Delete demo-slides.ipynb

demo-slides.ipynb

@@ -1,260 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "raw",
-   "id": "833c8e20",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "skip"
-    }
-   },
-   "source": [
-    "---\n",
-    "title: 🚀 Demo notebook\n",
-    "description: Simple notebook with widgets demo\n",
-    "output: slides\n",
-    "show-code: False\n",
-    "params:\n",
-    "    name:\n",
-    "        input: text\n",
-    "        label: What is your name?\n",
-    "        value: Piotr\n",
-    "    mu: \n",
-    "        input: slider\n",
-    "        label: X-data mean\n",
-    "        value: 0\n",
-    "        min: -5\n",
-    "        max: 5\n",
-    "    sigma:\n",
-    "        input: numeric\n",
-    "        label: X-data sigma\n",
-    "        value: 1\n",
-    "        min: 0\n",
-    "        max: 3\n",
-    "        step: 0.01\n",
-    "    points:\n",
-    "        input: select\n",
-    "        label: How many points?\n",
-    "        value: 100\n",
-    "        choices: [50, 100, 200, 500, 1000]\n",
-    "    ---"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "d3d4ffe5",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "skip"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "from IPython.display import Markdown as md\n",
-    "from matplotlib import pyplot as plt\n",
-    "from random import gauss\n",
-    "plt.rcParams.update({'font.size': 22})"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c418de47",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "<center>\n",
-    "    <h1> 🚀 Interactive slides from notebook 👋 </h1>\n",
-    "    <br /><br />\n",
-    "    by Piotr Płoński\n",
-    "</center>"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "05963627",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "skip"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "name = \"Piotr\"\n",
-    "mu = 0\n",
-    "sigma = 1\n",
-    "points = 100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "bf1faf4b",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/markdown": [
-       "# Welcome Piotr! 😀\n",
-       "\n",
-       "This presentation is interactive. You can change parameters on the left sidebar. \n",
-       "Please click `Run` to recompute the presentation with new values. \n",
-       "\n",
-       "How does it work?\n",
-       "\n",
-       "- The presentation was created in Jupyter Notebook and is converted to slides with [reveal.js](https://github.com/hakimel/reveal.js/) package.\n",
-       "- The interactive widgets are constructed by [Mercury](https://github.com/mljar/mercury) based on YAML config\n",
-       "- The presentation is served in HuggingFace Spaces!\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "md(f\"\"\"# Welcome {name}! 😀\n",
-    "\n",
-    "This presentation is interactive. You can change parameters on the left sidebar. \n",
-    "Please click `Run` to recompute the presentation with new values. \n",
-    "\n",
-    "How does it work?\n",
-    "\n",
-    "- The presentation was created in Jupyter Notebook and is converted to slides with [reveal.js](https://github.com/hakimel/reveal.js/) package.\n",
-    "- The interactive widgets are constructed by [Mercury](https://github.com/mljar/mercury) based on YAML config\n",
-    "- The presentation is served in HuggingFace Spaces!\n",
-    "\"\"\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f9ad4c4b",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "slide"
-    }
-   },
-   "source": [
-    "# Let's generate some data 💻"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "61efd84d",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "skip"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "# random data from gaussian distribution\n",
-    "data_x = [gauss(mu, sigma) for _ in range(int(points))]\n",
-    "data_y = [gauss(0, 1) for _ in range(int(points))]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "f4048f56",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "fragment"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(12,6))\n",
-    "_ = plt.hist(data_x, bins=40, label=\"X-data\")\n",
-    "_ = plt.hist(data_y, bins=40, label=\"Y-data\")\n",
-    "_ = plt.legend()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "f507bee7",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "subslide"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 864x432 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.figure(figsize=(12,6))\n",
-    "_ = plt.plot(data_x, data_y, 'o')\n",
-    "_ = plt.title(\"Random points scatter plot\")\n",
-    "_ = plt.hlines(0, min(data_x+[0]), max(data_x+[0]), color=\"lightgray\")\n",
-    "_ = plt.vlines(0, min(data_y), max(data_y), color=\"lightgray\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6a184383",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "celltoolbar": "Slideshow",
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}