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\"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"A Figure Displayed with fig.show()\"}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('328615b4-d1fc-47e6-b536-801789210989');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import requests, re\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "c = requests.get(\"http://www.rfc-editor.org/rfc/rfc-index.txt\").content.decode(\"utf-8\") \n",
    "m = re.compile(\"^[0-9]{4}\\ .*\\ [0-9]{4}\\.\", re.MULTILINE)\n",
    "t = m.findall(c)\n",
    "res = {}\n",
    "for i in t:\n",
    "    b = int(i[-5:-1])\n",
    "    if b in res:\n",
    "        res[b] += 1\n",
    "        continue\n",
    "    res[b] = 1\n",
    "sorted_res = sorted(res.items(), key=lambda kv: kv[0])\n",
    "data = sorted_res[1:-5]\n",
    "x_val = [x[0] for x in data]\n",
    "y_val = [x[1] for x in data]\n",
    "\n",
    "fig = go.Figure(\n",
    "    data=[go.Bar(x=x_val, y=y_val)],\n",
    "    layout_title_text=\"A Figure Displayed with fig.show()\"\n",
    ")\n",
    "fig.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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