notebook.ipybtntaen

{
  "metadata": {
    "kernelspec": {
      "name": "python",
      "display_name": "Python (Pyodide)",
      "language": "python"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "python",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8"
    }
  },
  "nbformat_minor": 5,
  "nbformat": 4,
  "cells": [
    {
      "cell_type": "markdown",
      "source": "# Check out your tilt history!\n\nUpdate your username below from \"LICHESS_USERNAME\", to your real username, ex. \"marcusbuffett\", then press the play button above.",
      "metadata": {},
      "id": "a35eeb9f-df70-4ab1-a243-2d2025888eb0"
    },
    {
      "cell_type": "code",
      "source": "from matplotlib import pyplot as plt\nimport numpy as np\n\nuser = \"LICHESS_USERNAME\"\n\n# Generate 100 random data points along 3 dimensions\nx, y, scale = np.random.randn(3, 100)\nfig, ax = plt.subplots()\n\n# Map each onto a scatterplot we'll create with Matplotlib\nax.scatter(x=x, y=y, c=scale, s=np.abs(scale)*500)\nax.set(title=\"\")\nplt.show()",
      "metadata": {
        "trusted": true
      },
      "execution_count": null,
      "outputs": [],
      "id": "fe55883a-6887-43dd-9498-5333a51799e2"
    },
    {
      "cell_type": "code",
      "source": "",
      "metadata": {},
      "execution_count": null,
      "outputs": [],
      "id": "439e5071-95c1-4be4-850e-f5ddaa1b3ba7"
    }
  ]
}