gcore_result_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"gcore_result_all.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x107d2c510>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dzmxXwOqDmAqbcsFISVKnDTFZguvzKmeb0NQFOSEQVhXTGJ3UMauTejxVTL0p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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107b220d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = df['comments'].plot()\n",
    "fig.grid(True)\n",
    "plt.xlabel('Artical No.')\n",
    "plt.ylabel('# of Comments')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x105520c90>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rjZ+7gO9N9+JWu2/LxTR9DWEOxP7gNOogcuBiynWQ2mezGjKxIFKJQZR4Exex\nmZaFy2Gso5HmbYY0icshrLRbtaqcQpEaOVMQUsrngNjy3tuBe43X9wJvsm3/udR5GagSQiyYzvUt\nCyKLldRWkHo6FoQ0snFEdmozNE1aiiFXCiJdC8JakzqFIkV7DCKsybjuI1ORmhZEuso+YKxn7bZc\nTMqCUChSYaZjEPOllB3G607AbA26CGi17ddmbMuY2HYPeVMoZ1tRLhvJND774D0DFkQq15gcg0i8\nr6lwzCK2eGO3lcXkNOtHUhI7cnxYw+VwWPEo1dFVoUiNWWv3LaWUQoi0R20hxF3obijq6upobm6O\nu9++7hAAe/fsRgCnTp2muflcxvICHDwVBGBk3Jfwuiajo6Nx9/EFAnR2nCMQhvGJ8JTnmYrhQOQR\n7ty9B9/ZqT/SRLIl4sxwRAnt2LWH8TPOpPsfadOf055duwA43tJCc+hM3H33dOmf0+hgLwDDI2OT\nZNvXo++zb88eggE/5zo6aG4eSFn+1nM+wkGNwwcP6Pfwyi76W5LfQzzSfW4ziZItM5RsyZlpBdEl\nhFggpewwXEjdxvZ2YLFtv0Zj2ySklPcA9wCsXbtWNjU1xb1Q4FAn7N7FZZdeimvHizQuWUJT07pp\nCb8vdByOvQoOF4mua9Lc3Bx3H0fz4yxubMQXDHN0uHvK80xF++AEPPMMAGvXX0jT+qnXa0gkWyJ2\nnRmAl14C4IING2maYk2Ijh1n4eABrrzicnjxWVasWEnTdSvi7ju2vwP27GZZ40Je7milqKR0kmzB\nw12wayeXX3Yp/9Oyh9r6SpqaLk5Z/t+d201XcJgtF2+EXdvZuGkzV66oSfl4k3Sf20yiZMsMJVty\nZtrF9Afgfcbr9wEP27a/18hmuhIYsrmiMsJ0c2Rz9bZIHUTmQWopsdaDyIpMgdy7mOz3m0qcI61u\nrlYMwnAxxTm9GXNwOc3srzSzmMIabofDWjxK1UEoFKmRyzTXXwPbgLVCiDYhxJ3Al4GbhRDHgZuM\nvwEeBU4CLcAPgQ9O9/r2fkDZSinNWh2Eg6w16/MF7YN36orreNdIys/En3YMQv+dTgyixGMUscV5\nJkFbFlO8z/Lel07z0xdPJbxGMCxxu2x1ECoGoVCkRM5cTFLKdyZ468Y4+0rg7mxeP5L5Yqy9kMXB\n2GyMZ85I05JL6nUQ2WrWNxFM34IY8Gnc8c3n+M67LuH1F06dLBZtQUythKxeTM7ULYhij9nKe/I+\nkc/SEVcUXoiqAAAgAElEQVRBPLinnbCm8TfXLE94DZfDYVV2KwtCoUiNgl+TWlgZQ9kdjP2hzBSE\ntC05mnUXU4rpPSMBvTK6c9iX0v5pZzHZ0lJhijqIULQFYR+7w5rkC388RJlX/5omsiBGJoJJXV/B\nsIbH6bAUlqqDUChSo+AVhDOLay/E+vtLvemfw2q1kQsXU4qtNvzGISO+UGr7px2D0H+7UurFFFnM\nB6ItiNb+cX6+7QwNFUVA4m6uw74gY/7Elk0oLKPrIFQltUKREgXbi8kcaCIxiOmfM8qdk8EJpZRW\nN1c9cD47MvmNQXnEF0xp/6hK6ozqIKZu92214rbt2z3iByKWjsupF8rZzyelZGgiyEQwHKXA7ei9\nmByqklqhSJOCVRCmm0MY6z9nZcnRNFtOTJLJEMEh9NhI9oPUqclkGg6ZWBCpuJjM20pnwaB4FkT3\nSLQLzOVw4BDR3Vx9Qc2yQvrHAwmuIXUFYbmY8suCaO0f5xfbTs+2GArFJApWQYRts9isuZiiZuvp\np7pGub2yFaQOpJ/FFLEgUlMQpgXhEOlZEA6h/yTvxaThcohIW3bbrj2GBWHidOiZSHYLYthmBQ2M\nJVIQejdX8xr5lsX0qx1n+deHDzEeSO3zUChmioJVEPbB2OFI3g8oVSaCYcuP7cvAgjAVgsNoOgfT\nl8tcLMjtFClnMZnu+uEUXUz+UBinQ1DicaWV5moF46do1hc1u4+yIKIVhMtwzdljEMMTkXvoT6og\nHFZdRjCHCytlwtn+cYCkcRSFYjYoXAVhG4yzleY6EQhTWewGMotB2H3zTpGdHlGmi6miyJ2ygvBl\nYEEUuRx4XY6UrJRIBpmeRTaVi8k+u5/SgojJYhqyKYiBJC4ml1NYjRvzrd13q6EglAWhyDcKVkFY\ns3UjzTUbg4IvGKaiyFAQIY1P/G4fP3r+ZAYyYVkQ03Uz+YJhvNbgrfHM0S7e9v1tSc/rt2IQqVsQ\nXrcTj8uRVpqrXsU+dR2EnmFkKojoIPWa+WUYujRumqvdCkpmQXickTqIfOvmmq8WxLOv9iildZ5T\nuArCDJSaq7dlycVUWaIrCH9I47lXe3nueG/Kx8e6XmD6CmIiGKbY48TrdhIIaew+M8iO0/0JB0vI\nLAZR5HLoCiKNdt9mm5NkRlIwJKPcP1EupmEfS+aVsGReCRC/Kn54InIPiWIQIU23IDKpg/CHwmw/\n2Zfy/rF88ZHDSScRQxNBBsd1JZdPg3HXsI/3/WQHf9g7vQaXirlNwSoIMzDqMNtaTHMgllLiC9pc\nTCGNMX9okhskGfYCsmy5mCYCYYrdTjxOfXY/apgHyeSKVwcxEQhz6NxQ/P1DGl63U7dS0lgwSA9S\nJ1fOZnwgnoupd9RPXXkRq+vLcDkEQkxWEKaLyekQibOYQjExCNvxI74gf/2jlzndOxb32Ef2dfD2\ne16mO8Wiwlj+tL8j6STCdC8BjCVI050Nuof178/AeGpWpqIwKVgFYV9kxpGF9Z8DYQ1NYikIXzDM\naCA9BWHPrMpekNpQEEZ8wFIQo4nlMmMQE8GwlWb6822nedN3XrSOj9rfcGOlakFIKwYhEGLqXkz2\n9aLDGhw+N0wwrNE3FqC+3Muly+Yx3yqWc8RYEPoAtqiqmIGx+IOZ33BjCWEsWWq7hxM9Y7zY0qd3\nrI1D31jmA2UorNEz6mcszjM1sSuI8ST7zTS9xn2P+pWCOJ8pXAVh6+aaDQvCF9AHFVNBDE4EkRL6\nx/wpnztSm6GvKAfZiEFoFBmz+0BYY9SXggVhG4fM/V/tGiUYlnQOTcTZ37QgnCkGqXXrAUionINh\njdb+8YgFYcQHzgxr3Pat5/nV9rNICXXlXv7uNSt48mPXAUxaiW/YF6TY7WR+hdcazKNlDxMIaZSb\n7Tqc0fEo8/4HJ+IPhKOGuRVPcU5F72iAsCaTKoizeWpB9I/q1thoim5IRWFSsApC2v3gDhF3pbJ0\nMGsgTAVh/gNpMnFwNBary6k9BpGFLKZiTySAbA5kvUksCH/Y7mLR9z/dp7tYOocmH+cLhvUYhDPF\nILWU1v0lClI/uLuNG7/2LJ3Dfj1I7dL37xrXz/+bV/QFBuvLvVaKLegWhL3QbXgiREWxi+oSDwNj\nQZ483MUPn4v4/M37KzeSC9wOh2U1QWSGPJTAPWUOkMkG+USYFeDJYj1n+8etZ5UPMYguQ2bzOz2S\nR1aNYuYpWAURjvL3Z8eVAzYFYZutpupmiriY9IEOmHa7jYlgmCK3w3AxpReDgEgW0BlDQXQksyDc\njpR7MQlhKoj4FkTbwASBsMbB9qGoNhiDPn3fwx3DANQbriUTpyNa4QxNBKkoclNT5qF/PMC3nznO\nPc/HUxA2CyKOgrRbEAfbh/jmU68CEQWSkYIY0gfbsSQD/9n+cVbWlRrXmF0LoqV7hCv+42l2nu6P\nuJiUBXFeU/AKQm9rkQUXU4yC6LNZDcn8/Xbs6Z9mI9hsBam9rvSC1KbLZcQXYsQXpNewiLriBGP9\naVoQesda/XWiOgizZiGsSaMOQj9gwB+9c115dEdEp8MRXSjnC1JZ7Ka6xEPfqJ8D7UMMjgesOIiZ\nymtaEC6nI2pNavN5DdpiDN9tbuGbTx3HHwpbg3YmLibTXTdVDGJ1fTkOMfsWREu3Pkk41jUScTEp\nC+K8pmAVhCalVaiVjVYbky0Im4JI1YKIqg/ITpDaFwpT5HbicelprqnEIHwhyfxKfWY+4gtypi/i\nB4/XAty0IFKugzBamkPiVhv2oK9eSa1/FYf8EeUCUFvmiTrOGVMVP+wLUlHsZl6pB03qrsVgWDJu\n+PNjLQi3QxAITbYgzGyogJG+DLr7ynSxZOZi0j+DYFjGjd2ENUnbwARLakoo9bhm3YIwJwcdgz7r\n+60UxPlNQSsIM5U0G2sv+IwBx5yJZqIgoiqps1UoZ0tz9Rupt5DcqvGHYX6FPjMf8YWs+IPH5bDc\nIlH7W8V4zpRdTA67iynOIfaaBY8tBVUCi6qLWVpTQlWJG6/LGXWcK8aC0F1MegzCjukyilgQposp\ngQVh7L/jVL+1TW8jbiiIKQLI9+04O8k9Z7fG4g3+HUMThDTJknklFHucs25BmPKeG5qwLGSlIM5v\nZkVBCCFOCyEOCCH2CiF2GtvmCSGeFEIcN35Xp3KuRw90cG5wst88rEWqlR1Cz5G/4j+eovlY95Tn\n7Bia4JIvPhlVF2BaECVGQLgviYI43jXCgZ7J/1hWfYBNQXzigf3802/2TikTwAd+sYv/++iRqG2R\nQjkjzTWQiotJMr88YkGYNQCbF1fFtSB8IS0qzvGzF09x+3+/kPD8pvUGiYPUsRaE27b4Uk2pl7++\nYgk3XzB/0nGxyn54IkSlYUEAFLt1hTJouLCGDQvBrIAvcjuiGhxaFoSx/1NHuqz3hiaClkWWbKAc\nGAvwqQcPcO9LZ6K22xVGPAvEzGBaMq+EUq/Lsnpmiy7D4jk3OGFlhKkYxPnNbFoQ10spN0spLzX+\n/hTwtJRyNfC08XdSpIQP/nI39zw3uVJVs/nBnQ7ByZ4xuob9HGiLXwxm50DbEP1jAY50jFjbTAVR\n7HHidTqsGXB5kWvSbP0bT73Kd/f5J7lWzOQZs4AM9Bnr7rPxc/Cj71Xy4ole9rUNRm3Xg9S6BTE4\nrqfelhe5GJoIxnVraJrEH44Ef3ULYpz5FV5W1JbGzWLSLQin1YtpT+sg+9qGGA+EePpIF7d847ko\n15O0WRCJYhCD4wE2NVYC4HY5jHoV/b3aMg93XbeSr75106Tj7AsGaZpkxHAx1RiuqJvW60plaNy0\nIKJdTFXFnqj+TXYLQkrJ00e7qDGUzfBE0Ho/mYvJ/PwPtkd/t7qMDC27HHZabQqiJI8siI4hn4pB\nKID8cjHdDtxrvL4XeNNUB5hFvYfPDU96z1y5DbB+w+QOofEwZ3Z2N4g56zSL0sxBakVtKT0x6xac\n7BljIqRn6tiJXeXOkml4sjKJZXA8yIgvFFUMpld3R+og7DIBVuDZjs9QGrr7xsGIP8SZvjGW1pTS\nUFlE76h/UpzBtCDMQLhpnZwb9PHSiT6OdY1YM3bzPq06CEeiGESAS5fNo8zrwmNYD2YcwrQG4mHG\nkz70q93838eOoEndOti4sJKvvPki7rx2uXH+aBeTuWxpZYk7WkEY7w9NBOkZ8dPaP8HrNjQAuvVh\nDpDJBspe43kcaB+y7lVKSeeQz/os4mUymSmuCyqL8ioG0T4wwVhAdyuOB8JZaUuvmJvMloKQwBNC\niF1CiLuMbfOllB3G605gsn8hBrNlwpGO4UmDkCZlxMVkH4xHpm6ZYCoIe+sGnzFoeo2BEnTf+aLq\nYnpG/JzsGaWlexRNk5wyXDaHYhRXVLtvm9KaCIan9HHHk8mMB5hZTCbLjUGpfWCCrce6oyqHzUGo\n1OOkvMjNiC/Iqd5xltWUWEt72p9RKKwR1qTNgtAsJds+OGHNgodtM+ToIPXkNFdfMIwvqDGv1MO3\n3rmZv7tOH9TdxudUU5Z4LVenEATDGo8d7OTHL5wC9MQBh0PwtssWW/cwOGHk8ftClHiclvKpKnbH\ntSCkhKOdusV4kWHZDMVYEJqUPH+8Z9J3zbQghiaC1qRgeCLERDDMyrqyqOvYOds/waKqYlxOByXe\n/LAg7JMfsweWsiLOX2ZrTeprpZTtQoh64EkhxFH7m1JKKYSIO20xFMpdABX1jVSjF/P87rGt1JVE\nBsmzrX60cIjm5mb6+yID3on2Hpqbm6PO2TmmUeISVHj1AWrPcX3/Qy1naG7uBODgKX1Q2bV9G+Gg\nPiB4HBr+oV7ODYR463eeo8wj+PDFXmvgfmzbfop6I7d2akgfnA8fOjjpvh556jkaSiPyT4QkPeMa\nSyp0n/rLHfo/af+on61btyKEYDSgP6K2MyeZsGXmMNoDwMd/tZ3WEY0VlQ7uushLQ6mDbqMQ7czJ\n47i0IK+82k7vqIYY6ab7jH7cY83bWF3ttOQAaD972lLIrX2jAGzdvpcjrbpcz760nbYq/Zi2dj/B\nYJjm5mZ8ExN0dvmjnnm/T5ehp+0UG4Sbzk7oPApI/fkMdrZazz2W1rMBpIxODz574hjNYycACBg1\nDnsOHmPRxClePeXHIzTr+sN9fvpGQ9bfnX0RK++PL+zR7/nccQBeOXDMUuptnT3sEWG+/fgOPntl\nEauqIsHzl09HFM59T7zEZQ0u2kb0e3SN6xlRr+zej+iI/nc7dHqCchc0NzczNuSjZ0Sb9N1MldHR\n0YyPBT0uNewLsarKQYvhxSyR+rN5qvl5aoozn0tOV7ZcomRLzqwoCCllu/G7Wwjxe+ByoEsIsUBK\n2SGEWADEjSZLKe8B7gGYt2SNFEKf/ZUvWc8zJ3rZuLCSt122mKcGD+Dt66SpqYnftu+Grg62LK2m\na9hHU1NT1Dmv/89m1i+s4DvvugSAL+xsBsYoqqihqUkPkewPH4djr3LT9a/lGweep2t8lOryYjav\nXczTZ19lIiQZDOhywC4EMO6dh9awmAd2t/Otd1xMZdsgbHuJTRddqF949062LK1m15kBll2wiStX\n1Fgy/fczx/mv7cfZ+dmbqSx2c/CZ48CrhCVsuepaKorcenD+mWe4aP1afVZ8XFdG11+6gYda9tI6\norGpsZIz/ePcd9rLQ3dfw5GOYXjuebZctJFXBk6wz4jJfOANV+MLhvn6rudZuHI9TRctAKBv1A9P\nPcX6tat119PxI1ahXVn9EgZbTgMaq9dfxHVr6gB4vH8/RYPdNDU1Ubqrmdq6CpqaLrHu7fC5YWh+\nnis2b6TpwgXW9uIXnmIs6OeKTetpunhR3O/O/vBxOKEXsS2rKeF03zhXX7qZq1fVWvsUNT/GvAWL\naWq6gN+07aI2OEpT02sBOKgd5/HTr3LVta/B63Iitz9DZXFIX9e6qBbo4M23XMeXdz6Fu3I+0AaA\np7SCCTEOBGhctZ6mjRG5X37sKO7jehxMq2qkqWmdngzx4ivccNkGHj6xl6Wr1tB02ZKoe/nY809y\nxdoGmpou5E89+2hv6Z303UyV5ubmjI8F9ESFJ5u5bsNSWl7ULbNL1ixmX89pNl58GWsbyjM+dyLZ\nRnxBPnLfXr7wxg0sNqyVmWa6zy2X5INsM+5iEkKUCiHKzdfA64CDwB+A9xm7vQ94eKpzBTXJliXV\nOAT8blcrP992hq88fhR/KByVallb5mFdQzlbllbTPRLt79c0SWv/ONtP9iOlNHLTjRiEzZ0zPBHE\na6xbYKZelnndViFXqcdJWJP8cZ/eHnlNtYPD54b5yp+P8af9HTxztDuqDXZtmRch4J2X64NGbNbR\n2f5xgmHJHiOAbe/ZY8ZGzCroEo8rKh10WU2p8azhq2/dxN1Nq9jbOkhL96jlxig2XEwAFyyoYHlt\nKQuM2gh79o3pWjOzmOwcOjdk1QnY3RCaFp3mGghpfOz+vbR065aHGa+oiklNNYvlasqSxyBAj1N8\n8tZ1CAELq4qj9qkq9ljPaMQXsgLUAJXGNYcmIkHsxmr9+MMdw5R7XVQWuyMK2GDMH2LYsNj6Y5oC\n9o76qS3zsmZ+uRWo7jDShVfXlxvPJ9qFOOoP0T8WsNw4pV7XrPZiMrPXLl5SZW0zv0e5ath3pGOE\nZ45280JL6i3zFTPLbMQg5gMvCCH2ATuAP0kp/wx8GbhZCHEcuMn4OymhMKxfWMGKujKeOtKNEHpg\n9tEDHWiatKqVP33bBdz/gauoL/cSCGlR/vL+8QAhTdI76uds/zgdQxPWgjL2VNZTvWOWb98cKMu8\nTpYa/0T/dvtGAJ483EWpx8mFdU7aByc42jmCEHDvS6ej6iAuaqzilX+5iZsuqAcmB8/NlEOzy6i9\nmM2swTjVo8c6lteWRg3e1SUeFlUV85cXLWTN/HJuv3ghTofggd1tViplqddlDZx/caEelK0s1gPX\n9loIv5G95XU5o64hBLxyOpJ9ZV98KCpILXTl9uDudp59VXdhmQHk2GC02dF1qiA1wMZFlbz+wgXs\n+MxNLDM+F5OqEndUHYSpCEGPQYCe5SSlZNQfURCnescsZVNR7OKcoSgri92M+cOMGF+H2JXrTAVx\n4aJKK1B9uncMj8vBqnojBhGTxWTGbhbP06+XahaTLxhO2mcrU8wA9bqGcorc+ue8pMaMQeRGcZnt\naswJmZ2vPXFsWutwKLLDjCsIKeVJKeUm42eDlPJLxvY+KeWNUsrVUsqbpJT9U51LQx8cL1hQAeiz\n8RV1pfzspTNRWUxFbicVRZHZvj3ryF7MtPP0AGeNgXhlXWlUFtOJnlEr4Oi1FISLK1fM4/lPXM+b\ntzTSWF2MP6SxvK6UJeX6PpXFbj50/SpeaOm1gqBOy7LxUlnsxuN0TLIgTLl2no5YEGbPHnOAOtGj\nz8hX1JVGBanLilz8/oNX89W3XARAfXkRTWvqeHB3m5VuWeJxWgriNsPNI4RgeW0prxoz/d/ubLUC\nwUW24DzA6vqyKKthJCpIHd2LyVRoZq2BKX91SWTgBqyOrrVJgtRmQd2Fi/TPPLYVB+gKwp7marcg\nqkoi3Xh9QT0A31itD4RS6kV6oH9uHYP6Z9BQUcSoP8SIZUHEUxAeNiysYHA8SOewj5O9YyyrKcHj\nclDkdkzKYrLXQICusINhOWWl+lf+fIzb/uv5rCyAZcdc/2F+ZRELq4pxOwULK/VnkataCDPLrj0m\n22/YF+Tbz7Tw0N72nFxXkTr5lOaaEctrS9nUWIkQ8P6rl/GeK5eyr3WQlp5Ra5AyMQeT7mE/vmAY\nTZNRCmLX2QHOGP+4mxdXMzgRJKzpbRLsA7Q5ky71uhBCWP7TzYurDJnKWFrhxOkQvPPyJfzNNctx\nOwUP7NL92Xa5hBDUlXvpHvERCmtW7YIp197WQcb8ITqHfWxerNcOmi6OEz1jLKoqpsTjiprdl3qd\n1FcUUeSOuJ3+1yWNdA37ec6YxZd4XNyyoYH3X72MFYbiM+9hX+sgYU3yH48e4ZfbzwKTLQjzXk3s\nCkJKiTHWI4SwFIJpOSRyMZkWRGxVtB3TdXXhosqE+1QVe6wspmFfiAq7i8ls1z4eZMQfWUvCxHxd\nUeS21r6or/BGuZhiV67rHQlQW+ZlbYOutI52jnCyZ9SyOMu8rkmZQK0xCqLEo39WU1kRTx3ponvE\nz3FDiWeLzmEfxW4n5V4XCyuLqS7xWIp11B+0/l+ySZ+hIGLTwV81JlIdcar6FTPLnFcQK2rLePeV\nS3nkw9eyZn45m4yB62TPWFStAegzadDTM6/7ylZ+8uIpy5Wzur6MXacHONs/jtspWL+wAil1X/WZ\nvnE0CSsNd4GZt2+fmYJdQZRS6RU8fPc1/NPNq5lX6mHxvBIr/TVWrrpyLz0jfr7y+DFu/+8X8YfC\nDIwHWV1fxkQwzJOHu5ASNi/WB0VzgGrpHmWFqbSckdTb2PYUAFev1APgpr+31OPkxgvm8/k3bph0\nD0MTetvsgfEgb76kkdesrmXjokrrvA4BFzbq91pV4qbU44yxIKJ7MZkuO1NR9I8FKfU4J8U03E4H\npW4mbbdT5nUhbNePR1WJ22q+N9nFpCufwfGANTOeV+qxBuiIiylyTENFESFNMmB0mrWnGmuapG/M\nT225l7Xz9XjD4XPDnO0ftxRvqdc1qdDubP+4Fe8AKDXamSeLQ5zpG7Msj51n4hvYTx3u4vnjPQnP\nkYiuYR8NlUUIIXjjpoW8ZUsjZcb3e2giyGu/upWfvnQ64fGZ1Er0WS6maAVhWtrx2r4oZpY5rSAE\nukugyO1kw0J98DRngEMTwckKwug/9MzRbrpH/Ow+O0DXsA8h4PUbG3i1e4QnDnWyuLrEahLXPxbg\nhDFbs1xMbjNIHa0gLlmqz/BNv7N9UF1UVWxbHjP6PkwF8dThLo52jnC6Vx8E/sLIJPrvrS0ArF9Y\niduptw2RUka7vUyZiuInplWXelhWU2L9MxZ7JisRwFKw339WTxv96E2r+cWdV1BX7rUG7poyrzXz\nXVxdYtVTmMT2YjIx739wPDDJegC9UK7cIyZtt/OGTQt58B+ujpr1x1JpKIhASMNvWyzIfM+UxZzV\nl3ldVmwi4mKKHNNgBO97jBRhuwUxNBEkGJa6u7DEzYLKIp4+0kUwLC0LQi+Ci1YQHUM+FlYVW9ak\n+XkkW1XueWPpUq/LkXAFvK88fpQv/elI3PeScW5wgnrDwn7bZYv5xK3rLKV1+NwwXcN+die4Zkv3\nKOs/92f2tQ7GfT8RpgXRNeKLqvo/ZiiIeJ2FFTPLnFYQ84rE5Nl4mdfKhonxMFHudeF1OXjmqJ5B\ne6Jbb79RU+rl1o0LqC3TB+ob1tVbgdKB8UCUrx8is/XSGAVx8eIqfvr+y3j9xoZJstoHtFjXV325\nl5O9Y5w0LIxtJ/SBYPPiKq5ZVUP3sF6Ru2Z+mbEwToDOYR/jgfAkq6bUG3/gh8jgD1gL8MSyZn45\nJR4ne1sHWVRVHJV+aMYg6sq8LKrSB80l80ooL4p2ocT2YjIZsMUgqkuj4w8AJW4nVd7kCqLY4+Ti\nJcnbdFWXeAiENWuAsVt65V4XDhHdZ6m8yGVlN5n3VWGzOsy2JD5jDLNbEGbA2JxQrG0oZ/dZfaBc\nYXMxxbba6BzyWR11IfK5JbMgXjjey6KqYl67pi6hgugY8nGsa8TKcIvlkf3nJvUuC4Q0Dp0bZmOM\n287pEJR6nOwxBn7z/yCWxw504A9p7G+fuo2NHfPZSYkV74GIghgYD1pt9hWzw5xWEPFmmw6HYIER\nXHPGDMRCCOorIoVsp3rHODc4wfwKL+sXVvDKv9zE/s/fwmf/cr3lB+8fC9DSPWr5+sGexeSadP7r\n19VHNZ4zsadixspVZ2RXmbx4Qs/emF9RxC//9kr2f/4WnvnfTZQX6U3pdKtGVyarDAsiItPkgdfE\ndIF5HJPdXJZsDmH59+11GfZr1Fd4jdkvLJ5XQlmRKyYGEd2LycRsEzIwHowbZ/g/b1zPey5IHKBO\nFdMaaDWyY+wuJodDUFHsNmIQhgVR5LIshkVVukI0XUxOh6DOlnYrBFHtTswq6jojsG66mSBS0V5W\n5JoUpO4c9rHAthiS+d1KZEGEwhovnujlNatruXRZNWf6xiclNoz5Q4z4QkgJe85Ons2PB0J86Fd7\n+IFhHZocOjeEP6SxZelkxVvqdVkZdCd7x+K6kp42JlzxspGS0TcWsCZi7YbSklJytHOYUsOi6hr2\n8Q//s4tvPPlqWudWZIc5rSASYc7W4w2CZhyiqkQPQu4+O8D8mFXLIJJqOTAW4ETPmGU9QGQmHRuD\nSEWmeHKZMpV5XTgdgpdPRhREPLl0paXPslbWl0bL5E0sk6kgkhgZUftdsWJe1HbTSqkv91LicfGD\nd2/hjmuWxXExRae5mkzlYlrXUMGi8ul/Jc1MpbZ+fdCJ/ZyqivU0WKuRn9dNVbEHt1NYbhbTgij1\nOKMsxcbqYkb9IcslYmbimAkQZkFZRZHL+g7pMYjITDgY1ugd9UdbEDExiH/+7T6+9sQx6/2jnSOM\n+EJctbKGLUv1z2VXTBzC3ol31+nJMQozW2hvjCvItEYujaMg7C7LQEiblHHUM+K3GkjGxhKmom/U\nb7U1MZVL57CPYV+Ia4zCx/aBCZ4+0m2lSCtmlsJUEIYf2RHrYyIy03vLJY2Ann0TbyA2Z7h9Y4Eo\nXz9EBuNYF1My7BZErFzmoHT58nksnVfCiC+Ex+mYlAYKeiyhf1xXWuVFLut+IjIlHv0vWFCB2ynw\nupK7cZrW1lPudfGa1bVR2838eHMwfN2GBuoriigvckWtXRzWZNwYxKg/RCCkGRZEYktnulQageh4\nFgToxXK6i8lo5FfkYsPCCi5eUm317TKDx+VF7qjP2bTYTCvCbNRnpuaaCmJFXZllPZV5nVEuuJ4R\nP1Ji9Y0CKPFGspiGxoM8uKedPx3osN433TyXLKlm46IKnA7BwfboXl9dRlDX6RDsitMh2BzAD3cM\nRy7RHs8AABmOSURBVLludp4eYPG84knLu0JkwmE+j5aekaj3tx7rRkr9O5yOggiFNQYngmxYqN+L\neawZoH7tWr0qf9vJPgJhjZM9o1M2tFRkn4JUEOZg7Ihzd2ag+l1XRNoemIvn2Cn2OCl2O3mxpZfx\nQJgLFkRcB4lcTMkwi7HiyWUOuFeumGdlvtRXeCfFKgDmGTGIV073s66h3NrHkqko8cBb5HayfkEF\nRVNYEFetrOHAF26xXHUmZsDdtHhMKmJcTLF1EHZ6Rv0M+4JJi+GmixnfMFNJ41kQQ+OBqCD1h29c\nzf1/f5W1T4XhcirzuqI+59WGC8mshegZ9eNyCGsAXVVfhtMhLPcSTA5Sm+mbC+JZEP4wza92Ezaa\nPpppr/taB6kp9dBYXYzX5aShoshyy5iYFsTVK2vYc3aQUFhD0ySvnO4nGNasWXowLPWWK+gunZ1n\nBtiSIK5jWhA3G23UT3SP8Ynf7ePXO/T0561Hu1lQWcQN6+ppT8HFpGmSHaf6GTBa08+vKKKhooi2\ngQl8wTAP7dFrH15rtG0xLYdhXyhqDRHFzFCQCqKxKn4MAnTF8G+3b2BFXZk164tnQYDuznnpRB8e\np4PXrY8EnjNxMc2vKLICt7FybVhYwT/euJq3bFlsuYwSyVRd6mFgPMjRzhHesGmhTab4mVWx/PMt\n63jTqswG58bqYv7369ZYhXUmehA2ug15ZE1qUz79mR1qH0JKPfspV5iprMe69KBqRYzSNCutR/wh\nvK7JLUTsx5R6nVYKLNgsCCNQ3WFk/5iWh9fl5N/ftNFqO66fwxXVNtsMns9PYEGYSRT2DrN7WwfZ\nvLjKUryN1cWTfP6m4vmLCxcwHgjzhT8e5q9/tJ23fn8bv93ZRtvAhPW5mG6m1v4Jekf9bFkW7U40\nMb9Ply+bR02ph4f3tXP/zjYe2a+3lDl0bpgtS6tZPK+E3tHAlEHlPx3o4G0/2Mbjh/RmjDWlXhqr\ni9l2oo9bv/kcD+89x53XLqexuoRSj5MDtsD3qd7s1n4opqYgFYTlYooTg1jXUMF7r1oGYBW+NSRR\nEAA3XlBPtW3G68nAxeRxOaxV3GLlcjkdfOzmNcwr9ViurIQyGa4Zt1PwhosiCsLe/iMZ166u5dKG\nzHo0CiH40A2rJ1Uvlxe58QU1gkZhWWy7b4j09TH/4XPZnK2+XG97Yc6SYxV5pRGkHo2pso7dB3SL\nzK50zawx04I4eG6Y9Qsroo595+VLojKCzOPPDU7QPeKz8vsbbBZEiZGmPDwRpPlYD1cs1wfsw+eG\nGfYFOdEzGlWc2FhdMsml0zXso6LIxRs2LeTWDQ3c98pZDrQPUex2sr9tkLbBCZbVlDK/wmulpG4/\npce74sUfdNkNy2h+GSvryiy3Vkv3KL5gmNaBcVbVl1kxtqncTM3HjI7BB3X3WU2ZhwsWVNA57GNe\nqYd777icf/3L9YBe1S0lVsD6hNFaxmTEF5y0zKsiuxSkgliYxIKwY/6z18dxMQGWUnjLlsao7Waw\nNh0Xky5X0ZRyraxLTaabLpgfV2kly2LKFVbFreFm0qRtuVfjG7asVlcI+9tMBZG4jmG6OByCb7/z\nYuvzia0NqSp2M+wLMuwLJfwMzSymcq/Lmgi4RKTyeWA8wJg/xIme0UnpobGYx7/9B9t4309esdZd\nsMdhXE69lcnD+84xNBHkvVcto7zIxZGOYQ606VbXpigFUUznsI9ASKNv1I8/rC9Q1FBZRKnXxfff\ns4Vd/3oz2z59A5csreJwxzBtAxMsqi5m8+Iqy4J4oaWX2jJPVPaVHfOzXV1fZlm3pR6nvjqjYQ2u\nrCuL6mf16QcP8Md95ybFDKSUvNCiK4iXT+pB9NoyD596/Tp2fvYmHvzgNZZrCSIuuGtX1+J2CqvQ\n1OTzfzjM6//r+YQpvYrpU5AKwvxixQtS29loFJ4lKrpaVFXM/Aqv1cba5DVr6njXFUsm+einYpHh\nVkkm16r6MjwuR5QP247ZN+htly2O2l7qcXLHNcu50Wj+N5OYg+yIpSDsWUz6i+W1uuI70D6Exxmx\npnLFstpSvv2ui3n/1csmpR1XlniQUndZJCosNAfGUq8Tt1N3Q5V7hDWo948FONwxjJTJ235AREGd\nG/JxpGOYPa2DNFQUxW0Fc6ZvnOvW1HHDunrWL6jgcMewNZjHKggpdavkjf/9Ir8+EqBr2Bfltqoo\nclNe5OaChgqOdY5wtm+MxupiLl5Szem+cc72jfPC8V6uXVUb19oGuHVjA//QtJLyIjfrF1biEPCh\nG1YDemNKMBWE/r38+bbT/HrHWT786z18/Lf7opTE8e5Ruob9VBS5LHdbTamXIrczbv8t8142LKxk\nybwSTvWM8cCuNu7bcRZNkzQf62ZwPMi9L55O+vwVmTNbCwblFPMLFy9IbedtlzZy5Yp5cVMuAT59\n2zo+cuPqSQPMyroy/uOvLkxbLtOCSCZXZbGbJ//puoTK55IlVTzxT9exJmbGJ4Tgc29Yn7ZM2cDM\nEjJ7G8k4ldTLDQuifyzA8trShANSNrl+bT3Xr52sMM06iYPtw/z9a1fEPdbtdFBb5rHcaWVeF2WO\nEC6ng8piNwNjAWt98ykVhOH2W1lXyomeMXac6ufyOD7/3/z9VTiFsFxP6xdW8OsdZxk02q5U2tp/\nmAPy9lN9tA9OMDwGXq8v7roN6xdW4DeqyhurS3jjpoV89fFj/MtDB+gbC3Dt6rpJx5hcuaLGqod5\n+6WLuWZlDRL4f38+yuOHOhFCLyD1OB24nYLnj/dSX+7lLy5awE9fPM0d10RiMWYfsDuuXc43nzqO\n0xbcj4fpZl3bUM7y2jL2tw3y7Ks9OIQ+keobC1Be5OJHL5zi/Ua6tSK7FKQFAXoV61QuIJfTEdWo\nLpaKIneUnzgbMgmhLxGajKU1pQn7EQkhJimH2cZshhffgtB/mx1CIbfxh1SoNQb9N1/SyCduWZdw\nv99+4Go+8NqVgG5JlBvziHmlHvrHgxxsH6K+3Bs3PdTOhoWVXLOqhh+97zJrphzve7Woqjhq+wUL\nKvAFNTqHfPz7mzZG7Wu6dB7Zr/vyR4J6ZXK82JU9RtJYXczCqmJet36+1bojNp05ER6X/v+yZF4J\nLofgTN84jUarG4cjYon/1SWL+MiNq/E4HTywu806/vnjvayoK+WNRnJFdYkn6UTBdOetX1DBirpS\nzg35rOV5P/fwIQC+/rbNDE0E+caTx1O6B0V6FKQFAfC1t22akVlqOvzVxY2sqi9PuubyXKQsjoKI\nTXOtLvFQVeKhZ8TP4urcxR9S4ZqVNfzPnVdw1cqahBXlQJSb7/UbFzDeow9280o9tA+MM+wLTWk9\nQKQiHuDaVTU8tPdcShOPa1bVsqmxkk/fdgFXxFS1N1QW4RDoWXYuh57SKqEhjuW5sq4Mj9NBIKxZ\niuX9Vy/jsYOdrJlfljBjLhFup4OlNSWc6BmLqg9qrNZX+HvLJY1UlXi4ef18Ht57jmuucXG6d4wX\nWnr529csZ3ltKfNKPVZ7kkS86eJFrJ5fxuJ5JdZn8cZNC9nbOsjhjmHWzi/n5vXzee9VS/nJi6e4\nemUNN62fcil7RRoUrAWxeF5J0oZus4HH5YjbzmCuY7mYjGCh3qxPf89UFJXFbsu1M9sWhMvp4NrV\ntUmVQyyfue0Cblqqy3/58nnsPquv0DdVgDoW052TyqC8qKqYhz907aSWJ6AP0gsqiwlrkgsXVbKm\nWv9XbqicPPlwOx2snq8P5KZr6vLl83jd+vm8I2YZ1FQxFYNdQdywrp43bFpo1Yq8ecsi+scCvNIZ\n5tvPtOByCO68djlCCN5+2WKuX5c8XlbkdlpV41euqGFdQzkfvWk1bzaKXK81LJ/P3HYB6xdU8MFf\n7eYDv9jFq10jCc+ZLp96YD/v+fH2rJ1vtkm32LBgLQjFzBFZN0C3IPT1IPQByxyDq0s9VnV6Lmsg\nZoJP3LKWpfNK+N6zJ7jpgvRmrNevrWNlXWnCtNJ0WFRdTPvgBJsaqxjrHeNofyBh7GrDwgpauket\nynshBPe899KMr72yvgwOd0UpiDtstR8A163W7/We/WMI0cb7r15uFVl+8tbErr14LK8t5c8fvQ6A\nt17ayIN72qw6oCK3k5+8/zK+19zCQ3vP8cFf7uaxj7wmbk+0dBgPhHhobzu+oEZL96jVpXmusv1k\nH594YD/ff/eWlI/JOwtCCHGrEOKYEKJFCPGp2ZZHMTXlNhfTRCDMiC8UFaR2O/WuoGaPpFymuM4E\nQgjecfkSnv3n67mwMT0LoqbMy9Mfb4rKSMoU0120eUkVNyxx8Z9v3cS6OEFqgA/fsJrvv2dL1tyu\nqywLIn62HeiW2u/vvobXNLpYUFnMBxIkBKTLwqpinv3n66PqQhoqi/jC7Rv5z7duoqV7lJ8ZmU3+\nUJg/H+yMu1KfpkmOD4Stor1YnjnajS+oH2fGUk70jHLT15/lM78/MGkRKDst3aPWevKgp//e+s3n\n+NmLp9K+32wgpeTLfz7Kmb5xPvfwwZSPyysLQgjhBL4D3Ay0Aa8IIf4gpTw8u5IpkuF1OfE4Hfxh\n7zm+s7WF8UCYt27RB06HQ++NJISwFMSSWXYxFQqmu2hzYxUnBwS3xNTr2Fk8rySrrr3bLlzAWCDE\nZQkqsE0qitzcsdFLU1NT1q6djJsuqOf6tXV886lXuXZ1LT/fdoZf7zjLHdcsj8ryO9M3xvt/+gqn\nen2wfRf/9Y7N3L55UdS5Hj3QQW2Zlw0LK/j97naa1tTx4V/vYSIY5r4dZ3n+eA+/vPNKltSUENYk\nH7t/L16Xg4/ctIa3/2AbI/4QD33wGjwuB+/+0XY6h3188U9H2Lioks2Lq/jh86f43a5W/vHG1bxx\n00I0CZ996AB7W4d4/cYGVoSndgeFwhrPHe/h6pW1UStIxvL88V72nB3k6pU1vHQi9bW+80pBAJcD\nLVLKkwBCiPuA2wGlIPKcimIXx7pGuHn9fP7m6mVcblQCN1aXMDyhz7TWzC9nWU1J0tRGReq8/bLF\n1Jd7WTyvmJMzfO1ij9PqSJBPCCH44ps28pbvbeMt33uJsUCYpTUl/OTFU9SUeVhUVUxIk3z9iWNM\nBMP83YUe9gyX8pkHD/DssR4OdwzzmtW1rF9YwdajPbx5yyKuWlHL3b/azdvveZnaMg8P/MPVjPiC\n3HnvTt5xzzZ+8J5L2Xqsm4f36u1H/rS/A03qcbc7732FgfEAJR4Xv/3AVXz8/n2858c7KPU66R0N\nUF/u5SP37eWXL5+lrMjFM0e7WddQzjeeepVyt6C//DT/v727D7KqruM4/v6wu7CLyAJCuDzEU2zK\ngwJq0IgmZIqkYsYomKSmg03SpI2a5uQ4zTRkVNOklaESpqZi5ogzKlqRT8WjgiwiD8oaT4uKKaA7\nwS7f/ji/ux6We3eXK3vP2fb7mrlzz/ntuXu/8z3nnu89D/f3Ky8rYWTfcvr36MyK6v/QtayYYRVd\nqT9gXLdgNU+u3s7plb2YO+OkhiKxZuuHzH56HV1LSzi+oiuPrtxCRXkp8y4/hWlzl/B2C/OZtgLR\nF9gSm98KjE0oFncYfnTuMDoWdWDSiGMP+gHYDycf3zCW8ZXjB3HFqYOydkLoDl/fbmVcOm5A0mGk\nTr/unXl45jim372E4X3LmX/FKVxy91LmLPqk+/TunUt44KqxvLvhVa746mjOu+Mlnlu3k+MrujL/\nn9UNw+ReMKovJ/TrxjUThjC4Zxe+Mrx3Qz9dD1w5lkvvXcp5d74EwJRRfRjRp5zZT69jztQT6du9\njBn3LuXUz/Vk9oUjqSgvY97lJ3PPi5vZX29MPO4znD28N/f9620eXPo2y6rf5/qzKpk1cSivb9/N\n1X94ueF2Xohuj68NfV31CcPDbvuglskjj+WpNTWcMecfHF1ajBGd0sp0FfTM2hpO6FfODyYdR2lJ\nEXdMH80Ts1qWS6WpC11JU4FJZnZVmJ8BjDWzWbFlZgIzAXr16nXSggULEom1OXv37qVLl3Re1PLY\n8uOx5Sep2PbVR7/HKe4g6g8Y79Z+sq8r7yTKitUQW22dUdIhWvbj/cbufUanIuhe2vRl2j37jOU1\ndWzbe4CplR0pKxa1dUZZ6FK/ts4oLTp0FMnGzIy9+w8eBG33nr3UduhM3QFYu6ue7R8dYGTPIvbs\nM9btqqfeYGSvIr7Ur4RlNXUs2/HJNZFjysT5QzpSVgwf7T90cLUJEyasNLPm71Iws9Q8gC8Ci2Lz\nNwM351q+srLS0mrx4sVJh5CTx5Yfjy0/Hlt+WjM2YIW1YJ+ctruYlgNDJQ2S1BGYBixMOCbnnGuX\nUnUNwszqJM0CFgFFwDwzW9vMy5xzzrWCVBUIADN7Cngq6Ticc669S9spJueccynhBcI551xWXiCc\nc85l5QXCOedcVl4gnHPOZZWqX1IfLkl7gPXNLpiMnsB7SQeRg8eWH48tPx5bfloztgFmlnus2SB1\nt7kepvXWkp+LJ0DSCo/t8Hls+fHY8uOxNc1PMTnnnMvKC4Rzzrms2nqBmJt0AE3w2PLjseXHY8uP\nx9aENn2R2jnnXOtp60cQzjnnWkmbLRCSJklaL2mTpJsSjqW/pMWSXpe0VtL3QvttkrZJWhUekxOK\nr1rSmhDDitDWQ9JzkjaG5+4FjunzsbyskrRb0rVJ5kzSPEnvSKqKtWXNkyK/Dtvfa5LGFDiuOZLe\nCO/9uKRuoX2gpNpY/u5qrbiaiC3nOpR0c8jZeklnJxDbI7G4qiWtCu2FzluufUbi29tBWjJoRNoe\nRF2BvwkMBjoCq4FhCcZTAYwJ00cDG4BhwG3A9SnIVzXQs1Hbz4CbwvRNwO0Jr88aYECSOQNOB8YA\nVc3lCZgMPA0IGAcsLXBcZwHFYfr2WFwD48sllLOs6zB8JlYDnYBB4TNcVMjYGv39F8CtCeUt1z4j\n8e0t/mirRxBfADaZ2Vtmtg94GJiSVDBmtsPMXgnTe4B1RONrp9kU4L4wfR9wQYKxfBl408xaOpZ6\nqzCzF4D3GzXnytMU4I8WWQJ0k1RRqLjM7Fkzy4wxuQTo1xrv3ZwcOctlCvCwmf3XzDYDm4g+ywWP\nTdEYoBcBD7XW+zeliX1G4ttbXFstEH2BLbH5raRkhyxpIDAaWBqaZoVDwnmFPo0TY8CzklYqGtMb\noLeZ7QjTNUDvZEIDopED4x/UNOQsI1ee0rQNfovo22XGIEmvSnpe0mkJxZRtHaYpZ6cBO81sY6wt\nkbw12mekantrqwUilSR1AR4DrjWz3cDvgCHAKGAH0SFtEsab2RjgHOAaSafH/2jRMWwit7MpGlr2\nfODR0JSWnB0iyTzlIukWoA54MDTtAD5rZqOB7wN/ktS1wGGldh3GTOfgLyWJ5C3LPqNBGra3tlog\ntgH9Y/P9QltiJJUQregHzewvAGa208zqzewAcDeteDjdFDPbFp7fAR4PcezMHKKG53eSiI2oaL1i\nZjtDjKnIWUyuPCW+DUq6HDgX+EbYmRBO3+wK0yuJzvNXFjKuJtZh4jkDkFQMXAg8kmlLIm/Z9hmk\nbHtrqwViOTBU0qDwDXQasDCpYML5zHuBdWb2y1h7/Bzh14Cqxq8tQGxHSTo6M010cbOKKF+XhcUu\nA54odGzBQd/k0pCzRnLlaSHwzXB3yTjgw9ipgVYnaRJwI3C+mX0ca+8lqShMDwaGAm8VKq7wvrnW\n4UJgmqROkgaF2JYVMrbgTOANM9uaaSh03nLtM0jb9laoq/ZH+kF0VX8DUaW/JeFYxhMdCr4GrAqP\nycD9wJrQvhCoSCC2wUR3jqwG1mZyBRwD/A3YCPwV6JFAbEcBu4DyWFtiOSMqVDuA/UTneK/MlSei\nu0l+E7a/NcDJBY5rE9E56cz2dldY9uthPa8CXgHOSyBnOdchcEvI2XrgnELHFtrnA99utGyh85Zr\nn5H49hZ/+C+pnXPOZdVWTzE555xrZV4gnHPOZeUFwjnnXFZeIJxzzmXlBcI551xWXiBcuyXpAkkm\n6bgmlukm6Tux+T6S/pzn+82XNDVH+zZJncJ8T0nV+byHc0eSFwjXnk0HXgrPhwi/uO0GNBQIM9tu\nZofs5I+AeqI+lZxLDS8Qrl0KfeCMJ/ph17RY+xmSXpS0EHgd+CkwJIwRMCeMG1AVli2S9HNJVaFj\nuu+G9lslLQ/tc8OvZpvzK+C6UJTicSq8b5WiMT0uPjIZcK55xc0v4tz/pSnAM2a2QdIuSSdZ1AcP\nRGMIjDCzzaGnzRFmNgoaet7MmEk0jsAoM6uT1CO032lmPw7L30/UX9KTzcTzb6KjmRmNlr2QqNO7\nE4GewHJJL1gBu/Vw7ZcfQbj2ajrROCKE5/hppmUWjVfQnDOB31sYl8HMMmMPTJC0VNIaYCIwvIUx\nzQZu4ODP5XjgIYs6v9sJPA+c0sL/59yn4kcQrt0J3/QnAiMlGdGIdibphrDIR5/if5cCvyXqK2eL\npNuA0pa81sw2KhoC86J839+5I8mPIFx7NBW438wGmNlAM+sPbCYaRKaxPURDQmbzHHB15rpBKDyZ\nYvBeuM5xuBe0fwJcH5t/Ebg4XO/oRTSMZhI9oLp2yAuEa4+mE42LEfcYWe5msmiMgJfDReI5jf58\nD9G1g9ckrQYuMbMPiMZAqAIWEXVN32JmtpaoN9GMx4l6/FwN/B240cxqAMLRhnOtxntzdc45l5Uf\nQTjnnMvKC4RzzrmsvEA455zLyguEc865rLxAOOecy8oLhHPOuay8QDjnnMvKC4Rzzrms/gf3W1RV\nmy8D0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10535cb10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = df['likes'].plot()\n",
    "fig.grid(True)\n",
    "plt.xlabel('Artical No.')\n",
    "plt.ylabel('# of Likes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f199310>"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CvA70SSltfUgbcJbePgs4DqCfTwBNlbTPYDAES0EYjAcxFwhX8uRSSgfYIISYB/wcWD3V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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f155510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = df.loc[:, ['likes','comments']][::-1].plot()\n",
    "#fig = dfrev.plot()\n",
    "fig.grid(True)\n",
    "plt.xlabel('Artical No.')\n",
    "plt.ylabel('Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x107f63e90>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+NJ1DA8aF7XpgYzg3dwBnh/IfAp8P218Afhi2zwZur1J8NwFnRhxf8X8npT5q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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10804b850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.scatter(df['likes'], df['comments'])\n",
    "plt.xlabel('# of Likes')\n",
    "plt.ylabel('# of Comments')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Coefficients: \\n', array([[ 0.77822024]]))\n",
      "('Intercept: \\n', array([ 13.41648952]))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/scipy/linalg/basic.py:1018: RuntimeWarning: internal gelsd driver lwork query error, required iwork dimension not returned. This is likely the result of LAPACK bug 0038, fixed in LAPACK 3.2.2 (released July 21, 2010). Falling back to 'gelss' driver.\n",
      "  warnings.warn(mesg, RuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1081cae10>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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45BF46KHg9UQ8ieCSSyolrErnZh7ENjyruZoo89SiLb7k4JWTm89Ti7ZEKCJj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\n4L1utffCQt7rVpdn3kI4r+3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Bk5y2Ae8A8U55LefxNuf5NhGKb6mzDzcAb3J8pFOl/5+U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\np7QnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108146c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "X = np.asarray(df['likes'])\n",
    "Y = np.asarray(df['comments'])\n",
    "regr.fit(X.reshape(-1,1),Y.reshape(-1,1) )\n",
    "\n",
    "print('Coefficients: \\n', regr.coef_)\n",
    "print('Intercept: \\n', regr.intercept_)\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.scatter(X.reshape(-1,1), Y.reshape(-1,1))\n",
    "plt.plot(X.reshape(-1,1), regr.predict(X.reshape(-1,1)), color='blue',\n",
    "         linewidth=3)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.text(20, 400, r'Comments = Likes * 0.778 + 13.416', fontsize=15)\n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('# of Likes')\n",
    "plt.ylabel('# of Comments')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No.</th>\n",
       "      <th>time</th>\n",
       "      <th>likes</th>\n",
       "      <th>comments</th>\n",
       "      <th>title</th>\n",
       "      <th>subtitle</th>\n",
       "      <th>title_len</th>\n",
       "      <th>subtitle_len</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>35</td>\n",
       "      <td>32</td>\n",
       "      <td>陌生而熟悉的味道，欢迎来到美国街机厅</td>\n",
       "      <td>这是一篇价值约 12.5 美金的街机自助餐。</td>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>55</td>\n",
       "      <td>16</td>\n",
       "      <td>缅怀素未谋面的郑问老师</td>\n",
       "      <td>很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。</td>\n",
       "      <td>33</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>39</td>\n",
       "      <td>23</td>\n",
       "      <td>16-BIT游戏漫谈（4）——魔界村外传：纹章篇</td>\n",
       "      <td>由路边杂鱼升格为主角的另类作品</td>\n",
       "      <td>58</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>46</td>\n",
       "      <td>90</td>\n",
       "      <td>悠悠八载街机路：执著、热情与精通</td>\n",
       "      <td>说说我的街机生涯，以及如何精通枪机游戏</td>\n",
       "      <td>48</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>39</td>\n",
       "      <td>44</td>\n",
       "      <td>三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘</td>\n",
       "      <td>我从来没想到CAPCOM爱僵尸会爱的如此深沉</td>\n",
       "      <td>63</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>14</td>\n",
       "      <td>60</td>\n",
       "      <td>火爆狂飙3：速度与对抗的巅峰</td>\n",
       "      <td>在13年前，娱乐向竞速游戏的巅峰出现了</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>294</td>\n",
       "      <td>80</td>\n",
       "      <td>《凯瑟琳》：性、生活与游戏底层的人性隐喻</td>\n",
       "      <td>正视自己的第一步，是了解欲望的来源在何处</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>45</td>\n",
       "      <td>33</td>\n",
       "      <td>那会儿想买电脑就是为了跟印第安纳琼斯去冒险</td>\n",
       "      <td>人有很多第一次，而冒险始终让人跃跃欲试。探索秘密的青春啊～～让人欲罢不能。</td>\n",
       "      <td>63</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2017-03-06</td>\n",
       "      <td>56</td>\n",
       "      <td>31</td>\n",
       "      <td>我真的喜欢游戏吗？</td>\n",
       "      <td>我想，这就是答案了~</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>2017-03-05</td>\n",
       "      <td>25</td>\n",
       "      <td>37</td>\n",
       "      <td>回顾FC时代的《仁王》——《不动明王传》</td>\n",
       "      <td>其实仔细想想，过去真的是有一些游戏难得没什么道理</td>\n",
       "      <td>56</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>37</td>\n",
       "      <td>30</td>\n",
       "      <td>《塞尔达传说》的这些广告，你都看过么？</td>\n",
       "      <td>《荒野之息》的广告，看塞尔达公主哭心里特难受</td>\n",
       "      <td>57</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>我和FC：保护那份最初的感动</td>\n",
       "      <td>当评价快乐的维度变多之后，快乐获取难度就随之增加。</td>\n",
       "      <td>38</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>47</td>\n",
       "      <td>70</td>\n",
       "      <td>16-BIT游戏漫谈（3）——超级忍</td>\n",
       "      <td>最好的忍者游戏之一</td>\n",
       "      <td>40</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2017-02-19</td>\n",
       "      <td>34</td>\n",
       "      <td>140</td>\n",
       "      <td>聊聊香港漫画改编的电影和游戏</td>\n",
       "      <td>一部老电影引发的怀旧情</td>\n",
       "      <td>42</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>34</td>\n",
       "      <td>71</td>\n",
       "      <td>记忆中的“三国题材”游戏</td>\n",
       "      <td>除了光荣的《三国志》和《割草无双》，其实还有很多好玩的三国游戏在等待着我们！</td>\n",
       "      <td>36</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>56</td>\n",
       "      <td>28</td>\n",
       "      <td>連仙水忍也為之羞澀：播音人黑盒子攻略錄影帶轉帶紀實</td>\n",
       "      <td>台灣最古老的電玩「實況」解說節目，與遙不可及的 Beta 年代</td>\n",
       "      <td>75</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>2017-02-14</td>\n",
       "      <td>18</td>\n",
       "      <td>49</td>\n",
       "      <td>网游考古系列：《最终兵器》</td>\n",
       "      <td>我多么希望这是一篇安利而不是悼词</td>\n",
       "      <td>39</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2017-02-12</td>\n",
       "      <td>26</td>\n",
       "      <td>42</td>\n",
       "      <td>网游考古系列：《疯狂坦克2》</td>\n",
       "      <td>炮，本能</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2017-02-07</td>\n",
       "      <td>45</td>\n",
       "      <td>69</td>\n",
       "      <td>网游考古系列：《沃土》</td>\n",
       "      <td>现实是生活，游戏中为何还要生活。</td>\n",
       "      <td>33</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>2017-02-07</td>\n",
       "      <td>123</td>\n",
       "      <td>225</td>\n",
       "      <td>我所看过与玩过的《生化危机》</td>\n",
       "      <td>可能是我见过最神奇的游戏系列，之一</td>\n",
       "      <td>42</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>19</td>\n",
       "      <td>41</td>\n",
       "      <td>我与游戏的二三事</td>\n",
       "      <td>从小到大，参与其中，乐在其中</td>\n",
       "      <td>24</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>75</td>\n",
       "      <td>58</td>\n",
       "      <td>回忆里的温暖角落——家中长辈们的游戏印记</td>\n",
       "      <td>致我最爱的亲人们</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>2017-02-04</td>\n",
       "      <td>43</td>\n",
       "      <td>40</td>\n",
       "      <td>我的暑假20XX：真红少年与热血兄贵</td>\n",
       "      <td>每一次少年们发现新大陆的时候，土坡上总有一群嚼着冰棍儿的大哥......</td>\n",
       "      <td>46</td>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>2017-02-03</td>\n",
       "      <td>49</td>\n",
       "      <td>54</td>\n",
       "      <td>网游考古系列：《魔力宝贝》</td>\n",
       "      <td>“魔力魔力，随心所欲”</td>\n",
       "      <td>39</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>35</td>\n",
       "      <td>32</td>\n",
       "      <td>陌生而熟悉的味道，欢迎来到美国街机厅</td>\n",
       "      <td>这是一篇价值约 12.5 美金的街机自助餐。</td>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>55</td>\n",
       "      <td>16</td>\n",
       "      <td>缅怀素未谋面的郑问老师</td>\n",
       "      <td>很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。</td>\n",
       "      <td>33</td>\n",
       "      <td>102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>39</td>\n",
       "      <td>23</td>\n",
       "      <td>16-BIT游戏漫谈（4）——魔界村外传：纹章篇</td>\n",
       "      <td>由路边杂鱼升格为主角的另类作品</td>\n",
       "      <td>58</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>46</td>\n",
       "      <td>90</td>\n",
       "      <td>悠悠八载街机路：执著、热情与精通</td>\n",
       "      <td>说说我的街机生涯，以及如何精通枪机游戏</td>\n",
       "      <td>48</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>39</td>\n",
       "      <td>44</td>\n",
       "      <td>三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘</td>\n",
       "      <td>我从来没想到CAPCOM爱僵尸会爱的如此深沉</td>\n",
       "      <td>63</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>14</td>\n",
       "      <td>60</td>\n",
       "      <td>火爆狂飙3：速度与对抗的巅峰</td>\n",
       "      <td>在13年前，娱乐向竞速游戏的巅峰出现了</td>\n",
       "      <td>40</td>\n",
       "      <td>53</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>2013-11-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>《ゲームになった映画たち 完全版》！~</td>\n",
       "      <td>电影改编游戏和游戏改编电影，一直都是大家关注和厌恶的话题，《Gameside》编辑部为此出版...</td>\n",
       "      <td>53</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>2013-10-29</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>《ダイナマイト刑事2》与海贼们的斗争！～</td>\n",
       "      <td>3D动作清版游戏我玩儿的最多的还是《ダイナマイト刑事2》！～</td>\n",
       "      <td>58</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>2013-10-28</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>神的孩子都喷火-《卡诺夫》！～</td>\n",
       "      <td>Data East公司的吉祥物比马里奥，索尼克那些看着霸道多了！～</td>\n",
       "      <td>43</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>2013-10-24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>怀古名作3D化之《青蛙过河3D》！～</td>\n",
       "      <td>我最爱3DS的一点就是，能玩到不少怀旧名作的重制版！～</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>2013-10-17</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>回到港产片吓哭你的时代-《灵幻道士》！～</td>\n",
       "      <td>看多了西洋僵尸，咱们也来点儿本土的吧！～</td>\n",
       "      <td>58</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>2013-10-15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>怪逼的《トリオ・ザ・パンチ》！~</td>\n",
       "      <td>Data East公司最怪的游戏当属《トリオ・ザ・パンチ》！～</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>2013-10-14</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>XBOX360首发作品：卡蜜欧—元素力量</td>\n",
       "      <td>《卡蜜欧—元素力量》是XBOX360的首发游戏之一，作为大名鼎鼎的RARE十年磨一剑的作品，...</td>\n",
       "      <td>46</td>\n",
       "      <td>297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>2013-10-14</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>我其实还是喜欢VICE CITY！～</td>\n",
       "      <td>能跟掌机上玩到GTA系列，以前一直觉得是件可望而不可即的美事儿！～</td>\n",
       "      <td>36</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>2013-10-11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>我这14年PM经历的流水账</td>\n",
       "      <td>我这14年PM经历的流水账</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>2013-10-10</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>初次接触Game Boy时所玩的游戏系列1！～</td>\n",
       "      <td>第一次玩的那盘GB盗版合卡里的小游戏，现在想起来都很难忘，那种乐趣是以往俄罗斯方块掌机所难以...</td>\n",
       "      <td>51</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>2013-10-08</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>黎明期的电子游戏-《铁板阵》！～</td>\n",
       "      <td>我的名字安藤杰尼斯便是音译自《铁板阵》里的母舰-Andor Genesis！～</td>\n",
       "      <td>46</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>2013-09-29</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>悲惨的国庆节与《Konami世界》！～</td>\n",
       "      <td>20世纪游戏小子的国庆节到底是什么样呢？</td>\n",
       "      <td>45</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>2013-09-28</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>进化！</td>\n",
       "      <td>进化！</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>2013-09-26</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>丧逼一家人--《とんでもクライシス!》！～</td>\n",
       "      <td>丧逼一家人的日常究竟是什么样呢？</td>\n",
       "      <td>57</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>201</td>\n",
       "      <td>2013-09-25</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>怀旧游戏迷们最后的纸媒阵地-GameSide</td>\n",
       "      <td>《GameSide》大概是怀旧游戏迷们最后的纸媒阵地了。</td>\n",
       "      <td>48</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>202</td>\n",
       "      <td>2013-09-24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DS-《美文字トレーニング》!~</td>\n",
       "      <td>没有智能手机的各种应用软件的时代，DS上总是有各种有意思的教育软件登场，真令人怀念！～</td>\n",
       "      <td>38</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>203</td>\n",
       "      <td>2013-09-23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>電気グルーヴ游戏大时代《グルーヴ地獄V》</td>\n",
       "      <td>与音乐家跨界合作的游戏中，具有KUSO味的肯定还得是《グルーヴ地獄V》！~</td>\n",
       "      <td>58</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>204</td>\n",
       "      <td>2013-09-16</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PS-《風のノータム》！～</td>\n",
       "      <td>乘坐热气球旅行的游戏会给我们带来治愈性的体验吗？？？</td>\n",
       "      <td>33</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>205</td>\n",
       "      <td>2013-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>ずんずん教の野望与朱莉安娜女郎!~</td>\n",
       "      <td>今天是周末，来聊点儿和大妞儿有关系的游戏话题吧！！！~</td>\n",
       "      <td>47</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>206</td>\n",
       "      <td>2013-09-12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>翘曲空间的放浪冒险---Arkanoid！～</td>\n",
       "      <td>《Arkanoid》大概属于那种能玩到世界末日的游戏。</td>\n",
       "      <td>44</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>207</td>\n",
       "      <td>2013-09-11</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>Famicom上的知名西游记系列！~</td>\n",
       "      <td>每年暑假电视台都会重播《西游记》电视剧。不过，以《西游记》为题材的游戏你玩过多少呢？</td>\n",
       "      <td>38</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>208</td>\n",
       "      <td>2013-09-09</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>涂鸦小子的今与昔-《Jet Set Radio》！</td>\n",
       "      <td>游戏机进化到光碟媒介之后,真正打动我心的,超不过10款.非要列出来的话,《Jet Set R...</td>\n",
       "      <td>47</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>209</td>\n",
       "      <td>2013-09-06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>WS-たねをまく鳥！~</td>\n",
       "      <td>Wonder Swan算是个设计独特的掌机。可以横着玩也可以竖着玩，但是发售游戏阵容中，实际...</td>\n",
       "      <td>25</td>\n",
       "      <td>248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>210</td>\n",
       "      <td>2013-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>平民小英雄-パーマン！～</td>\n",
       "      <td>也来点漫画改编的游戏系列吧，就先从启蒙的 藤子.F.不二雄和藤子.A.不二雄的作品说起！~</td>\n",
       "      <td>34</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>211</td>\n",
       "      <td>2013-09-03</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>西单台球儿风云录！~</td>\n",
       "      <td>好多时候儿，1盘游戏摆我面前，想的并不是游戏的内容如何精彩，而是当年接触游戏时的一些生活片段...</td>\n",
       "      <td>28</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>212</td>\n",
       "      <td>2013-09-02</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>《いっき》-农夫起义的豪快行进曲！~</td>\n",
       "      <td>Sun-Soft公司现在能拿的出手的恐怕也只有《上海》系列了。而最打动我的还是《いっき》！！~</td>\n",
       "      <td>50</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>213</td>\n",
       "      <td>2013-08-30</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>公路上的轰鸣-《暴走卡车》回顾！~</td>\n",
       "      <td>日式艺术卡车游戏和历史背景回顾！~</td>\n",
       "      <td>47</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>214</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>PS1的冷门游戏合集-セロファーンズ ！</td>\n",
       "      <td>PS1时代被遗忘的冷门街机游戏合集-《セロファーンズ 》！~</td>\n",
       "      <td>50</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>215</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>3DS的《热血硬派くにおくん》系列的前世</td>\n",
       "      <td>热血硬派くにおくん</td>\n",
       "      <td>54</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>216</td>\n",
       "      <td>2013-08-16</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>To Games——我的快乐时代</td>\n",
       "      <td>怀旧  长文</td>\n",
       "      <td>32</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>216 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     No.        time  likes  comments                      title  \\\n",
       "0      1  2017-04-02     35        32         陌生而熟悉的味道，欢迎来到美国街机厅   \n",
       "1      2  2017-03-30     55        16                缅怀素未谋面的郑问老师   \n",
       "2      3  2017-03-27     39        23   16-BIT游戏漫谈（4）——魔界村外传：纹章篇   \n",
       "3      4  2017-03-18     46        90           悠悠八载街机路：执著、热情与精通   \n",
       "4      5  2017-03-17     39        44  三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘   \n",
       "5      6  2017-03-13     14        60             火爆狂飙3：速度与对抗的巅峰   \n",
       "6      7  2017-03-13    294        80       《凯瑟琳》：性、生活与游戏底层的人性隐喻   \n",
       "7      8  2017-03-09     45        33      那会儿想买电脑就是为了跟印第安纳琼斯去冒险   \n",
       "8      9  2017-03-06     56        31                  我真的喜欢游戏吗？   \n",
       "9     10  2017-03-05     25        37       回顾FC时代的《仁王》——《不动明王传》   \n",
       "10    11  2017-03-02     37        30        《塞尔达传说》的这些广告，你都看过么？   \n",
       "11    12  2017-02-23     18        20             我和FC：保护那份最初的感动   \n",
       "12    13  2017-02-22     47        70         16-BIT游戏漫谈（3）——超级忍   \n",
       "13    14  2017-02-19     34       140             聊聊香港漫画改编的电影和游戏   \n",
       "14    15  2017-02-16     34        71               记忆中的“三国题材”游戏   \n",
       "15    16  2017-02-15     56        28  連仙水忍也為之羞澀：播音人黑盒子攻略錄影帶轉帶紀實   \n",
       "16    17  2017-02-14     18        49              网游考古系列：《最终兵器》   \n",
       "17    18  2017-02-12     26        42             网游考古系列：《疯狂坦克2》   \n",
       "18    19  2017-02-07     45        69                网游考古系列：《沃土》   \n",
       "19    20  2017-02-07    123       225             我所看过与玩过的《生化危机》   \n",
       "20    21  2017-02-05     19        41                   我与游戏的二三事   \n",
       "21    22  2017-02-05     75        58       回忆里的温暖角落——家中长辈们的游戏印记   \n",
       "22    23  2017-02-04     43        40         我的暑假20XX：真红少年与热血兄贵   \n",
       "23    24  2017-02-03     49        54              网游考古系列：《魔力宝贝》   \n",
       "24    25  2017-04-02     35        32         陌生而熟悉的味道，欢迎来到美国街机厅   \n",
       "25    26  2017-03-30     55        16                缅怀素未谋面的郑问老师   \n",
       "26    27  2017-03-27     39        23   16-BIT游戏漫谈（4）——魔界村外传：纹章篇   \n",
       "27    28  2017-03-18     46        90           悠悠八载街机路：执著、热情与精通   \n",
       "28    29  2017-03-17     39        44  三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘   \n",
       "29    30  2017-03-13     14        60             火爆狂飙3：速度与对抗的巅峰   \n",
       "..   ...         ...    ...       ...                        ...   \n",
       "186  187  2013-11-05      1         0        《ゲームになった映画たち 完全版》！~   \n",
       "187  188  2013-10-29      0         1       《ダイナマイト刑事2》与海贼们的斗争！～   \n",
       "188  189  2013-10-28      4         8            神的孩子都喷火-《卡诺夫》！～   \n",
       "189  190  2013-10-24      1         1         怀古名作3D化之《青蛙过河3D》！～   \n",
       "190  191  2013-10-17      5         3       回到港产片吓哭你的时代-《灵幻道士》！～   \n",
       "191  192  2013-10-15      1         1           怪逼的《トリオ・ザ・パンチ》！~   \n",
       "192  193  2013-10-14      3         1       XBOX360首发作品：卡蜜欧—元素力量   \n",
       "193  194  2013-10-14      6         6         我其实还是喜欢VICE CITY！～   \n",
       "194  195  2013-10-11      2         0              我这14年PM经历的流水账   \n",
       "195  196  2013-10-10      2         4    初次接触Game Boy时所玩的游戏系列1！～   \n",
       "196  197  2013-10-08      4         6           黎明期的电子游戏-《铁板阵》！～   \n",
       "197  198  2013-09-29      2         6        悲惨的国庆节与《Konami世界》！～   \n",
       "198  199  2013-09-28      1         5                        进化！   \n",
       "199  200  2013-09-26      4         7      丧逼一家人--《とんでもクライシス!》！～   \n",
       "200  201  2013-09-25      3         6     怀旧游戏迷们最后的纸媒阵地-GameSide   \n",
       "201  202  2013-09-24      1         0           DS-《美文字トレーニング》!~   \n",
       "202  203  2013-09-23      1         0       電気グルーヴ游戏大时代《グルーヴ地獄V》   \n",
       "203  204  2013-09-16      0         1              PS-《風のノータム》！～   \n",
       "204  205  2013-09-13      1         1          ずんずん教の野望与朱莉安娜女郎!~   \n",
       "205  206  2013-09-12      0         2     翘曲空间的放浪冒险---Arkanoid！～   \n",
       "206  207  2013-09-11      0         7         Famicom上的知名西游记系列！~   \n",
       "207  208  2013-09-09      3         4  涂鸦小子的今与昔-《Jet Set Radio》！   \n",
       "208  209  2013-09-06      0         0                WS-たねをまく鳥！~   \n",
       "209  210  2013-09-05      0         3               平民小英雄-パーマン！～   \n",
       "210  211  2013-09-03      0         1                 西单台球儿风云录！~   \n",
       "211  212  2013-09-02      2         6         《いっき》-农夫起义的豪快行进曲！~   \n",
       "212  213  2013-08-30      1         3          公路上的轰鸣-《暴走卡车》回顾！~   \n",
       "213  214  2013-08-29      2         5       PS1的冷门游戏合集-セロファーンズ ！   \n",
       "214  215  2013-08-29      8        13       3DS的《热血硬派くにおくん》系列的前世   \n",
       "215  216  2013-08-16      3         8           To Games——我的快乐时代   \n",
       "\n",
       "                                              subtitle  title_len  \\\n",
       "0                               这是一篇价值约 12.5 美金的街机自助餐。         54   \n",
       "1                   很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。         33   \n",
       "2                                      由路边杂鱼升格为主角的另类作品         58   \n",
       "3                                  说说我的街机生涯，以及如何精通枪机游戏         48   \n",
       "4                               我从来没想到CAPCOM爱僵尸会爱的如此深沉         63   \n",
       "5                                  在13年前，娱乐向竞速游戏的巅峰出现了         40   \n",
       "6                                 正视自己的第一步，是了解欲望的来源在何处         60   \n",
       "7                人有很多第一次，而冒险始终让人跃跃欲试。探索秘密的青春啊～～让人欲罢不能。         63   \n",
       "8                                           我想，这就是答案了~         27   \n",
       "9                             其实仔细想想，过去真的是有一些游戏难得没什么道理         56   \n",
       "10                              《荒野之息》的广告，看塞尔达公主哭心里特难受         57   \n",
       "11                           当评价快乐的维度变多之后，快乐获取难度就随之增加。         38   \n",
       "12                                           最好的忍者游戏之一         40   \n",
       "13                                         一部老电影引发的怀旧情         42   \n",
       "14              除了光荣的《三国志》和《割草无双》，其实还有很多好玩的三国游戏在等待着我们！         36   \n",
       "15                     台灣最古老的電玩「實況」解說節目，與遙不可及的 Beta 年代         75   \n",
       "16                                    我多么希望这是一篇安利而不是悼词         39   \n",
       "17                                                炮，本能         40   \n",
       "18                                    现实是生活，游戏中为何还要生活。         33   \n",
       "19                                   可能是我见过最神奇的游戏系列，之一         42   \n",
       "20                                      从小到大，参与其中，乐在其中         24   \n",
       "21                                            致我最爱的亲人们         60   \n",
       "22                每一次少年们发现新大陆的时候，土坡上总有一群嚼着冰棍儿的大哥......         46   \n",
       "23                                         “魔力魔力，随心所欲”         39   \n",
       "24                              这是一篇价值约 12.5 美金的街机自助餐。         54   \n",
       "25                  很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。         33   \n",
       "26                                     由路边杂鱼升格为主角的另类作品         58   \n",
       "27                                 说说我的街机生涯，以及如何精通枪机游戏         48   \n",
       "28                              我从来没想到CAPCOM爱僵尸会爱的如此深沉         63   \n",
       "29                                 在13年前，娱乐向竞速游戏的巅峰出现了         40   \n",
       "..                                                 ...        ...   \n",
       "186  电影改编游戏和游戏改编电影，一直都是大家关注和厌恶的话题，《Gameside》编辑部为此出版...         53   \n",
       "187                     3D动作清版游戏我玩儿的最多的还是《ダイナマイト刑事2》！～         58   \n",
       "188                  Data East公司的吉祥物比马里奥，索尼克那些看着霸道多了！～         43   \n",
       "189                        我最爱3DS的一点就是，能玩到不少怀旧名作的重制版！～         46   \n",
       "190                               看多了西洋僵尸，咱们也来点儿本土的吧！～         58   \n",
       "191                    Data East公司最怪的游戏当属《トリオ・ザ・パンチ》！～         46   \n",
       "192  《卡蜜欧—元素力量》是XBOX360的首发游戏之一，作为大名鼎鼎的RARE十年磨一剑的作品，...         46   \n",
       "193                  能跟掌机上玩到GTA系列，以前一直觉得是件可望而不可即的美事儿！～         36   \n",
       "194                                      我这14年PM经历的流水账         31   \n",
       "195  第一次玩的那盘GB盗版合卡里的小游戏，现在想起来都很难忘，那种乐趣是以往俄罗斯方块掌机所难以...         51   \n",
       "196            我的名字安藤杰尼斯便是音译自《铁板阵》里的母舰-Andor Genesis！～         46   \n",
       "197                               20世纪游戏小子的国庆节到底是什么样呢？         45   \n",
       "198                                                进化！          9   \n",
       "199                                   丧逼一家人的日常究竟是什么样呢？         57   \n",
       "200                       《GameSide》大概是怀旧游戏迷们最后的纸媒阵地了。         48   \n",
       "201        没有智能手机的各种应用软件的时代，DS上总是有各种有意思的教育软件登场，真令人怀念！～         38   \n",
       "202              与音乐家跨界合作的游戏中，具有KUSO味的肯定还得是《グルーヴ地獄V》！~         58   \n",
       "203                         乘坐热气球旅行的游戏会给我们带来治愈性的体验吗？？？         33   \n",
       "204                        今天是周末，来聊点儿和大妞儿有关系的游戏话题吧！！！~         47   \n",
       "205                        《Arkanoid》大概属于那种能玩到世界末日的游戏。         44   \n",
       "206         每年暑假电视台都会重播《西游记》电视剧。不过，以《西游记》为题材的游戏你玩过多少呢？         38   \n",
       "207  游戏机进化到光碟媒介之后,真正打动我心的,超不过10款.非要列出来的话,《Jet Set R...         47   \n",
       "208  Wonder Swan算是个设计独特的掌机。可以横着玩也可以竖着玩，但是发售游戏阵容中，实际...         25   \n",
       "209      也来点漫画改编的游戏系列吧，就先从启蒙的 藤子.F.不二雄和藤子.A.不二雄的作品说起！~         34   \n",
       "210  好多时候儿，1盘游戏摆我面前，想的并不是游戏的内容如何精彩，而是当年接触游戏时的一些生活片段...         28   \n",
       "211    Sun-Soft公司现在能拿的出手的恐怕也只有《上海》系列了。而最打动我的还是《いっき》！！~         50   \n",
       "212                                  日式艺术卡车游戏和历史背景回顾！~         47   \n",
       "213                     PS1时代被遗忘的冷门街机游戏合集-《セロファーンズ 》！~         50   \n",
       "214                                          热血硬派くにおくん         54   \n",
       "215                                             怀旧  长文         32   \n",
       "\n",
       "     subtitle_len  \n",
       "0              54  \n",
       "1             102  \n",
       "2              45  \n",
       "3              57  \n",
       "4              54  \n",
       "5              53  \n",
       "6              60  \n",
       "7             111  \n",
       "8              28  \n",
       "9              72  \n",
       "10             66  \n",
       "11             75  \n",
       "12             27  \n",
       "13             33  \n",
       "14            114  \n",
       "15             81  \n",
       "16             48  \n",
       "17             12  \n",
       "18             48  \n",
       "19             51  \n",
       "20             42  \n",
       "21             24  \n",
       "22             96  \n",
       "23             33  \n",
       "24             54  \n",
       "25            102  \n",
       "26             45  \n",
       "27             57  \n",
       "28             54  \n",
       "29             53  \n",
       "..            ...  \n",
       "186           185  \n",
       "187            84  \n",
       "188            81  \n",
       "189            75  \n",
       "190            60  \n",
       "191            75  \n",
       "192           297  \n",
       "193            93  \n",
       "194            31  \n",
       "195           149  \n",
       "196            89  \n",
       "197            56  \n",
       "198             9  \n",
       "199            48  \n",
       "200            68  \n",
       "201           125  \n",
       "202            99  \n",
       "203            78  \n",
       "204            79  \n",
       "205            65  \n",
       "206           126  \n",
       "207           132  \n",
       "208           248  \n",
       "209           119  \n",
       "210           152  \n",
       "211           123  \n",
       "212            49  \n",
       "213            78  \n",
       "214            27  \n",
       "215            14  \n",
       "\n",
       "[216 rows x 8 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['title_len'] = df['title'].str.len()\n",
    "df['subtitle_len'] = df['subtitle'].str.len()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: 0.746943193311\n",
      "Intercept: 3.07276870693\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10a8a8890>"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IxcXFCV1fNCzG2LAYYyMdYlRNjzhjGSOwTD3sw4O2QajqcufvwroP4P+ESzwi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\n+/4ExJNOEn1Ve8IThIi0AJq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4LZViFJF84FdAH1Xtju/WB1eRjO+kqtojyAPoCKwOeL0W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\nd3xVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109a5d150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "X = np.asarray(df['title_len'])\n",
    "Y = np.asarray(df['likes'])\n",
    "regr.fit(X.reshape(-1,1),Y.reshape(-1,1) )\n",
    "\n",
    "print('Coefficients: {}'.format(regr.coef_[0][0]))\n",
    "print('Intercept: {}\\n'.format(regr.intercept_[0]))\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.scatter(X.reshape(-1,1), Y.reshape(-1,1))\n",
    "plt.plot(X.reshape(-1,1), regr.predict(X.reshape(-1,1)), color='blue',\n",
    "         linewidth=3)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.text(20, 300, r'Likes = Title_len * {0:.2f} + {1:.2f}'.format(regr.coef_[0][0], regr.intercept_[0]), fontsize=15)\n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('Title_len')\n",
    "plt.ylabel('# of Likes')\n",
    "plt.title('# of Likes Vs Title_len')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: 0.631896376303\n",
      "Intercept: 13.6256900347\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10a693a90>"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jjHFlCcIYY4wrSxDGGGNcWYIwxhjjKmqCEJGOIlLbed5fRP4gIrnJD80YY0w6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\np7TCPDv2ldJ+wtyENYON5b7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UJYzbqbJbnXMsp7rR1lnZ6ckQrb7XS0x9Ozb2tK1wnafi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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108e16f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "X = np.asarray(df['title_len'])\n",
    "Y = np.asarray(df['comments'])\n",
    "regr.fit(X.reshape(-1,1),Y.reshape(-1,1) )\n",
    "\n",
    "print('Coefficients: {}'.format(regr.coef_[0][0]))\n",
    "print('Intercept: {}\\n'.format(regr.intercept_[0]))\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.scatter(X.reshape(-1,1), Y.reshape(-1,1))\n",
    "plt.plot(X.reshape(-1,1), regr.predict(X.reshape(-1,1)), color='blue',\n",
    "         linewidth=3)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.text(10, 400, r'Comments = Title_len * {0:.2f} + {0:.2f}'.format(regr.coef_[0][0], regr.intercept_[0]), fontsize=15)\n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('Title_len')\n",
    "plt.ylabel('# of Comments')\n",
    "plt.title('# of Comments Vs Title_len')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: -0.113017290307\n",
      "Intercept: 43.2025920324\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x109886350>"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EmgBJqrrXvaraRFHuygLGz1lNcYlzz6SCwmLGz1kNYEHCGBMT4XQxzRGRBqq6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\nHTA3zmWKt7nAaPf5aJz+d1/6KHfGTj9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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1097bf1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "X = np.asarray(df['subtitle_len'])\n",
    "Y = np.asarray(df['likes'])\n",
    "regr.fit(X.reshape(-1,1),Y.reshape(-1,1) )\n",
    "\n",
    "print('Coefficients: {}'.format(regr.coef_[0][0]))\n",
    "print('Intercept: {}\\n'.format(regr.intercept_[0]))\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.scatter(X.reshape(-1,1), Y.reshape(-1,1))\n",
    "plt.plot(X.reshape(-1,1), regr.predict(X.reshape(-1,1)), color='blue',\n",
    "         linewidth=3)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.text(20, 300, r'Likes = SubTitle_len * {0:.2f} + {0:.2f}'.format(regr.coef_[0][0], regr.intercept_[0]), fontsize=15)\n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('SubTitle_len')\n",
    "plt.ylabel('# of Likes')\n",
    "plt.title('# of Likes Vs SubTitle_len')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients: -0.123250617127\n",
      "Intercept: 49.5127492917\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x109b1c710>"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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B/W76w+52xhhjkiTsFYSqjqlIxqqqQIH7Ns1dFBiAc38FwDPA3cDjwEXua4BX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\nAcIYY4wnCxDGGGM8/X8BuoYIq57/UwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108f32250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "# Create linear regression object\n",
    "regr = linear_model.LinearRegression()\n",
    "\n",
    "# Train the model using the training sets\n",
    "X = np.asarray(df['subtitle_len'])\n",
    "Y = np.asarray(df['comments'])\n",
    "regr.fit(X.reshape(-1,1),Y.reshape(-1,1) )\n",
    "\n",
    "print('Coefficients: {}'.format(regr.coef_[0][0]))\n",
    "print('Intercept: {}\\n'.format(regr.intercept_[0]))\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.scatter(X.reshape(-1,1), Y.reshape(-1,1))\n",
    "plt.plot(X.reshape(-1,1), regr.predict(X.reshape(-1,1)), color='blue',\n",
    "         linewidth=3)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.text(20, 400, r'Comments = SubTitle_len * {0:.2f} + {0:.2f}'.format(regr.coef_[0][0], regr.intercept_[0]), fontsize=15)\n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('SubTitle_len')\n",
    "plt.ylabel('# of Comments')\n",
    "plt.title('# of Comments Vs SubTitle_len')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## article number group by years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2015', '2014', '2017', '2016', '2013']"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['year'] = df['time'].str[0:4]\n",
    "g1 = df.groupby(['year'])\n",
    "g1.groups.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[33, 14, 33, 72, 64]"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g1.count()['time'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2013', '2014', '2015', '2016', '2017']"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g1.count()['time'].index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10bd35590>"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i8h+puVdqa2tbHhEt1ZYb6BjBoWSjju7R6zjB7sDEag1LOgXojIjlklqrh/xfRcQiYBFA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10bc8c150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g1.count()['time'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g1.count()['time'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of articles')\n",
    "plt.title('# of Article Vs Year')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# article number group by month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2014-04',\n",
       " '2014-06',\n",
       " '2014-03',\n",
       " '2014-02',\n",
       " '2013-08',\n",
       " '2013-09',\n",
       " '2015-11',\n",
       " '2015-10',\n",
       " '2015-12',\n",
       " '2016-10',\n",
       " '2016-11',\n",
       " '2016-12',\n",
       " '2015-06',\n",
       " '2015-07',\n",
       " '2015-04',\n",
       " '2015-05',\n",
       " '2015-03',\n",
       " '2015-08',\n",
       " '2015-09',\n",
       " '2013-12',\n",
       " '2013-11',\n",
       " '2013-10',\n",
       " '2017-01',\n",
       " '2017-02',\n",
       " '2017-03',\n",
       " '2017-04',\n",
       " '2016-07',\n",
       " '2016-06',\n",
       " '2016-05',\n",
       " '2016-04',\n",
       " '2016-03',\n",
       " '2016-02',\n",
       " '2016-01',\n",
       " '2016-09',\n",
       " '2016-08']"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['month'] = df['time'].str[0:7]\n",
    "g2 = df.groupby(['month'])\n",
    "g2.groups.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[4,\n",
       " 15,\n",
       " 10,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 1,\n",
       " 3,\n",
       " 3,\n",
       " 7,\n",
       " 1,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 10,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 6,\n",
       " 9,\n",
       " 15,\n",
       " 12,\n",
       " 30,\n",
       " 20,\n",
       " 2]"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g2.count()['time'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2013-08',\n",
       " '2013-09',\n",
       " '2013-10',\n",
       " '2013-11',\n",
       " '2013-12',\n",
       " '2014-02',\n",
       " '2014-03',\n",
       " '2014-04',\n",
       " '2014-06',\n",
       " '2015-03',\n",
       " '2015-04',\n",
       " '2015-05',\n",
       " '2015-06',\n",
       " '2015-07',\n",
       " '2015-08',\n",
       " '2015-09',\n",
       " '2015-10',\n",
       " '2015-11',\n",
       " '2015-12',\n",
       " '2016-01',\n",
       " '2016-02',\n",
       " '2016-03',\n",
       " '2016-04',\n",
       " '2016-05',\n",
       " '2016-06',\n",
       " '2016-07',\n",
       " '2016-08',\n",
       " '2016-09',\n",
       " '2016-10',\n",
       " '2016-11',\n",
       " '2016-12',\n",
       " '2017-01',\n",
       " '2017-02',\n",
       " '2017-03',\n",
       " '2017-04']"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g2.count()['time'].index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No.</th>\n",
       "      <th>time</th>\n",
       "      <th>likes</th>\n",
       "      <th>comments</th>\n",
       "      <th>title</th>\n",
       "      <th>subtitle</th>\n",
       "      <th>title_len</th>\n",
       "      <th>subtitle_len</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         No.  time  likes  comments  title  subtitle  title_len  subtitle_len  \\\n",
       "month                                                                           \n",
       "2013-08    4     4      4         4      4         4          4             4   \n",
       "2013-09   15    15     15        15     15        15         15            15   \n",
       "2013-10   10    10     10        10     10        10         10            10   \n",
       "2013-11    3     3      3         3      3         3          3             3   \n",
       "2013-12    1     1      1         1      1         1          1             1   \n",
       "2014-02    5     5      5         5      5         5          5             5   \n",
       "2014-03    2     2      2         2      2         2          2             2   \n",
       "2014-04    5     5      5         5      5         5          5             5   \n",
       "2014-06    2     2      2         2      2         2          2             2   \n",
       "2015-03    2     2      2         2      2         2          2             2   \n",
       "2015-04    5     5      5         5      5         5          5             5   \n",
       "2015-05    1     1      1         1      1         1          1             1   \n",
       "2015-06    3     3      3         3      3         3          3             3   \n",
       "2015-07    3     3      3         3      3         3          3             3   \n",
       "2015-08    7     7      7         7      7         7          7             7   \n",
       "2015-09    1     1      1         1      1         1          1             1   \n",
       "2015-10    4     4      4         4      4         4          4             4   \n",
       "2015-11    2     2      2         2      2         2          2             2   \n",
       "2015-12    5     5      5         5      5         5          5             5   \n",
       "2016-01    5     5      5         5      5         5          5             5   \n",
       "2016-02    2     2      2         2      2         2          2             2   \n",
       "2016-03    6     6      6         6      6         6          6             6   \n",
       "2016-04    3     3      3         3      3         3          3             3   \n",
       "2016-05   10    10     10        10     10        10         10            10   \n",
       "2016-06    3     3      3         3      3         3          3             3   \n",
       "2016-07    5     5      5         5      5         5          5             5   \n",
       "2016-08    2     2      2         2      2         2          2             2   \n",
       "2016-09    6     6      6         6      6         6          6             6   \n",
       "2016-10    6     6      6         6      6         6          6             6   \n",
       "2016-11    9     9      9         9      9         9          9             9   \n",
       "2016-12   15    15     15        15     15        15         15            15   \n",
       "2017-01   12    12     12        12     12        12         12            12   \n",
       "2017-02   30    30     30        30     30        30         30            30   \n",
       "2017-03   20    20     20        20     20        20         20            20   \n",
       "2017-04    2     2      2         2      2         2          2             2   \n",
       "\n",
       "         year  \n",
       "month          \n",
       "2013-08     4  \n",
       "2013-09    15  \n",
       "2013-10    10  \n",
       "2013-11     3  \n",
       "2013-12     1  \n",
       "2014-02     5  \n",
       "2014-03     2  \n",
       "2014-04     5  \n",
       "2014-06     2  \n",
       "2015-03     2  \n",
       "2015-04     5  \n",
       "2015-05     1  \n",
       "2015-06     3  \n",
       "2015-07     3  \n",
       "2015-08     7  \n",
       "2015-09     1  \n",
       "2015-10     4  \n",
       "2015-11     2  \n",
       "2015-12     5  \n",
       "2016-01     5  \n",
       "2016-02     2  \n",
       "2016-03     6  \n",
       "2016-04     3  \n",
       "2016-05    10  \n",
       "2016-06     3  \n",
       "2016-07     5  \n",
       "2016-08     2  \n",
       "2016-09     6  \n",
       "2016-10     6  \n",
       "2016-11     9  \n",
       "2016-12    15  \n",
       "2017-01    12  \n",
       "2017-02    30  \n",
       "2017-03    20  \n",
       "2017-04     2  "
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g2.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f445ad0>"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j6F+p2Gfc/YaBhy0iIoOl5g/KzOwHxNNGP0w8ffStwO511H0RcEyV/ue4+0HppSQgIjLE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\niJScEoGISMn9H4Gm+87p4G/SAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cb3a7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g2.count()['time'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g2.count()['time'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of articles')\n",
    "plt.title('# of Article Vs Month')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# likes and comments groupby year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['year'] = df['time'].str[0:4]\n",
    "g3 = df.groupby(['year'])\n",
    "g3sum = g3.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year\n",
       "2013      74\n",
       "2014      39\n",
       "2015     780\n",
       "2016    3380\n",
       "2017    3347\n",
       "Name: likes, dtype: int64"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g3sum['likes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10b2885d0>"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CYEZ6PgO4cZDj7C1pTHq+O3Ac8HD9I66veuUfERdExMSI2J9iyv6biPhwCSHX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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b15de50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g3sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g3sum['likes'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of likes')\n",
    "plt.title('# of Likes Vs Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10bf32890>"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4Ib1GAA09yF7SSGA+sCPwnbSeZRGxNs3yKjCpj2VnAjMB2tra6OzsbKTpUnV1dQ3p+IpW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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10bddcc10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "articlecount = g1.count()['time'].tolist()\n",
    "\n",
    "objects = g3sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlelikes = g3sum['likes'].tolist()\n",
    "\n",
    "div = [ai/bi for ai,bi in zip(articlelikes,articlecount)] \n",
    "    \n",
    "plt.bar(y_pos, div, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of likes per article')\n",
    "plt.title('# of Likes per article Vs Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10b36d790>"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JXBURv5N0L3CtpFOBp4Dpqf8C4BigDXgVOKX2IZuZWbeaF46IeAJ4Xy/tLwKH\n99IewGk1CM3MzCrQSJfjmpnZEODCYWZmubhwmJlZLi4cZmaWiwuHmZnl4sJhZma5uHCYmVkuLhxm\nZpaLC4eZmeXiwmFmZrm4cJiZWS4uHGZmlosLh5mZ5VKvJwA2tNo8Ca2r8HG+ckTxTwIzs+HHexxm\nZpaLC4eZmeXiwmFmZrkMmcIhaaqkRyW1STqn3vGYmQ1XQ+LkuKQRwMXAEcBq4F5J8yNieX0j2/Js\nKRcGgC8OMCvKUNnjmAK0RcQTEfEaMA+YVueYzMyGJUVEvWMYkKRPAlMj4u/T/InAgRFxelmfmcDM\nNLsP8GjNA81nN+CFegdRJ8M5dxje+Q/n3KHx898rInYfqNOQOFRViYiYDcyudxyVkrQ4IlrqHUc9\nDOfcYXjnP5xzhy0n/6FyqKodGF82Py61mZlZjQ2VwnEvMEnSRElbA8cD8+sck5nZsDQkDlVFxEZJ\npwO3ACOAORGxrM5hba4hc1itAMM5dxje+Q/n3GELyX9InBw3M7PGMVQOVZmZWYNw4TAzs1xcOKpE\n0nhJt0taLmmZpDNS+y6SFkpamV53Tu3vkvRHSV2S/rFsO6Ml3SPpgbSd79YrpzyqlX/Z9kZIul/S\nzbXOJa9q5i7pSUkPSVoqaXE98smjyrmPkXS9pEckrZB0cD1yyqOK/9/vkz7z7mmDpDPrlddAfI6j\nSiSNBcZGxH2SdgCWAMcBJwNrI+IH6R5bO0fE2ZL2APZKfdZFxI/SdgRsFxEdkkYBdwJnRMRddUir\nYtXKv2x7XwVagB0j4tha5pJXNXOX9CTQEhGN/COxN1U597nA7yPi0nT15NsiYn2tc8qj2v/dp22O\nIPu5wYER8VStcsnDexxVEhHPRsR96f3LwAqgmezWKHNTt7lk/8EQEWsi4l7g9R7biYjoSLOj0tTw\n1b1a+QNIGgd8BLi0BqFvtmrmPtRUK3dJOwEfAi5L/V5r9KIBhX32hwOPN2rRABeOQkiaAOwP3A00\nRcSzadFzQFMF64+QtBRYAyyMiLsLCrUQm5s/8BPg68CmIuIrUhVyD+C/JS1RdhudIWMzc58I/D/g\nl+kQ5aWStisq1iJU4bPvdjxwdVWDqzIXjiqTtD1wA3BmRGwoXxbZccEB9x4i4o2I2I/sF/JTJL2n\nkGALsLn5SzoWWBMRS4qLshjV+OyBD0bEAcDRwGmSPlT9SKuvCrmPBA4ALomI/YFXgCHz+IQqffak\nQ3QfA667vQ6dAAACy0lEQVSrepBV5MJRRemcxA3AryLi16n5+XQctPt46JpKt5d21W8HplY71iJU\nKf9DgI+lY/3zgMMk/WdBIVdNtT77iGhPr2uAG8nuDN3QqpT7amB12d719WSFpOFV+f/7o4H7IuL5\n6kdaPS4cVZJOal8GrIiIC8sWzQdmpPczgJsG2M7uksak99uSPYPkkepHXF3Vyj8izo2IcRExgWyX\n/baI+FwBIVdNFT/77dIJVtJhmiOBh6sfcfVU8XN/Dnha0j6p6XCg4Z+3U638y5xAgx+mAiAiPFVh\nAj5Itjv6ILA0TccAuwKLgJXArcAuqf/byf7K2gCsT+93BN4L3J+28zDwrXrnVsv8e2yzFbi53rnV\n8LN/B/BAmpYB36x3brX83IH9gMVpW/9FdiVS3XOsYf7bAS8CO9U7r4EmX45rZma5+FCVmZnl4sJh\nZma5uHCYmVkuLhxmZpaLC4eZmeXiwmFWBcrcKenosrZPSfpdPeMyK4IvxzWrknRrmOvI7lc0kuz3\nOFMj4vHN2ObIiNhYpRDNqsJ7HGZVEhEPA78Bzga+BVwREY9LmqHsGStLJf1M0lYAkmZLWpye4/Ct\n7u1IWi3pB5LuBz5el2TM+jGy3gGYbWG+C9wHvAa0pL2QjwMfiIiNkmaT3UrlKuCciFgraSRwu6Tr\nI6L7NhtrIrvZn1nDceEwq6KIeEXSNUBHRHRJ+jDwN8Di7LZGbAs8nbqfIOlUsv8P9wT25a37M11T\n28jNKufCYVZ9m3jrWSIC5kTEP5d3kDQJOAOYEhHr0x2AR5d1eaUmkZoNgs9xmBXrVmC6pN0AJO0q\n6a/Ibmr4MrAh3Xb7qDrGaJaL9zjMChQRD0n6LnBrOin+OvBFsrvALie7Zf5TwP+pX5Rm+fhyXDMz\ny8WHqszMLBcXDjMzy8WFw8zMcnHhMDOzXFw4zMwsFxcOMzPLxYXDzMxy+f9QkLam5VqMygAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b323350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g3sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g3sum['comments'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of comments')\n",
    "plt.title('# of Coments Vs Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10d8fc2d0>"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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dBhwrac90UfzYVGZmZiVpWleVpB+QvVV3L0mrye6O+jpwnaTTgWeAD6fNFwFT\nyd7E+zJwGkBEbJB0AXBv2u78iOh8wd3MzHpR0xJHRJzcxaqjt7NtAGd0sZ+rgKsaGJqZmdXBT46b\nmVkhThxmZlaIE4eZmRXixGFmZoU4cZiZWSGlPTlu1lfV/eTw1m3ctW59j+vX/eSwWZP5jMPMzApx\n4jAzs0KcOMzMrBAnDjMzK8SJw8zMCnHiMDOzQpw4zMysECcOMzMrxInDzMwKceIwM7NCSkkckp6W\n9JCkFZKWpbKRkhZLeiL93DOVS9KlklZJelDSIWXEbGZmmTLPOCZHxKSIaE3Ls4DbI2IicHtaBjge\nmJimmcDlvR6pmZn9Xl/qqpoGzEvz84CTqsqviczdwAhJe5cRoJmZgbLhvnv5oNJTwEYggP+IiDmS\nXoyIEWm9gI0RMULSLcDXI+LOtO524JyIWNZpnzPJzkhoaWl57/z583uxRX+ovb2d4cOHl3b8svX3\n9q/bvLWu+kO3bWHway/3uP6woXW+tHq3t9VV3e0fuO2fPHny8qpeoC6V9Vr190fEGklvBRZL+mX1\nyogISYUyWkTMAeYAtLa2RltbW8OCLapSqVDm8cvW39tf92vVNy1l5KYVPa5f92vV26bXVd3tH9jt\nz6OUrqqIWJN+rgMWAIcCz3d0QaWf69Lma4B9qqqPTWVmZlaCXk8ckoZJ2q1jHjgWeBhYCMxIm80A\nbkrzC4FT091VhwObImJtL4dtZmZJGV1VLcCC7DIGg4FrI+Inku4FrpN0OvAM8OG0/SJgKrAKeBk4\nrfdDNjOzDr2eOCLiSeA92ylfDxy9nfIAzuiF0MzMLIe+dDuumZn1A04cZmZWiBOHmZkV4sRhZmaF\nOHGYmVkhThxmZlaIE4eZmRXixGFmZoU4cZiZWSFOHGZmVogTh5mZFeLEYWZmhThxmJlZIWWNALhj\n2/wcLPlaecefPLu8Y5vZDs9nHGZmVogTh5mZFeKuqu2oe7D6rdu4a936Hteve7B6M7Mm6jdnHJKm\nSHpM0ipJs8qOx8xsoOoXZxySBgHfAo4BVgP3SloYEY+UG9mOqe4zrk2ruWvu3/e4ft1nXL45wKyp\n+ssZx6HAqoh4MiJ+B8wHppUck5nZgKSIKDuGbkn6IDAlIj6Vlk8BDouIM6u2mQnMTIsHAI/1eqBv\n2At4ocTjl83td/vd/v5p34gY3d1G/aKrKo+ImAPMKTsOAEnLIqK17DjK4va7/W7/jt3+/tJVtQbY\np2p5bCqKqft7AAAFKElEQVQzM7Ne1l8Sx73AREnjJb0FmA4sLDkmM7MBqV90VUXENklnArcBg4Cr\nImJlyWHV0ie6zErk9g9sbv8Orl9cHDczs76jv3RVmZlZH+HEYWZmhThx5CBpH0lLJD0iaaWks1L5\nSEmLJT2Rfu6Zyt8l6S5JWyX9fdV+dpa0VNIDaT9fKatNRTSq/VX7GyTpfkm39HZbeqKR7Zf0tKSH\nJK2QtKyM9hTV4PaPkHS9pF9KelTSEWW0qYgG/v8/IP3eO6aXJH22rHbVw9c4cpC0N7B3RNwnaTdg\nOXAS8AlgQ0R8Pb0/a8+IOEfSW4F90zYbI+Jf0n4EDIuIdklDgDuBsyLi7hKalVuj2l+1v88BrcDu\nEXFCb7alJxrZfklPA60R0W8eEGtw++cBv4iIK9MdkrtGxIu93aYiGv3vP+1zENkjBYdFxDO91ZZG\n8RlHDhGxNiLuS/ObgUeBMWSvPZmXNptH9g+FiFgXEfcCr3baT0REe1ockqY+n7kb1X4ASWOBvwSu\n7IXQG6KR7e+PGtV+SXsAfwbMTdv9rq8nDWja7/9o4Ff9MWmAE0dhksYBBwP3AC0RsTateg5oyVF/\nkKQVwDpgcUTc06RQm6Le9gOXAF8AXm9GfM3WgPYH8FNJy5W9JqdfqbP944HfAN9JXZVXShrWrFib\noQG//w7TgR80NLhe5MRRgKThwA3AZyPipep1kfX5dXv2EBGvRcQksqffD5X07qYE2wT1tl/SCcC6\niFjevCibpxG/f+D9EXEIcDxwhqQ/a3ykzdGA9g8GDgEuj4iDgS1AvxkioUG/f1IX3YnAjxoeZC9x\n4sgpXZO4Afh+RNyYip9P/Z8d/aDr8u4vnaIvAaY0OtZmaFD7jwROTP3884GjJH2vSSE3VKN+/xGx\nJv1cBywge/Nzn9eg9q8GVledZV9Plkj6vAb//z8euC8inm98pL3DiSOHdFF7LvBoRFxUtWohMCPN\nzwBu6mY/oyWNSPO7kI0v8svGR9xYjWp/RMyOiLERMY7sVP2OiPh4E0JuqAb+/oeli6ukLppjgYcb\nH3FjNfD3/xzwrKQDUtHRQJ8fU6dR7a9yMv24mwqAiPDUzQS8n+w09EFgRZqmAqOA24EngJ8BI9P2\nbyP7dvUS8GKa3x34Y+D+tJ+HgfPKbltvtr/TPtuAW8puWy///icAD6RpJfDFstvW279/YBKwLO3r\nx2R3IpXexl5s/zBgPbBH2e2qZ/LtuGZmVoi7qszMrBAnDjMzK8SJw8zMCnHiMDOzQpw4zMysECcO\nswZQ5k5Jx1eVfUjST8qMy6wZfDuuWYOk18f8iOxdRoPJntmZEhG/qmOfgyNiW4NCNGsIn3GYNUhE\nPAzcDJwDnAdcExG/kjRD2TgsKyRdJmknAElzJC1LYzyc17EfSaslfV3S/cAHSmmMWQ2Dyw7AbAfz\nFeA+4HdAazoL+QDwvojYJmkO2etWrgVmRcQGSYOBJZKuj4iOV3Csi+xFgGZ9jhOHWQNFxBZJPwTa\nI2KrpL8A/gRYlr3yiF2AZ9PmJ0s6nez/4duBA3nj3U0/7N3IzfJz4jBrvNd5Y7wRAVdFxD9WbyBp\nInAWcGhEvJjeErxz1SZbeiVSsx7wNQ6z5voZ8GFJewFIGiXpHWQvPdwMvJReyX1ciTGaFeIzDrMm\nioiHJH0F+Fm6KP4q8BmyN8Q+QvZa/WeA/yovSrNifDuumZkV4q4qMzMrxInDzMwKceIwM7NCnDjM\nzKwQJw4zMyvEicPMzApx4jAzs0L+PwaxC8GxdiKiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d619510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g3sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "comments = g3sum['comments'].tolist()\n",
    " \n",
    "objects = g3sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "likes = g3sum['likes'].tolist()\n",
    "\n",
    "plt.bar(y_pos, likes, align='center', alpha=0.5, width=0.5)\n",
    "plt.bar(y_pos, comments, align='edge', alpha=0.5, width=0.5)\n",
    "\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of likes/comments')\n",
    "plt.title('# of Likes/Coments Vs Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10c18a8d0>"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cCOqQNAq4GvhMRKysnRZZv1rd/+4j4tWI2JPsKup9Je1RSLBNtqm5SzoSWBYR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\nZmYV50JgZlZxLgRmZhX3/wF5A0OMh6TdIAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c04f550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "articlecount = g1.count()['time'].tolist()\n",
    "\n",
    "objects = g3sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlecomments = g3sum['comments'].tolist()\n",
    " \n",
    "div = [ai/bi for ai,bi in zip(articlecomments,articlecount)] \n",
    "    \n",
    "plt.bar(y_pos, div, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of comments per article')\n",
    "plt.title('# of Coments per article Vs Year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10e4603d0>"
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EZmYll+eZxeW2+jFYeGr7tj/rhPZt28xKwUcEZmYl50RgZlZyw75p6PQFdzdU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\nKVadhgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e2ff150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "articlecount = g1.count()['time'].tolist()\n",
    "\n",
    "objects = g3sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlecomments = g3sum['comments'].tolist()\n",
    "\n",
    "objects = g3sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlelikes = g3sum['likes'].tolist()\n",
    " \n",
    "divcomments = [ai/bi for ai,bi in zip(articlecomments,articlecount)] \n",
    "divlikes = [ai/bi for ai,bi in zip(articlelikes,articlecount)] \n",
    "\n",
    "    \n",
    "plt.bar(y_pos, divlikes, align='center', alpha=0.5, width=0.5)\n",
    "plt.bar(y_pos, divcomments, align='edge', alpha=0.5, width=0.5)\n",
    "\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('# of likes/comments per article')\n",
    "plt.title('# of Likes/Coments per article Vs Year')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# likes and comment groupby month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['month'] = df['time'].str[0:7]\n",
    "g4 = df.groupby(['month'])\n",
    "g4sum = g4.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No.</th>\n",
       "      <th>likes</th>\n",
       "      <th>comments</th>\n",
       "      <th>title_len</th>\n",
       "      <th>subtitle_len</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-08</th>\n",
       "      <td>858</td>\n",
       "      <td>14</td>\n",
       "      <td>29</td>\n",
       "      <td>183</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09</th>\n",
       "      <td>3075</td>\n",
       "      <td>18</td>\n",
       "      <td>49</td>\n",
       "      <td>601</td>\n",
       "      <td>1527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10</th>\n",
       "      <td>1925</td>\n",
       "      <td>28</td>\n",
       "      <td>31</td>\n",
       "      <td>461</td>\n",
       "      <td>1034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11</th>\n",
       "      <td>558</td>\n",
       "      <td>11</td>\n",
       "      <td>18</td>\n",
       "      <td>116</td>\n",
       "      <td>653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12</th>\n",
       "      <td>184</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02</th>\n",
       "      <td>905</td>\n",
       "      <td>16</td>\n",
       "      <td>12</td>\n",
       "      <td>96</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03</th>\n",
       "      <td>355</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>99</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04</th>\n",
       "      <td>870</td>\n",
       "      <td>12</td>\n",
       "      <td>11</td>\n",
       "      <td>203</td>\n",
       "      <td>555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06</th>\n",
       "      <td>341</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>51</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03</th>\n",
       "      <td>337</td>\n",
       "      <td>19</td>\n",
       "      <td>11</td>\n",
       "      <td>81</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04</th>\n",
       "      <td>825</td>\n",
       "      <td>71</td>\n",
       "      <td>92</td>\n",
       "      <td>173</td>\n",
       "      <td>357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-05</th>\n",
       "      <td>162</td>\n",
       "      <td>31</td>\n",
       "      <td>36</td>\n",
       "      <td>55</td>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06</th>\n",
       "      <td>480</td>\n",
       "      <td>81</td>\n",
       "      <td>116</td>\n",
       "      <td>107</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-07</th>\n",
       "      <td>471</td>\n",
       "      <td>91</td>\n",
       "      <td>85</td>\n",
       "      <td>144</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-08</th>\n",
       "      <td>1064</td>\n",
       "      <td>100</td>\n",
       "      <td>196</td>\n",
       "      <td>290</td>\n",
       "      <td>555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09</th>\n",
       "      <td>148</td>\n",
       "      <td>11</td>\n",
       "      <td>26</td>\n",
       "      <td>50</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10</th>\n",
       "      <td>582</td>\n",
       "      <td>91</td>\n",
       "      <td>192</td>\n",
       "      <td>166</td>\n",
       "      <td>161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11</th>\n",
       "      <td>285</td>\n",
       "      <td>55</td>\n",
       "      <td>35</td>\n",
       "      <td>84</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12</th>\n",
       "      <td>695</td>\n",
       "      <td>230</td>\n",
       "      <td>189</td>\n",
       "      <td>252</td>\n",
       "      <td>303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01</th>\n",
       "      <td>670</td>\n",
       "      <td>91</td>\n",
       "      <td>153</td>\n",
       "      <td>243</td>\n",
       "      <td>484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02</th>\n",
       "      <td>261</td>\n",
       "      <td>46</td>\n",
       "      <td>52</td>\n",
       "      <td>86</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03</th>\n",
       "      <td>759</td>\n",
       "      <td>117</td>\n",
       "      <td>111</td>\n",
       "      <td>238</td>\n",
       "      <td>315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04</th>\n",
       "      <td>366</td>\n",
       "      <td>87</td>\n",
       "      <td>112</td>\n",
       "      <td>105</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05</th>\n",
       "      <td>1155</td>\n",
       "      <td>302</td>\n",
       "      <td>368</td>\n",
       "      <td>440</td>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06</th>\n",
       "      <td>327</td>\n",
       "      <td>143</td>\n",
       "      <td>139</td>\n",
       "      <td>135</td>\n",
       "      <td>235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07</th>\n",
       "      <td>525</td>\n",
       "      <td>143</td>\n",
       "      <td>208</td>\n",
       "      <td>225</td>\n",
       "      <td>295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08</th>\n",
       "      <td>203</td>\n",
       "      <td>62</td>\n",
       "      <td>74</td>\n",
       "      <td>99</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09</th>\n",
       "      <td>585</td>\n",
       "      <td>303</td>\n",
       "      <td>495</td>\n",
       "      <td>241</td>\n",
       "      <td>394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10</th>\n",
       "      <td>549</td>\n",
       "      <td>384</td>\n",
       "      <td>318</td>\n",
       "      <td>347</td>\n",
       "      <td>412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11</th>\n",
       "      <td>756</td>\n",
       "      <td>692</td>\n",
       "      <td>806</td>\n",
       "      <td>381</td>\n",
       "      <td>564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12</th>\n",
       "      <td>1080</td>\n",
       "      <td>1010</td>\n",
       "      <td>1220</td>\n",
       "      <td>684</td>\n",
       "      <td>1025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01</th>\n",
       "      <td>702</td>\n",
       "      <td>601</td>\n",
       "      <td>709</td>\n",
       "      <td>494</td>\n",
       "      <td>667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02</th>\n",
       "      <td>982</td>\n",
       "      <td>1376</td>\n",
       "      <td>1973</td>\n",
       "      <td>1229</td>\n",
       "      <td>1699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03</th>\n",
       "      <td>370</td>\n",
       "      <td>1300</td>\n",
       "      <td>888</td>\n",
       "      <td>1010</td>\n",
       "      <td>1296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04</th>\n",
       "      <td>26</td>\n",
       "      <td>70</td>\n",
       "      <td>64</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          No.  likes  comments  title_len  subtitle_len\n",
       "month                                                  \n",
       "2013-08   858     14        29        183           168\n",
       "2013-09  3075     18        49        601          1527\n",
       "2013-10  1925     28        31        461          1034\n",
       "2013-11   558     11        18        116           653\n",
       "2013-12   184      3         2         36            87\n",
       "2014-02   905     16        12         96            67\n",
       "2014-03   355      6         4         99            84\n",
       "2014-04   870     12        11        203           555\n",
       "2014-06   341      5         4         51            37\n",
       "2015-03   337     19        11         81           168\n",
       "2015-04   825     71        92        173           357\n",
       "2015-05   162     31        36         55           150\n",
       "2015-06   480     81       116        107           284\n",
       "2015-07   471     91        85        144           196\n",
       "2015-08  1064    100       196        290           555\n",
       "2015-09   148     11        26         50            57\n",
       "2015-10   582     91       192        166           161\n",
       "2015-11   285     55        35         84            89\n",
       "2015-12   695    230       189        252           303\n",
       "2016-01   670     91       153        243           484\n",
       "2016-02   261     46        52         86            93\n",
       "2016-03   759    117       111        238           315\n",
       "2016-04   366     87       112        105           249\n",
       "2016-05  1155    302       368        440           643\n",
       "2016-06   327    143       139        135           235\n",
       "2016-07   525    143       208        225           295\n",
       "2016-08   203     62        74         99           135\n",
       "2016-09   585    303       495        241           394\n",
       "2016-10   549    384       318        347           412\n",
       "2016-11   756    692       806        381           564\n",
       "2016-12  1080   1010      1220        684          1025\n",
       "2017-01   702    601       709        494           667\n",
       "2017-02   982   1376      1973       1229          1699\n",
       "2017-03   370   1300       888       1010          1296\n",
       "2017-04    26     70        64        108           108"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g4sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f649ad0>"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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XMWx9DN8JuMfdPwpgZpOiPot5VR9xbfHYJjO7Bvi0u9fRhu3xiGMDcLG7H0xa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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f4a1bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g4sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g4sum['likes'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of likes')\n",
    "plt.title('# of Likes Vs Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f8bcc90>"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CuCgizpe0M/AdYD9gR2AZsAH4AfBa4OXAYkDAE6TzES8nJT/l588CfwVMApYC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f7e1f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "articlecount = g2.count()['time'].tolist()\n",
    "objects = g4sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlelikes = g4sum['likes'].tolist()\n",
    " \n",
    "div = [ai/bi for ai,bi in zip(articlelikes,articlecount)] \n",
    "\n",
    "plt.bar(y_pos, div, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of likes per article')\n",
    "plt.title('# of Likes per article Vs Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10fabd810>"
      ]
     },
     "execution_count": 300,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/KTAjdy4EdikNvnMuW09EXAhcCDBp0qSYPHnyJsd66623sqHx9FSdgRjLQJzm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\nDRc0HBtSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f75eed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g4sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = g4sum['comments'].tolist()\n",
    " \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of comments')\n",
    "plt.title('# of Comments Vs Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10fda7d90>"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Hds2vycAPmx6pmZm9pL+TR6WjgPPz5/OBt5XKL4jkZmCkpLH9EaCZmYEion8a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\nmVndnDzMzKxuTh5mZlY3Jw8zM6vb/we5D9SzICQRmAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fcf0a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "objects = g4sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "comments = g4sum['comments'].tolist()\n",
    "\n",
    "objects = g4sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "likes = g4sum['likes'].tolist()\n",
    " \n",
    "plt.bar(y_pos, likes, align='center', alpha=0.5, width=0.5)\n",
    "plt.bar(y_pos, comments, align='edge', alpha=0.5, width=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of likes/comments')\n",
    "plt.title('# of Likes/Comments Vs Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11010c390>"
      ]
     },
     "execution_count": 302,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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8l/tlzfwYUoppGfBYfs9YYAywemm6gOvy33I7w0j9H3XKjAU2qOnbZXSM49bA\nhnk+olRHOZb1cxur01m5nVeAHWum18byMvC6Up8EsJiOMXoNaQyLz9iy/HcJHcvlYmBz0jK1NM83\nwC+ALXI7o0jjNLLUVm0s5eWl6N/yMrV7bmMJnZf/AP5F5zEalh9FuX8AL9ExRsOACaTlpqsxWitP\nr7d8F2M0lI5luChXxFKM0bBSPdTE8gqwJR3Ldb1+eRnYio6xjtwH36TzGEVNLEuAJ+gYoy1y3y7L\nrwm4lvSZKOZ5/Zo4qIllaG5rRK5zeK7vCxHxA0kXkj6zG+XpI/Lj6og4CEDSWcDEXOdLpHXiENLl\n+N+lRNLpwAcjYgwVrAp7BEuAEyJie9IC/fF8S4ovAtcDewIXAFfk6YcDPwLuAB6JiNcANwOPkAZr\nO+BZ4HngEOD6XObGXMfGwDO53WuA/YFbgTeT+utc0gd5fn4EaaHZPb/3StIK8hbSYC2qaWd14K8R\nMQT4c37/bFLyKsrcAFyV659GGvhzizKlebyCtADfD7STFvy35fcfRbqVx5mkhXgxcA9phfNEbucs\n4NIc99Bc5ulinkt9F8DVuU9mAJNL/bJn7tvFuV+eBo7P8czMdZyf23kSaMuPX+T33lNqZykpwQRp\npVNbZlau90lSsptOSqwH5n45LY/FPOCpXMcRNbH8pBTLy/n9te1sQlrRbAi8CCwslyF9wXF8fv87\ngYtIH+ryGF0N/D3HciGwIPddebm8iXTRxKw8ls/m9l5Lx7JwM2l5PD7XtYC0YVSO94Zcx1LSt/Rn\n1PTL8Xm+H8ll5gEfyPNVO0aXkJbZNuBs0m1gymO0WZ6HyPHWxjIrz8OcPEa1sRRj9DDpMzizTizF\nGBWxzK0Tyyb5/ceXxmh5LKUxeh74n9IYXVhnjB4C/pL7djpwZ80YXUtaP3w5z98yUrIrxujPpHXQ\n8Ny3QbpjQrlfrgLOIX2GDsxxvUDHhs2FpKQ1hvR5/zZpvbBV6RY8n4mInUkbkq8jbfS+6jY9kiYC\na9MLAz4RRMTMiLgj/z8feIC0EBwMTI6ImcB3gEPy9HtJC8ZrgNtzNWcAe0REW0Q8DtxNWoFuSVqp\nFWXeCOwH/Im0Iij651nSAvAKcADwR9LCuZg06PNyXXcDu0REsaJbmOvYEpgsSaQsXgz+N/P7hwI7\nlGL5CmnvZThpsBeTtnx2yPN8TY53nxzTnaSkMwvYibSFcFnul8NIK8IZOR5yvACnkrZCjiAt3E/U\nzDOkD+DB3BW0AAAMJ0lEQVTI3JdtpJVAseX6bO7/TXN/PpZjeTxPX1LTzsjc9tN07O0UMf00z+Pl\nOZbb65R5kLSV9HhE3Aj8k7TCL/ru/cAHScn2MVISLb6hWcRyRo5lVK7r1jrtvJhj3YX0gZ1eU2bd\nUpm/0pG8lo8R8FbgY6Qt8e/kPltK5+Xy66QP9Jq5zD2klcC2dCwLJ5P2Mu/N/TqXji3OIt7/IY3B\n4hzPHaREVywvF+b53o40xnNIy0q5X04F9spxzyGN0fCads4nffZOIY3RP+rE8ihp+f5nHqNOsZDG\n6BM5ljtIY1Qbyxk5ln1zv91aJ5aXciz30jFG5VjWzWU2Im00FmNU/qy9FTiR1N+H0TFGW9J5jHbI\n/19HSsrLSHs2xRidQNoQ3DX33eL8KMf7HdL91ZaQNhQfAu4i73lGxDWRrtzZlfRZ3Y60h3Q++RY8\nEVF8bnclfY6ej5rb9OR7uX0/z1dlAz4RlEkaT8qGtwHj8koI0kprXM30MaQt6vL0oZLuJ23NPgyM\nqq0D+AFwJKlv7iIfRoiIxcBHSAv5/yN9OC/K5UaSPgBbABvl70f8JNfXVmqnWIGMk3QnaY9jCGlQ\nx9bEslkuuybpQzCjTpn1SAvcI7ncTGC1OmWKLZi5pIV9ZGn6lqS9i5m5zEI6Hzopbv3xUdIu8Jty\nLMOA1SWtlesfStrdPoiUUIfXtDM+990GpJXh+qQV8Rq5zKH577dyXUU75TJFcv53Sc+R9tKml/p3\nK9LWXvH+d5C2rmtjGUdaaS8jrWxqYzk213FV7p/1amKZQ1rpDCVtFPw890d5jMaRNgyGkA5hrpZj\nqF0uNySN4XdJW9Cj6DzOq+U6vk1aIa1PWnGW410txzOMtNW+T657VE09Ii2jW5CW8RHUH6P1SWO0\nU007H8x/T8jzvk+dWIbneCdJmlMnlq1IK62hpPHbv4tYNsz1tJPGqDaWb+Y6ppLGaOOaWObQcZjx\nHNKe8bBcpjxGC3I7P859tCZ11h35/41IK+iFvPqzOI6UmIpDO7XLbvFZXAL8J2ndMa80vfBvudya\nucz0XC8Aks4h7aEMyzFTU+a/gCtLsVWyyiQCSWOAy4BPlzIjADmTRoXpo0krkw+QFjTVKfMT0i7b\nk6TBKNofTloZLiQN6nWkwwLK738xT1+N9GF8hZxsyu0UzZFWVI+TFpraczUHkFZSi0lbUPNJH4ja\nMiJtNbwfuI+OcxaFg+g4/noaHVtc5XluJ22VbURawIpj2Uh6PemDO4+0ZUKOZcNSNcNIW6PFLvzF\nwOcoLVu5nZeBz+QYzyMlbOV2Ngbek9v5ahftAPx3rudXpA+4SMmrMJI0Pi/nv48DH6oTS5A+PO2k\n+1ktjyX7DGkFcUwuM7wcS67j8NxXxSNq483lirF7hbS7Xm+ZG0vq50/Qcby6UKzMluZpfyJtEVJT\nZghpDNpJh4q27KIMwHtJY1XbL6/Qcf7g56Q+HArLx+htefrU/LYb6sTyk/z3+lx2Rk0sxXkr8vw8\n0kUsQUpKIvX18liyo/Lfb+d5fqEcS67jS7ne3UifpWV14i36dwfScrOMUv+XYim2tJfRsZVfW+Zw\n0uf/E9R8XktlAN4O/Jr6PkxKVrvVKxMRx5KW2bmkcVyu9Dn6ce37erJKJIK8Er4MuDAifpNfniVp\nozx9M1L2LU9vI33AyOVml+q4gLSLvETS/pLulHQv6cP/XtIK5Nek3b9lwKdIu6BF8niStOW6hDS4\nq+ct/O+QksRc0jHFO0gL1xJJ+5M+xOPza5fl58+Rtr4XSro31/MR0oK3GWnlMRZ4V02ZH+ZYJpJW\n4tuTTna3l8qckcuMBD5O2loeUsSb5zlIK8JhpIVoi/ye9YDfkbaqxwCfpuODuAlpxfSpPA+Lcj/N\nIe2SLsnPKbXTTkpYz+V+fJCOFegtpAV/LOm8BaQtpU1IH+BD8/wcldvYn7S19Fye9/bcxjDSymMI\naRd+QzoONZVjWQxsQzomfW45Fkn3kJJsG2nr6lnSB782ljeTkvDzpOP8i3KZBbmNUZJOISWRK0l7\nXPNz32xSimVhbvvyXE87sEzShNzOBbmPdiMts9+jY6uziOXgPB6jSMvV9/L4tdcsL5AOq/2GdAw+\navplYY5vVl4O7qfjZO8tdBwi+VL++/o6sbwpx7Ir6ZDF8+VY8hgNz3U+nfusXiyLchvTc7zLY8lj\ntFfut/3zGC2rE8uWeX6eIm24vZLLLB8j0t5IcUz/WdLGyLKaMWrP8/4Q6XBkAPOLMcplhpCWm5cj\n4pwc+/JYJJ2Y+2IEcHdEzCIt44vy9Dsl/S73TTtwRy6zKdBWKnN87rc24N25neI2PW8grbMelfQE\nsJqkR6lgwCeCfFz9LOCBiDi1NOlK4Og8/Yo60x8irSQBjiZfORIRp0oaTVpIHgN2iojXkz6I80nH\nIzcmrQBfyu87G9ibtPJ4jLQw/SdpBRnAkpo6pueyfyRtIZTbKX4j8gE6dtcXkQ5DXZDL/CXH30Y6\nHjuHdCXPXaQVwxmkhfghUvJ6P2kvZAjpGP0FpMMaY/PzmaTDWTeTFs4lpA/sFaSkdg5p4TsvP18M\ntEfEZqSrkB4mnbgrVhJz83yfTVr4Xs7zPIK0sh6S+21pnn4taYvtn6SFfzZpC3gZsDgitsztPAT8\nLNf9eJ7vAH6V+2W93NbwPG+r59fuy/P8v8D7SCv2NUgrgP2KWHIdF+S4/gUMzyfZlseS412S+/62\nXM+wOrGsm+t5mI4t3tmkDYYLSFtlx+Z5aidtRY8hrcy3KcUyO7f3l1zHiNzH++Yyt+Z2r8nz/e46\nsSygYwv0atKW++hSv5xButKnjbQRsEUuUztGs3Pda5ESae0YfSX3/8W5/UvrxFIczhmZY4iaWP6X\ntKe6gLSR80Q5llK/FBc/rJbjrTdGi3L/r5Ffr42FXGY2aQNsMWnjoTxG78mxjCUlizG5THmM5uRY\nRtFxO5z7S2P09zy/z5CSzBZ0XPlW7pdL8hjemA8f7whMy9PPIC1TB5DWHdeVbsFzfp7nQyPiZ6Rz\nM9sAz5Rv0xMRV0fEhhExPiLGk5LS1lQw4L9ZLOlNpBXYPXQctjiJ9CG9hNQhm5IGpjjMsiFpYIoT\nfPeQOnIhHVvIi0lbCCPpOJG6PR3HyIvLyYoTvs+TEkT58sfi0EqxKzmftHCXy0DHZWtP03HCMOh8\nOKJcZjidb8xXTH85tzWSjg/bYjoud12U4y1OhELHLnVxKKWIt/h/tfx3CR3nBYpj8TNIH5LXldor\nYqntl/KldZFjKfYg2um4dDTouHSxnY7DB0U7RfzUKbMBHcm36LvyOL5AStLlhbq4rLOIpVgWFuU6\niq3TcjtDSZd11hvrokxxyWBZuV/KsdSOc3HZ61OkJFKvzNI8fZM8b93FUm95WUJaXkbSMW6L6LgM\nuOiXYmOwGKNFdD6MVCSYGXmeJpL6u7hkuTaW9XPflOepHEvRL0UshXIsxRg9Q0r0xbJcjiVIyaG7\nflmNVx9erDdGxeWc5TIrMkbFfNRbppbkftkov6/8eW3LcT5J+hzsQNrYmku6Bc8pkoaQ1oNr5Dqf\nI425ijI184mktqh4+eiATwRmZtZYA/7QkJmZNZYTgZlZi3MiMDNrcU4EZmYtzonAzKzFORGYAZJC\n0gWl58MkPSfpqhWsby1JHys9n7SidZk1mhOBWbIA2DF/2RDS/W1mrER9a5FuOmc24DkRmHW4hvTN\nTkjfUL6omCBpHUm/lXS3pL9J2im/frKksyXdIOkxSZ/Mb/ku6RbCd0r6fn5tjKRLJT0o6cL8rXiz\nfudEYNZhCnC4pFGku13eVpr2ddKtlXcifbP9vNK07Ui3stgV+Fq+N9YXgX9FxOsj4vO53BtI92za\nnvRt1b0aOTNmVTkRmGURcTfpnjTvI+0dlL2JfAfWiPgzsK6k4hbCV0dEe0TMId3XZhz1/T0ipkfE\nMtI9oMb37RyYrZgB/1OVZk12Jek3KSaRbgJWRfmWw0vp+nNVtZxZU3mPwKyzs4GvR8Q9Na/fTPol\nNyRNAubU/u5Fjfnk26CbDXTeIjEriYjpwOl1Jp0MnC3pbtKdNI/uoZ7nJf0l36v+WtLtoc0GJN99\n1MysxfnQkJlZi3MiMDNrcU4EZmYtzonAzKzFORGYmbU4JwIzsxbnRGBm1uL+P+NzRAhAq7pcAAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fda7350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "articlecount = g2.count()['time'].tolist()\n",
    "\n",
    "objects = g4sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlecomments = g4sum['comments'].tolist()\n",
    "\n",
    "div = [ai/bi for ai,bi in zip(articlecomments,articlecount)] \n",
    " \n",
    "plt.bar(y_pos, div, align='center', alpha=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of comments per article')\n",
    "plt.title('# of Comments per article Vs Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x110377a10>"
      ]
     },
     "execution_count": 303,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wx3oGJiIijVHkZPHxFbqd0MVxiIhIN6l2juADwAeBsWZ2S67XUEAPnBMR6SOqnSO4j/TS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cb4d0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "articlecount = g2.count()['time'].tolist()\n",
    "\n",
    "objects = g4sum['comments'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlecomments = g4sum['comments'].tolist()\n",
    "\n",
    "objects = g4sum['likes'].index.tolist()\n",
    "y_pos = np.arange(len(objects))\n",
    "articlelikes = g4sum['likes'].tolist()\n",
    "\n",
    "divcomments = [ai/bi for ai,bi in zip(articlecomments,articlecount)] \n",
    "divlikes = [ai/bi for ai,bi in zip(articlelikes,articlecount)] \n",
    "\n",
    "plt.bar(y_pos, divlikes, align='center', alpha=0.5, width=0.5) \n",
    "plt.bar(y_pos, divcomments, align='edge', alpha=0.5, width=0.5)\n",
    "plt.grid()\n",
    "\n",
    "plt.xticks(y_pos, objects)\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('# of likes/comments per article')\n",
    "plt.title('# of Likes/Comments per article Vs Month')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# trend of title/subtitle length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No.</th>\n",
       "      <th>time</th>\n",
       "      <th>likes</th>\n",
       "      <th>comments</th>\n",
       "      <th>title</th>\n",
       "      <th>subtitle</th>\n",
       "      <th>title_len</th>\n",
       "      <th>subtitle_len</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>35</td>\n",
       "      <td>32</td>\n",
       "      <td>陌生而熟悉的味道，欢迎来到美国街机厅</td>\n",
       "      <td>这是一篇价值约 12.5 美金的街机自助餐。</td>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "      <td>2017</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>55</td>\n",
       "      <td>16</td>\n",
       "      <td>缅怀素未谋面的郑问老师</td>\n",
       "      <td>很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。</td>\n",
       "      <td>33</td>\n",
       "      <td>102</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>39</td>\n",
       "      <td>23</td>\n",
       "      <td>16-BIT游戏漫谈（4）——魔界村外传：纹章篇</td>\n",
       "      <td>由路边杂鱼升格为主角的另类作品</td>\n",
       "      <td>58</td>\n",
       "      <td>45</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>46</td>\n",
       "      <td>90</td>\n",
       "      <td>悠悠八载街机路：执著、热情与精通</td>\n",
       "      <td>说说我的街机生涯，以及如何精通枪机游戏</td>\n",
       "      <td>48</td>\n",
       "      <td>57</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>39</td>\n",
       "      <td>44</td>\n",
       "      <td>三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘</td>\n",
       "      <td>我从来没想到CAPCOM爱僵尸会爱的如此深沉</td>\n",
       "      <td>63</td>\n",
       "      <td>54</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>14</td>\n",
       "      <td>60</td>\n",
       "      <td>火爆狂飙3：速度与对抗的巅峰</td>\n",
       "      <td>在13年前，娱乐向竞速游戏的巅峰出现了</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>294</td>\n",
       "      <td>80</td>\n",
       "      <td>《凯瑟琳》：性、生活与游戏底层的人性隐喻</td>\n",
       "      <td>正视自己的第一步，是了解欲望的来源在何处</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>45</td>\n",
       "      <td>33</td>\n",
       "      <td>那会儿想买电脑就是为了跟印第安纳琼斯去冒险</td>\n",
       "      <td>人有很多第一次，而冒险始终让人跃跃欲试。探索秘密的青春啊～～让人欲罢不能。</td>\n",
       "      <td>63</td>\n",
       "      <td>111</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2017-03-06</td>\n",
       "      <td>56</td>\n",
       "      <td>31</td>\n",
       "      <td>我真的喜欢游戏吗？</td>\n",
       "      <td>我想，这就是答案了~</td>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>2017-03-05</td>\n",
       "      <td>25</td>\n",
       "      <td>37</td>\n",
       "      <td>回顾FC时代的《仁王》——《不动明王传》</td>\n",
       "      <td>其实仔细想想，过去真的是有一些游戏难得没什么道理</td>\n",
       "      <td>56</td>\n",
       "      <td>72</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>37</td>\n",
       "      <td>30</td>\n",
       "      <td>《塞尔达传说》的这些广告，你都看过么？</td>\n",
       "      <td>《荒野之息》的广告，看塞尔达公主哭心里特难受</td>\n",
       "      <td>57</td>\n",
       "      <td>66</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>2017-02-23</td>\n",
       "      <td>18</td>\n",
       "      <td>20</td>\n",
       "      <td>我和FC：保护那份最初的感动</td>\n",
       "      <td>当评价快乐的维度变多之后，快乐获取难度就随之增加。</td>\n",
       "      <td>38</td>\n",
       "      <td>75</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2017-02-22</td>\n",
       "      <td>47</td>\n",
       "      <td>70</td>\n",
       "      <td>16-BIT游戏漫谈（3）——超级忍</td>\n",
       "      <td>最好的忍者游戏之一</td>\n",
       "      <td>40</td>\n",
       "      <td>27</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2017-02-19</td>\n",
       "      <td>34</td>\n",
       "      <td>140</td>\n",
       "      <td>聊聊香港漫画改编的电影和游戏</td>\n",
       "      <td>一部老电影引发的怀旧情</td>\n",
       "      <td>42</td>\n",
       "      <td>33</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2017-02-16</td>\n",
       "      <td>34</td>\n",
       "      <td>71</td>\n",
       "      <td>记忆中的“三国题材”游戏</td>\n",
       "      <td>除了光荣的《三国志》和《割草无双》，其实还有很多好玩的三国游戏在等待着我们！</td>\n",
       "      <td>36</td>\n",
       "      <td>114</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>2017-02-15</td>\n",
       "      <td>56</td>\n",
       "      <td>28</td>\n",
       "      <td>連仙水忍也為之羞澀：播音人黑盒子攻略錄影帶轉帶紀實</td>\n",
       "      <td>台灣最古老的電玩「實況」解說節目，與遙不可及的 Beta 年代</td>\n",
       "      <td>75</td>\n",
       "      <td>81</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>2017-02-14</td>\n",
       "      <td>18</td>\n",
       "      <td>49</td>\n",
       "      <td>网游考古系列：《最终兵器》</td>\n",
       "      <td>我多么希望这是一篇安利而不是悼词</td>\n",
       "      <td>39</td>\n",
       "      <td>48</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2017-02-12</td>\n",
       "      <td>26</td>\n",
       "      <td>42</td>\n",
       "      <td>网游考古系列：《疯狂坦克2》</td>\n",
       "      <td>炮，本能</td>\n",
       "      <td>40</td>\n",
       "      <td>12</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2017-02-07</td>\n",
       "      <td>45</td>\n",
       "      <td>69</td>\n",
       "      <td>网游考古系列：《沃土》</td>\n",
       "      <td>现实是生活，游戏中为何还要生活。</td>\n",
       "      <td>33</td>\n",
       "      <td>48</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>2017-02-07</td>\n",
       "      <td>123</td>\n",
       "      <td>225</td>\n",
       "      <td>我所看过与玩过的《生化危机》</td>\n",
       "      <td>可能是我见过最神奇的游戏系列，之一</td>\n",
       "      <td>42</td>\n",
       "      <td>51</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>19</td>\n",
       "      <td>41</td>\n",
       "      <td>我与游戏的二三事</td>\n",
       "      <td>从小到大，参与其中，乐在其中</td>\n",
       "      <td>24</td>\n",
       "      <td>42</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>75</td>\n",
       "      <td>58</td>\n",
       "      <td>回忆里的温暖角落——家中长辈们的游戏印记</td>\n",
       "      <td>致我最爱的亲人们</td>\n",
       "      <td>60</td>\n",
       "      <td>24</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>2017-02-04</td>\n",
       "      <td>43</td>\n",
       "      <td>40</td>\n",
       "      <td>我的暑假20XX：真红少年与热血兄贵</td>\n",
       "      <td>每一次少年们发现新大陆的时候，土坡上总有一群嚼着冰棍儿的大哥......</td>\n",
       "      <td>46</td>\n",
       "      <td>96</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>2017-02-03</td>\n",
       "      <td>49</td>\n",
       "      <td>54</td>\n",
       "      <td>网游考古系列：《魔力宝贝》</td>\n",
       "      <td>“魔力魔力，随心所欲”</td>\n",
       "      <td>39</td>\n",
       "      <td>33</td>\n",
       "      <td>2017</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>35</td>\n",
       "      <td>32</td>\n",
       "      <td>陌生而熟悉的味道，欢迎来到美国街机厅</td>\n",
       "      <td>这是一篇价值约 12.5 美金的街机自助餐。</td>\n",
       "      <td>54</td>\n",
       "      <td>54</td>\n",
       "      <td>2017</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>55</td>\n",
       "      <td>16</td>\n",
       "      <td>缅怀素未谋面的郑问老师</td>\n",
       "      <td>很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。</td>\n",
       "      <td>33</td>\n",
       "      <td>102</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>39</td>\n",
       "      <td>23</td>\n",
       "      <td>16-BIT游戏漫谈（4）——魔界村外传：纹章篇</td>\n",
       "      <td>由路边杂鱼升格为主角的另类作品</td>\n",
       "      <td>58</td>\n",
       "      <td>45</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>2017-03-18</td>\n",
       "      <td>46</td>\n",
       "      <td>90</td>\n",
       "      <td>悠悠八载街机路：执著、热情与精通</td>\n",
       "      <td>说说我的街机生涯，以及如何精通枪机游戏</td>\n",
       "      <td>48</td>\n",
       "      <td>57</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>2017-03-17</td>\n",
       "      <td>39</td>\n",
       "      <td>44</td>\n",
       "      <td>三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘</td>\n",
       "      <td>我从来没想到CAPCOM爱僵尸会爱的如此深沉</td>\n",
       "      <td>63</td>\n",
       "      <td>54</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>2017-03-13</td>\n",
       "      <td>14</td>\n",
       "      <td>60</td>\n",
       "      <td>火爆狂飙3：速度与对抗的巅峰</td>\n",
       "      <td>在13年前，娱乐向竞速游戏的巅峰出现了</td>\n",
       "      <td>40</td>\n",
       "      <td>53</td>\n",
       "      <td>2017</td>\n",
       "      <td>03</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>187</td>\n",
       "      <td>2013-11-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>《ゲームになった映画たち 完全版》！~</td>\n",
       "      <td>电影改编游戏和游戏改编电影，一直都是大家关注和厌恶的话题，《Gameside》编辑部为此出版...</td>\n",
       "      <td>53</td>\n",
       "      <td>185</td>\n",
       "      <td>2013</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>188</td>\n",
       "      <td>2013-10-29</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>《ダイナマイト刑事2》与海贼们的斗争！～</td>\n",
       "      <td>3D动作清版游戏我玩儿的最多的还是《ダイナマイト刑事2》！～</td>\n",
       "      <td>58</td>\n",
       "      <td>84</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>189</td>\n",
       "      <td>2013-10-28</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>神的孩子都喷火-《卡诺夫》！～</td>\n",
       "      <td>Data East公司的吉祥物比马里奥，索尼克那些看着霸道多了！～</td>\n",
       "      <td>43</td>\n",
       "      <td>81</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>190</td>\n",
       "      <td>2013-10-24</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>怀古名作3D化之《青蛙过河3D》！～</td>\n",
       "      <td>我最爱3DS的一点就是，能玩到不少怀旧名作的重制版！～</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>191</td>\n",
       "      <td>2013-10-17</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>回到港产片吓哭你的时代-《灵幻道士》！～</td>\n",
       "      <td>看多了西洋僵尸，咱们也来点儿本土的吧！～</td>\n",
       "      <td>58</td>\n",
       "      <td>60</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>192</td>\n",
       "      <td>2013-10-15</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>怪逼的《トリオ・ザ・パンチ》！~</td>\n",
       "      <td>Data East公司最怪的游戏当属《トリオ・ザ・パンチ》！～</td>\n",
       "      <td>46</td>\n",
       "      <td>75</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>193</td>\n",
       "      <td>2013-10-14</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>XBOX360首发作品：卡蜜欧—元素力量</td>\n",
       "      <td>《卡蜜欧—元素力量》是XBOX360的首发游戏之一，作为大名鼎鼎的RARE十年磨一剑的作品，...</td>\n",
       "      <td>46</td>\n",
       "      <td>297</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>194</td>\n",
       "      <td>2013-10-14</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>我其实还是喜欢VICE CITY！～</td>\n",
       "      <td>能跟掌机上玩到GTA系列，以前一直觉得是件可望而不可即的美事儿！～</td>\n",
       "      <td>36</td>\n",
       "      <td>93</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>195</td>\n",
       "      <td>2013-10-11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>我这14年PM经历的流水账</td>\n",
       "      <td>我这14年PM经历的流水账</td>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>196</td>\n",
       "      <td>2013-10-10</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>初次接触Game Boy时所玩的游戏系列1！～</td>\n",
       "      <td>第一次玩的那盘GB盗版合卡里的小游戏，现在想起来都很难忘，那种乐趣是以往俄罗斯方块掌机所难以...</td>\n",
       "      <td>51</td>\n",
       "      <td>149</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>197</td>\n",
       "      <td>2013-10-08</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>黎明期的电子游戏-《铁板阵》！～</td>\n",
       "      <td>我的名字安藤杰尼斯便是音译自《铁板阵》里的母舰-Andor Genesis！～</td>\n",
       "      <td>46</td>\n",
       "      <td>89</td>\n",
       "      <td>2013</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>198</td>\n",
       "      <td>2013-09-29</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>悲惨的国庆节与《Konami世界》！～</td>\n",
       "      <td>20世纪游戏小子的国庆节到底是什么样呢？</td>\n",
       "      <td>45</td>\n",
       "      <td>56</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>199</td>\n",
       "      <td>2013-09-28</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>进化！</td>\n",
       "      <td>进化！</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>200</td>\n",
       "      <td>2013-09-26</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>丧逼一家人--《とんでもクライシス!》！～</td>\n",
       "      <td>丧逼一家人的日常究竟是什么样呢？</td>\n",
       "      <td>57</td>\n",
       "      <td>48</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>201</td>\n",
       "      <td>2013-09-25</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>怀旧游戏迷们最后的纸媒阵地-GameSide</td>\n",
       "      <td>《GameSide》大概是怀旧游戏迷们最后的纸媒阵地了。</td>\n",
       "      <td>48</td>\n",
       "      <td>68</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>202</td>\n",
       "      <td>2013-09-24</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DS-《美文字トレーニング》!~</td>\n",
       "      <td>没有智能手机的各种应用软件的时代，DS上总是有各种有意思的教育软件登场，真令人怀念！～</td>\n",
       "      <td>38</td>\n",
       "      <td>125</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>203</td>\n",
       "      <td>2013-09-23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>電気グルーヴ游戏大时代《グルーヴ地獄V》</td>\n",
       "      <td>与音乐家跨界合作的游戏中，具有KUSO味的肯定还得是《グルーヴ地獄V》！~</td>\n",
       "      <td>58</td>\n",
       "      <td>99</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>204</td>\n",
       "      <td>2013-09-16</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>PS-《風のノータム》！～</td>\n",
       "      <td>乘坐热气球旅行的游戏会给我们带来治愈性的体验吗？？？</td>\n",
       "      <td>33</td>\n",
       "      <td>78</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>205</td>\n",
       "      <td>2013-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>ずんずん教の野望与朱莉安娜女郎!~</td>\n",
       "      <td>今天是周末，来聊点儿和大妞儿有关系的游戏话题吧！！！~</td>\n",
       "      <td>47</td>\n",
       "      <td>79</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>206</td>\n",
       "      <td>2013-09-12</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>翘曲空间的放浪冒险---Arkanoid！～</td>\n",
       "      <td>《Arkanoid》大概属于那种能玩到世界末日的游戏。</td>\n",
       "      <td>44</td>\n",
       "      <td>65</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>207</td>\n",
       "      <td>2013-09-11</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>Famicom上的知名西游记系列！~</td>\n",
       "      <td>每年暑假电视台都会重播《西游记》电视剧。不过，以《西游记》为题材的游戏你玩过多少呢？</td>\n",
       "      <td>38</td>\n",
       "      <td>126</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>208</td>\n",
       "      <td>2013-09-09</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>涂鸦小子的今与昔-《Jet Set Radio》！</td>\n",
       "      <td>游戏机进化到光碟媒介之后,真正打动我心的,超不过10款.非要列出来的话,《Jet Set R...</td>\n",
       "      <td>47</td>\n",
       "      <td>132</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>209</td>\n",
       "      <td>2013-09-06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>WS-たねをまく鳥！~</td>\n",
       "      <td>Wonder Swan算是个设计独特的掌机。可以横着玩也可以竖着玩，但是发售游戏阵容中，实际...</td>\n",
       "      <td>25</td>\n",
       "      <td>248</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>210</td>\n",
       "      <td>2013-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>平民小英雄-パーマン！～</td>\n",
       "      <td>也来点漫画改编的游戏系列吧，就先从启蒙的 藤子.F.不二雄和藤子.A.不二雄的作品说起！~</td>\n",
       "      <td>34</td>\n",
       "      <td>119</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>211</td>\n",
       "      <td>2013-09-03</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>西单台球儿风云录！~</td>\n",
       "      <td>好多时候儿，1盘游戏摆我面前，想的并不是游戏的内容如何精彩，而是当年接触游戏时的一些生活片段...</td>\n",
       "      <td>28</td>\n",
       "      <td>152</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>212</td>\n",
       "      <td>2013-09-02</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>《いっき》-农夫起义的豪快行进曲！~</td>\n",
       "      <td>Sun-Soft公司现在能拿的出手的恐怕也只有《上海》系列了。而最打动我的还是《いっき》！！~</td>\n",
       "      <td>50</td>\n",
       "      <td>123</td>\n",
       "      <td>2013</td>\n",
       "      <td>09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>213</td>\n",
       "      <td>2013-08-30</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>公路上的轰鸣-《暴走卡车》回顾！~</td>\n",
       "      <td>日式艺术卡车游戏和历史背景回顾！~</td>\n",
       "      <td>47</td>\n",
       "      <td>49</td>\n",
       "      <td>2013</td>\n",
       "      <td>08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>214</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>PS1的冷门游戏合集-セロファーンズ ！</td>\n",
       "      <td>PS1时代被遗忘的冷门街机游戏合集-《セロファーンズ 》！~</td>\n",
       "      <td>50</td>\n",
       "      <td>78</td>\n",
       "      <td>2013</td>\n",
       "      <td>08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>215</td>\n",
       "      <td>2013-08-29</td>\n",
       "      <td>8</td>\n",
       "      <td>13</td>\n",
       "      <td>3DS的《热血硬派くにおくん》系列的前世</td>\n",
       "      <td>热血硬派くにおくん</td>\n",
       "      <td>54</td>\n",
       "      <td>27</td>\n",
       "      <td>2013</td>\n",
       "      <td>08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>216</td>\n",
       "      <td>2013-08-16</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>To Games——我的快乐时代</td>\n",
       "      <td>怀旧  长文</td>\n",
       "      <td>32</td>\n",
       "      <td>14</td>\n",
       "      <td>2013</td>\n",
       "      <td>08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>216 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     No.        time  likes  comments                      title  \\\n",
       "0      1  2017-04-02     35        32         陌生而熟悉的味道，欢迎来到美国街机厅   \n",
       "1      2  2017-03-30     55        16                缅怀素未谋面的郑问老师   \n",
       "2      3  2017-03-27     39        23   16-BIT游戏漫谈（4）——魔界村外传：纹章篇   \n",
       "3      4  2017-03-18     46        90           悠悠八载街机路：执著、热情与精通   \n",
       "4      5  2017-03-17     39        44  三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘   \n",
       "5      6  2017-03-13     14        60             火爆狂飙3：速度与对抗的巅峰   \n",
       "6      7  2017-03-13    294        80       《凯瑟琳》：性、生活与游戏底层的人性隐喻   \n",
       "7      8  2017-03-09     45        33      那会儿想买电脑就是为了跟印第安纳琼斯去冒险   \n",
       "8      9  2017-03-06     56        31                  我真的喜欢游戏吗？   \n",
       "9     10  2017-03-05     25        37       回顾FC时代的《仁王》——《不动明王传》   \n",
       "10    11  2017-03-02     37        30        《塞尔达传说》的这些广告，你都看过么？   \n",
       "11    12  2017-02-23     18        20             我和FC：保护那份最初的感动   \n",
       "12    13  2017-02-22     47        70         16-BIT游戏漫谈（3）——超级忍   \n",
       "13    14  2017-02-19     34       140             聊聊香港漫画改编的电影和游戏   \n",
       "14    15  2017-02-16     34        71               记忆中的“三国题材”游戏   \n",
       "15    16  2017-02-15     56        28  連仙水忍也為之羞澀：播音人黑盒子攻略錄影帶轉帶紀實   \n",
       "16    17  2017-02-14     18        49              网游考古系列：《最终兵器》   \n",
       "17    18  2017-02-12     26        42             网游考古系列：《疯狂坦克2》   \n",
       "18    19  2017-02-07     45        69                网游考古系列：《沃土》   \n",
       "19    20  2017-02-07    123       225             我所看过与玩过的《生化危机》   \n",
       "20    21  2017-02-05     19        41                   我与游戏的二三事   \n",
       "21    22  2017-02-05     75        58       回忆里的温暖角落——家中长辈们的游戏印记   \n",
       "22    23  2017-02-04     43        40         我的暑假20XX：真红少年与热血兄贵   \n",
       "23    24  2017-02-03     49        54              网游考古系列：《魔力宝贝》   \n",
       "24    25  2017-04-02     35        32         陌生而熟悉的味道，欢迎来到美国街机厅   \n",
       "25    26  2017-03-30     55        16                缅怀素未谋面的郑问老师   \n",
       "26    27  2017-03-27     39        23   16-BIT游戏漫谈（4）——魔界村外传：纹章篇   \n",
       "27    28  2017-03-18     46        90           悠悠八载街机路：执著、热情与精通   \n",
       "28    29  2017-03-17     39        44  三十年相伴相随——聊聊CAPCOM与僵尸的不解情缘   \n",
       "29    30  2017-03-13     14        60             火爆狂飙3：速度与对抗的巅峰   \n",
       "..   ...         ...    ...       ...                        ...   \n",
       "186  187  2013-11-05      1         0        《ゲームになった映画たち 完全版》！~   \n",
       "187  188  2013-10-29      0         1       《ダイナマイト刑事2》与海贼们的斗争！～   \n",
       "188  189  2013-10-28      4         8            神的孩子都喷火-《卡诺夫》！～   \n",
       "189  190  2013-10-24      1         1         怀古名作3D化之《青蛙过河3D》！～   \n",
       "190  191  2013-10-17      5         3       回到港产片吓哭你的时代-《灵幻道士》！～   \n",
       "191  192  2013-10-15      1         1           怪逼的《トリオ・ザ・パンチ》！~   \n",
       "192  193  2013-10-14      3         1       XBOX360首发作品：卡蜜欧—元素力量   \n",
       "193  194  2013-10-14      6         6         我其实还是喜欢VICE CITY！～   \n",
       "194  195  2013-10-11      2         0              我这14年PM经历的流水账   \n",
       "195  196  2013-10-10      2         4    初次接触Game Boy时所玩的游戏系列1！～   \n",
       "196  197  2013-10-08      4         6           黎明期的电子游戏-《铁板阵》！～   \n",
       "197  198  2013-09-29      2         6        悲惨的国庆节与《Konami世界》！～   \n",
       "198  199  2013-09-28      1         5                        进化！   \n",
       "199  200  2013-09-26      4         7      丧逼一家人--《とんでもクライシス!》！～   \n",
       "200  201  2013-09-25      3         6     怀旧游戏迷们最后的纸媒阵地-GameSide   \n",
       "201  202  2013-09-24      1         0           DS-《美文字トレーニング》!~   \n",
       "202  203  2013-09-23      1         0       電気グルーヴ游戏大时代《グルーヴ地獄V》   \n",
       "203  204  2013-09-16      0         1              PS-《風のノータム》！～   \n",
       "204  205  2013-09-13      1         1          ずんずん教の野望与朱莉安娜女郎!~   \n",
       "205  206  2013-09-12      0         2     翘曲空间的放浪冒险---Arkanoid！～   \n",
       "206  207  2013-09-11      0         7         Famicom上的知名西游记系列！~   \n",
       "207  208  2013-09-09      3         4  涂鸦小子的今与昔-《Jet Set Radio》！   \n",
       "208  209  2013-09-06      0         0                WS-たねをまく鳥！~   \n",
       "209  210  2013-09-05      0         3               平民小英雄-パーマン！～   \n",
       "210  211  2013-09-03      0         1                 西单台球儿风云录！~   \n",
       "211  212  2013-09-02      2         6         《いっき》-农夫起义的豪快行进曲！~   \n",
       "212  213  2013-08-30      1         3          公路上的轰鸣-《暴走卡车》回顾！~   \n",
       "213  214  2013-08-29      2         5       PS1的冷门游戏合集-セロファーンズ ！   \n",
       "214  215  2013-08-29      8        13       3DS的《热血硬派くにおくん》系列的前世   \n",
       "215  216  2013-08-16      3         8           To Games——我的快乐时代   \n",
       "\n",
       "                                              subtitle  title_len  \\\n",
       "0                               这是一篇价值约 12.5 美金的街机自助餐。         54   \n",
       "1                   很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。         33   \n",
       "2                                      由路边杂鱼升格为主角的另类作品         58   \n",
       "3                                  说说我的街机生涯，以及如何精通枪机游戏         48   \n",
       "4                               我从来没想到CAPCOM爱僵尸会爱的如此深沉         63   \n",
       "5                                  在13年前，娱乐向竞速游戏的巅峰出现了         40   \n",
       "6                                 正视自己的第一步，是了解欲望的来源在何处         60   \n",
       "7                人有很多第一次，而冒险始终让人跃跃欲试。探索秘密的青春啊～～让人欲罢不能。         63   \n",
       "8                                           我想，这就是答案了~         27   \n",
       "9                             其实仔细想想，过去真的是有一些游戏难得没什么道理         56   \n",
       "10                              《荒野之息》的广告，看塞尔达公主哭心里特难受         57   \n",
       "11                           当评价快乐的维度变多之后，快乐获取难度就随之增加。         38   \n",
       "12                                           最好的忍者游戏之一         40   \n",
       "13                                         一部老电影引发的怀旧情         42   \n",
       "14              除了光荣的《三国志》和《割草无双》，其实还有很多好玩的三国游戏在等待着我们！         36   \n",
       "15                     台灣最古老的電玩「實況」解說節目，與遙不可及的 Beta 年代         75   \n",
       "16                                    我多么希望这是一篇安利而不是悼词         39   \n",
       "17                                                炮，本能         40   \n",
       "18                                    现实是生活，游戏中为何还要生活。         33   \n",
       "19                                   可能是我见过最神奇的游戏系列，之一         42   \n",
       "20                                      从小到大，参与其中，乐在其中         24   \n",
       "21                                            致我最爱的亲人们         60   \n",
       "22                每一次少年们发现新大陆的时候，土坡上总有一群嚼着冰棍儿的大哥......         46   \n",
       "23                                         “魔力魔力，随心所欲”         39   \n",
       "24                              这是一篇价值约 12.5 美金的街机自助餐。         54   \n",
       "25                  很多人可能不清楚郑问老师对中国游戏行业的影响，他不仅仅是一位漫画家。         33   \n",
       "26                                     由路边杂鱼升格为主角的另类作品         58   \n",
       "27                                 说说我的街机生涯，以及如何精通枪机游戏         48   \n",
       "28                              我从来没想到CAPCOM爱僵尸会爱的如此深沉         63   \n",
       "29                                 在13年前，娱乐向竞速游戏的巅峰出现了         40   \n",
       "..                                                 ...        ...   \n",
       "186  电影改编游戏和游戏改编电影，一直都是大家关注和厌恶的话题，《Gameside》编辑部为此出版...         53   \n",
       "187                     3D动作清版游戏我玩儿的最多的还是《ダイナマイト刑事2》！～         58   \n",
       "188                  Data East公司的吉祥物比马里奥，索尼克那些看着霸道多了！～         43   \n",
       "189                        我最爱3DS的一点就是，能玩到不少怀旧名作的重制版！～         46   \n",
       "190                               看多了西洋僵尸，咱们也来点儿本土的吧！～         58   \n",
       "191                    Data East公司最怪的游戏当属《トリオ・ザ・パンチ》！～         46   \n",
       "192  《卡蜜欧—元素力量》是XBOX360的首发游戏之一，作为大名鼎鼎的RARE十年磨一剑的作品，...         46   \n",
       "193                  能跟掌机上玩到GTA系列，以前一直觉得是件可望而不可即的美事儿！～         36   \n",
       "194                                      我这14年PM经历的流水账         31   \n",
       "195  第一次玩的那盘GB盗版合卡里的小游戏，现在想起来都很难忘，那种乐趣是以往俄罗斯方块掌机所难以...         51   \n",
       "196            我的名字安藤杰尼斯便是音译自《铁板阵》里的母舰-Andor Genesis！～         46   \n",
       "197                               20世纪游戏小子的国庆节到底是什么样呢？         45   \n",
       "198                                                进化！          9   \n",
       "199                                   丧逼一家人的日常究竟是什么样呢？         57   \n",
       "200                       《GameSide》大概是怀旧游戏迷们最后的纸媒阵地了。         48   \n",
       "201        没有智能手机的各种应用软件的时代，DS上总是有各种有意思的教育软件登场，真令人怀念！～         38   \n",
       "202              与音乐家跨界合作的游戏中，具有KUSO味的肯定还得是《グルーヴ地獄V》！~         58   \n",
       "203                         乘坐热气球旅行的游戏会给我们带来治愈性的体验吗？？？         33   \n",
       "204                        今天是周末，来聊点儿和大妞儿有关系的游戏话题吧！！！~         47   \n",
       "205                        《Arkanoid》大概属于那种能玩到世界末日的游戏。         44   \n",
       "206         每年暑假电视台都会重播《西游记》电视剧。不过，以《西游记》为题材的游戏你玩过多少呢？         38   \n",
       "207  游戏机进化到光碟媒介之后,真正打动我心的,超不过10款.非要列出来的话,《Jet Set R...         47   \n",
       "208  Wonder Swan算是个设计独特的掌机。可以横着玩也可以竖着玩，但是发售游戏阵容中，实际...         25   \n",
       "209      也来点漫画改编的游戏系列吧，就先从启蒙的 藤子.F.不二雄和藤子.A.不二雄的作品说起！~         34   \n",
       "210  好多时候儿，1盘游戏摆我面前，想的并不是游戏的内容如何精彩，而是当年接触游戏时的一些生活片段...         28   \n",
       "211    Sun-Soft公司现在能拿的出手的恐怕也只有《上海》系列了。而最打动我的还是《いっき》！！~         50   \n",
       "212                                  日式艺术卡车游戏和历史背景回顾！~         47   \n",
       "213                     PS1时代被遗忘的冷门街机游戏合集-《セロファーンズ 》！~         50   \n",
       "214                                          热血硬派くにおくん         54   \n",
       "215                                             怀旧  长文         32   \n",
       "\n",
       "     subtitle_len  year month  \n",
       "0              54  2017    04  \n",
       "1             102  2017    03  \n",
       "2              45  2017    03  \n",
       "3              57  2017    03  \n",
       "4              54  2017    03  \n",
       "5              53  2017    03  \n",
       "6              60  2017    03  \n",
       "7             111  2017    03  \n",
       "8              28  2017    03  \n",
       "9              72  2017    03  \n",
       "10             66  2017    03  \n",
       "11             75  2017    02  \n",
       "12             27  2017    02  \n",
       "13             33  2017    02  \n",
       "14            114  2017    02  \n",
       "15             81  2017    02  \n",
       "16             48  2017    02  \n",
       "17             12  2017    02  \n",
       "18             48  2017    02  \n",
       "19             51  2017    02  \n",
       "20             42  2017    02  \n",
       "21             24  2017    02  \n",
       "22             96  2017    02  \n",
       "23             33  2017    02  \n",
       "24             54  2017    04  \n",
       "25            102  2017    03  \n",
       "26             45  2017    03  \n",
       "27             57  2017    03  \n",
       "28             54  2017    03  \n",
       "29             53  2017    03  \n",
       "..            ...   ...   ...  \n",
       "186           185  2013    11  \n",
       "187            84  2013    10  \n",
       "188            81  2013    10  \n",
       "189            75  2013    10  \n",
       "190            60  2013    10  \n",
       "191            75  2013    10  \n",
       "192           297  2013    10  \n",
       "193            93  2013    10  \n",
       "194            31  2013    10  \n",
       "195           149  2013    10  \n",
       "196            89  2013    10  \n",
       "197            56  2013    09  \n",
       "198             9  2013    09  \n",
       "199            48  2013    09  \n",
       "200            68  2013    09  \n",
       "201           125  2013    09  \n",
       "202            99  2013    09  \n",
       "203            78  2013    09  \n",
       "204            79  2013    09  \n",
       "205            65  2013    09  \n",
       "206           126  2013    09  \n",
       "207           132  2013    09  \n",
       "208           248  2013    09  \n",
       "209           119  2013    09  \n",
       "210           152  2013    09  \n",
       "211           123  2013    09  \n",
       "212            49  2013    08  \n",
       "213            78  2013    08  \n",
       "214            27  2013    08  \n",
       "215            14  2013    08  \n",
       "\n",
       "[216 rows x 10 columns]"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10cbbfbd0>"
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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u+gY5H8TRRx/Nd77zHb7//e9zwQUX8MEPfjDj+hdddBGlpaWUlpZy5plnsnz5cmpqagZd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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10df7a090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = df.loc[:, ['title_len','subtitle_len']][::-1].plot()\n",
    "\n",
    "fig.grid(True)\n",
    "plt.xlabel('Artical No.')\n",
    "plt.ylabel('Title/Subtitle Length')\n",
    "plt.title('Trend of Title/Subtitle Length')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10bacb910>"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XTExC4CkQEKV8EFkrD8LnSNazBUSifh9B8mQJCCnl/xFC3A0sAe6UuavrAT5c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\nnpQnRbrN7AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b341dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = df['subtitle_len'].plot()\n",
    "fig.grid(True)\n",
    "plt.xlabel('Artical No.')\n",
    "plt.ylabel('SubTitle Length')\n",
    "plt.title('Trend of SubTitle Length')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}