AltairSaver.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "AltairSaver.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ezu9OhdMDaES",
        "colab_type": "text"
      },
      "source": [
        "# Testing Altair-Saver\n",
        "\n",
        "<a href=\"https://colab.research.google.com/github/altair-viz/altair_saver/blob/master/AltairSaver.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
        "\n",
        "This notebook demonstrates the installation and use of [altair-saver](http://github.com/altair-viz/altair_saver). The following was tested in Colab.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZiTDBCAM_Ni8",
        "colab_type": "code",
        "outputId": "547c4b1f-6d58-4356-9a41-6aed648dcc7b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "!pip install -q altair_saver"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[K     |████████████████████████████████| 286kB 3.8MB/s \n",
            "\u001b[K     |████████████████████████████████| 911kB 9.0MB/s \n",
            "\u001b[?25h  Building wheel for altair-saver (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KJh7JMMzDjae",
        "colab_type": "text"
      },
      "source": [
        "## Setup Selenium + Chromedriver"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "lIYdn1woOS1n",
        "outputId": "ca17198b-8895-4d2e-c7be-c5bf033a2c9a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "!apt-get -qq install chromium-chromedriver"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Selecting previously unselected package chromium-codecs-ffmpeg-extra.\n",
            "(Reading database ... 135004 files and directories currently installed.)\n",
            "Preparing to unpack .../chromium-codecs-ffmpeg-extra_79.0.3945.79-0ubuntu0.18.04.1_amd64.deb ...\n",
            "Unpacking chromium-codecs-ffmpeg-extra (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Selecting previously unselected package chromium-browser.\n",
            "Preparing to unpack .../chromium-browser_79.0.3945.79-0ubuntu0.18.04.1_amd64.deb ...\n",
            "Unpacking chromium-browser (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Selecting previously unselected package chromium-browser-l10n.\n",
            "Preparing to unpack .../chromium-browser-l10n_79.0.3945.79-0ubuntu0.18.04.1_all.deb ...\n",
            "Unpacking chromium-browser-l10n (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Selecting previously unselected package chromium-chromedriver.\n",
            "Preparing to unpack .../chromium-chromedriver_79.0.3945.79-0ubuntu0.18.04.1_amd64.deb ...\n",
            "Unpacking chromium-chromedriver (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Setting up chromium-codecs-ffmpeg-extra (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Setting up chromium-browser (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "update-alternatives: using /usr/bin/chromium-browser to provide /usr/bin/x-www-browser (x-www-browser) in auto mode\n",
            "update-alternatives: using /usr/bin/chromium-browser to provide /usr/bin/gnome-www-browser (gnome-www-browser) in auto mode\n",
            "Setting up chromium-chromedriver (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Setting up chromium-browser-l10n (79.0.3945.79-0ubuntu0.18.04.1) ...\n",
            "Processing triggers for hicolor-icon-theme (0.17-2) ...\n",
            "Processing triggers for mime-support (3.60ubuntu1) ...\n",
            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4pjnxI1bDosm",
        "colab_type": "text"
      },
      "source": [
        "## Setup npm and the Vega CLI"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "if6t54-6_DvU",
        "colab_type": "code",
        "outputId": "6e247009-9fe0-44bc-ee1e-738d9d8cad65",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        }
      },
      "source": [
        "!npm install --silent vega-lite vega-cli canvas"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[K\u001b[?25h[canvas] Success: \"/content/node_modules/canvas/build/Release/canvas.node\" is installed via remote\n",
            "\u001b[K\u001b[?25h+ vega-cli@5.9.0\n",
            "+ canvas@2.6.1\n",
            "+ vega-lite@4.0.2\n",
            "added 177 packages from 84 contributors in 10.934s\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R5126EyEN4hT",
        "colab_type": "text"
      },
      "source": [
        "## Create and save a chart"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qd-Tcr8LBSqM",
        "colab_type": "code",
        "outputId": "05b179f7-abd4-4a64-ad2b-f943be0302cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "source": [
        "import altair as alt\n",
        "from vega_datasets import data\n",
        "cars = data.cars.url\n",
        "\n",
        "chart = alt.Chart(cars).mark_bar().encode(\n",
        "  x=alt.X('Miles_per_Gallon:Q', bin=True),\n",
        "  y='count()',\n",
        ")\n",
        "\n",
        "chart.display()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "alt.Chart(...)"
            ],
            "text/html": [
              "\n",
              "<div id=\"altair-viz-1\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "  (function(spec, embedOpt){\n",
              "    const outputDiv = document.getElementById(\"altair-viz-1\");\n",
              "    const paths = {\n",
              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.0?noext\",\n",
              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
              "    };\n",
              "\n",
              "    function loadScript(lib) {\n",
              "      return new Promise(function(resolve, reject) {\n",
              "        var s = document.createElement('script');\n",
              "        s.src = paths[lib];\n",
              "        s.async = true;\n",
              "        s.onload = () => resolve(paths[lib]);\n",
              "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
              "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
              "      });\n",
              "    }\n",
              "\n",
              "    function showError(err) {\n",
              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
              "      throw err;\n",
              "    }\n",
              "\n",
              "    function displayChart(vegaEmbed) {\n",
              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
              "    }\n",
              "\n",
              "    if(typeof define === \"function\" && define.amd) {\n",
              "      requirejs.config({paths});\n",
              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
              "    } else if (typeof vegaEmbed === \"function\") {\n",
              "      displayChart(vegaEmbed);\n",
              "    } else {\n",
              "      loadScript(\"vega\")\n",
              "        .then(() => loadScript(\"vega-lite\"))\n",
              "        .then(() => loadScript(\"vega-embed\"))\n",
              "        .catch(showError)\n",
              "        .then(() => displayChart(vegaEmbed));\n",
              "    }\n",
              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"https://vega.github.io/vega-datasets/data/cars.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"Miles_per_Gallon\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.0.json\"}, {\"mode\": \"vega-lite\"});\n",
              "</script>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fAQLIM7qBX_u",
        "colab_type": "code",
        "outputId": "c40e4c70-3f72-4554-c071-07d3437c00ef",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "from altair_saver import save\n",
        "for fmt in ['json', 'vg.json', 'html', 'png', 'svg', 'pdf']:\n",
        "  save(chart, f'chart.{fmt}')\n",
        "!ls -lh chart.*"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-rw-r--r-- 1 root root  788 Jan  3 18:17 chart.html\n",
            "-rw-r--r-- 1 root root  464 Jan  3 18:17 chart.json\n",
            "-rw-r--r-- 1 root root  15K Jan  3 18:17 chart.pdf\n",
            "-rw-r--r-- 1 root root  17K Jan  3 18:17 chart.png\n",
            "-rw-r--r-- 1 root root  11K Jan  3 18:17 chart.svg\n",
            "-rw-r--r-- 1 root root 4.0K Jan  3 18:17 chart.vg.json\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x5v8HdYJGO3B",
        "colab_type": "text"
      },
      "source": [
        "## View saved charts\n",
        "\n",
        "Here we use a variety of IPython display mechanisms to load and display the saved charts."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QVO2E2Y7Bhxx",
        "colab_type": "code",
        "outputId": "33c18996-d86b-4607-d6ad-b9f6ef8bba8b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        }
      },
      "source": [
        "from PIL import Image\n",
        "Image.open(\"chart.png\")"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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+Xdti5pjeSsegBkJSES5btgwhISHYtWsXKioq8Prrr+Pll1/2dDYiIiKPk1SE3t7eePHF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\nRESkaixCIiJSNRYhERGp2v8HaYFLCTwP2fQAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=450x347 at 0x7F226F483898>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ievDaZFaB6A1",
        "colab_type": "code",
        "outputId": "00d3ae91-1693-4332-d633-ad85e6ddf349",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "source": [
        "from IPython.display import display, SVG\n",
        "with open(\"chart.svg\") as f:\n",
        "  display(SVG(f.read()))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.SVG object>"
            ],
            "image/svg+xml": "<svg class=\"marks\" height=\"347\" version=\"1.1\" viewBox=\"0 0 450 347\" width=\"450\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><rect height=\"347\" style=\"fill: white;\" width=\"450\"/><g transform=\"translate(44,10)\"><g class=\"mark-group role-frame root\"><g transform=\"translate(0,0)\"><path class=\"background\" d=\"M0.5,0.5h400v300h-400Z\" style=\"fill: none; stroke: #ddd;\"/><g><g class=\"mark-group role-axis\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" d=\"M0,0h0v0h0Z\" style=\"pointer-events: none; fill: none;\"/><g><g class=\"mark-rule role-axis-grid\" style=\"pointer-events: none;\"><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,300)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,270)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,240)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,210)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,180)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,150)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,120)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,90)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,60)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,30)\" x2=\"400\" y2=\"0\"/><line style=\"fill: none; stroke: #ddd; stroke-width: 1; opacity: 1;\" transform=\"translate(0,0)\" x2=\"400\" y2=\"0\"/></g></g><path class=\"foreground\" d=\"\" style=\"pointer-events: none; display: none; fill: none;\"/></g></g><g class=\"mark-group role-axis\"><g transform=\"translate(0.5,300.5)\"><path class=\"background\" d=\"M0,0h0v0h0Z\" style=\"pointer-events: none; fill: none;\"/><g><g class=\"mark-rule role-axis-tick\" style=\"pointer-events: none;\"><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(44,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(89,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(133,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(178,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(222,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(267,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(311,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(356,0)\" x2=\"0\" y2=\"5\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(400,0)\" x2=\"0\" y2=\"5\"/></g><g class=\"mark-text role-axis-label\" style=\"pointer-events: none;\"><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"start\" transform=\"translate(0,15)\">5</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(44.44444444444444,15)\">10</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(88.88888888888889,15)\">15</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(133.33333333333331,15)\">20</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(177.77777777777777,15)\">25</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(222.22222222222223,15)\">30</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(266.66666666666663,15)\">35</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(311.11111111111114,15)\">40</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(355.55555555555554,15)\">45</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(400,15)\">50</text></g><g class=\"mark-rule role-axis-domain\" style=\"pointer-events: none;\"><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,0)\" x2=\"400\" y2=\"0\"/></g><g class=\"mark-text role-axis-title\" style=\"pointer-events: none;\"><text style=\"font-family: sans-serif; font-size: 11px; font-weight: bold; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(200,30)\">Miles_per_Gallon (binned)</text></g></g><path class=\"foreground\" d=\"\" style=\"pointer-events: none; display: none; fill: none;\"/></g></g><g class=\"mark-group role-axis\"><g transform=\"translate(0.5,0.5)\"><path class=\"background\" d=\"M0,0h0v0h0Z\" style=\"pointer-events: none; fill: none;\"/><g><g class=\"mark-rule role-axis-tick\" style=\"pointer-events: none;\"><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,300)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,270)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,240)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,210)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,180)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,150)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,120)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,90)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,60)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,30)\" x2=\"-5\" y2=\"0\"/><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,0)\" x2=\"-5\" y2=\"0\"/></g><g class=\"mark-text role-axis-label\" style=\"pointer-events: none;\"><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,303)\">0</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,273)\">10</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,243)\">20</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,213)\">30</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,183)\">40</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,153)\">50</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,123)\">60</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,93.00000000000001)\">70</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,62.999999999999986)\">80</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,32.99999999999999)\">90</text><text style=\"font-family: sans-serif; font-size: 10px; fill: #000; opacity: 1;\" text-anchor=\"end\" transform=\"translate(-7,3)\">100</text></g><g class=\"mark-rule role-axis-domain\" style=\"pointer-events: none;\"><line style=\"fill: none; stroke: #888; stroke-width: 1; opacity: 1;\" transform=\"translate(0,300)\" x2=\"0\" y2=\"-300\"/></g><g class=\"mark-text role-axis-title\" style=\"pointer-events: none;\"><text style=\"font-family: sans-serif; font-size: 11px; font-weight: bold; fill: #000; opacity: 1;\" text-anchor=\"middle\" transform=\"translate(-27.6845703125,150) rotate(-90) translate(0,-2)\">Count of Records</text></g></g><path class=\"foreground\" d=\"\" style=\"pointer-events: none; display: none; fill: none;\"/></g></g><g class=\"mark-rect role-mark marks\"><path d=\"M89.88888888888889,6.000000000000005h43.44444444444443v294h-43.44444444444443Z\" style=\"fill: #4c78a8;\"/><path d=\"M45.44444444444444,144h43.44444444444444v156h-43.44444444444444Z\" style=\"fill: #4c78a8;\"/><path d=\"M134.33333333333331,65.99999999999999h43.44444444444446v234h-43.44444444444446Z\" style=\"fill: #4c78a8;\"/><path d=\"M178.77777777777777,69h43.44444444444446v231h-43.44444444444446Z\" style=\"fill: #4c78a8;\"/><path d=\"M1,297h43.44444444444444v3h-43.44444444444444Z\" style=\"fill: #4c78a8;\"/><path d=\"M223.22222222222223,131.99999999999997h43.4444444444444v168.00000000000003h-43.4444444444444Z\" style=\"fill: #4c78a8;\"/><path d=\"M267.66666666666663,219h43.444444444444514v81h-43.444444444444514Z\" style=\"fill: #4c78a8;\"/><path d=\"M312.11111111111114,276h43.4444444444444v24h-43.4444444444444Z\" style=\"fill: #4c78a8;\"/><path d=\"M356.55555555555554,297h43.44444444444446v3h-43.44444444444446Z\" style=\"fill: #4c78a8;\"/></g></g><path class=\"foreground\" d=\"\" style=\"display: none; fill: none;\"/></g></g></g></svg>"
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zUMlMKIKCQIW",
        "colab_type": "code",
        "outputId": "f6c3630c-498a-4f44-92a4-41321eb70112",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "source": [
        "import json\n",
        "\n",
        "with open('chart.json') as f:\n",
        "  display(alt.VegaLite(json.load(f)))"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<altair.vegalite.v4.display.VegaLite at 0x7f226d3159e8>"
            ],
            "text/html": [
              "\n",
              "<div id=\"altair-viz-2\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "  (function(spec, embedOpt){\n",
              "    const outputDiv = document.getElementById(\"altair-viz-2\");\n",
              "    const paths = {\n",
              "      \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n",
              "      \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n",
              "      \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.0?noext\",\n",
              "      \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n",
              "    };\n",
              "\n",
              "    function loadScript(lib) {\n",
              "      return new Promise(function(resolve, reject) {\n",
              "        var s = document.createElement('script');\n",
              "        s.src = paths[lib];\n",
              "        s.async = true;\n",
              "        s.onload = () => resolve(paths[lib]);\n",
              "        s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n",
              "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
              "      });\n",
              "    }\n",
              "\n",
              "    function showError(err) {\n",
              "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
              "      throw err;\n",
              "    }\n",
              "\n",
              "    function displayChart(vegaEmbed) {\n",
              "      vegaEmbed(outputDiv, spec, embedOpt)\n",
              "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
              "    }\n",
              "\n",
              "    if(typeof define === \"function\" && define.amd) {\n",
              "      requirejs.config({paths});\n",
              "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
              "    } else if (typeof vegaEmbed === \"function\") {\n",
              "      displayChart(vegaEmbed);\n",
              "    } else {\n",
              "      loadScript(\"vega\")\n",
              "        .then(() => loadScript(\"vega-lite\"))\n",
              "        .then(() => loadScript(\"vega-embed\"))\n",
              "        .catch(showError)\n",
              "        .then(() => displayChart(vegaEmbed));\n",
              "    }\n",
              "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"https://vega.github.io/vega-datasets/data/cars.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"Miles_per_Gallon\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.0.json\"}, {\"mode\": \"vega-lite\"});\n",
              "</script>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ouREXcHvCkV0",
        "colab_type": "code",
        "outputId": "2dba7fbb-7b39-4402-dee5-f2f3bc2dc694",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "source": [
        "import json\n",
        "from altair import vega\n",
        "vega.renderers.enable('colab')\n",
        "\n",
        "with open('chart.vg.json') as f:\n",
        "  display(vega.Vega(json.load(f)))"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<altair.vega.v5.display.Vega at 0x7f226d1ff898>"
            ],
            "text/html": [
              "<!DOCTYPE html>\n",
              "<html>\n",
              "<head>\n",
              "  <style>\n",
              "    .error {\n",
              "        color: red;\n",
              "    }\n",
              "  </style>\n",
              "  <script type=\"text/javascript\" src=\"https://cdn.jsdelivr.net/npm//vega@5.9.0\"></script>\n",
              "  <script type=\"text/javascript\" src=\"https://cdn.jsdelivr.net/npm//vega-embed@3\"></script>\n",
              "</head>\n",
              "<body>\n",
              "  <div id=\"altair-viz\"></div>\n",
              "  <script>\n",
              "    (function(vegaEmbed) {\n",
              "      var spec = {\"$schema\": \"https://vega.github.io/schema/vega/v5.json\", \"axes\": [{\"domain\": false, \"grid\": true, \"gridScale\": \"x\", \"labels\": false, \"maxExtent\": 0, \"minExtent\": 0, \"orient\": \"left\", \"scale\": \"y\", \"tickCount\": {\"signal\": \"ceil(height/40)\"}, \"ticks\": false, \"zindex\": 0}, {\"grid\": false, \"labelFlush\": true, \"labelOverlap\": true, \"orient\": \"bottom\", \"scale\": \"x\", \"tickCount\": {\"signal\": \"ceil(width/10)\"}, \"title\": \"Miles_per_Gallon (binned)\", \"zindex\": 0}, {\"grid\": false, \"labelOverlap\": true, \"orient\": \"left\", \"scale\": \"y\", \"tickCount\": {\"signal\": \"ceil(height/40)\"}, \"title\": \"Count of Records\", \"zindex\": 0}], \"background\": \"white\", \"data\": [{\"format\": {\"type\": \"json\"}, \"name\": \"source_0\", \"transform\": [{\"field\": \"Miles_per_Gallon\", \"signal\": \"bin_maxbins_10_Miles_per_Gallon_extent\", \"type\": \"extent\"}, {\"as\": [\"bin_maxbins_10_Miles_per_Gallon\", \"bin_maxbins_10_Miles_per_Gallon_end\"], \"extent\": {\"signal\": \"bin_maxbins_10_Miles_per_Gallon_extent\"}, \"field\": \"Miles_per_Gallon\", \"maxbins\": 10, \"signal\": \"bin_maxbins_10_Miles_per_Gallon_bins\", \"type\": \"bin\"}, {\"as\": [\"__count\"], \"fields\": [null], \"groupby\": [\"bin_maxbins_10_Miles_per_Gallon\", \"bin_maxbins_10_Miles_per_Gallon_end\"], \"ops\": [\"count\"], \"type\": \"aggregate\"}, {\"expr\": \"isValid(datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"]) && isFinite(+datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"])\", \"type\": \"filter\"}], \"url\": \"https://vega.github.io/vega-datasets/data/cars.json\"}], \"height\": 300, \"marks\": [{\"encode\": {\"update\": {\"fill\": {\"value\": \"#4c78a8\"}, \"x\": [{\"test\": \"!isValid(datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"]) || !isFinite(+datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"])\", \"value\": 0}, {\"field\": \"bin_maxbins_10_Miles_per_Gallon_end\", \"scale\": \"x\"}], \"x2\": [{\"test\": \"!isValid(datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"]) || !isFinite(+datum[\\\"bin_maxbins_10_Miles_per_Gallon\\\"])\", \"value\": 0}, {\"field\": \"bin_maxbins_10_Miles_per_Gallon\", \"offset\": 1, \"scale\": \"x\"}], \"y\": {\"field\": \"__count\", \"scale\": \"y\"}, \"y2\": {\"scale\": \"y\", \"value\": 0}}}, \"from\": {\"data\": \"source_0\"}, \"name\": \"marks\", \"style\": [\"bar\"], \"type\": \"rect\"}], \"padding\": 5, \"scales\": [{\"bins\": {\"signal\": \"bin_maxbins_10_Miles_per_Gallon_bins\"}, \"domain\": {\"signal\": \"[bin_maxbins_10_Miles_per_Gallon_bins.start, bin_maxbins_10_Miles_per_Gallon_bins.stop]\"}, \"name\": \"x\", \"range\": [0, {\"signal\": \"width\"}], \"type\": \"linear\", \"zero\": false}, {\"domain\": {\"data\": \"source_0\", \"field\": \"__count\"}, \"name\": \"y\", \"nice\": true, \"range\": [{\"signal\": \"height\"}, 0], \"type\": \"linear\", \"zero\": true}], \"style\": \"cell\", \"width\": 400};\n",
              "      var embedOpt = {\"mode\": \"vega\"};\n",
              "\n",
              "      function showError(el, error){\n",
              "          el.innerHTML = ('<div class=\"error\" style=\"color:red;\">'\n",
              "                          + '<p>JavaScript Error: ' + error.message + '</p>'\n",
              "                          + \"<p>This usually means there's a typo in your chart specification. \"\n",
              "                          + \"See the javascript console for the full traceback.</p>\"\n",
              "                          + '</div>');\n",
              "          throw error;\n",
              "      }\n",
              "      const el = document.getElementById('altair-viz');\n",
              "      vegaEmbed(\"#altair-viz\", spec, embedOpt)\n",
              "        .catch(error => showError(el, error));\n",
              "    })(vegaEmbed);\n",
              "\n",
              "  </script>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JQU9wGCa21K-",
        "colab_type": "code",
        "outputId": "23317414-f3c2-4049-83e0-c3df3c432cc6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        }
      },
      "source": [
        "from IPython.display import HTML\n",
        "\n",
        "with open(\"chart.html\") as f:\n",
        "  html = f.read()\n",
        "HTML(html)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "<!DOCTYPE html>\n",
              "<html>\n",
              "<head>\n",
              "  <script src=\"https://cdn.jsdelivr.net/npm/vega@5\"></script>\n",
              "  <script src=\"https://cdn.jsdelivr.net/npm/vega-lite@4.0.0\"></script>\n",
              "  <script src=\"https://cdn.jsdelivr.net/npm/vega-embed@6\"></script>\n",
              "</head>\n",
              "<body>\n",
              "<div id=\"vis\"></div>\n",
              "<script type=\"text/javascript\">\n",
              "  const spec = {\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"data\": {\"url\": \"https://vega.github.io/vega-datasets/data/cars.json\"}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"bin\": true, \"field\": \"Miles_per_Gallon\"}, \"y\": {\"type\": \"quantitative\", \"aggregate\": \"count\"}}, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.0.json\"};\n",
              "  const embedOpt = {};\n",
              "  vegaEmbed('#vis', spec, embedOpt).catch(console.error);\n",
              "</script>\n",
              "</body>\n",
              "</html>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LTPTM_ZMJekM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "1293f7cb-fe38-4ab7-ce37-c60a1192369e"
      },
      "source": [
        "from IPython.display import HTML\n",
        "import base64\n",
        "\n",
        "with open(\"chart.pdf\", 'rb') as f:\n",
        "  pdf_base64 = base64.b64encode(f.read()).decode()\n",
        "\n",
        "HTML(f'Right-click and choose \"Open In New Tab\": <a download=\"chart.pdf\" href=\"data:application/pdf;base64,{pdf_base64}\">chart.pdf</a>')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "Right-click and choose \"Open In New Tab\": <a download=\"chart.pdf\" 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\">chart.pdf</a>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RT6t8A_4ie2Y",
        "colab_type": "text"
      },
      "source": [
        "## Renderers\n",
        "\n",
        "Alternatively, you can enable an altair-viewer renderer and display the chart within a notebook as a specific type or set of types.\n",
        "\n",
        "For example, the following encodes both the vega-lite custom mimetype (which is supported by JupyterLab and other frontends via custom frontend extensions), as well as a PNG fallback that will be displayed in other environments:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IlgGMKKUixmL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "outputId": "0d70e8b8-0014-4522-c64b-4b4bce9ed362"
      },
      "source": [
        "alt.renderers.enable('altair_saver', fmts=['vega-lite', 'png'])\n",
        "chart.display()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JUIRBI2wzA4pQly9zJwGKkNdA0AQowqARUoS6CJk7CQREgEOjAWELz5MoQt1+Z0Soy5e5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\n8SSuLOPbpcCvRn3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5tfuVr/ddV4rQcsoskARIgARIoN0SoAjbbdeyYSRAAiRA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\nTkSuQmCC\n",
            "application/vnd.vegalite.v4+json": {
              "data": {
                "url": "https://vega.github.io/vega-datasets/data/cars.json"
              },
              "$schema": "https://vega.github.io/schema/vega-lite/v4.0.0.json",
              "encoding": {
                "y": {
                  "aggregate": "count",
                  "type": "quantitative"
                },
                "x": {
                  "bin": true,
                  "field": "Miles_per_Gallon",
                  "type": "quantitative"
                }
              },
              "config": {
                "view": {
                  "continuousWidth": 400,
                  "continuousHeight": 300
                }
              },
              "mark": "bar"
            },
            "text/plain": [
              "alt.Chart(...)"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nyZ_H5jZmrNx",
        "colab_type": "text"
      },
      "source": [
        "The content of the output can be confirmed by looking at the ``_repr_mimebundle_`` method, which is the special method used by IPython/Jupyter for rich rendering:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2uYnHFManE7t",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 190
        },
        "outputId": "ef214440-0dcc-4314-adfb-47dc0c554785"
      },
      "source": [
        "chart._repr_mimebundle_(include=None, exclude=None)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'application/vnd.vegalite.v4+json': {'$schema': 'https://vega.github.io/schema/vega-lite/v4.0.0.json',\n",
              "  'config': {'view': {'continuousHeight': 300, 'continuousWidth': 400}},\n",
              "  'data': {'url': 'https://vega.github.io/vega-datasets/data/cars.json'},\n",
              "  'encoding': {'x': {'bin': True,\n",
              "    'field': 'Miles_per_Gallon',\n",
              "    'type': 'quantitative'},\n",
              "   'y': {'aggregate': 'count', 'type': 'quantitative'}},\n",
              "  'mark': 'bar'},\n",
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            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    }
  ]
}