load_ext sql\n",
 62 |         "%config SqlMagic.feedback=False \n",
 63 |         "%config SqlMagic.autopandas=True\n",
 64 |         "%sql postgresql+psycopg2://@/postgres"
 65 |       ],
 66 |       "execution_count": 0,
 67 |       "outputs": []
 68 |     },
 69 |     {
 70 |       "cell_type": "code",
 71 |       "metadata": {
 72 |         "id": "TlbbE1CxfbKU",
 73 |         "colab_type": "code",
 74 |         "colab": {},
 75 |         "cellView": "form"
 76 |       },
 77 |       "source": [
 78 |         "#@title Download data as CSV files\n",
 79 |         "!wget -q https://raw.githubusercontent.com/baldwint/binder-postgres/postgres/data/actor.csv"
 80 |       ],
 81 |       "execution_count": 0,
 82 |       "outputs": []
 83 |     },
 84 |     {
 85 |       "cell_type": "code",
 86 |       "metadata": {
 87 |         "id": "w72wAJVBfcHW",
 88 |         "colab_type": "code",
 89 |         "colab": {
 90 |           "base_uri": "https://localhost:8080/",
 91 |           "height": 49
 92 |         },
 93 |         "cellView": "form",
 94 |         "outputId": "779a5675-65bc-4999-9d65-420c85477104"
 95 |       },
 96 |       "source": [
 97 |         "#@title Create Tables\n",
 98 |         "%%sql\n",
 99 |         "DROP TABLE IF EXISTS actor;\n",
100 |         "CREATE TABLE actor(\n",
101 |         " actor_id int primary key,\n",
102 |         " first_name varchar(50),\n",
103 |         " last_name varchar(50),\n",
104 |         " last_update timestamp\n",
105 |         ");\n",
106 |         "COPY actor\n",
107 |         "FROM '/content/actor.csv' DELIMITER ',' CSV HEADER;"
108 |       ],
109 |       "execution_count": 3,
110 |       "outputs": [
111 |         {
112 |           "output_type": "stream",
113 |           "text": [
114 |             " * postgresql+psycopg2://@/postgres\n"
115 |           ],
116 |           "name": "stdout"
117 |         },
118 |         {
119 |           "output_type": "execute_result",
120 |           "data": {
121 |             "text/html": [
122 |               "<div>\n",
123 |               "<style scoped>\n",
124 |               "    .dataframe tbody tr th:only-of-type {\n",
125 |               "        vertical-align: middle;\n",
126 |               "    }\n",
127 |               "\n",
128 |               "    .dataframe tbody tr th {\n",
129 |               "        vertical-align: top;\n",
130 |               "    }\n",
131 |               "\n",
132 |               "    .dataframe thead th {\n",
133 |               "        text-align: right;\n",
134 |               "    }\n",
135 |               "</style>\n",
136 |               "<table border=\"1\" class=\"dataframe\">\n",
137 |               "  <thead>\n",
138 |               "    <tr style=\"text-align: right;\">\n",
139 |               "      <th></th>\n",
140 |               "    </tr>\n",
141 |               "  </thead>\n",
142 |               "  <tbody>\n",
143 |               "  </tbody>\n",
144 |               "</table>\n",
145 |               "</div>"
146 |             ],
147 |             "text/plain": [
148 |               "Empty DataFrame\n",
149 |               "Columns: []\n",
150 |               "Index: []"
151 |             ]
152 |           },
153 |           "metadata": {
154 |             "tags": []
155 |           },
156 |           "execution_count": 3
157 |         }
158 |       ]
159 |     },
160 |     {
161 |       "cell_type": "markdown",
162 |       "metadata": {
163 |         "id": "yd7tHlVpgGjx",
164 |         "colab_type": "text"
165 |       },
166 |       "source": [
167 |         "# Get Started"
168 |       ]
169 |     },
170 |     {
171 |       "cell_type": "code",
172 |       "metadata": {
173 |         "id": "kbKrfnA8gIDm",
174 |         "colab_type": "code",
175 |         "colab": {
176 |           "base_uri": "https://localhost:8080/",
177 |           "height": 376
178 |         },
179 |         "outputId": "3bfb0cdb-17eb-4175-a7f9-6d4182801297"
180 |       },
181 |       "source": [
182 |         "%%sql\n",
183 |         "SELECT * FROM actor LIMIT 10"
184 |       ],
185 |       "execution_count": 4,
186 |       "outputs": [
187 |         {
188 |           "output_type": "stream",
189 |           "text": [
190 |             " * postgresql+psycopg2://@/postgres\n"
191 |           ],
192 |           "name": "stdout"
193 |         },
194 |         {
195 |           "output_type": "execute_result",
196 |           "data": {
197 |             "text/html": [
198 |               "<div>\n",
199 |               "<style scoped>\n",
200 |               "    .dataframe tbody tr th:only-of-type {\n",
201 |               "        vertical-align: middle;\n",
202 |               "    }\n",
203 |               "\n",
204 |               "    .dataframe tbody tr th {\n",
205 |               "        vertical-align: top;\n",
206 |               "    }\n",
207 |               "\n",
208 |               "    .dataframe thead th {\n",
209 |               "        text-align: right;\n",
210 |               "    }\n",
211 |               "</style>\n",
212 |               "<table border=\"1\" class=\"dataframe\">\n",
213 |               "  <thead>\n",
214 |               "    <tr style=\"text-align: right;\">\n",
215 |               "      <th></th>\n",
216 |               "      <th>actor_id</th>\n",
217 |               "      <th>first_name</th>\n",
218 |               "      <th>last_name</th>\n",
219 |               "      <th>last_update</th>\n",
220 |               "    </tr>\n",
221 |               "  </thead>\n",
222 |               "  <tbody>\n",
223 |               "    <tr>\n",
224 |               "      <th>0</th>\n",
225 |               "      <td>1</td>\n",
226 |               "      <td>Penelope</td>\n",
227 |               "      <td>Guiness</td>\n",
228 |               "      <td>2006-02-15 10:05:00</td>\n",
229 |               "    </tr>\n",
230 |               "    <tr>\n",
231 |               "      <th>1</th>\n",
232 |               "      <td>2</td>\n",
233 |               "      <td>Nick</td>\n",
234 |               "      <td>Wahlberg</td>\n",
235 |               "      <td>2006-02-15 10:05:00</td>\n",
236 |               "    </tr>\n",
237 |               "    <tr>\n",
238 |               "      <th>2</th>\n",
239 |               "      <td>3</td>\n",
240 |               "      <td>Ed</td>\n",
241 |               "      <td>Chase</td>\n",
242 |               "      <td>2006-02-15 10:05:00</td>\n",
243 |               "    </tr>\n",
244 |               "    <tr>\n",
245 |               "      <th>3</th>\n",
246 |               "      <td>4</td>\n",
247 |               "      <td>Jennifer</td>\n",
248 |               "      <td>Davis</td>\n",
249 |               "      <td>2006-02-15 10:05:00</td>\n",
250 |               "    </tr>\n",
251 |               "    <tr>\n",
252 |               "      <th>4</th>\n",
253 |               "      <td>5</td>\n",
254 |               "      <td>Johnny</td>\n",
255 |               "      <td>Lollobrigida</td>\n",
256 |               "      <td>2006-02-15 10:05:00</td>\n",
257 |               "    </tr>\n",
258 |               "    <tr>\n",
259 |               "      <th>5</th>\n",
260 |               "      <td>6</td>\n",
261 |               "      <td>Bette</td>\n",
262 |               "      <td>Nicholson</td>\n",
263 |               "      <td>2006-02-15 10:05:00</td>\n",
264 |               "    </tr>\n",
265 |               "    <tr>\n",
266 |               "      <th>6</th>\n",
267 |               "      <td>7</td>\n",
268 |               "      <td>Grace</td>\n",
269 |               "      <td>Mostel</td>\n",
270 |               "      <td>2006-02-15 10:05:00</td>\n",
271 |               "    </tr>\n",
272 |               "    <tr>\n",
273 |               "      <th>7</th>\n",
274 |               "      <td>8</td>\n",
275 |               "      <td>Matthew</td>\n",
276 |               "      <td>Johansson</td>\n",
277 |               "      <td>2006-02-15 10:05:00</td>\n",
278 |               "    </tr>\n",
279 |               "    <tr>\n",
280 |               "      <th>8</th>\n",
281 |               "      <td>9</td>\n",
282 |               "      <td>Joe</td>\n",
283 |               "      <td>Swank</td>\n",
284 |               "      <td>2006-02-15 10:05:00</td>\n",
285 |               "    </tr>\n",
286 |               "    <tr>\n",
287 |               "      <th>9</th>\n",
288 |               "      <td>10</td>\n",
289 |               "      <td>Christian</td>\n",
290 |               "      <td>Gable</td>\n",
291 |               "      <td>2006-02-15 10:05:00</td>\n",
292 |               "    </tr>\n",
293 |               "  </tbody>\n",
294 |               "</table>\n",
295 |               "</div>"
296 |             ],
297 |             "text/plain": [
298 |               "   actor_id first_name     last_name         last_update\n",
299 |               "0         1   Penelope       Guiness 2006-02-15 10:05:00\n",
300 |               "1         2       Nick      Wahlberg 2006-02-15 10:05:00\n",
301 |               "2         3         Ed         Chase 2006-02-15 10:05:00\n",
302 |               "3         4   Jennifer         Davis 2006-02-15 10:05:00\n",
303 |               "4         5     Johnny  Lollobrigida 2006-02-15 10:05:00\n",
304 |               "5         6      Bette     Nicholson 2006-02-15 10:05:00\n",
305 |               "6         7      Grace        Mostel 2006-02-15 10:05:00\n",
306 |               "7         8    Matthew     Johansson 2006-02-15 10:05:00\n",
307 |               "8         9        Joe         Swank 2006-02-15 10:05:00\n",
308 |               "9        10  Christian         Gable 2006-02-15 10:05:00"
309 |             ]
310 |           },
311 |           "metadata": {
312 |             "tags": []
313 |           },
314 |           "execution_count": 4
315 |         }
316 |       ]
317 |     }
318 |   ]
319 | }


--------------------------------------------------------------------------------