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+ {
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+ "cells": [
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+ {
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+ "cell_type": "raw",
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+ "id": "833c8e20",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "skip"
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+ }
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+ },
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+ "source": [
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+ "---\n",
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+ "title: πŸš€ Demo notebook\n",
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+ "description: Simple notebook with widgets demo\n",
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+ "output: slides\n",
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+ "show-code: False\n",
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+ "params:\n",
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+ " name:\n",
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+ " input: text\n",
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+ " label: What is your name?\n",
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+ " value: Piotr\n",
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+ " mu: \n",
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+ " input: slider\n",
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+ " label: X-data mean\n",
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+ " value: 0\n",
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+ " min: -5\n",
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+ " max: 5\n",
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+ " sigma:\n",
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+ " input: numeric\n",
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+ " label: X-data sigma\n",
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+ " value: 1\n",
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+ " min: 0\n",
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+ " max: 3\n",
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+ " step: 0.01\n",
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+ " points:\n",
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+ " input: select\n",
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+ " label: How many points?\n",
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+ " value: 100\n",
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+ " choices: [50, 100, 200, 500, 1000]\n",
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+ " ---"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "id": "d3d4ffe5",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "skip"
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+ }
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+ },
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+ "outputs": [],
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+ "source": [
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+ "from IPython.display import Markdown as md\n",
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+ "from matplotlib import pyplot as plt\n",
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+ "from random import gauss\n",
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+ "plt.rcParams.update({'font.size': 22})"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "c418de47",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "slide"
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+ }
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+ },
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+ "source": [
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+ "<center>\n",
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+ " <h1> πŸš€ Interactive slides from notebook πŸ‘‹ </h1>\n",
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+ " <br /><br />\n",
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+ " by Piotr PΕ‚oΕ„ski\n",
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+ "</center>"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "id": "05963627",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "skip"
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+ }
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+ },
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+ "outputs": [],
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+ "source": [
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+ "name = \"Piotr\"\n",
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+ "mu = 0\n",
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+ "sigma = 1\n",
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+ "points = 100"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "id": "bf1faf4b",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "slide"
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+ }
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+ },
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/markdown": [
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+ "# Welcome Piotr! πŸ˜€\n",
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+ "\n",
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+ "This presentation is interactive. You can change parameters on the left sidebar. \n",
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+ "Please click `Run` to recompute the presentation with new values. \n",
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+ "\n",
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+ "How does it work?\n",
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+ "\n",
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+ "- The presentation was created in Jupyter Notebook and is converted to slides with [reveal.js](https://github.com/hakimel/reveal.js/) package.\n",
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+ "- The interactive widgets are constructed by [Mercury](https://github.com/mljar/mercury) based on YAML config\n",
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+ "- The presentation is served in HuggingFace Spaces!\n"
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+ ],
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+ "text/plain": [
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+ "<IPython.core.display.Markdown object>"
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+ ]
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+ },
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+ "execution_count": 3,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
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+ "md(f\"\"\"# Welcome {name}! πŸ˜€\n",
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+ "\n",
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+ "This presentation is interactive. You can change parameters on the left sidebar. \n",
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+ "Please click `Run` to recompute the presentation with new values. \n",
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+ "\n",
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+ "How does it work?\n",
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+ "\n",
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+ "- The presentation was created in Jupyter Notebook and is converted to slides with [reveal.js](https://github.com/hakimel/reveal.js/) package.\n",
135
+ "- The interactive widgets are constructed by [Mercury](https://github.com/mljar/mercury) based on YAML config\n",
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+ "- The presentation is served in HuggingFace Spaces!\n",
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+ "\"\"\")"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "id": "f9ad4c4b",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "slide"
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+ }
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+ },
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+ "source": [
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+ "# Let's generate some data πŸ’»"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 4,
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+ "id": "61efd84d",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "skip"
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+ }
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+ },
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+ "outputs": [],
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+ "source": [
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+ "# random data from gaussian distribution\n",
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+ "data_x = [gauss(mu, sigma) for _ in range(int(points))]\n",
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+ "data_y = [gauss(0, 1) for _ in range(int(points))]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 5,
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+ "id": "f4048f56",
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+ "metadata": {
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+ "slideshow": {
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+ "slide_type": "fragment"
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+ }
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+ },
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+ "outputs": [
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+ {
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+ "data": {
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+ "image/png": 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\n",
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+ "text/plain": [
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+ "<Figure size 864x432 with 1 Axes>"
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+ ]
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+ },
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+ "metadata": {
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+ "needs_background": "light"
187
+ },
188
+ "output_type": "display_data"
189
+ }
190
+ ],
191
+ "source": [
192
+ "plt.figure(figsize=(12,6))\n",
193
+ "_ = plt.hist(data_x, bins=40, label=\"X-data\")\n",
194
+ "_ = plt.hist(data_y, bins=40, label=\"Y-data\")\n",
195
+ "_ = plt.legend()"
196
+ ]
197
+ },
198
+ {
199
+ "cell_type": "code",
200
+ "execution_count": 6,
201
+ "id": "f507bee7",
202
+ "metadata": {
203
+ "slideshow": {
204
+ "slide_type": "subslide"
205
+ }
206
+ },
207
+ "outputs": [
208
+ {
209
+ "data": {
210
+ "image/png": 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\n",
211
+ "text/plain": [
212
+ "<Figure size 864x432 with 1 Axes>"
213
+ ]
214
+ },
215
+ "metadata": {
216
+ "needs_background": "light"
217
+ },
218
+ "output_type": "display_data"
219
+ }
220
+ ],
221
+ "source": [
222
+ "plt.figure(figsize=(12,6))\n",
223
+ "_ = plt.plot(data_x, data_y, 'o')\n",
224
+ "_ = plt.title(\"Random points scatter plot\")\n",
225
+ "_ = plt.hlines(0, min(data_x+[0]), max(data_x+[0]), color=\"lightgray\")\n",
226
+ "_ = plt.vlines(0, min(data_y), max(data_y), color=\"lightgray\")"
227
+ ]
228
+ },
229
+ {
230
+ "cell_type": "code",
231
+ "execution_count": null,
232
+ "id": "6a184383",
233
+ "metadata": {},
234
+ "outputs": [],
235
+ "source": []
236
+ }
237
+ ],
238
+ "metadata": {
239
+ "celltoolbar": "Slideshow",
240
+ "kernelspec": {
241
+ "display_name": "Python 3",
242
+ "language": "python",
243
+ "name": "python3"
244
+ },
245
+ "language_info": {
246
+ "codemirror_mode": {
247
+ "name": "ipython",
248
+ "version": 3
249
+ },
250
+ "file_extension": ".py",
251
+ "mimetype": "text/x-python",
252
+ "name": "python",
253
+ "nbconvert_exporter": "python",
254
+ "pygments_lexer": "ipython3",
255
+ "version": "3.6.5"
256
+ }
257
+ },
258
+ "nbformat": 4,
259
+ "nbformat_minor": 5
260
+ }