Interactive_dashboard.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fdc9dea9-977d-47ec-a607-c4302a010733",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.3.2/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"tabulator\"], function(Tabulator) {\n",
       "\twindow.Tabulator = Tabulator\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"moment\"], function(moment) {\n",
       "\twindow.moment = moment\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 4;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n",
       "    }    if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.1/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/css/tabulator_simple.min.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/dataframe.css\"];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHN0eWxlPSJtYXJnaW46IGF1dG87IGJhY2tncm91bmQ6IG5vbmU7IGRpc3BsYXk6IGJsb2NrOyBzaGFwZS1yZW5kZXJpbmc6IGF1dG87IiB2aWV3Qm94PSIwIDAgMTAwIDEwMCIgcHJlc2VydmVBc3BlY3RSYXRpbz0ieE1pZFlNaWQiPiAgPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSIjYzNjM2MzIiBzdHJva2Utd2lkdGg9IjEwIiByPSIzNSIgc3Ryb2tlLWRhc2hhcnJheT0iMTY0LjkzMzYxNDMxMzQ2NDE1IDU2Ljk3Nzg3MTQzNzgyMTM4Ij4gICAgPGFuaW1hdGVUcmFuc2Zvcm0gYXR0cmlidXRlTmFtZT0idHJhbnNmb3JtIiB0eXBlPSJyb3RhdGUiIHJlcGVhdENvdW50PSJpbmRlZmluaXRlIiBkdXI9IjFzIiB2YWx1ZXM9IjAgNTAgNTA7MzYwIDUwIDUwIiBrZXlUaW1lcz0iMDsxIj48L2FuaW1hdGVUcmFuc2Zvcm0+ICA8L2NpcmNsZT48L3N2Zz4=\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n",
       "    },    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, js_modules, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'tabulator': 'https://cdn.jsdelivr.net/npm/tabulator-tables@5.3.2/dist/js/tabulator', 'moment': 'https://cdn.jsdelivr.net/npm/luxon/build/global/luxon.min', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n      require([\"tabulator\"], function(Tabulator) {\n\twindow.Tabulator = Tabulator\n\ton_load()\n      })\n      require([\"moment\"], function(moment) {\n\twindow.moment = moment\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 4;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n    }    if (((window['Tabulator'] !== undefined) && (!(window['Tabulator'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['moment'] !== undefined) && (!(window['moment'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.1/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/js/tabulator.js\", \"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/luxon/build/global/luxon.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.1/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.1/dist/bundled/datatabulator/tabulator-tables@5.3.2/dist/css/tabulator_simple.min.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.1/dist/css/dataframe.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
       "}\n",
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       "\n",
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       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        comm_manager.register_target(comm_id, function(comm) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        });\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        });\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
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       "\n",
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       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
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       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
       "          });\n",
       "        };\n",
       "        var comm = {\n",
       "          send: sendClosure\n",
       "        };\n",
       "      }\n",
       "      window.PyViz.comms[comm_id] = comm;\n",
       "      return comm;\n",
       "    }\n",
       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
       "    \n",
       "\n",
       "\n",
       "var JS_MIME_TYPE = 'application/javascript';\n",
       "var HTML_MIME_TYPE = 'text/html';\n",
       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
       "var CLASS_NAME = 'output';\n",
       "\n",
       "/**\n",
       " * Render data to the DOM node\n",
       " */\n",
       "function render(props, node) {\n",
       "  var div = document.createElement(\"div\");\n",
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       "\n",
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       " */\n",
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       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "    return\n",
       "  }\n",
       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
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       "    var html_node = toinsert[nchildren-1].children[0];\n",
       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var scripts = [];\n",
       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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       "      if (nodelist.hasOwnProperty(i)) {\n",
       "        scripts.push(nodelist[i])\n",
       "      }\n",
       "    }\n",
       "\n",
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       "    });\n",
       "    if (JS_MIME_TYPE in output.data) {\n",
       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
       "    }\n",
       "    output_area._hv_plot_id = id;\n",
       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
       "    } else {\n",
       "      window.PyViz.plot_index[id] = null;\n",
       "    }\n",
       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "    var bk_div = document.createElement(\"div\");\n",
       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var script_attrs = bk_div.children[0].attributes;\n",
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       "    // store reference to server id on output_area\n",
       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when an output is cleared or removed\n",
       " */\n",
       "function handle_clear_output(event, handle) {\n",
       "  var id = handle.cell.output_area._hv_plot_id;\n",
       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
       "  if (server_id !== null) {\n",
       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
       "    return;\n",
       "  } else if (comm !== null) {\n",
       "    comm.send({event_type: 'delete', 'id': id});\n",
       "  }\n",
       "  delete PyViz.plot_index[id];\n",
       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
       "    var doc = window.Bokeh.index[id].model.document\n",
       "    doc.clear();\n",
       "    const i = window.Bokeh.documents.indexOf(doc);\n",
       "    if (i > -1) {\n",
       "      window.Bokeh.documents.splice(i, 1);\n",
       "    }\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle kernel restart event\n",
       " */\n",
       "function handle_kernel_cleanup(event, handle) {\n",
       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
       "  window.PyViz.plot_index = {}\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle update_display_data messages\n",
       " */\n",
       "function handle_update_output(event, handle) {\n",
       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
       "  handle_add_output(event, handle)\n",
       "}\n",
       "\n",
       "function register_renderer(events, OutputArea) {\n",
       "  function append_mime(data, metadata, element) {\n",
       "    // create a DOM node to render to\n",
       "    var toinsert = this.create_output_subarea(\n",
       "    metadata,\n",
       "    CLASS_NAME,\n",
       "    EXEC_MIME_TYPE\n",
       "    );\n",
       "    this.keyboard_manager.register_events(toinsert);\n",
       "    // Render to node\n",
       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "    render(props, toinsert[0]);\n",
       "    element.append(toinsert);\n",
       "    return toinsert\n",
       "  }\n",
       "\n",
       "  events.on('output_added.OutputArea', handle_add_output);\n",
       "  events.on('output_updated.OutputArea', handle_update_output);\n",
       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
       "  events.on('delete.Cell', handle_clear_output);\n",
       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
       "\n",
       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "    safe: true,\n",
       "    index: 0\n",
       "  });\n",
       "}\n",
       "\n",
       "if (window.Jupyter !== undefined) {\n",
       "  try {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  } catch(err) {\n",
       "  }\n",
       "}\n"
      ],
      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = 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the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.bk-root, .bk-root .bk:before, .bk-root .bk:after {\n",
       "  font-family: var(--jp-ui-font-size1);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--jp-ui-font-color1);\n",
       "}\n",
       "</style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import panel as pn\n",
    "pn.extension('tabulator')\n",
    "\n",
    "import hvplot.pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "97cbf1e9-b3cb-4dbf-a5c4-77d98d13a987",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df = pd.read_csv(\"https://raw.githubusercontent.com/owid/co2-data/master/owid-co2-data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "58f973fa-e01c-4b6b-ba6a-532a62b2e1e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# cache data to improve dashboard performance\n",
    "if 'data' not in pn.state.cache.keys():\n",
    "\n",
    "    df = pd.read_csv('https://raw.githubusercontent.com/owid/co2-data/master/owid-co2-data.csv')\n",
    "\n",
    "    pn.state.cache['data'] = df.copy()\n",
    "\n",
    "else: \n",
    "\n",
    "    df = pn.state.cache['data']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "28c34f25-8c33-4b36-9597-a876d2e9c02a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>iso_code</th>\n",
       "      <th>population</th>\n",
       "      <th>gdp</th>\n",
       "      <th>cement_co2</th>\n",
       "      <th>cement_co2_per_capita</th>\n",
       "      <th>co2</th>\n",
       "      <th>co2_growth_abs</th>\n",
       "      <th>co2_growth_prct</th>\n",
       "      <th>...</th>\n",
       "      <th>share_global_cumulative_other_co2</th>\n",
       "      <th>share_global_flaring_co2</th>\n",
       "      <th>share_global_gas_co2</th>\n",
       "      <th>share_global_luc_co2</th>\n",
       "      <th>share_global_oil_co2</th>\n",
       "      <th>share_global_other_co2</th>\n",
       "      <th>total_ghg</th>\n",
       "      <th>total_ghg_excluding_lucf</th>\n",
       "      <th>trade_co2</th>\n",
       "      <th>trade_co2_share</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1850</td>\n",
       "      <td>AFG</td>\n",
       "      <td>3752993.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.121</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1851</td>\n",
       "      <td>AFG</td>\n",
       "      <td>3769828.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1852</td>\n",
       "      <td>AFG</td>\n",
       "      <td>3787706.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.116</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1853</td>\n",
       "      <td>AFG</td>\n",
       "      <td>3806634.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.115</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1854</td>\n",
       "      <td>AFG</td>\n",
       "      <td>3825655.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46518</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2017</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14751101.0</td>\n",
       "      <td>2.194784e+10</td>\n",
       "      <td>0.469</td>\n",
       "      <td>0.032</td>\n",
       "      <td>9.596</td>\n",
       "      <td>-0.937</td>\n",
       "      <td>-8.899</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.219</td>\n",
       "      <td>0.026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115.59</td>\n",
       "      <td>28.30</td>\n",
       "      <td>0.910</td>\n",
       "      <td>9.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46519</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2018</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>15052191.0</td>\n",
       "      <td>2.271535e+10</td>\n",
       "      <td>0.558</td>\n",
       "      <td>0.037</td>\n",
       "      <td>11.795</td>\n",
       "      <td>2.199</td>\n",
       "      <td>22.920</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.211</td>\n",
       "      <td>0.033</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118.22</td>\n",
       "      <td>30.83</td>\n",
       "      <td>0.771</td>\n",
       "      <td>6.537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46520</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2019</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>15354606.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.037</td>\n",
       "      <td>11.115</td>\n",
       "      <td>-0.681</td>\n",
       "      <td>-5.772</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.183</td>\n",
       "      <td>0.030</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117.96</td>\n",
       "      <td>30.53</td>\n",
       "      <td>0.978</td>\n",
       "      <td>8.795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46521</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>15669663.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.036</td>\n",
       "      <td>10.608</td>\n",
       "      <td>-0.507</td>\n",
       "      <td>-4.559</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.194</td>\n",
       "      <td>0.030</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.006</td>\n",
       "      <td>9.481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46522</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2021</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>15993525.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.036</td>\n",
       "      <td>11.296</td>\n",
       "      <td>0.688</td>\n",
       "      <td>6.488</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.190</td>\n",
       "      <td>0.030</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>46523 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           country  year iso_code  population           gdp  cement_co2  \\\n",
       "0      Afghanistan  1850      AFG   3752993.0           NaN         NaN   \n",
       "1      Afghanistan  1851      AFG   3769828.0           NaN         NaN   \n",
       "2      Afghanistan  1852      AFG   3787706.0           NaN         NaN   \n",
       "3      Afghanistan  1853      AFG   3806634.0           NaN         NaN   \n",
       "4      Afghanistan  1854      AFG   3825655.0           NaN         NaN   \n",
       "...            ...   ...      ...         ...           ...         ...   \n",
       "46518     Zimbabwe  2017      ZWE  14751101.0  2.194784e+10       0.469   \n",
       "46519     Zimbabwe  2018      ZWE  15052191.0  2.271535e+10       0.558   \n",
       "46520     Zimbabwe  2019      ZWE  15354606.0           NaN       0.570   \n",
       "46521     Zimbabwe  2020      ZWE  15669663.0           NaN       0.570   \n",
       "46522     Zimbabwe  2021      ZWE  15993525.0           NaN       0.570   \n",
       "\n",
       "       cement_co2_per_capita     co2  co2_growth_abs  co2_growth_prct  ...  \\\n",
       "0                        NaN     NaN             NaN              NaN  ...   \n",
       "1                        NaN     NaN             NaN              NaN  ...   \n",
       "2                        NaN     NaN             NaN              NaN  ...   \n",
       "3                        NaN     NaN             NaN              NaN  ...   \n",
       "4                        NaN     NaN             NaN              NaN  ...   \n",
       "...                      ...     ...             ...              ...  ...   \n",
       "46518                  0.032   9.596          -0.937           -8.899  ...   \n",
       "46519                  0.037  11.795           2.199           22.920  ...   \n",
       "46520                  0.037  11.115          -0.681           -5.772  ...   \n",
       "46521                  0.036  10.608          -0.507           -4.559  ...   \n",
       "46522                  0.036  11.296           0.688            6.488  ...   \n",
       "\n",
       "       share_global_cumulative_other_co2  share_global_flaring_co2  \\\n",
       "0                                    NaN                       NaN   \n",
       "1                                    NaN                       NaN   \n",
       "2                                    NaN                       NaN   \n",
       "3                                    NaN                       NaN   \n",
       "4                                    NaN                       NaN   \n",
       "...                                  ...                       ...   \n",
       "46518                                NaN                       0.0   \n",
       "46519                                NaN                       0.0   \n",
       "46520                                NaN                       0.0   \n",
       "46521                                NaN                       0.0   \n",
       "46522                                NaN                       0.0   \n",
       "\n",
       "       share_global_gas_co2  share_global_luc_co2  share_global_oil_co2  \\\n",
       "0                       NaN                 0.121                   NaN   \n",
       "1                       NaN                 0.118                   NaN   \n",
       "2                       NaN                 0.116                   NaN   \n",
       "3                       NaN                 0.115                   NaN   \n",
       "4                       NaN                 0.114                   NaN   \n",
       "...                     ...                   ...                   ...   \n",
       "46518                   0.0                 0.219                 0.026   \n",
       "46519                   0.0                 0.211                 0.033   \n",
       "46520                   0.0                 0.183                 0.030   \n",
       "46521                   0.0                 0.194                 0.030   \n",
       "46522                   0.0                 0.190                 0.030   \n",
       "\n",
       "       share_global_other_co2  total_ghg  total_ghg_excluding_lucf  trade_co2  \\\n",
       "0                         NaN        NaN                       NaN        NaN   \n",
       "1                         NaN        NaN                       NaN        NaN   \n",
       "2                         NaN        NaN                       NaN        NaN   \n",
       "3                         NaN        NaN                       NaN        NaN   \n",
       "4                         NaN        NaN                       NaN        NaN   \n",
       "...                       ...        ...                       ...        ...   \n",
       "46518                     NaN     115.59                     28.30      0.910   \n",
       "46519                     NaN     118.22                     30.83      0.771   \n",
       "46520                     NaN     117.96                     30.53      0.978   \n",
       "46521                     NaN        NaN                       NaN      1.006   \n",
       "46522                     NaN        NaN                       NaN        NaN   \n",
       "\n",
       "       trade_co2_share  \n",
       "0                  NaN  \n",
       "1                  NaN  \n",
       "2                  NaN  \n",
       "3                  NaN  \n",
       "4                  NaN  \n",
       "...                ...  \n",
       "46518            9.486  \n",
       "46519            6.537  \n",
       "46520            8.795  \n",
       "46521            9.481  \n",
       "46522              NaN  \n",
       "\n",
       "[46523 rows x 74 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bf0160fd-b26f-406b-97f5-18979365bf20",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th>iso_code</th>\n",
       "      <th>population</th>\n",
       "      <th>gdp</th>\n",
       "      <th>cement_co2</th>\n",
       "      <th>cement_co2_per_capita</th>\n",
       "      <th>co2</th>\n",
       "      <th>co2_growth_abs</th>\n",
       "      <th>co2_growth_prct</th>\n",
       "      <th>...</th>\n",
       "      <th>share_global_cumulative_other_co2</th>\n",
       "      <th>share_global_flaring_co2</th>\n",
       "      <th>share_global_gas_co2</th>\n",
       "      <th>share_global_luc_co2</th>\n",
       "      <th>share_global_oil_co2</th>\n",
       "      <th>share_global_other_co2</th>\n",
       "      <th>total_ghg</th>\n",
       "      <th>total_ghg_excluding_lucf</th>\n",
       "      <th>trade_co2</th>\n",
       "      <th>trade_co2_share</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>30258</th>\n",
       "      <td>North America</td>\n",
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       "    <tr>\n",
       "      <th>30259</th>\n",
       "      <td>North America</td>\n",
       "      <td>1751</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>30260</th>\n",
       "      <td>North America</td>\n",
       "      <td>1752</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>0.000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30261</th>\n",
       "      <td>North America</td>\n",
       "      <td>1753</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>North America</td>\n",
       "      <td>1754</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30525</th>\n",
       "      <td>North America</td>\n",
       "      <td>2017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>581258143.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.813</td>\n",
       "      <td>0.131</td>\n",
       "      <td>6425.781</td>\n",
       "      <td>-47.450</td>\n",
       "      <td>-0.733</td>\n",
       "      <td>...</td>\n",
       "      <td>16.573</td>\n",
       "      <td>20.852</td>\n",
       "      <td>25.996</td>\n",
       "      <td>11.418</td>\n",
       "      <td>24.038</td>\n",
       "      <td>9.941</td>\n",
       "      <td>7418.35</td>\n",
       "      <td>7566.229</td>\n",
       "      <td>386.995</td>\n",
       "      <td>6.023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30526</th>\n",
       "      <td>North America</td>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>585864285.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>74.562</td>\n",
       "      <td>0.127</td>\n",
       "      <td>6614.565</td>\n",
       "      <td>188.784</td>\n",
       "      <td>2.938</td>\n",
       "      <td>...</td>\n",
       "      <td>16.308</td>\n",
       "      <td>23.347</td>\n",
       "      <td>27.322</td>\n",
       "      <td>12.033</td>\n",
       "      <td>24.345</td>\n",
       "      <td>8.880</td>\n",
       "      <td>7630.50</td>\n",
       "      <td>7777.590</td>\n",
       "      <td>388.395</td>\n",
       "      <td>5.872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30527</th>\n",
       "      <td>North America</td>\n",
       "      <td>2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>590497015.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.227</td>\n",
       "      <td>0.127</td>\n",
       "      <td>6500.850</td>\n",
       "      <td>-113.715</td>\n",
       "      <td>-1.719</td>\n",
       "      <td>...</td>\n",
       "      <td>16.071</td>\n",
       "      <td>25.761</td>\n",
       "      <td>27.536</td>\n",
       "      <td>11.097</td>\n",
       "      <td>24.243</td>\n",
       "      <td>9.281</td>\n",
       "      <td>7515.65</td>\n",
       "      <td>7663.030</td>\n",
       "      <td>382.097</td>\n",
       "      <td>5.878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30528</th>\n",
       "      <td>North America</td>\n",
       "      <td>2020</td>\n",
       "      <td>NaN</td>\n",
       "      <td>594263186.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.718</td>\n",
       "      <td>0.127</td>\n",
       "      <td>5805.619</td>\n",
       "      <td>-695.230</td>\n",
       "      <td>-10.694</td>\n",
       "      <td>...</td>\n",
       "      <td>15.855</td>\n",
       "      <td>23.337</td>\n",
       "      <td>27.318</td>\n",
       "      <td>12.876</td>\n",
       "      <td>23.093</td>\n",
       "      <td>9.241</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>450.022</td>\n",
       "      <td>7.751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30529</th>\n",
       "      <td>North America</td>\n",
       "      <td>2021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597123384.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.944</td>\n",
       "      <td>0.131</td>\n",
       "      <td>6137.900</td>\n",
       "      <td>332.281</td>\n",
       "      <td>5.723</td>\n",
       "      <td>...</td>\n",
       "      <td>15.653</td>\n",
       "      <td>23.155</td>\n",
       "      <td>26.120</td>\n",
       "      <td>13.483</td>\n",
       "      <td>23.550</td>\n",
       "      <td>9.246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>272 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             country  year iso_code   population  gdp  cement_co2  \\\n",
       "30258  North America  1750      NaN   11396206.0  NaN       0.000   \n",
       "30259  North America  1751      NaN          NaN  NaN       0.000   \n",
       "30260  North America  1752      NaN          NaN  NaN       0.000   \n",
       "30261  North America  1753      NaN          NaN  NaN       0.000   \n",
       "30262  North America  1754      NaN          NaN  NaN       0.000   \n",
       "...              ...   ...      ...          ...  ...         ...   \n",
       "30525  North America  2017      NaN  581258143.0  NaN      75.813   \n",
       "30526  North America  2018      NaN  585864285.0  NaN      74.562   \n",
       "30527  North America  2019      NaN  590497015.0  NaN      75.227   \n",
       "30528  North America  2020      NaN  594263186.0  NaN      75.718   \n",
       "30529  North America  2021      NaN  597123384.0  NaN      77.944   \n",
       "\n",
       "       cement_co2_per_capita       co2  co2_growth_abs  co2_growth_prct  ...  \\\n",
       "30258                  0.000     0.000             NaN              NaN  ...   \n",
       "30259                    NaN     0.000           0.000              NaN  ...   \n",
       "30260                    NaN     0.000           0.000              NaN  ...   \n",
       "30261                    NaN     0.000           0.000              NaN  ...   \n",
       "30262                    NaN     0.000           0.000              NaN  ...   \n",
       "...                      ...       ...             ...              ...  ...   \n",
       "30525                  0.131  6425.781         -47.450           -0.733  ...   \n",
       "30526                  0.127  6614.565         188.784            2.938  ...   \n",
       "30527                  0.127  6500.850        -113.715           -1.719  ...   \n",
       "30528                  0.127  5805.619        -695.230          -10.694  ...   \n",
       "30529                  0.131  6137.900         332.281            5.723  ...   \n",
       "\n",
       "       share_global_cumulative_other_co2  share_global_flaring_co2  \\\n",
       "30258                                NaN                       NaN   \n",
       "30259                                NaN                       NaN   \n",
       "30260                                NaN                       NaN   \n",
       "30261                                NaN                       NaN   \n",
       "30262                                NaN                       NaN   \n",
       "...                                  ...                       ...   \n",
       "30525                             16.573                    20.852   \n",
       "30526                             16.308                    23.347   \n",
       "30527                             16.071                    25.761   \n",
       "30528                             15.855                    23.337   \n",
       "30529                             15.653                    23.155   \n",
       "\n",
       "       share_global_gas_co2  share_global_luc_co2  share_global_oil_co2  \\\n",
       "30258                   NaN                   NaN                   NaN   \n",
       "30259                   NaN                   NaN                   NaN   \n",
       "30260                   NaN                   NaN                   NaN   \n",
       "30261                   NaN                   NaN                   NaN   \n",
       "30262                   NaN                   NaN                   NaN   \n",
       "...                     ...                   ...                   ...   \n",
       "30525                25.996                11.418                24.038   \n",
       "30526                27.322                12.033                24.345   \n",
       "30527                27.536                11.097                24.243   \n",
       "30528                27.318                12.876                23.093   \n",
       "30529                26.120                13.483                23.550   \n",
       "\n",
       "       share_global_other_co2  total_ghg  total_ghg_excluding_lucf  trade_co2  \\\n",
       "30258                     NaN        NaN                       NaN        NaN   \n",
       "30259                     NaN        NaN                       NaN        NaN   \n",
       "30260                     NaN        NaN                       NaN        NaN   \n",
       "30261                     NaN        NaN                       NaN        NaN   \n",
       "30262                     NaN        NaN                       NaN        NaN   \n",
       "...                       ...        ...                       ...        ...   \n",
       "30525                   9.941    7418.35                  7566.229    386.995   \n",
       "30526                   8.880    7630.50                  7777.590    388.395   \n",
       "30527                   9.281    7515.65                  7663.030    382.097   \n",
       "30528                   9.241        NaN                       NaN    450.022   \n",
       "30529                   9.246        NaN                       NaN        NaN   \n",
       "\n",
       "       trade_co2_share  \n",
       "30258              NaN  \n",
       "30259              NaN  \n",
       "30260              NaN  \n",
       "30261              NaN  \n",
       "30262              NaN  \n",
       "...                ...  \n",
       "30525            6.023  \n",
       "30526            5.872  \n",
       "30527            5.878  \n",
       "30528            7.751  \n",
       "30529              NaN  \n",
       "\n",
       "[272 rows x 74 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['country'] == 'North America']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "263e941d-3bfc-4364-8baa-e6848d0a3580",
   "metadata": {},
   "outputs": [
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       "      <td>World</td>\n",
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       "    <tr>\n",
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       "      <td>37123.852</td>\n",
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       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>272 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      country  year iso_code    population           gdp  cement_co2  \\\n",
       "45735   World  1750      NaN  7.456645e+08           NaN         NaN   \n",
       "45736   World  1751      NaN           NaN           NaN         NaN   \n",
       "45737   World  1752      NaN           NaN           NaN         NaN   \n",
       "45738   World  1753      NaN           NaN           NaN         NaN   \n",
       "45739   World  1754      NaN           NaN           NaN         NaN   \n",
       "...       ...   ...      ...           ...           ...         ...   \n",
       "46002   World  2017      NaN  7.599822e+09  1.104307e+14    1507.923   \n",
       "46003   World  2018      NaN  7.683790e+09  1.136302e+14    1569.218   \n",
       "46004   World  2019      NaN  7.764951e+09           NaN    1617.507   \n",
       "46005   World  2020      NaN  7.840953e+09           NaN    1637.537   \n",
       "46006   World  2021      NaN  7.909295e+09           NaN    1672.592   \n",
       "\n",
       "       cement_co2_per_capita        co2  co2_growth_abs  co2_growth_prct  ...  \\\n",
       "45735                    NaN      9.351             NaN              NaN  ...   \n",
       "45736                    NaN      9.351           0.000            0.000  ...   \n",
       "45737                    NaN      9.354           0.004            0.039  ...   \n",
       "45738                    NaN      9.354           0.000            0.000  ...   \n",
       "45739                    NaN      9.358           0.004            0.039  ...   \n",
       "...                      ...        ...             ...              ...  ...   \n",
       "46002                  0.198  36096.738         572.547            1.612  ...   \n",
       "46003                  0.204  36826.508         729.772            2.022  ...   \n",
       "46004                  0.208  37082.559         256.049            0.695  ...   \n",
       "46005                  0.209  35264.086       -1818.472           -4.904  ...   \n",
       "46006                  0.211  37123.852        1859.764            5.274  ...   \n",
       "\n",
       "       share_global_cumulative_other_co2  share_global_flaring_co2  \\\n",
       "45735                                NaN                       NaN   \n",
       "45736                                NaN                       NaN   \n",
       "45737                                NaN                       NaN   \n",
       "45738                                NaN                       NaN   \n",
       "45739                                NaN                       NaN   \n",
       "...                                  ...                       ...   \n",
       "46002                              100.0                     100.0   \n",
       "46003                              100.0                     100.0   \n",
       "46004                              100.0                     100.0   \n",
       "46005                              100.0                     100.0   \n",
       "46006                              100.0                     100.0   \n",
       "\n",
       "       share_global_gas_co2  share_global_luc_co2  share_global_oil_co2  \\\n",
       "45735                   NaN                   NaN                   NaN   \n",
       "45736                   NaN                   NaN                   NaN   \n",
       "45737                   NaN                   NaN                   NaN   \n",
       "45738                   NaN                   NaN                   NaN   \n",
       "45739                   NaN                   NaN                   NaN   \n",
       "...                     ...                   ...                   ...   \n",
       "46002                 100.0                 100.0                 100.0   \n",
       "46003                 100.0                 100.0                 100.0   \n",
       "46004                 100.0                 100.0                 100.0   \n",
       "46005                 100.0                 100.0                 100.0   \n",
       "46006                 100.0                 100.0                 100.0   \n",
       "\n",
       "       share_global_other_co2  total_ghg  total_ghg_excluding_lucf  trade_co2  \\\n",
       "45735                     NaN        NaN                       NaN        NaN   \n",
       "45736                     NaN        NaN                       NaN        NaN   \n",
       "45737                     NaN        NaN                       NaN        NaN   \n",
       "45738                     NaN        NaN                       NaN        NaN   \n",
       "45739                     NaN        NaN                       NaN        NaN   \n",
       "...                       ...        ...                       ...        ...   \n",
       "46002                   100.0  48251.879                 47031.820      0.000   \n",
       "46003                   100.0  49368.039                 47980.469     -0.004   \n",
       "46004                   100.0  49758.230                 48116.559      0.000   \n",
       "46005                   100.0        NaN                       NaN      0.000   \n",
       "46006                   100.0        NaN                       NaN      0.000   \n",
       "\n",
       "       trade_co2_share  \n",
       "45735              NaN  \n",
       "45736              NaN  \n",
       "45737              NaN  \n",
       "45738              NaN  \n",
       "45739              NaN  \n",
       "...                ...  \n",
       "46002              0.0  \n",
       "46003             -0.0  \n",
       "46004              0.0  \n",
       "46005              0.0  \n",
       "46006              0.0  \n",
       "\n",
       "[272 rows x 74 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['country'] == 'World']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf78b9c7-2ceb-410a-ba9c-e668d41587db",
   "metadata": {},
   "source": [
    "## (0) Some minor data preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "81ded706-a096-4b08-8358-519af91555aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fill NAs with 0s and create GDP per capita column\n",
    "df = df.fillna(0)\n",
    "df['gdp_per_capita'] = np.where(df['population']!= 0, df['gdp']/ df['population'], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3b6d5f4a-f7ef-47fc-a3df-7d60b3cfd97e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Make DataFrame Pipeline Interactive\n",
    "idf = df.interactive()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54629e7a-8cb8-4fbe-a616-6481a8e6ff31",
   "metadata": {},
   "source": [
    "## (1) CO2 emission over time by continent"
   ]
  },
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   "cell_type": "code",
   "execution_count": 9,
   "id": "b81a227b-996c-4eec-8dd0-4968831b9eb9",
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   "outputs": [
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      "text/plain": [
       "IntSlider(end=2020, name='Year slider', start=1750, step=5, value=1850)"
      ]
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     "execution_count": 9,
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    "# Define Panel widgets\n",
    "year_slider = pn.widgets.IntSlider(name='Year slider', start=1750, end=2020, step=5, value=1850)\n",
    "year_slider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5131fd1d-f9a9-48b2-9168-769435d830fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Radio buttons for CO2 measures\n",
    "yaxis_co2 = pn.widgets.RadioButtonGroup(\n",
    "    name='Y axis', \n",
    "    options=['co2', 'co2_per_capita',],\n",
    "    button_type='success'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4c357628-af69-4ec4-9e2d-91bcdd21c3c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "continents = ['World', 'Asia', 'Oceania', 'Europe', 'Africa', 'North America', 'South America', 'Antarctica']\n",
    "\n",
    "co2_pipeline = (\n",
    "    idf[\n",
    "        (idf.year <= year_slider) &\n",
    "        (idf.country.isin(continents))\n",
    "    ]\n",
    "    .groupby(['country', 'year'])[yaxis_co2].mean()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ad349aaf-1612-4a0d-9303-3a379cf83fad",
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    "tags": []
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   "outputs": [
    {
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     "metadata": {},
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       "</div>\n",
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class=&quot;dataframe panel-df&quot;&gt;\\n  &lt;thead&gt;\\n    &lt;tr style=&quot;text-align: right;&quot;&gt;\\n      &lt;th&gt;&lt;/th&gt;\\n      &lt;th&gt;country&lt;/th&gt;\\n      &lt;th&gt;year&lt;/th&gt;\\n      &lt;th&gt;co2&lt;/th&gt;\\n    &lt;/tr&gt;\\n  &lt;/thead&gt;\\n  &lt;tbody&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;0&lt;/th&gt;\\n      &lt;td&gt;Africa&lt;/td&gt;\\n      &lt;td&gt;1750&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;1&lt;/th&gt;\\n      &lt;td&gt;North America&lt;/td&gt;\\n      &lt;td&gt;1750&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;2&lt;/th&gt;\\n      &lt;td&gt;South America&lt;/td&gt;\\n      &lt;td&gt;1750&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;3&lt;/th&gt;\\n      &lt;td&gt;Asia&lt;/td&gt;\\n      &lt;td&gt;1750&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n 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&lt;th&gt;689&lt;/th&gt;\\n      &lt;td&gt;North America&lt;/td&gt;\\n      &lt;td&gt;1848&lt;/td&gt;\\n      &lt;td&gt;16.825&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;690&lt;/th&gt;\\n      &lt;td&gt;Europe&lt;/td&gt;\\n      &lt;td&gt;1848&lt;/td&gt;\\n      &lt;td&gt;156.991&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;691&lt;/th&gt;\\n      &lt;td&gt;South America&lt;/td&gt;\\n      &lt;td&gt;1848&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;692&lt;/th&gt;\\n      &lt;td&gt;Oceania&lt;/td&gt;\\n      &lt;td&gt;1848&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;693&lt;/th&gt;\\n      &lt;td&gt;World&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;183.511&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;694&lt;/th&gt;\\n      &lt;td&gt;North America&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;18.269&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;695&lt;/th&gt;\\n      &lt;td&gt;Oceania&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;696&lt;/th&gt;\\n      &lt;td&gt;Africa&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;697&lt;/th&gt;\\n      &lt;td&gt;South America&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;698&lt;/th&gt;\\n      &lt;td&gt;Europe&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;165.243&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;699&lt;/th&gt;\\n      &lt;td&gt;Asia&lt;/td&gt;\\n      &lt;td&gt;1849&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;700&lt;/th&gt;\\n      &lt;td&gt;Asia&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.015&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;701&lt;/th&gt;\\n      &lt;td&gt;Oceania&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;702&lt;/th&gt;\\n      &lt;td&gt;North America&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;19.852&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;703&lt;/th&gt;\\n      &lt;td&gt;Africa&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;704&lt;/th&gt;\\n      &lt;td&gt;South America&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;705&lt;/th&gt;\\n      &lt;td&gt;Europe&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;177.030&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;706&lt;/th&gt;\\n      &lt;td&gt;World&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;196.896&lt;/td&gt;\\n    &lt;/tr&gt;\\n  &lt;/tbody&gt;\\n&lt;/table&gt;\"},\"id\":\"1013\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"end\":2020,\"margin\":[5,10,5,10],\"start\":1750,\"step\":5,\"title\":\"Year slider\",\"value\":1850},\"id\":\"1009\",\"type\":\"Slider\"}],\"root_ids\":[\"1005\",\"1014\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"ea74263e-38ab-4077-b86d-22939d028505\",\"root_ids\":[\"1005\"],\"roots\":{\"1005\":\"5e4b7f6c-75c2-47cb-8996-a5233414b4a3\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "<hvplot.interactive.Interactive at 0x1342dad60>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1005"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "96b7ed90-92db-41b2-a2ab-ea80aa34d2db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='1809'>\n",
       "  <div class=\"bk-root\" id=\"304008bc-bcf0-4c34-84cc-f74e27f874a3\" data-root-id=\"1809\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
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      "text/plain": [
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     "execution_count": 14,
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     "output_type": "execute_result"
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   ],
   "source": [
    "co2_plot = co2_pipeline.hvplot(x = 'year', by='country', y=yaxis_co2,line_width=2, title=\"CO2 emission by continent\")\n",
    "co2_plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2e3cb1b-093c-47ae-b6df-60a0487d0023",
   "metadata": {},
   "source": [
    "## (2) Table - CO2 emission over time by continent "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f9496235-820f-49c8-a375-fbef06be6c1e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
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    },
    {
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       "    var docs_json = {\"6b958bbb-f918-4e5a-9a7e-a071c922c905\":{\"defs\":[{\"extends\":null,\"module\":null,\"name\":\"ReactiveHTML1\",\"overrides\":[],\"properties\":[]},{\"extends\":null,\"module\":null,\"name\":\"FlexBox1\",\"overrides\":[],\"properties\":[{\"default\":\"flex-start\",\"kind\":null,\"name\":\"align_content\"},{\"default\":\"flex-start\",\"kind\":null,\"name\":\"align_items\"},{\"default\":\"row\",\"kind\":null,\"name\":\"flex_direction\"},{\"default\":\"wrap\",\"kind\":null,\"name\":\"flex_wrap\"},{\"default\":\"flex-start\",\"kind\":null,\"name\":\"justify_content\"}]},{\"extends\":null,\"module\":null,\"name\":\"TemplateActions1\",\"overrides\":[],\"properties\":[{\"default\":0,\"kind\":null,\"name\":\"open_modal\"},{\"default\":0,\"kind\":null,\"name\":\"close_modal\"}]},{\"extends\":null,\"module\":null,\"name\":\"MaterialTemplateActions1\",\"overrides\":[],\"properties\":[{\"default\":0,\"kind\":null,\"name\":\"open_modal\"},{\"default\":0,\"kind\":null,\"name\":\"close_modal\"}]}],\"roots\":{\"references\":[{\"attributes\":{},\"id\":\"5138\",\"type\":\"NumberFormatter\"},{\"attributes\":{},\"id\":\"5150\",\"type\":\"IntEditor\"},{\"attributes\":{\"editor\":{\"id\":\"5145\"},\"field\":\"country\",\"formatter\":{\"id\":\"5144\"},\"title\":\"country\",\"width\":0},\"id\":\"5146\",\"type\":\"TableColumn\"},{\"attributes\":{\"children\":[{\"id\":\"5130\"},{\"id\":\"5135\"}],\"margin\":[0,0,0,0],\"name\":\"Column35262\"},\"id\":\"5129\",\"type\":\"Column\"},{\"attributes\":{\"data\":{\"co2_per_capita\":{\"__ndarray__\":\"+n5qvHSTiD/pJjEIrBzwPwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[10]},\"country\":[\"World\",\"Europe\",\"Europe\",\"World\",\"Europe\",\"World\",\"World\",\"Europe\",\"Europe\",\"World\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"year\":[1750,1750,1751,1751,1752,1752,1753,1753,1754,1754]},\"selected\":{\"id\":\"5137\"},\"selection_policy\":{\"id\":\"5161\"}},\"id\":\"5136\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"indices\":[]},\"id\":\"5137\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"5144\",\"type\":\"StringFormatter\"},{\"attributes\":{},\"id\":\"5145\",\"type\":\"StringEditor\"},{\"attributes\":{\"children\":[{\"id\":\"5129\"}],\"margin\":[0,0,0,0],\"name\":\"Row35263\"},\"id\":\"5128\",\"type\":\"Row\"},{\"attributes\":{\"end\":2020,\"margin\":[5,10,5,10],\"start\":1750,\"step\":5,\"title\":\"Year 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Application\",\"version\":\"2.4.2\"}};\n",
       "    var render_items = [{\"docid\":\"6b958bbb-f918-4e5a-9a7e-a071c922c905\",\"root_ids\":[\"5128\"],\"roots\":{\"5128\":\"7b694703-7952-49e9-bf69-f5296b133da0\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "<hvplot.interactive.Interactive at 0x1370c89d0>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "5128"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_table = co2_pipeline.pipe(pn.widgets.Tabulator, pagination='remote', page_size = 10, sizing_mode='stretch_width') \n",
    "co2_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3483f4a-15d2-4361-9f42-0f0dcf0ac399",
   "metadata": {},
   "source": [
    "## (3) CO2 vs GDP scatterplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8cd37bd6-28e0-4805-843a-397873fa2f59",
   "metadata": {},
   "outputs": [],
   "source": [
    "co2_vs_gdp_scatterplot_pipeline = (\n",
    "    idf[\n",
    "        (idf.year == year_slider) &\n",
    "        (~ (idf.country.isin(continents)))\n",
    "    ]\n",
    "    .groupby(['country', 'year', 'gdp_per_capita'])['co2'].mean()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6b00d3dd-3df7-497c-aba8-27ba742223bc",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
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       "\n",
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       "\n",
       "  <div class=\"bk-root\" id=\"841d1c73-632d-4640-ab28-830d70adc5d9\" data-root-id=\"6972\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
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USA)&lt;/td&gt;\\n      &lt;td&gt;1890&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;12.414&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;9&lt;/th&gt;\\n      &lt;td&gt;North Macedonia&lt;/td&gt;\\n      &lt;td&gt;1890&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.010&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;10&lt;/th&gt;\\n      &lt;td&gt;Norway&lt;/td&gt;\\n      &lt;td&gt;1890&lt;/td&gt;\\n      &lt;td&gt;2757.082556&lt;/td&gt;\\n      &lt;td&gt;2.077&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;11&lt;/th&gt;\\n      &lt;td&gt;Peru&lt;/td&gt;\\n      &lt;td&gt;1890&lt;/td&gt;\\n      &lt;td&gt;841.425722&lt;/td&gt;\\n      &lt;td&gt;0.011&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;12&lt;/th&gt;\\n      &lt;td&gt;Poland&lt;/td&gt;\\n      &lt;td&gt;1890&lt;/td&gt;\\n      &lt;td&gt;2242.448563&lt;/td&gt;\\n      &lt;td&gt;41.865&lt;/td&gt;\\n    &lt;/tr&gt;\\n  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       "    var render_items = [{\"docid\":\"0cba018f-684c-4b0a-8068-d6a24f3cff8c\",\"root_ids\":[\"6972\"],\"roots\":{\"6972\":\"841d1c73-632d-4640-ab28-830d70adc5d9\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
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       "        attempts++;\n",
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       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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      "text/plain": [
       "<hvplot.interactive.Interactive at 0x137244be0>"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "6972"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_vs_gdp_scatterplot_pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "da1d4289-2f65-4a94-88fc-841bf3e40068",
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
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      "text/plain": [
       "<hvplot.interactive.Interactive at 0x13729c610>"
      ]
     },
     "execution_count": 16,
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   "source": [
    "co2_vs_gdp_scatterplot = co2_vs_gdp_scatterplot_pipeline.hvplot(x='gdp_per_capita', \n",
    "                                                                y='co2', \n",
    "                                                                by='country', \n",
    "                                                                size=80, kind=\"scatter\", \n",
    "                                                                alpha=0.7,\n",
    "                                                                legend=False, \n",
    "                                                                height=500, \n",
    "                                                                width=500)\n",
    "co2_vs_gdp_scatterplot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "582ad1e4-a76a-4033-b380-bf1a82db634e",
   "metadata": {},
   "source": [
    "## (4) Bar chart with CO2 sources by continent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5bf7f84e-44b1-4e4b-9486-7cfd10fa0d03",
   "metadata": {},
   "outputs": [],
   "source": [
    "yaxis_co2_source = pn.widgets.RadioButtonGroup(\n",
    "    name='Y axis', \n",
    "    options=['coal_co2', 'oil_co2', 'gas_co2'], \n",
    "    button_type='success'\n",
    ")\n",
    "\n",
    "continents_excl_world = ['Asia', 'Oceania', 'Europe', 'Africa', 'North America', 'South America', 'Antarctica']\n",
    "\n",
    "co2_source_bar_pipeline = (\n",
    "    idf[\n",
    "        (idf.year == year_slider) &\n",
    "        (idf.country.isin(continents_excl_world))\n",
    "    ]\n",
    "    .groupby(['year', 'country'])[yaxis_co2_source].sum()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2c80f1dd-a24d-4342-916c-be7720ee0988",
   "metadata": {},
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    {
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       "<hvplot.interactive.Interactive at 0x140c2ce80>"
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   "source": [
    "co2_source_bar_plot = co2_source_bar_pipeline.hvplot(kind='bar', \n",
    "                                                     x='country', \n",
    "                                                     y=yaxis_co2_source, \n",
    "                                                     title='CO2 source by continent')\n",
    "co2_source_bar_plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef1d523e-0409-4024-9783-2b654b8f9d53",
   "metadata": {},
   "source": [
    "## Creating Dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "1c2e45bf-37c7-48e0-a2d3-a36da8843362",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Layout using Template\n",
    "template = pn.template.FastListTemplate(\n",
    "    title='World CO2 emission dashboard', \n",
    "    sidebar=[pn.pane.Markdown(\"# CO2 Emissions and Climate Change\"), \n",
    "             pn.pane.Markdown(\"#### Carbon dioxide emissions are the primary driver of global climate change. It’s widely recognised that to avoid the worst impacts of climate change, the world needs to urgently reduce emissions. But, how this responsibility is shared between regions, countries, and individuals has been an endless point of contention in international discussions.\"), \n",
    "             pn.pane.PNG('climate_day.png', sizing_mode='scale_both'),\n",
    "             pn.pane.Markdown(\"## Settings\"),   \n",
    "             year_slider],\n",
    "    main=[pn.Row(pn.Column(yaxis_co2, \n",
    "                           co2_plot.panel(width=700), margin=(0,25)), \n",
    "                 co2_table.panel(width=500)), \n",
    "          pn.Row(pn.Column(co2_vs_gdp_scatterplot.panel(width=600), margin=(0,25)), \n",
    "                 pn.Column(yaxis_co2_source, co2_source_bar_plot.panel(width=600)))],\n",
    "    accent_base_color=\"#88d8b0\",\n",
    "    header_background=\"#88d8b0\",\n",
    ")\n",
    "# template.show()\n",
    "template.servable();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "438f8daa-0017-4cb2-a8cb-c86784a6ab52",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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