├── Procfile
├── requirements.txt
├── media
    ├── banner.jpg
    ├── notebook-to-pdf.gif
    └── jupyter-dashboard-finance.gif
├── welcome.md
├── README.md
├── LICENSE
├── .gitignore
└── dashboard.ipynb


/Procfile:
--------------------------------------------------------------------------------
1 | web: mercury run 0.0.0.0:$PORT
2 | 


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | mljar-mercury
2 | mplfinance
3 | yfinance
4 | 


--------------------------------------------------------------------------------
/media/banner.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/HEAD/media/banner.jpg


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/media/notebook-to-pdf.gif:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/HEAD/media/notebook-to-pdf.gif


--------------------------------------------------------------------------------
/media/jupyter-dashboard-finance.gif:
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https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/HEAD/media/jupyter-dashboard-finance.gif


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/welcome.md:
--------------------------------------------------------------------------------
 1 | # Dashboard in Python with Jupyter Notebook
 2 | 
 3 | The finance dashboard was created in Python. The development was done with Jupyter Notebook. This website is serving notebook as web app. It is using MLJAR <a href="https://github.com/mljar/mercury" target="_blank">Mercury</a> framework.
 4 | 
 5 | The <a href="https://github.com/pplonski/dashboard-python-jupyter-notebook" target="_blank">link</a> to the code repository.
 6 | 
 7 | The article on <a href="https://mljar.com/blog/dashboard-python-jupyter-notebook" target="_blank">how to build a dashboard in Python with Jupyter Notebook</a>.
 8 | 
 9 | ## Dashboard
10 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | ![](https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/main/media/banner.jpg)
 2 | 
 3 | # Dashboard in Python with Jupyter Notebook
 4 | 
 5 | The finance dashboard was created in Python. The development was done with Jupyter Notebook. This website is serving notebook as web app. It is using MLJAR <a href="https://github.com/mljar/mercury" target="_blank">Mercury</a> framework.
 6 | 
 7 | ## Links
 8 | 
 9 | Th web app is running at https://dashboard-jupyter-notebook.herokuapp.com/.
10 | 
11 | The article on <a href="https://mljar.com/blog/dashboard-python-jupyter-notebook" target="_blank">how to build a dashboard in Python with Jupyter Notebook</a>.
12 | 
13 | ## Dahsboard web app
14 | ![](https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/main/media/jupyter-dashboard-finance.gif)
15 | 
16 | 
17 | ## Export notebook to PDF 
18 | ![](https://raw.githubusercontent.com/pplonski/dashboard-python-jupyter-notebook/main/media/notebook-to-pdf.gif)
19 | 


--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2022 Piotr
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
  1 | # Byte-compiled / optimized / DLL files
  2 | __pycache__/
  3 | *.py[cod]
  4 | *$py.class
  5 | 
  6 | # C extensions
  7 | *.so
  8 | 
  9 | # Distribution / packaging
 10 | .Python
 11 | build/
 12 | develop-eggs/
 13 | dist/
 14 | downloads/
 15 | eggs/
 16 | .eggs/
 17 | lib/
 18 | lib64/
 19 | parts/
 20 | sdist/
 21 | var/
 22 | wheels/
 23 | pip-wheel-metadata/
 24 | share/python-wheels/
 25 | *.egg-info/
 26 | .installed.cfg
 27 | *.egg
 28 | MANIFEST
 29 | 
 30 | # PyInstaller
 31 | #  Usually these files are written by a python script from a template
 32 | #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 33 | *.manifest
 34 | *.spec
 35 | 
 36 | # Installer logs
 37 | pip-log.txt
 38 | pip-delete-this-directory.txt
 39 | 
 40 | # Unit test / coverage reports
 41 | htmlcov/
 42 | .tox/
 43 | .nox/
 44 | .coverage
 45 | .coverage.*
 46 | .cache
 47 | nosetests.xml
 48 | coverage.xml
 49 | *.cover
 50 | *.py,cover
 51 | .hypothesis/
 52 | .pytest_cache/
 53 | 
 54 | # Translations
 55 | *.mo
 56 | *.pot
 57 | 
 58 | # Django stuff:
 59 | *.log
 60 | local_settings.py
 61 | db.sqlite3
 62 | db.sqlite3-journal
 63 | 
 64 | # Flask stuff:
 65 | instance/
 66 | .webassets-cache
 67 | 
 68 | # Scrapy stuff:
 69 | .scrapy
 70 | 
 71 | # Sphinx documentation
 72 | docs/_build/
 73 | 
 74 | # PyBuilder
 75 | target/
 76 | 
 77 | # Jupyter Notebook
 78 | .ipynb_checkpoints
 79 | 
 80 | # IPython
 81 | profile_default/
 82 | ipython_config.py
 83 | 
 84 | # pyenv
 85 | .python-version
 86 | 
 87 | # pipenv
 88 | #   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
 89 | #   However, in case of collaboration, if having platform-specific dependencies or dependencies
 90 | #   having no cross-platform support, pipenv may install dependencies that don't work, or not
 91 | #   install all needed dependencies.
 92 | #Pipfile.lock
 93 | 
 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow
 95 | __pypackages__/
 96 | 
 97 | # Celery stuff
 98 | celerybeat-schedule
 99 | celerybeat.pid
100 | 
101 | # SageMath parsed files
102 | *.sage.py
103 | 
104 | # Environments
105 | .env
106 | .venv
107 | env/
108 | venv/
109 | ENV/
110 | env.bak/
111 | venv.bak/
112 | 
113 | # Spyder project settings
114 | .spyderproject
115 | .spyproject
116 | 
117 | # Rope project settings
118 | .ropeproject
119 | 
120 | # mkdocs documentation
121 | /site
122 | 
123 | # mypy
124 | .mypy_cache/
125 | .dmypy.json
126 | dmypy.json
127 | 
128 | # Pyre type checker
129 | .pyre/
130 | 


--------------------------------------------------------------------------------
/dashboard.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "raw",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "---\n",
  8 |     "title: Finance dashboard\n",
  9 |     "description: Dashboard with financial data\n",
 10 |     "show-code: False\n",
 11 |     "params:\n",
 12 |     "    ticker: \n",
 13 |     "        input: select\n",
 14 |     "        value: TSLA\n",
 15 |     "        label: Select ticker\n",
 16 |     "        choices: [TSLA, COIN, MSFT, PLTR, SNOW, NFLX]\n",
 17 |     "---"
 18 |    ]
 19 |   },
 20 |   {
 21 |    "cell_type": "code",
 22 |    "execution_count": 1,
 23 |    "metadata": {},
 24 |    "outputs": [],
 25 |    "source": [
 26 |     "import yfinance as yf\n",
 27 |     "import mplfinance as mpf"
 28 |    ]
 29 |   },
 30 |   {
 31 |    "cell_type": "markdown",
 32 |    "metadata": {},
 33 |    "source": [
 34 |     "# Historic stock price 📈"
 35 |    ]
 36 |   },
 37 |   {
 38 |    "cell_type": "code",
 39 |    "execution_count": 2,
 40 |    "metadata": {},
 41 |    "outputs": [],
 42 |    "source": [
 43 |     "ticker = \"TSLA\""
 44 |    ]
 45 |   },
 46 |   {
 47 |    "cell_type": "code",
 48 |    "execution_count": 3,
 49 |    "metadata": {},
 50 |    "outputs": [
 51 |     {
 52 |      "name": "stdout",
 53 |      "output_type": "stream",
 54 |      "text": [
 55 |       "Selected ticker: TSLA\n"
 56 |      ]
 57 |     }
 58 |    ],
 59 |    "source": [
 60 |     "print(f\"Selected ticker: {ticker}\")"
 61 |    ]
 62 |   },
 63 |   {
 64 |    "cell_type": "code",
 65 |    "execution_count": 4,
 66 |    "metadata": {},
 67 |    "outputs": [],
 68 |    "source": [
 69 |     "history = yf.Ticker(ticker).history(period=\"3mo\")"
 70 |    ]
 71 |   },
 72 |   {
 73 |    "cell_type": "code",
 74 |    "execution_count": 5,
 75 |    "metadata": {},
 76 |    "outputs": [
 77 |     {
 78 |      "name": "stdout",
 79 |      "output_type": "stream",
 80 |      "text": [
 81 |       "3 months low: 620\n",
 82 |       "3 months high: 1152\n"
 83 |      ]
 84 |     }
 85 |    ],
 86 |    "source": [
 87 |     "print(f\"3 months low: {history.Low.min().astype(int)}\")\n",
 88 |     "print(f\"3 months high: {history.High.max().astype(int)}\")"
 89 |    ]
 90 |   },
 91 |   {
 92 |    "cell_type": "code",
 93 |    "execution_count": 6,
 94 |    "metadata": {},
 95 |    "outputs": [
 96 |     {
 97 |      "data": {
 98 |       "text/html": [
 99 |        "<div>\n",
100 |        "<style scoped>\n",
101 |        "    .dataframe tbody tr th:only-of-type {\n",
102 |        "        vertical-align: middle;\n",
103 |        "    }\n",
104 |        "\n",
105 |        "    .dataframe tbody tr th {\n",
106 |        "        vertical-align: top;\n",
107 |        "    }\n",
108 |        "\n",
109 |        "    .dataframe thead th {\n",
110 |        "        text-align: right;\n",
111 |        "    }\n",
112 |        "</style>\n",
113 |        "<table border=\"1\" class=\"dataframe\">\n",
114 |        "  <thead>\n",
115 |        "    <tr style=\"text-align: right;\">\n",
116 |        "      <th></th>\n",
117 |        "      <th>Open</th>\n",
118 |        "      <th>High</th>\n",
119 |        "      <th>Low</th>\n",
120 |        "      <th>Close</th>\n",
121 |        "      <th>Volume</th>\n",
122 |        "      <th>Dividends</th>\n",
123 |        "      <th>Stock Splits</th>\n",
124 |        "    </tr>\n",
125 |        "    <tr>\n",
126 |        "      <th>Date</th>\n",
127 |        "      <th></th>\n",
128 |        "      <th></th>\n",
129 |        "      <th></th>\n",
130 |        "      <th></th>\n",
131 |        "      <th></th>\n",
132 |        "      <th></th>\n",
133 |        "      <th></th>\n",
134 |        "    </tr>\n",
135 |        "  </thead>\n",
136 |        "  <tbody>\n",
137 |        "    <tr>\n",
138 |        "      <th>2022-06-06</th>\n",
139 |        "      <td>733.059998</td>\n",
140 |        "      <td>734.599976</td>\n",
141 |        "      <td>703.049988</td>\n",
142 |        "      <td>714.840027</td>\n",
143 |        "      <td>28068200</td>\n",
144 |        "      <td>0</td>\n",
145 |        "      <td>0</td>\n",
146 |        "    </tr>\n",
147 |        "    <tr>\n",
148 |        "      <th>2022-06-07</th>\n",
149 |        "      <td>702.000000</td>\n",
150 |        "      <td>719.989990</td>\n",
151 |        "      <td>690.280029</td>\n",
152 |        "      <td>716.659973</td>\n",
153 |        "      <td>24269500</td>\n",
154 |        "      <td>0</td>\n",
155 |        "      <td>0</td>\n",
156 |        "    </tr>\n",
157 |        "    <tr>\n",
158 |        "      <th>2022-06-08</th>\n",
159 |        "      <td>720.260010</td>\n",
160 |        "      <td>749.890015</td>\n",
161 |        "      <td>717.530029</td>\n",
162 |        "      <td>725.599976</td>\n",
163 |        "      <td>25403500</td>\n",
164 |        "      <td>0</td>\n",
165 |        "      <td>0</td>\n",
166 |        "    </tr>\n",
167 |        "    <tr>\n",
168 |        "      <th>2022-06-09</th>\n",
169 |        "      <td>748.020020</td>\n",
170 |        "      <td>766.640015</td>\n",
171 |        "      <td>717.979980</td>\n",
172 |        "      <td>719.119995</td>\n",
173 |        "      <td>32163800</td>\n",
174 |        "      <td>0</td>\n",
175 |        "      <td>0</td>\n",
176 |        "    </tr>\n",
177 |        "    <tr>\n",
178 |        "      <th>2022-06-10</th>\n",
179 |        "      <td>705.469971</td>\n",
180 |        "      <td>718.500000</td>\n",
181 |        "      <td>683.739990</td>\n",
182 |        "      <td>696.690002</td>\n",
183 |        "      <td>32512200</td>\n",
184 |        "      <td>0</td>\n",
185 |        "      <td>0</td>\n",
186 |        "    </tr>\n",
187 |        "  </tbody>\n",
188 |        "</table>\n",
189 |        "</div>"
190 |       ],
191 |       "text/plain": [
192 |        "                  Open        High         Low       Close    Volume  \\\n",
193 |        "Date                                                                   \n",
194 |        "2022-06-06  733.059998  734.599976  703.049988  714.840027  28068200   \n",
195 |        "2022-06-07  702.000000  719.989990  690.280029  716.659973  24269500   \n",
196 |        "2022-06-08  720.260010  749.890015  717.530029  725.599976  25403500   \n",
197 |        "2022-06-09  748.020020  766.640015  717.979980  719.119995  32163800   \n",
198 |        "2022-06-10  705.469971  718.500000  683.739990  696.690002  32512200   \n",
199 |        "\n",
200 |        "            Dividends  Stock Splits  \n",
201 |        "Date                                 \n",
202 |        "2022-06-06          0             0  \n",
203 |        "2022-06-07          0             0  \n",
204 |        "2022-06-08          0             0  \n",
205 |        "2022-06-09          0             0  \n",
206 |        "2022-06-10          0             0  "
207 |       ]
208 |      },
209 |      "execution_count": 6,
210 |      "metadata": {},
211 |      "output_type": "execute_result"
212 |     }
213 |    ],
214 |    "source": [
215 |     "history.tail()"
216 |    ]
217 |   },
218 |   {
219 |    "cell_type": "code",
220 |    "execution_count": 7,
221 |    "metadata": {},
222 |    "outputs": [
223 |     {
224 |      "data": {
225 |       "image/png": 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\n",
226 |       "text/plain": [
227 |        "<Figure size 745.2x414 with 2 Axes>"
228 |       ]
229 |      },
230 |      "metadata": {
231 |       "needs_background": "light"
232 |      },
233 |      "output_type": "display_data"
234 |     }
235 |    ],
236 |    "source": [
237 |     "mpf.plot(history, type='candle', mav=(7),figratio=(18,10))"
238 |    ]
239 |   },
240 |   {
241 |    "cell_type": "code",
242 |    "execution_count": null,
243 |    "metadata": {},
244 |    "outputs": [],
245 |    "source": []
246 |   },
247 |   {
248 |    "cell_type": "code",
249 |    "execution_count": null,
250 |    "metadata": {},
251 |    "outputs": [],
252 |    "source": []
253 |   }
254 |  ],
255 |  "metadata": {
256 |   "kernelspec": {
257 |    "display_name": "djenv",
258 |    "language": "python",
259 |    "name": "djenv"
260 |   },
261 |   "language_info": {
262 |    "codemirror_mode": {
263 |     "name": "ipython",
264 |     "version": 3
265 |    },
266 |    "file_extension": ".py",
267 |    "mimetype": "text/x-python",
268 |    "name": "python",
269 |    "nbconvert_exporter": "python",
270 |    "pygments_lexer": "ipython3",
271 |    "version": "3.8.10"
272 |   }
273 |  },
274 |  "nbformat": 4,
275 |  "nbformat_minor": 4
276 | }
277 | 


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