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Plotly-bug.ipynb
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "provenance": [], | |
| "authorship_tag": "ABX9TyMJt6DGGA/9eTfwXwnhadJr", | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| }, | |
| "language_info": { | |
| "name": "python" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/alonsosilvaallende/92a592a57b31adab52431c3268473d75/untitled33.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!pip install -q -U plotly" | |
| ], | |
| "metadata": { | |
| "id": "skdGA88YuRls" | |
| }, | |
| "execution_count": 1, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import plotly\n", | |
| "plotly.__version__" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 35 | |
| }, | |
| "id": "xhdR2srVuJDC", | |
| "outputId": "56661f26-e469-46f2-d664-837eca2c955e" | |
| }, | |
| "execution_count": 2, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'5.14.1'" | |
| ], | |
| "application/vnd.google.colaboratory.intrinsic+json": { | |
| "type": "string" | |
| } | |
| }, | |
| "metadata": {}, | |
| "execution_count": 2 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": { | |
| "id": "OnVMSRaCuE_G", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 617 | |
| }, | |
| "outputId": "252463fe-a6db-424d-e0ca-7bb8e59f13cd" | |
| }, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "text/html": [ | |
| "<html>\n", | |
| "<head><meta charset=\"utf-8\" /></head>\n", | |
| "<body>\n", | |
| " <div> <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script> <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n", | |
| " <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-2.20.0.min.js\"></script> <div id=\"3175e534-44a9-46a8-b7d5-cf5e7174e274\" class=\"plotly-graph-div\" style=\"height:600px; width:800px;\"></div> <script type=\"text/javascript\"> window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"3175e534-44a9-46a8-b7d5-cf5e7174e274\")) { Plotly.newPlot( \"3175e534-44a9-46a8-b7d5-cf5e7174e274\", [{\"name\":\"y_train\",\"x\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22],\"y\":[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],\"type\":\"scatter\"},{\"name\":\"y_test\",\"x\":[23,24,25,26,27,28,29,30,31,32,33],\"y\":[1,1,1,1,1,1,1,1,1,1,1],\"type\":\"scatter\"}], 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unified\"}, {\"responsive\": true} ).then(function(){\n", | |
| " \n", | |
| "var gd = document.getElementById('3175e534-44a9-46a8-b7d5-cf5e7174e274');\n", | |
| "var x = new MutationObserver(function (mutations, observer) {{\n", | |
| " var display = window.getComputedStyle(gd).display;\n", | |
| " if (!display || display === 'none') {{\n", | |
| " console.log([gd, 'removed!']);\n", | |
| " Plotly.purge(gd);\n", | |
| " observer.disconnect();\n", | |
| " }}\n", | |
| "}});\n", | |
| "\n", | |
| "// Listen for the removal of the full notebook cells\n", | |
| "var notebookContainer = gd.closest('#notebook-container');\n", | |
| "if (notebookContainer) {{\n", | |
| " x.observe(notebookContainer, {childList: true});\n", | |
| "}}\n", | |
| "\n", | |
| "// Listen for the clearing of the current output cell\n", | |
| "var outputEl = gd.closest('.output');\n", | |
| "if (outputEl) {{\n", | |
| " x.observe(outputEl, {childList: true});\n", | |
| "}}\n", | |
| "\n", | |
| " }) }; </script> </div>\n", | |
| "</body>\n", | |
| "</html>" | |
| ] | |
| }, | |
| "metadata": {} | |
| } | |
| ], | |
| "source": [ | |
| "import plotly.graph_objects as go\n", | |
| "\n", | |
| "x = [i for i in range(34)]\n", | |
| "y = [1 for i in range(34)]\n", | |
| "fig = go.Figure()\n", | |
| "fig.add_trace(go.Scatter(x=x[:23], y=y[:23], name=\"y_train\"))\n", | |
| "fig.add_trace(go.Scatter(x=x[23:], y=y[23:], name=\"y_test\"))\n", | |
| "fig.update_layout(\n", | |
| " autosize=False,\n", | |
| " width=800,\n", | |
| " height=600,\n", | |
| " hovermode=\"x unified\")" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [], | |
| "metadata": { | |
| "id": "lgp4o_YIuHZc" | |
| }, | |
| "execution_count": 3, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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