Live 02-02 - Short Squeeze.ipynb

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   "source": [
    "# 1. Abrindo Bibliotecas"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bibliotecas genérias"
   ]
  },
  {
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   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-13T22:45:51.610943Z",
     "start_time": "2020-04-13T22:45:48.198631Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### As seguintes bibliotecas serão alvo do nosso estudo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas_datareader import data\n",
    "import quandl\n",
    "import cufflinks as cf\n",
    "import yahoofinancials"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A intenção desse estudo é trazer dados úteis que podem esclarecer um pouco mais o que aconteceu com GME na situação do short squeeze"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conceito de Data Hedging\n",
    "https://www.investopedia.com/terms/d/deltahedging.asp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O que é o Short Interest?\n",
    "\n",
    "https://www.investopedia.com/articles/01/082201.asp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Cufflinks"
   ]
  },
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    "cf.set_config_file(theme='pearl',sharing='public',offline=True)"
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   "source": [
    "gme = data.DataReader('GME', data_source='yahoo', start='2020-12-01')"
   ]
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{\"bgcolor\": \"rgba(150, 200, 250, 1)\", \"buttons\": [{\"count\": 1, \"label\": \"1m\", \"step\": \"month\", \"stepmode\": \"backward\"}, {\"count\": 1, \"label\": \"1y\", \"step\": \"year\", \"stepmode\": \"backward\"}], \"font\": {\"size\": 13}, \"visible\": false, \"x\": 0, \"y\": 0.9}, \"rangeslider\": {\"visible\": false}, \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis\": {\"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"showticklabels\": false, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis2\": {\"domain\": [0.69, 0.9], \"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis3\": {\"domain\": [0.46, 0.61], \"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis4\": {\"domain\": [0.23, 0.38], \"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis5\": {\"domain\": [0.0, 0.15], \"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}},                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('1ac35ae9-7a15-4a4f-90ca-e481b344b26e');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "qf=cf.QuantFig(gme,title='GME Quant Figure',legend='top',name='GS')\n",
    "\n",
    "qf.add_adx()\n",
    "qf.add_cci()\n",
    "qf.add_dmi()\n",
    "qf.add_ema()\n",
    "\n",
    "qf.iplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Quandl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Quandl será usada aqui para capturar dados do Volume de Ações Vendidas (Short Sale Volume) obtidos da FINRA.\n",
    "\n",
    "O que é isso?\n",
    "\n",
    "Seguindo uma norma da SEC, a FINRA disponibiliza publicamente dados diários do volume de papéis vendidtos (short) de negociações de ações não listadas em exchanges (over the counter securities), reportadas ao OTC Reporting Facility.\n",
    "\n",
    "Esses dados fornecem o volume agregado por ação de todas as negociações vendidas executadas e reportadas à OFR durante o horário de pregão.\n",
    "\n",
    "Para saber mais sobre os dados:\n",
    "https://www.finra.org/filing-reporting/orf/orf-regulation-sho\n",
    "\n",
    "\n",
    "Para saber mais sobre a OFR:\n",
    "https://www.finra.org/filing-reporting/over-the-counter-reporting-facility-orf#:~:text=The%20OTC%20Reporting%20Facility%20(ORF,dissemination%20of%20last%20sale%20reports."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Documentação da FINRA na Quandl\n",
    "\n",
    "https://www.quandl.com/data/FINRA/FNYX_GME-FINRA-NYSE-TRF-Short-Interest-GME"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Agora que você já obteve seu token de acesso a Quandl, vamos salvá-lo num arquivo .txt de nome \"senha\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A seguir, vamos abrir esse arquivo, e chamar de \"token\" o seu conteúdo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Chave da Quandl vem num formato parecido com esse:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = open(\"senha.txt\", \"r\")\n",
    "\n",
    "token = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'77TfLxTY9XzxycV_uzSe'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "token"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "quandl.ApiConfig.api_key = token"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "quandl.ApiConfig.api_key = \"77TfLxTY9XzxycV_uzSe\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note que tanto esse resultado quanto o do S&P 500 são consolidados por mês"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "finra = quandl.get(\"FINRA/FNYX_GME\", trim_start = \"2020-08-01\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ShortVolume</th>\n",
       "      <th>ShortExemptVolume</th>\n",
       "      <th>TotalVolume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>28678.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>167741.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-04</th>\n",
       "      <td>434953.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1411726.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-05</th>\n",
       "      <td>205375.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>459608.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-06</th>\n",
       "      <td>69919.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>199033.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-07</th>\n",
       "      <td>143366.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>339322.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            ShortVolume  ShortExemptVolume  TotalVolume\n",
       "Date                                                   \n",
       "2020-08-03      28678.0                0.0     167741.0\n",
       "2020-08-04     434953.0                0.0    1411726.0\n",
       "2020-08-05     205375.0                0.0     459608.0\n",
       "2020-08-06      69919.0                0.0     199033.0\n",
       "2020-08-07     143366.0                0.0     339322.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finra.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explicar\n",
    "* O que é a FINRA\n",
    "* O que são Market Makers\n",
    "* O que é hedge\n",
    "* O que são calls - opções de compra\n",
    "* Falar que nos EUA a margem precisa ser respeitada, se não o vendido (short seller) precisa comprar o papel\n",
    "* O que é o short interest?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Procurar dados de compra do papel e hold por parte dos acionistas\n",
    "\n",
    "# Uma opção é mostrar isso através da diminuição do float geral do papel\n",
    "\n",
    "# Quanto do free float passou a ser 'segurado' pelos acionistas?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x191eb0d3d00>,\n",
       " <matplotlib.lines.Line2D at 0x191eb369550>,\n",
       " <matplotlib.lines.Line2D at 0x191eb369490>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "finra = quandl.get(\"FINRA/FNYX_GME\", trim_start = \"2020-08-01\")\n",
    "plt.figure(figsize=(9,7))\n",
    "plt.plot(finra)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x191eb58b490>,\n",
       " <matplotlib.lines.Line2D at 0x191eb3e1c70>,\n",
       " <matplotlib.lines.Line2D at 0x191eb3e1bb0>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ktvFqNqAwgw2rW2cqMxtgBhv+iJ+tx7aOuNzqsTFhsCEdRIUQQuQyyWyMZNVHpLJmA2BNwxrsys5LR14acfl43UMtEmwIIYTIeeO1K4cCDTaircFTuRoFzJ/p8prlY5p7tXnbKHIUxepkRpNgQwghRM4LGSEUCrs63lAqFmwUYBdRK7ORio3YRlvbuJZtXdtGBHHW1vJKqbi3kWBDCCFEzgsZIZw254g3O7fdjcvmoj/Yn8GRZYaV2UhVu/Lh1jWuw9AGr7W/Frus3Tv+slcwa0ck2BBCCJHTgpEgLrtrzOWFuhlbLNhIcc0GwIraFRQ5ikYsgZ2oeyjIahQhhBB5wMpsjFawwUYkfZkNl93F6vrVsWAjGAnS5e8at3somMFGWIdje9jkOgk2hBCiAIWNcNxgo9xVXpjBRhqnUcDcBXZ/337ave10eDuA8Ze9wvHakXxp7CXBhhBCFKCQERrRY8NSqJkNqz4iHdMoYNZtgLnlvNVjY7xlr3A82MiXluUSbAghRAEKRWQaZbh0ZzYWVy2m2lPNy20v0z40cfdQkMyGEEKIPBAyQjhsjjGXF2qw4Qv7gPQsfQWwKRunN5zOy20v0zZoZjbqiyeo2Yh2MrWCoFwnwYYQQhQgKRAdyZpGSXVTr+HWNa6j09fJi0depNpTPWEWxQp68mX566TBhlKqSSn1tFJqp1Jqu1Lqc3GOUUqpHyul9iilXldKrU7PcIUQQqTCRDUbQSOYN29yibIyCOnKbACsm23WbWw6umnCeo3h48iX30MimY0w8E9a62XAOuDTSqmTRh3zDmBx9HQj8IuUjlIIIURKjZvZcBZmy3J/xI/T5sRus09+8BTNKZ1DU1kTAA3FEmyMoLVu01pvip4fAHYCc0YddgVwqza9DFQqpcavfBFCCJFRwUgQly1+Uy+g4LqI+sP+tBWHDmetSmksnfgtsuCCjeGUUguAVcAro66aA7QM+76VsQEJSqkblVIblFIbjh07luRQhRBCpMpE0yhQmJmNdC17HS4WbEywEgUKONhQSpUC9wCf11qPDnnj7SSjx1yg9a+01mu01mtqa2uTG6kQQoiUmahAFAow2JihzMYZs89gdd1qTm84fcLjrNUo+dKyfOy6pziUUk7MQON2rfWf4xzSCjQN+34ucGT6wxNCCJEO4/XZsLY8l2AjPcpcZfzuHb+b9LiCy2woc0vAXwM7tdY/GOewB4Dro6tS1gF9Wuu2FI5TCCFECklmY6RAJDAj0yiJyrdgI5HMxlnAh4E3lFJbopf9GzAPQGt9M/AwcBmwBxgC/i7lIxVCCJEyUrMxki/sm5HMRqKswKdggg2t9fPEr8kYfowGPp2qQQkhhEiv8TZic9vdOG3Oggs2/BE/1c7qTA8jJt8yG9JBVAghCtB4NRtKqYLsIhoIB9LaPTRZDpsDm7JJsCGEECJ3jVezAYXZsnymlr4mSimF2+7Om9UoEmwIIUQBChrBuDUbYHYR7Q8VXlMva7lptnDb3ZLZEEIIkZsiRgRDG5LZGCbbMhsALrtLgg0hhBC5KWSEACTYGGam+mwkw2P3SLAhhBAiN0mwMVLICBHREclspJEEG0IIUWBiwcY4NRvlrnIGg4MzOaSMsraXl8xG+kiwIYQQBSYUmTyz4Y/4CUaCMzmsjLHe0CWzkT4SbAghRIFJZBoFCqeLqC/sA7Iws+GQzIYQQogcNVmwUeoqBQon2LCmUbJt6avL7pI+G0IIIXJTIjUbUDjBhpU9KLJnTwdRkJoNIYQQOcyq2XDZXHGvl2mU7CA1G0IIIXLWpDUbTjPYKJQuotYburX5WbaQzIYQQoicNdk0SqFlNqyajWzaiA0ksyGEECKHJbL0FQon2LCmUbIusyGrUYQQQuSqyaZRihxFOJSjYBp7xfpsZGHNRtgIEzEimR7KtEmwIYQQBcYKNhw2R9zrlVKUucroDxZGzUa2TqNYTcbyIbshwYYQQhSYyWo2oLD2R/FHon02smwaxWU3VwtJsCGEECLnTDaNAmZjr4IJNsLZGWxIZkMIIUTOmqxAFAossxH247F7UEpleigjSGZDCCFEzgoa5gZrEwUb5a7ywgk2Iv6sKw6F4wWrEmwIIYTIObEOovb4HUShADMbWRhsWNM6+bA/igQbQghRYBKp2ShzljEQKpBgI+LPuu3l4XiwYRWw5jIJNoQQosAkFGy4yvCFfbEsSD4LhANZndkIRoIZHsn0SbAhhBAFJmSEsCkbdpt93GNiXUQLILvhi/iybiUKSGZDCCFEDgsZoQmzGnA82CiELqKS2Ug/CTaEEKLAhCKTBxvlrnKgMPZH8Uf8FNmzq3sogNsRzWyEJbMhhBAixyST2SiEluX+sD/2xp5NJLMhhBAiZ4WN8KTBRqmrFCiczIasRkkvCTaEEKLABCPBCfdFgQKbRsnSPhtWACSZDSGEEDknmWmUQgg2ApFAVmY2HDYHCiWZDSGEELknZIQmzWwUO4qxKVve12xorfGFfVmZ2VBK4XF4JLMhhBAi9ySS2VBKFUTLcmvfkWwMNsBsKS+rUYQQQuScRJa+QmG0LI8FG1k4jQJmkai1cV4uk2BDCCEKTCKZDTDrNvK9qZcv7APIyqWvYAYbktkQQgiRcxINNgphm/mcyGxIzYYQQohck0iBKJiZjXwvELWyBkWO7OsgCtHMhqxGEUIIkWsSzWyUukrzPrMRm0bJwo3YQDIbQgghclTCBaKyGiXjJLMhhBAiJ4WMEC67a9LjylxlDIWHCBvhGRhVZljTKFlbs+GQzIYQQogclGhmw2pZns8rUqysQVZnNmQ1ihBCiFwTMkI4bI5JjyuEluWxzEYWBxuS2RBCCJFzEu6z4YxuMx/K3xUpWT+NIjUbQgghclEyS18B+gN5HGzkwDSKZDaEEELknEQzGxXuCoC87rUhmY2ZIcGGEEIUkIgRwdBGUsFGX6Av3cPKmEAkgF3ZE6phyQS3w03YCBMxIpkeyrRIsCGEEAUkZIQAJNiIsraXV0pleihxWc3GrH4guUqCDSGEKCDWDqKJBBtuu5siR1FeBxv+iD9ru4fC8WAj1+s2JNgQQogCEoqYmY1EmnqB2WujL5i/wUYgHMjafVHgeLCR63UbEmwIIUQBSWYaBcyplN5AbxpHlFmS2ZgZEmwIIUQBiQUbCSx9Bah0V+b30tewP2uXvYJkNoQQQuSgqWQ28r1mI1uXvcLx/h+S2RBCCJEzrJqNRIONfK/ZyPbMhlVbk+v7o0iwIYQQBcTawTXZmg2tdTqHlTFZn9mwS2ZDCCFEjkl2GqXSXUnYCOML+9I5rIzxh/24HdlbIBrLbEjNhhBCiFyRbIFovjf2yvalrwWT2VBK/UYpdVQptW2c69crpfqUUluip6+lfphCCCFSIdmajQpXNNjI07oNX8SX1dMo+ZLZSKQZ/G+BnwK3TnDMc1rry1MyIiGEEGmTTAdRgHJ3OUDe9trI9mkUq3g1EM7zduVa62eB7hkYixBCiDSbSp8NyM9plIgRIWSEKLJn7zSKldmQvVFMZyiltiqlHlFKnTzeQUqpG5VSG5RSG44dO5aihxZCCJGopKdR8rhmw3oDz+rMRnSKR4IN2ATM11qvAH4C3DfegVrrX2mt12it19TW1qbgoYUQQiQj2dUo5S5zGqU/mH9dRK06iGyu2XDanCiUBBta636t9WD0/MOAUylVM+2RCSGESLlkgw2Pw4PH7qHX35vGUWWG1Sgrm1ejKKVw290SbCilGpRSKnr+9Oh9dk33foUQQqResjUbEG1ZnoerUaxgI5s3YgNzmifXg41JV6Mope4E1gM1SqlW4OuAE0BrfTNwFfBJpVQY8AHX6nxtNSeEEDku2ZoNyN/9UWLTKFncrhzAbSuAYENrfd0k1/8Uc2msEEKILJfsNArkcbARzv6aDciPzIZ0EBVCiAIylWCj0l2Zn8FGrmQ27O7877MhhBAifwQjQWzKht1mT/g2+brzayyzkQvBhmQ2hBBC5IqwEcZlcyV1G2saJd/K8XJmGkWCDSGEELkkZISSmkIBM9gIGaG82/nVegOXzEb6SbAhhBAFJGSEklr2CvnbstwKnrJ+6asEG0IIIXJJyAjhsCWyB+dx+brzq/UGns1NvUBWowghhMgxoUjy0yjWzq/5ltnImaZeshpFCCFELplqzQbkX7Dhi/hw2pxJrczJBJlGEUIIkVOmU7PRG+hN/YAyKBAOZH1xKEiwIYQQIsdMJbORrzu/+iP+rF/2ChJsCCGEyDHBSDDpYMPa+TXfplH8YX/OZDZCRoiIEcn0UKZMgg0hhCggISOEy55cUy8wi0Ql2MgMt8MsYA0awQyPZOok2BBCiAIylWkUMOs28q1mI5emUYCcXpEiwYYQQhSQqSx9hfzc+TVnMhtWsJHDdRsSbAghRAGZamajwlWRlwWi2d5jAyTYEEIIkWPCRlgyG1GBcCDru4eCBBtCCCFyzFT6bIAZbPQGerNm59c3u9/kgb0PTOs+cq5mQ4INIYQQuWA6NRvZtPPrf7z8H3zzxW9OK/jxhX2xlR7ZzBqjBBtCCCFywlQ2YoPjm7FlQ93GlqNbeP3Y6wSNIEPhoSnfTyASyK3MhqxGEUIIkQuCRvJNvSC79ke5bcdtsfM9/p4p34+sRpk5EmwIIUQBCUWm1tTLCjYy3Wvj8OBhnjj0BIsqF01rPCEjRERHciuzIcGGEEKIbKe1HrP09daXDrC7Y2DS22ZLZuP2nbdjw8YnVnwCgG5/95Tux9peXjIbM0OCDSGEKBARHUGjY8FGxNB87f7t/PG1lklva9Vs9AUzF2wMBgf58+4/8/bmt7O0eikw9cxGLNiQzMaMkGBDCCEKRMgIAcSWvg4FwwB0eyffcyMbMht/3v1nvCEvHz7pw1R5qoCp12z4IzmU2ciD1SjJlyQLIYTISbFgw2YFG+Yuol0JBBuZ3vk1bIS5feftnFZ/GifPOhmtNXZln3ZmIyeWvkpmQwghRK4IRUYGG4MBM7PR5U3sTSyTO78+eehJjniPcP1J1wOglKLSXTnlzIb1xl1kz/4Ooi6bWdArwYYQQoisNyazEYhmNgYT27o8ky3Lb9txG01lTZw397zYZVWeqikHG1ZzslyYRlFK4ba7pc+GEEKI7De6ZsMbtDIbwYQ6cVa4KjJSILrl6Ba2HtvKh5Z9CLvNHru8ylM1/WmUHNiIDcxxSmZDCCFE1hs9jWIViAbDRmxKZSKV7sqMZDZu23EbZa4yrlx05Zjx9ASmOY2SAxuxgblqRoINIYQQWW/0NMpgdBoFEl+RMtPBhtXE66oTr6LYWTziuip3Fb3+3indrzWNkiuZDZfdFVtBk4sk2BBCiAJhBRtWB9GhYdmMzgTqNqwC0Znc+fWOnXdgw8YHln5gzHXWNErEiMS55cSsLEEu1GyAOc5gJLHammwkwYYQQhQIK9iwNmLzBo+/SXcNTp6ir3BVEDSCM7bz62BwkHt238MlCy6hoaRhzPVVnio0ekqbw1k1G7kyjeKyu2JjzkUSbAghRIEYU7MxLLORyDRKpbsSmLmdX+/dcy/ekDe23HW88UylbsOaksiVaRSPXTIbQgghcsCYmo1gGLtNAYk19prJLqJWE6/Vdas5uebkuMdUuc0uolOp28i11ShSsyGEECInjGlXHohQUeSkxGVPqNfGTAYbTx16isODh7n+5PhZDWBaLcv9YT8euwel1JTHOJNyPbMh7cqFEKJAjM5seINhil12St2OhLqIzuQ287ftuI25pXNZP3f9uMfEgo0pTqPkSnEoSGZDCCFEjhhds+ENhClxOagucSW29HWGdn7demwrW45t4UMnjWziNWY80wh+/OHcCjZkNYoQQoicEDTMN6vhG7GVuO3UlLoSWvo6U9Mot+24jTJnGe9Z9J4JjytyFFHkKJraNErEnxPby1tkNYoQQoicMGYaJRCmxG1mNhJZ+upxeHDb3fQH0rca5cjgEZ44GL+JVzxV7qntjxIIB3Irs5HjNRsSbAghRIGwplFiTb2CEYpddmaVuulOdH8Ud0Vaazbu2HkHAB9YNraJVzyVnqm1LPdFfDmzEgWkZkMIIUSOGNuu3KzZmFXiImxo+n2T74+Szpbl3pB3wiZe8Uy1ZXnO1WzYPYSMEIY2Mj2UKZFgQwghCsSYpa/BCCVuB7NKzUxHQitS0rjz672772UwNDhuE694pprZCEQCFNlzo3soHM9G5epmbBJsCCFEgYi1K1fRduWBMMVuO7NKzOmERBt7pSOzETEi/H7n71ldt5rlNcsTvt1Uazb8YT9uR+5Mo1hZmFyt25BgQwghCkQoEsKu7NhtdsIRg0DYiC19hcT2R0nXNvNPtUSbeCWR1QCz18ZQeCjpT/y5uBoFyNkVKRJsCCFEgQgb4WENvcxN2IpddmpKE89spGvn11u332o28Wpan9TtrP1Rkq3byMWaDZDMhhBCiCwXMkLDemyYxaCl7uGZjcQaewWNYEpXRrx+7PWEmnjFY3URTXaFjNWuPFfEMhs5uiJFgg0hhCgQwUgwVhzqDUQzG24HLoeNMo8jsS6iaWjsZTXxunLRlUnf1tqMrdvfnfBttNY5165cMhtCCCFyQsgI4bCZxaFWZqPEZWYSakrddCZYswGpCzbaBtt4/ODjvO/E91HiLEn69lPJbFj1HbkUbEhmQwghRE4IGSFcNvNNazBgBhvFLjP4MLuIznxm445d0SZeSxNr4jWaFfwksyLFCjZyqamXFRjJ0lchhBBZLWSERmwvD2bNBsCsBDdjK3eVA6nZjM0b8nL3W3dzyfxLaCxtnNJ9TGUzti5fF3A8K5ILYn02whJsCCGEyGKhSGjE9vIAxW5zGmVWqSupbeZTkdmwmnh9+KQPT/k+HDYHFe6KpGo22rxtADSWTC3AyQSrZiNgSLAhhBAiiw1fjWIViJa4rMyGuT+KYUy8pDW21HSa+6NYTbxW1a3ilNpTpnVfVe6qpMaTi8GGZDaEEELkhHhLX0uGZTYMDb2+0IT3kaqdX59ueXpKTbziqXRXJtVno83bhk3ZqC2unfZjz5RYZkNqNoQQQmSz4TUbsaWvwwpEAbpnaH+UW3fcypzSOZzfdP607gfM2otk9kdp97ZTW1QbC7xygeyNIoQQIieMzmx4nDbsNgUQ6yLamcCKFKuL6FS9cewNNh/dzIeWJd/EK54qT3L7o7R523JqCgVkNYoQQogcMbxA1Npe3pJMF9FKd+W0ajZu23Ebpc5S3rP4PVO+j9Hj6Qn0JNxCvW0w94INa8ly3gYbSqnfKKWOKqW2jXO9Ukr9WCm1Ryn1ulJqdeqHKYQQYrpGZjbM7eUt1jbzCU2jTGPn17bBNv568K+8b/HUmnjFU+WuImyE8Ya8kx5raIP2oXYaShtS8tgzRSmF2+7O32AD+C1w6QTXvwNYHD3dCPxi+sMSQgiRaiNrNsIUu45PYVQXm8FGItMoFe6KKReI3rnrTgA+sGxqTbzisfplJFK30eXrImyEcy6zAWbdRt6uRtFaPwtMtID5CuBWbXoZqFRK5d5vUQgh8tzwaZTRmQ2H3UZlsTOx/VGmWCBqNfG6eP7FzC6dnfTtxxMLNhKo28jFZa8Wj92T15mNycwBWoZ93xq9bAyl1I1KqQ1KqQ3Hjh1LwUMLIYRI1PBplMFRmQ0wu4gm2tgrEAngC/uSevz79tzHQGhgWk284kmm90cuBxv5Po0yGRXnsrhVOlrrX2mt12it19TW5s76ZiGEyAejV6OUDstsgNnYK9FpFEiui2jEiPD7Hb9nZe1KTq09NYlRT87a+TWRzEa7tx2AhpLcqtkACTZagaZh388FjqTgfoUQQqTQ6D4bxa5RwUZpYvujTCXYeKblGVoHW7n+5Ok38RotmZ1f27xtFDuKY3u85BK3o7CDjQeA66OrUtYBfVrrthTcrxBCiBQavTeK1T3UMqvURVcC28xXuMxgoz+YeJGo1cTrgqYLkhhxYkqcJThsjoT2R7GWvSoVLymf3XI5s+GY7ACl1J3AeqBGKdUKfB1wAmitbwYeBi4D9gBDwN+la7BCCCGmRms9cholTmajusRNry9EOGLgsI//WTTZnVa3dW5j09FNfOltX0pJE6/RlFIJ74/S5m3LuWWvFrfdjT/sz/QwpmTSYENrfd0k12vg0ykbkRBCiJSL6AgajdPmJBg2CEYMSkdlNmpKXWgNPUMhasvc495XstMot+641WzitSg1TbziqfRUJlyzcXLNyWkbRzq57e6U7LabCdJBVAghCkAwYtZiOO1OfMGR+6JYju+PMnHdRjLBRru3nb8e+CvvXfxeSl2lSY87UdXu6kkzG76wj55AT06uRIHcnkaRYEMIIQpAyDB3c3XZXAyO2vHVMqvEzGZMVrfhsXtw2VwJ9dq4Y+cdaDQfXPbBqQw7YYlkNqyVKBJszDwJNoQQogBYwYbT5mQoYAYb8VajAHROktlQSlHprpw0szEUGkpLE694rP1RJpLLy15BVqMIIYTIcmHDDDCcdife6DTK2D4b0WmUBFakJLLz67177k1LE694qjxV9Af6Y88znrzIbORru3IhhBC5LxSJl9kYOY1SWezCpqArwV4bEwUbVhOvFbUrWFG7YhojT0yVuwqNnnA5bpu3DYWivrg+7eNJB5lGEUIIkdWGT6MMBqyajZGZDbtNUVXsSizYmGR/lGdao028Tkp9E694Etkfpc3bRm1RbayxWa5x290EjSCGNjI9lKRJsCGEEAVgRM1GdBpldLABiTf2qvRU0ucfP9i4dfutzC6ZzQXzUt/EK+54ovujTBZs5GqPDTCDDTi+siiXSLAhhBAFIBZs2J14rdUorrENtqpLXHQlsj/KBJmN7Z3b2XR0Ex9c9kEctknbOaVEIi3L273tOVuvAceDjVycSpFgQwghCoAVbDhsDoYC0T4bcTMb7oT2Ryl3lxOIBOJ2tLx1x62UOEt47+L3TnPUiYttxjbOihStdaxVea5yOyTYEEIIkcViTb2G1WwUO8dmNmpKXHQmMo0SnbYYXSQ6U028xozHY45nvGmUbn83QSOYs8teYVhmIwdXpEiwIYQQBWBkzUaYYpcdm23sZmTVJW76/WGC4YmLEMfbH+WOXXdgYKS9iddobrubYkfxuMFGri97BZlGEUIIkeWspa8uuwtvcOwmbBarsVfP0CQty+Ps/Go18bpo3kXMKZ2TimEnpcoz/mZsbV5zM/JEg41wJPtWfEiwIYQQIqsNz2x4A2O3l7dYjb0mKxKNtz/KfXvuYyA4M0284qlyV41bs5FMsPHi3k5O+cZf2Xhw8o3dZpIEG0IIIbLayGBjosxGdH8U78RvaKOnUSJGhN/v/D2n1p7KyrqVqRl0kibaH6XN20aRoyg27om80dqHLxTh83/czIA/lOphTpkVbPgjubfNvAQbQghRAIYvfR0KhsdsL2+pnmJm45nWZ2gZaJmxJl7xVLmr6PX3xr2u3dtOQ0kDSo2tUxmtpWcIl8PGkV4/X7t/e4pHOXXWahTpsyGEECIrjchsTFCzUROt2Zisi+jonV9v23Ebs0tmc+G8C1M46uRUeSaYRkli2WtLt48l9WV85oJF3Lv5MPdvOZzKYU6Z2yaZDSGEEFls+N4oE9VslHucOGxq0i6iSikq3BX0B/rZ3rmdjR0b+cCyD8xYE694qjxV+MK+uL0/2rxJBBs9Q8ytKuIfz1/EafOr+Oq922jpHkr1cJMmmQ0hhBBZbfQW8+NlNmw2RVWJK6HGXhXuCnoDvRlp4hWP1ftj9IqUQCRAl78roR4bhqFp7fHRVF2Mw27jh9esBOALf9yS8RUqsZqNOMFUtpNgQwghCsDIduWRMdvLDzerxEVnIi3L3RXs6d0Ta+JV5ipL2XinItZFdFSRaIe3A0hsJcqxwQDBsEFTVREATdXFfOvK5Ww42MPPn9mb4hEnR/ZGEUIIkdVGbDEfbeo1nlmlrklXo4DZa+Ng/8GMNPGKJ7bz66i6jWSWvVrTJXOri2OXXblqDlesnM2Pntyd0eWwshpFCCFEVgsZIRzKQSiiCUV03B1fLbNKEtsfxVqRcuG8CzPSxGs0q2X56BUpyQQbrT0+AJqqikdc/q0rl9NY4cnocljJbAghhMhqISNkLnuNbsIWb8dXi7nN/ORvaFaNRCaXuw433mZsVrBRX1I/6X3EMhvRaRRLucfJD69ZyeEeH19/IDPLYZVSuGyunMxsZK5sWAghxIwJGSEcNkdse/l4O75aZpW4GAyE8YcieOJs1ma5YtEV1BbXZqyJ12jlrnIUakzNRru3nZqiGlx216T30dIzRG2ZO+7zXrOgms9csJgfPbmb9UvqePeK2Skbe6LcDrdkNoQQQmSnUCQU6x4KUDLOahQ43kV0sqmUEypPyFhr8njsNjuV7soxq1GS7bHRNCqrMdxnLljE6nmVfOXeN2jtmfnlsG67W1ajCCGEyE4hIxpsxDIb42csrC6iidRtZJt4LcvbvG0Jby3f0jNEU3XxuNc77DZ+dO0qtM7Mcli3XTIbQgghspQVbFg1GxMtfbW6iHZO0tgrG1W5R+78qrWm3dueUGYjHDFo6/OPKQ4dzVwOezKvHejhFzO8HNZj9+RkzYYEG0IIUQCsAtFYZmOCAtHqkuhmbAkUiWabSncl3f7u2Pe9gV78EX9CwUZbn5+IoWmqHn8axXLlyjm8e8VsfvjkbjYdmrnlsC67SzIbQgghslMwEoy1KofJajZydxqlyjMys5FUj41oDcZkmQ0wV4Z8+z3LaSj38Pk/bJmx5bAeh2Q2hBBCZKnjNRvmNMpENRtlbgcuu43OBBp7ZZsqj7nzq9YaOB5sNJROXrPR2m322JibQLAB5nLYH127ktaeIb7xwI4pjjg5ktkQQgiRtUJGCJfdxVA0szFRzYZSiuoSF905Oo0S1mEGQ4OAuewVEs9s2BQ0VnoSfrw1C6r5xwsWc8+mVv6y9cjUBj3KRFkSj90jq1GEEEJkp9jS12AEpcDjGD+zAVbL8twLNmIty6MrUtoG23Db3bGGXxNp6R6isaIIpz25t8bPXrCIVfMq+bcULIe97aUDrPn2E+Puuuuy52ZTLwk2hBCiAISNcKxmo9hpx2ZTEx5fXeKadJv5bDS6i6i1tbxSEz9fgJYeX0LFoaM57DZ+dI25HPaLf9xKxNBJ3wfAYCDMTU/sJhA22H6kP+4x9cX1tHvbMXRmd6BNlgQbQghRAGJLX4PhCbuHWmpK3Tmd2bD2R2n3tifcY6O1Zyih4tB45s0q5j+uOJlXD3Tzi2f2TOk+/ve5fbGi3Lc6BuIes7ByIb6wLzY9lCsk2BBCiAIQW/oamHh7ecusksT2R8k21n4tozMbk/GHInT0ByZs6DWZ96yaw7tWzOamJ3azOcnlsF2DAW55dh/vWN5ATambN9vHCTYqFgKwtzez290nS4INIYQoANbeKJNtL2+pLnXhC0UYivblyBXVnmrArNkIRoIc8x1LKNg43GutREl+GsWilOLbV5rLYT/3hy0MBhL/2f3s6b34QhH+6ZIlLGkoHT+zEQ029vXtm/I4M0GCDSGEKABWgehgIDxhjw1LTY429ipyFOGyuegJ9NAx1AGQ0DSKtdvrdDIbABVFTm66xloOm9jusK09Q/z+5YNcfVoTi+pKObG+jLc6BjHi1H5Ueaqo9lSzv2//tMY50yTYEEKIAhA0gtGajciEPTYsubo/ilKKSk8lvf7e48teSxNZ9mpmNqZaszHc6c3VfPr8Rdy9sZUHX598OeyPntgNCj530WIAltSX4QtFaI2OabTmimbJbAghhMg+saZegTAlidRsRLuIduViYy93FT2BnqS6h7Z2D+Fy2Kgrc6dkDJ+9cDErmyr51z+/EZuiiWd3xwD3bGrl+nXzmV1pTuGc2FAGwJsTTKXs7d0ba1yWCyTYEEKIAhCKmE29vIEIJQnUbMyKTqN05tg0CphTDT3+HtoGzWCjvrh+0tu09Awxt7Jo0iXBiXLabfzo2pUYhuYLf9wy7nLY//nrmxS7HHzq/EWxyxbXlQLjr0g5ofIE+oP9dPm7UjLWmSDBhhBCFIDhW8wXJ1CzkdP7o0R3fm3ztlHtqcbjmLwjaGuPj7nTrNcYbf6sEv7jiuW8ur+bm/82dvXI5kM9PLa9gxvPXRibtgIo8ziZU1k07oqU5opmgJyq25BgQwgh8pzWethqlMSWvha77Hictpxs7FXpqaTH35Pw1vJgFohOZyXKeN67eg6Xn9rITY+/xZaW3tjlWmu+9+ibzCpxccPZzWNut6ShbNIVKbm0/FWCDSGEyHNhbS7BtOEgYuiECkSVUswqydHGXu4q+oP9tA62JhRsDAbC9AyFUlIcOppSiu+85xTqyz187g+bY7vuPr+nk5f2dfGZCxbFraE5sb6MvccGCUXGdgqtL66nxFmSU0WiEmwIIUSeC0XMjb20YQYZiSx9hej+KDlaswFwqP9QksteU5/ZgOPLYVu6zeWwhmFmNeZWFXHd2nlxb7OkoZRQRHOg0zvmOqUUCysW5lSwkdhfnBBCiJwVMsxgw9BmsJFIUy8wl7925ug0CoBGJxdspCGzYTm9uZpPrV/ET5/eQ8TQvHG4j/939Qrc42yId2L98RUpi6Pnh2uuaOalIy+lbbypJpkNIYTIc7FgI5rZSKRmA8wVKbm4zfzwHV4T21o+2mMjxQWio33uInM57J83H+bE+lKuXDVn3GNPqC3FpuCtcYpET6g8gWO+YwwE41+fbSTYEEKIPGdNo0QM819+IhuxAdSUuuj0BnOqnwMc3x8FEuyx0TNEsctOVbEzjaM6vhz25NnlfP1dJ2OfYJmtx2lnQU3JhL02IHfalkuwIYQQec7KbEQi5r/8RPpsgDmNEgwbeIORtI0tHaz9USDB7qHdPpqqihPahn665s8q4aHPnsNZi2omPXZJtG15PLFgo1eCDSGEEFlgdLCRSJ8NgFml1v4ouVW3YWU2nDbniMBjPK09Q2krDp2OE+vLONDlxR8aG+zNKZ2Dy+aSzIYQQojsYAUb4UiyNRtmo6lcKxJ12p2UOktpKGnApiZ+m9NaR3tspLdeYyqWNJShNew5Oja7YbfZWVCxQIINIYQQ2cGq2QiHrZqNxKZRmmtKAMZN5WezSndlQvUaPUMhvMFI2otDpyK2ImWcIlFrj5RcIMGGEELkOSuzEQxbNRuJZTbmzyqmosjJ66296Rpa2nz05I9y3dLrJj3u+LLX7JtGWTCrGJfdNn4n0cqFHBk8gj/sn+GRJU/6bAghRJ6zgo1QWGFT4HEm9jlTKcWKpkq2tPSlc3hpcc3SaxI6rqXHDDaycRrFYbdxQl3phCtSNJoD/QdYWr10hkeXHMlsCCFEnjue2VCUuBxJrbpYObeCtzoG8OXYipREtcZ6bGRfZgNgSX3puL02cmmPFAk2hBAiz1k1G4GgSrhew3Lq3Eoihmb7kezKbjy2vZ3/eezNad9PS/cQlcVOyjzp7bExVSc2lHGkz0+/PzTmuvnl87EpW04UiUqwIYQQec7KbASimY1knNpUATBix9JMe/iNNj51+yZ+9sye2MZmU9XS40trm/LpWhItEt0dZyrFZXcxr2xeTmw1L8GGEELkuaBhthwPhFTcHUYnUlfmYU5lEVtbsyOz8dft7Xz2zs1UFTvRmnGLJxPV2p2dPTYsx1ekxF8R1FzRnD/TKEqpS5VSbyql9iilvhzn+vVKqT6l1Jbo6WupH6oQQoipsKZRfMHEN2Eb7tS5FWzNgszG07uO8uk7NrF8TgW3/v1aAHa2TT3YMAxNa5ZnNuZUFlHiso+/IqViIYf6D8WyV9lq0mBDKWUHfga8AzgJuE4pdVKcQ5/TWq+Mnv4jxeMUQggxRdYbkS+YfGYDYEVTJYe6h+jxZm5Ttud2H+Mffr+RJQ1l/O7vT2dpQxmlbge72vunfJ9HBwIEIwZzs3DZq8VmUyyuLxu318YJlScQ1mFaBlpmeGTJSSSzcTqwR2u9T2sdBP4AXJHeYQkhhEgVK9jwB9SUMhsr5lYCsDVD/TZe2tvFx2/dwMKaEn5/w1oqipzYbIolDWXsmkZmo9Va9pqFDb2GM/dImWRDtizfIyWRYGMOMDxkao1eNtoZSqmtSqlHlFInx7sjpdSNSqkNSqkNx44dm8JwhRBCJCtsmEWUQ0GdcKvy4U6ZW4FSsDUD/TY2HOjmht+9RlNVMbd/bC2Vxa7Ydcsay9jZ3j/lXWmtHhvZPI0CZtvyLm8wbtv45opmIPt3f03kry7eguzRv9lNwHyt9aBS6jLgPmDxmBtp/SvgVwBr1qzJrT2LhZgirTVd/i4O9h/kYP9BDvQf4GDfQUpdpXz7rG/PyE6TorDFplH8KuFN2IYrdTtYVFs6451ENx/q4aP/9xoN5R5u//ja2MZwlqUN5fzef4jDvb4pNeVq6TZ7bGTzNAqYwQbAW+0D1Cwa+TModhbTWNKYF8FGK9A07Pu5wJHhB2it+4edf1gp9XOlVI3WujM1wxQitwyFhvjuq9/lrZ63ONh/kMHQ8Upyh81Buaucbn83n131WepL6jM4UlEIrAJRb9CgJMk+G5YVTZU88+ZRtNYzEiC/0drH9b95lVmlLu74+DrqyjxjjlnWaL4J72obmGKwMURdmRuPc2o/k5kSW5HSMcCZcbamX1ixMOunURIJNl4DFiulmoHDwLXAB4YfoJRqADq01lopdTrm9ExXqgcrRK54rf017t1zL6vrVvOuE97F/PL5sdPsktls7NjIDX+9gX19+yTYEGkXMkLYlQND26aU2QBYMbeCuze2TjmLkIwdR/r58G9eoaLIyR0fX0dDxdhAA2BJQzkAu9r7ueik5F9HLT1DWbkB22g1pS6qS1zj1m00VzSzsWMjhjYm3eU2Uyb9q9Nah5VS/wg8BtiB32ittyulPhG9/mbgKuCTSqkw4AOu1VOdRBMiD1gpzZ9c+BPKXeVjrrfmWff37eeM2WfM6NhE4QkZIZw289996TQyGwCvt/alNdh4q2OAD/36FYqcdu78+DrmVI4/xVHqdjCvupid46zUmExLt481C6qmOtQZo5TixPrSCVek+CN+2rxtzCmNV1KZeQmFuFrrh4GHR11287DzPwV+mtqhCZG79vXto6aoJm6gAVBTVEOZsyzr51lFfghGgthtZjvuqWY2ljaU47Lb2NrSy2WnTL51+1TsPTbIB255BYdNcefH1yWUdVjaUMautuSXv4YiBm19PpqqsvPNebQl9WXcs+lw3Gms4XukZGuwkZ35FiFy3L6+fbHsRTxKKZormznQd2DmBiUKVsgI4VBmkDHVmg2Xw8ay2eVpa1t+oNPLB255GdDc8fF1LKgpSeh2SxvL2d/pxR9KbqO49j4/hs7eDdhGO7GhjMFAmCN9Y7eTt4KNbG5bLsGGECmmtWZ/7/7YP4DxNJc3S2ZDzAizZmN6mQ0wd4DddriPiJHaWfKW7iE+cMvLBMMGt39sHYvqShO+7bKGMowptC1v6c6NZa8Wa4+UeDvAVnoqqfZUZ/X/Ewk2hEixTl8nA6GBCTMbAAsrF3LMd4yB4PT2dhBiMiEjhA0rszH1YGNFUyXeYIS9x+Lv0zEVR3p9XHfLy3iDEX7/sbWxZZ6JWtoYLRJNsrlXrMdGDhSIAiwetiIlnoUVC7N6jxQJNoRIMSuVmUhmY/jxQqRLKBLCNs1pFDC3m4fU7QDb0e/nA7e8TN9QiNtuOJ2TZ1ckfR/zq4spctrZmWTb8pZuH3abonGclS7ZpqLISWOFJ25mA6LLX/v2TbnBWbpJsCFEilmpzMmCjYWVC0ccL0S6hIwQyspsTGMaZWFNCWVuR0qaex0bCPCBW17m2ECA391weiyQSZbVtnxnkkWiLT1DNJR7cNhz523wxPqy8TMblQsZCA7Q5c/OrhO581MWIkfs69tHibOEuuK6CY+bUzoHp80pmQ2RdiEjhNJmRmMqe6NYbDbFqU0V025b3jUY4IP/+zJHev3839+dzup501t+uqyxjF3tA0l9qm/J8q3l41nSUMbuo4Nxa2aGr0jJRhJsCJFi+/r20VzePGmXRYfNwfzy+ZLZEGlntis3g4zp1GyAOZWys60/6dUflt6hIB/69asc7Bri1x9Zw+nN1dMaD5jLcnuHQnT0j907ZDzZvrV8PCfWlxEMGxzs8o65LrYhW5b+P5FgQ4gU29+7PzZFMpnmCln+KtIvFAmBtmO3KdyO6f3bXzG3krChk562AOjzhfjwr19l79FBbrl+TdzW21OxLFokmmjdhj8U4ehAIGeKQy2xFSlxplLqiusodZZmbdtyCTaESKGB4ABHfUcnXYliaa5opmWgJbZ3hRDpEDJCaMNBscs+7X1NVkY7iW5Nskh0MBDmo//3Krva+7n5w6s598TaaY1jOGsFS6IB0Et7zbqG5XPiN93LVovqSlEK3mwfuxpIKcXCioUTTst2+7v5z1f+k25/dzqHGZcEG0KkkJWlmKw41NJc0UxERzg0cCiNoxKFLmSE0No2pe3lR2uo8FBf7mZra+J1G0PBMH/3f6/yRmsfP/3Aai5Ymtr9gCqKnMypLEp4+esj29ooczs4K0WZlZlS5LIzv7p4wj1S9vaNrdkIG2Fu33k7l//5cv705p/Y0L4h3UMdQ4INIVIo0ZUolmyfZxX5IRQJYUQzG6lw6txKtia4IsUXjHDDbzew8WAPP7p2FW8/uSElYxhtaUMZuxKYRglHDB7f0cEFy+pwO7J7t9d4TqwvY8c4GZwTKk+g09dJf/D49a+2vcrVf7ma7776XZbXLOeed9/DJQsumanhxkiwkSe++MwX+cHGH2R6GAVvX98+HDYHc8vmJnT8gvIFgPTaEOkVMkIYhm3axaGWlU2V7Dvmpc838fSfPxThxts28PL+Ln7w/pW889T07KkCZt3G3mNeAuGJC1df2d9Nz1CIdyxPT9CTbqc3V7O/08uRXt+Y62IfXnr30TbYxj8980/c8Ncb8IV9/PD8H/LLi3+ZcD1ZqkmwkQf6An08eehJHtv/WKaHUvD29e1jftl8HLbE/qkXO4tpLGmUzIZIq5ARIhKxpyyzsSLaE+ONCaZSgmGDT92+ied2d/Lf7zuVK1eld4OwpY1lRAzNnqMTdzd9ZFsbRU4755048dL0bHXOYrPW5fndnWOus4KNn27+Ke++7938rfVvfGrlp7jvivu4cN6F067XmQ4JNvLAS20vYWiDI94jtHvbMz2cgra/L/GVKJbmimbJbIi0MoON1NRsAJwy1+z0Od5USihi8I93bOKpXUf5znuW8/41TSl53IksbYiuSJmgbsMwNI9t72D9klqKUhR4zbQT60upK3Pz7O5jY66bXTobj93DK+2vcM7cc3jgygf45IpP4nFkvktqav7yREa9ePhFbMqGoQ02H93MO5rfkekhFaRgJEjrQCtvX/D2pG63sGIh9+y+B0Mb2JTE/yL1QkaIcMQ2rU3YhqsocrKwpiTuipRwxODzf9jCX3d08I13ncQH185PyWNOZsGsYtwO24TbzW861MOxgQCX5ugUCpirTs5eXMPTu45iGBqb7Xi2wm6z8z/n/Q/FzmLe1vC2DI5yLPnPluO01rxw+AXObzqfEmcJmzo2ZXpIBetQ/yEiOpJwcailuaIZX9hHh7cjTSMThS4UCRGK2Ka1L8poK5rGFolGDM0//2krD73RxlcuW8ZHz0psCXgqOOw2Tqw3O4mO55Ft7bjsNi5YmptTKJZzF9fSMxRi+5GxgdV5TedlXaABEmzkvD29ezjqO8q5c89lRe0KNh2VYCNTkl2JYrF6cshUikiXkBEiHFYpy2wAnDq3go7+AO19fsCcovj/7nmd+7Yc4V/evoSPnzvzhYhm2/L4mQ2tNY9ua+fsxTWUeZwzPLLUspbsxptKyVYSbOS4F4+8CMCZs89kVd0qdvfsHrHsScwcK9iYX55c2liWv4p00loTMqzMRuqCjRVWc6/WXrTWfOW+bdy9sZXPXbiYT5+/KGWPk4ylDeV0DgY5OuAfc90bh/s43OvL6SkUS22Zm2WN5TwnwYaYKc8ffp4TKk6goaSB1XWr0Wi2Ht2a6WEVpH19+5hdMptiZ3ItkKs91ZS7yiWzIdIibIQB0IadkhQWRZ7UWI7Dptja0ss3HtjOna8e4lPrT+DzFy1O2WMka2mj2Uk0XnOvR7a1Y7cpLl6W2oZimXLu4ho2HuzBGwhneigJkWAjh/nCPjZ1bOKsOWcBsLxmOQ7lYPPRzRkeWWHa37ef5srk56itNsOS2RDpYG7CBlo7KE5hZsPjtLO0sYzfvLCf3710kI+d3cy/vH1JRpdXLouuSBk9lWJNoZyxcBZVJa5MDC3lzllcSyiieXX/zLcenwoJNnLYhvYNBI0gZ802g41iZzHLZi2Tuo0MMLTBgb4DSddrWGT5q0gXK9hApzazAWa/DX/I4CNnzOcr71yW0UADoKrERUO5Z0xm482OAfZ3evNiCsWyZkEVboctZ+o2JNjIYS8eeRG33c3q+tWxy1bVrWJb5zaCkWAGR1Z42rxt+CP+KQcbCysW0uXvoi+Q+H4TQiRiRLCRwswGwD9esIjvX3Uq33j3yRkPNCxLG8vYOWpFyiNvtKMUXHJyfkyhgJlZOr25mufiNPfKRhJs5LDnDz/Pmvo1Ixq2rK5fTSASYEfXjgyOrPBY2zonutvraLIiRaSLtaOw1nZKUrgaBaCxooir1zRlTaABZpHonqMDBMNG7LLHtrfztvnV1JVlvrlVKp27uJY9Rwdp6xvbujzbSLCRo44MHuFA/4FYvYZlVd0qAJlKmWHJLns1DI0veHwPB+t2EmyIVDue2XBQnMI+G9lqWWMZoYhmX6fZtnx/p5dd7QO8PY+mUCxnLzaXwOZCdkOCjRz1wpEXAGL1GpZqTzULyhewuUOKRGfS/r79VLmrqPJUTXhcMGxw14YWLrrpb5z53ScZCpqV5LNLZ+OyuSTYECk3smYj/5tGL2uMFolG6zYe2dYGkFf1GpalDWXUlLol2BDp88LhF2goaYibtl9dv5rNxzZjaCPOLUU67O/bP+EUylAwzK+f389533+aL939OsGwQc9QiBf2dAFmm+H5FfNlRYpIuZE1G/mf2WiuKcFlt7EzuiLl0W3trJhbwZzKogyPLPWUUpy7uIYX9nRiGDrTw5mQBBs5KGSEeKXtFc6afVbcudJVdavoC/TJp+QZtK9vX9wN2HqHgvzoid2c9d2n+NaDO2iqLua3f/c2nvyn8yh1O3hq19HYsc3lzRJsiJSzisXTUbORjZx2G4vqStnZNkBrzxCvt/Zx6fL0bW2faWcvrqHbG2THBHvCZIP8/8vLQ28ce4PB0OCYeg3L6jpzdcqmo5s4ofKEmRxaQer2d9Mb6B1RrxGOGPzPX9/itpcO4A1GuGhZHZ9cfwKnza+OHXP2ohqeefMoWmuz10blQp449ASBSAC33Z2JpyLy0PDMRiHUbIC5IuX53Z08us3cBfsdeTiFYjl7WOvy5XMqMjya8UlmIwe9cOQF7MrO2sa1ca9vKmtilmeW1G3MkHgrUR56o42b/7aX9UvrePTz5/C/H3nbiEAD4IKldbT1+WMbRzWXN2Nog4P9B2du8CKnaa25b899fOPFb8Q6hY5mBRt2mwO3ozCCjWUN5RwdCPCH11pY2lDGgpqSTA8pberKPSxtKOO5t7K7bkOCjRz0wuEXOKXmFMpd5XGvV0qxun61rEiZIfFWojz4ehsN5R5+cu0qljbE/z2tX1ILEJtKsaZhZPpLJKIv0Me/PPsv/PsL/849u+/hudbn4h5nLX31FFC2zCoS3XN0kHfk8RSK5Zxo63Kr4DwbSbCRY3r8Pezo2sGZc86c8LjVdas5PHiYdm/7DI2scO3v20+Ro4iGEjNV2+cL8bc3j3HZKY3YbOP3H6gr97B8TjlPR4ON+eXzUSip2xCT2tixkav/cjVPHnySz676LHXFdfzxrT/GPdbKbBQ58qNNdyKsPVIA3nFK/k6hWM5ZXEswYvBKFrcul2Ajx7x05CU0mrNnnz3hcavqzX4bW45umYFRFbb9fftZUL4AmzJfTo/v6CAYMXjXisk/UV2wpI5Nh3ro8QYpchQxu3S2ZDbEuMJGmJ9t+Rl//9jf47Q5ue2y2/j4qR/nqsVX8eLhF2kZaBlzm1iw4SqczEZNqZuaUjcLa0tYXFea6eGk3enN1bgctqyeSsm7YOOxA49x3577Mj2MtHnhyAtUuCs4adZJEx63pGoJRY4imUqZAaNXojz4+hHmVhWxMroF90TOX1qHoYntbyB7pIjxtA608tFHP8rNW2/mXQvfxV3vuovlNcsBeO/i92JTNu5+6+4xt7OCjWJn4WQ2AP798mV87fKTsqq7abp4nHbWNldn9ZbzeRVsWMVSX3vhazyw94FMDyfltNa8eORFzmg8A7tt4kIvh83BitoVsgNsmg2FhmjztsXqNXq8QZ7f3cnlp85O6J/cirmVzCpxxeo2miuaOdB3QHqkiBEe2vcQV//lavb27uV7536Pb5/9bUqcx4se60vqWd+0nvv23DdmXySrZqPYWTiZDYArVs5h/ZK6TA9jxpy9qIbdRwdp7/OPe0zE0NyzsRV/KDLuMemSV8GGUoofrP8Bpzeczlef/yoP7nsw00NKqbd63qLT1znuktfRVtet5q2etxgIDkx+cJ4aDA6idfqa3ezvN7MQ1kqUR7e3EzY0l5+aWFGazaY4b0ktf3vrGBFDs7BiIf6InzZvW9rGLHLHYHCQf3vu3/jyc19mUeUi7n733byj+R1xj33/ie+n29/NEwefGHF5LLNRQNMoheicxWbB+XjZjc2HerjyZy/wT3/aygNbj8zk0IA8CzYAihxF/OTCn7CmYQ1fef4rPLL/kUwPKWWeP/w8AGfOnrg41LKqfhWGNnj92OvpHFbWeuzAY5z1h7O47qHr+Mvev6RlJ1xr2auV2fjL1iM015Rw8uz4K1DiuWBpHb1DIba09MiGbCLmjWNvcPVfruah/Q/xqRWf4v8u/T/mlM4Z9/h1s9fRVNbEXW/dNeJyK9godRXWNEqhGa91eddggC/dvZX3/PxFOvr9/OjalVx92twZH1/eBRtgBhw/veCnrKpbxb8+9688duCxTA8pJV488iKLqxZTV5xYavDUmlOxKzsbOzameWTZ57X21/jX5/6VJVVLGAoP8W/P/xuX3H0JP9/yczp9qSui2t+3H7uyM69sHscGAry8r4t3ndqY1DzxOYtrsdsUT+06GgtarCBGFJ6IEeGW12/h+keux9AGv730t3xy5Sdx2CbuwWhTNq4+8Wo2dmxkb+/e2OXWNEqpO792PBUj2WyKsxfNirUuD0cMfvfiAc7/n2f486bD/MO5C3nqn9dzxco5GaljyctgA6DYWczPL/w5K2pX8P89+//x+MHHMz2kaRkKDbHp6KYxG69NpNhZzNLqpQVXt/FWz1t87qnP0VTWxC2X3ML9V9zPLy/6JSfXnMwvtv6Ci+++mH997l/Z3rl92o+1v28/TWVNOO1OHtnWhqHh8hWzk7qPiiInp82v4qldx6jyVFHprpTlrwWq3dvOx/76MX68+cdcNP8i/vTuP8V2ck7EFYuuwGlzctebx7MbxzMbMo2S785ZXEuXN8jtrxzkXT99ga8/sJ1T5lbw6OfP4V8vW0apO3NNw/M22IBowHHRzzml5hS+9Lcv8eTBJzM9pCl7rf01wkY44XoNy+r61bzR+Ubs002+a/e288knPkmRo4ibL7qZCncFSinOnHMmP7vwZzz4nge5Zsk1PN3yNNc+dC0fevhDPLL/keMtnZO0r2/fiCmUJfVlnFhfNsmtxrpgaR072/pp6/OxsGKhTKMUoCcOPsH7Hngf27u28+2zvs33zv3euI37xlPtqebi+Rfzl71/YSg0BEAgOn1Y6pLMRr47J7rl/L/fv52+oSA//+Bqfn/DWhbVJf8/KdXyfm+UEmcJv7joF/zD4//AP//tn/nB+h9w/rzzMbRBu7ed/X37OdB/wPzad4A2bxslzpLYJ8xqTzWV7kqqPFVjLqtwV0ya2pyOkBHipSMv8eDeB3m65WnKnGWxfU8StbpuNbftuI0d3TtYUbsiTSOdWF+gj46hDjp9nXT5uujyddHp66TT3xmb0vjEqZ9gTcOaaT/OJx7/BEOhIX73jt/RWDq2SHN++Xy+fPqX+ceV/8j9e+/njp138KVnv0RdUR3XLL2Gq068impPdZx7HytkhDjUf4jzm86nrc/Hawd6+KeLT5zS2C9YWsd3H9nF07uO0VzRzFOHnprS/UzXQHCAQwOHGAoN4bA5cCgHdps9dt5hc+C2u6kvqc/I+PLRUGiI7732Pe7ZfQ8nzzqZ7537PeaVz5vy/V2z5Boe3v8wjx54lPcufi++UBCt7ZR68v7ffcGrK/fwsbObKXbZ+cT6EyjOoo33smckaVTqKuXmi2/mxr/eyBf/9kUWVizkUP8h/JHjS4TKnGU0VzRz0qyT8IV99Ph7aBloocffw2BocNz7LneVx4KQKncVlZ5RX0cFKmWusljzp3i01rze+ToP7n2Qxw48Rk+ghwp3BVcsuoL3L3k/LntyRV4r61YCsLlj84wEG/6wn13du3j92Ou80fkGb3S+weHBw2OO89g9zCqaRU1RDR1DHfzdY3/HlYuu5IunfZEqT1XSjxuIBPjsU5/l0MAhfnnxLzmxauI3/VJXKR9c9kGuW3odzx9+ntt33s5PNv+EX279JZctvIwPLvsgS6uXTngfLQMthHWYhZULeeh1c/VIslMolsV1pcypLOKpXUc5Z00zPYEeevw9U/pZTERrTW+gl0MDhzjUf4jWgVbz/MAhWvpb6An0JHQ/71n0Hr5+xtcnXYItJrazaydfevZLHOw/yA3Lb+DTKz+N0+6c1n2uqlvFospF3PXmXdFgIxDdXr4g/t0XvK9ePnEPpkwpmL++MlcZv7zkl3zrpW8xFB5iXeM6FlQsoLm8mQUVC5jlmTVu0UwoEqI30Eu3v5ueQA+9gV56/b3meX8vPf4eegI9tA+1s7N7Jz3+HoJG/JUPdmWnwl0RNzCJ6AiPH3ycloEW3HY35zedzzsXvpOzZp815X9ANUU1zC+fz6ajm/goH53SfYzH0AYH+g/wxjEzqHj92Ovs7tlNWJv9+RtKGjil5hSuWXINc0rnxIKLmqIaih3FsZ+3L+zjl1t/ye+2/46nW57mi6d9kSsXXTlhUDZcxIjw5We/zKajm/j+ed/nbQ1vS/g52JSNc+eey7lzz2Vv717u3HUnD+x9gPv23Mdp9afxoWUfYn3T+rgZrP295lTHwoqF/PrRNpbPKad5ihs+KaW4YGkdd29s5brz5pv337d/SsGG1ppOXyctAy2xoMI639LfwkDo+FJohaKhpIF5ZfO4cP6FzCubR1NZE2WuMiJGhLAOEzbMU0RHCBthtnVu445ddxA2wnzrrG9JwDEFhja4bcdt/HDTD6l2V3PLJbeMu7HihPdjaJ7cdZT9nYN87OyF2GwKpRTvX/J+/vOV/2R753aGQkEz2MiiT7mi8BTUX1+5q5zvn/f9pG/ntDupLa6ltrg2oeO11vjCPnoDxwMSaxvyHn80WImeP9B/gJ6j5mWGNljbuJYbT72Ri+ZdRKkrNW12V9Wt4pmWZ2JbmU9Vl68rFlRs69zGts5tsTeuEmcJy2ct56PLP8opNadwSs0pCf+8ihxFfP60z3P5wsv51svf4usvfp3799zPV9d9lcVViye8rdaa7776XZ449ARfetuXuHTBpVN+fidUnsBX132Vz6z6DPftuY87d93JF575Ao0ljVy39Dreu/i9VLiPb+Fs9dhwGvVsbTnIl98xcSZkMucvreW2lw/S129O4+zv28/q+vjTZoY2ODp0lEP9h0ZkJg4NmIGFL+yLHWtXdmaXzmZe2TxOXXgq88rnxYKKOWVzkt7O/l0nvIsqTxU/2/IzIjrCd87+TlqnE/NNp6+Trzz/FV488iIXNF3AN8/8JpWeyqTuwx+KcM+mVn793H72dXoBs4vk9WcsAODyhZdz08abuOutu/CHI2htp9glQaHIHPkPkQZKKYqdxRQ7i5ldmlha3dAGISOU9D9+gGDY4J//tJUFs4r54iVLxly/um419+25j/19+0e01Z7IRNMhdmVncdViLm2+NBZYNFc0T/sT7qKqRfz20t9y3577+MHGH/D+v7yfD5/8YT5y0kcIGSEGg4MMhoadgoPs7NrJXW/dxUdP/igfPunD03p8S4W7go+c/BE+tOxDPNP6DLfvvJ0fbPwBP9/ycy4/4XI+uPSDLKpaxL7efdQX1/Pkjj4A3nnK9HaXPGNhDW6Hja37FW67mz29e2gZaIkFEVYg0dLfQstAy4jsmdPmZG7ZXOaVzeP0htOZV24GE/PK5tFY2ojTNr3U/GifWPEJHDYHP9r0IyI6wn+d818pf4x89Gzrs/z7C//OUGiIr53xNa5afFVSHwC6BgPc9vJBbn3pIN3eIKfMqeDH163i7o2t/NfDuzjvxFrmzyqhzFXGZc2X8dC+h1hW+TbQ9oyuRBBCpbO74kTWrFmjN2zYkJHHzidaa75411bu3WwGAr+/YS1nRyuSLQf7D3L5vZfjsXtoLG1kdsnsMV9LnCXs6t4VCyze6n4rNh3SWNLI8prlnFpzKqfUnsKy6mUUO4vT+rx6/D3ctPEm7t1z76THXrnoSr555jcTnnaZije73+SOXXfw0L6HCEQCrG1cS+tAK/PK5tG688O4nTbu/VRyK4Xi+bv/e5V9nV5ql/yMN3veHHGdx+6hqdwMIOaVzaOpvCkWUNQX12dkOuP/tv0fP9j4Ay6efzH/fe5/ZzTgMLRBl6+LjqEOOrwdtA+1x84fHTpKx1AHDSUNfPusbyf8ISBVApEAP9jwA+7YdQdLqpbwvXO/l3DgD7Dv2CD/+/x+7tnYSiBscOHSOj5+7kLWNlejlKKtz8clNz3LsoZy/nDjOmw2xfau7Vz74LXYlYNQoILbL70vof16hJgqpdRGrXXcSn8JNnLc9x/bxc+e3stnLljEw2+04Q8ZPPr5cyjzjPyn/5e9f2Fn907aBts44j1C22Bb3GJAazrklNpTkp4OSYctR7fw+rHXKXWVUuIsodRpfi1zlcW+H2+66aHX2/jB429SV+Zh9fxKVjVVsWpeJbNKp95voMffwz277+HOXXdydOgo715wLbc/spJ/v/wkbji7ecr3a7ntpQP8+/3b+f71Ltr8O2kqiwYU5fOoLarNyk2lbt1+K9/f8H0uaLqA/znvf6Zd4BhP2AjT6euk3Xs8gOgY6hhx/tjQsViAbHHanNQV11FfXE9dcR3PH34ep83J98/7/pRqJJIRMSJs7NjIowce5fGDj9Mb6OVDyz7E50/7fEIZTK01rx3o4Zbn9vHEzg6cdhvvWz2HG85ujruU8e6Nrfzzn7by1Xcu42PnmIHMdQ9ex7aubUQCddx/xX0snsKybCESJcFGnrr9lYN85d5tXHd6E//5nlPY3NLLVb94kWveNo//eu8pk95+KDREu7edI94j9Af6ObHqxJRMh2TaYCDMNx/Yzp82trK0oQyn3caOtn4ihvm3Pn9WMauaKlk1r4rV86pY2mgek4yQEeK1ttd4bpubm59p56UvX0hDxfT7GLT2DHH2fz894g0jF9y+83a+++p3WT93Pf9v/f9LatVUMBKMZR7iBREd3g46/Z1jNqfz2D00lDRQX1xPfUm9+XX4+ZJ6qtxVIwK0g/0H+dxTn2N//36+sPoLfOTkj6Q0gLO2B3j0wKM8duAxOn2dFDmKWN+0nqtPvDqh4uVwxOCx7R386rl9bG3ppbLYyfXr5vPhMxZQWzZ+kKK15mO/28Dzezp5+HPncEJtKffuvpevvfg1Iv5GHr/mfuZUFqXsuQoxWkEFG95AGI/Tjt2WfZ8AU+nJnR18/NYNnHdiLbdcvwZH9M3yvx7eyS+f3cdtN5we25inkGw+1MPn/7iFlu4h/vH8RXzmwsU47TZ8wQhvHO5j86EeNh/qZdOhHo4OBABwO2ycOrciGnyYQUh9+eSBg9aai296luoSF3f9wxkpew6X3PQ3akrd3PHxdSm7z0T5QxG6vUEqi51Jr9H/w64/8J1XvsPpDaezqm4VGo3WOvbVwAANQ+GhEcFEt797zH2VOkvHBA6jg4lyV/mUAoWh0BBffeGrPH7wcS5dcCnfPPObE04LhiIhnj38LE8deoqIjuCyuXDZzZPb7o593+3v5vGDj9PmbcNlc3Hu3HO5tPlSzp17LkWOyd/kvYEwd21o4Tcv7Kel28eCWcXccM5Crlo9l6IEizuP9vu5+KZnWVhbwt2fOJOg4eecO89nyFvFS9c/QEWx1NWI9CmYYENrzafv2ETXYJCbrlnJ7CSj+Bf2dHLrSwc4f0kd7109F5cjOxusbm3p5dpfvcyiulL+cOO6Eevn/aEI7/zxc+NOp+SriKH5+dN7+OGTu2ko93DTNSs5vXn85lxaa470+UcEH9sP9xOMmJ+eZ1d4WDW/KpYBOXl2OR7nyH/4u9r7ufSHz/GtK5fz4XXzU/Zc/uvhnfz6+f1s/trF0/r9GYam1xei2xscceoZCo65zDr5oltPe5w2LlxazztPbeT8JXUJv9nd/dbdfPfV7xKIBFAobMqGQoECGzaUUngcnrFZiOj5huIG6orrUrYSazxaa36z7Tf8ePOPOaHyBH60/kc0lTeNuH5n907u33M/D+9/mN5Ab6xPTjASJBgJEogECBpBwoY5deOwOThz9plcuuBSzm86P+HncLTfz29fPMDvXz5Ivz/MmvlVfOychVx8Uv2UPjTdv+Uwn/vDFr78jqV84rwT+OwD/8vD24+w41++mrX/00R+KKhg455Nh/n6/duw2xT/9d5TeWcCW337QxG+9+ib/OaF/RS77AwFI8yu8PAP553ANW9rGvMmk0mHuoZ47y9ewOO08+dPnUld2dhP4JsO9SQ1nZJJwbDB3mODzK4omvKnrpbuIb541xZeO9DDu1fM5ltXLqeiKPn7CoQj7DjSHws+Nh/q5XCvuYTUZbdx0uxyVs2rjGVA7nz1EL94Zi+vfuUiaqZRBzLay/u6uPZXL3Pzh1Zz6fLjf7++YITuoSDdg0G6h4L0eIN0eUd+7faa13V7g/QOBTHGeXmXuOxUlbiYVeKiqsRFdYmL6mLzfFWxi51t/TyyrY3OwSDFLjsXLavn8lMbOffE2klfD9NdYj2TXjzyIl969ksY2uC/z/lvllYv5aF9D3H/3vvZ07sHp83J+U3nc8WiKzhz9plxl/ga2iAYCaKUSmo12ZvtA/zvc/u4b8thwobm0pMb+Ng5Czlt/vQauWmt+eTvN/HUrqM8+Nmz+fOmw/zm+f289Z34W9MLkSoFE2xYDnR6+dwft7C1pZerT5vLN9598rjd87Yd7uMLf9zC7qODfOSM+Xz5Hct4ZX8XP3lqDxsP9lBT6ubGc5v54Nr5aevAF4oYDAUihAyD6mIXtnE+zfR4g7zvFy/S5Q1yzyfPZFHd+J+csn06ZX+nlz+8doi7N7TS5TWXcFYVO5k/q4TmmhLmzyqOfi2hqtiJP2TgC0XwBSP4Q5HY+aMDAX7+9B408O0rl3PlqvG34J6Ko/1+Nrf0xgKQ11t78YeO1w6cvaiG338stYWGoYjB6m89TkWRk6pi15isw2h2m6Kq2El1NFCYVRr9OjyQGHVdIgF0OGLw6v5u/vJ6G49ua6NnKESZ28HFJ9Vz6fIGzllcm3DGI5u1DrTyhWe+wJvdb2JTNiI6wqk1p3LFoit4+4K3j+itMl1aa17Y08Utz+3jb28do8hp5+o1c7nh7Gbmz5paQ7h4OgcDXHLTs8ypLGL5nAoe2dbGlq9dkrL7FyKeggs2wPyH/aMndvOzZ/Ywv7qYH167asSyr4ihuflve/nhE29RVezi+1ev4LwTj78pa615eV83P316Ny/s6aKy2MkNZzVzzdua0MBQMII3EDa/BsP4Rn0/FIgwFIwwFAzjDUYYil434vtQhKFAJJa6B/MT9NyqIuZWF9NUVURTdTFNVcXMqSriWw/u4I3Dfdz+sbW8bcHE+3dY0ym+YITHvnBuVkynBMIR/rq9gztfPcSLe7uw2xQXLavj7Sc30DUYZH+Xl4NdXg50DnGkz0eif5pr5ldx0zUraapO73JcMN+Ad7UPsLmll+2H+7jqtLmsmeR3MRU/e3oPf93ebgYJwzIQs6JBQ/WwIKLc4xw3QE2VUMTgxb1dPLj1CI9tb6ffH8bjtHH2olouObmeC5fWTWuVT6porTk2GOBQ1xCHuqOn6PmD3UOUexx85oLFvGvF7BFTFL6wj1tevwWN5l0nvCu2uV6qBMMGD71xhF89u5+dbf3UlLr56Jnz+eDa+VSVJLcFQaIefqONT92+iSKnneoSFy98+YK0PI4QloIMNiyv7Ovii3dtpaPfzxcuPpFPnHcCh3t8fPGuLWw42MNlpzTwnStPmfAFv/FgDz97eg9P7Tqa8OPaFBS7HBS7zD0Jil326MlBidseu67Y5aDEZafIZcdhU7T1+WnpGaKl20dLzxC9Q8d3I1UKfvaB1VyWYPOozYd6eN8MTadorYkYmrChCUUMwhFNyDC/9g6FuH/LYf60sZVub5C5VUVcd/o8rj5tLnXjFGL6QxFauofY3+ml3x+myGmnyGXD47RHz0e/Ou3UlrlzJm2fD0LRjMdft7fz+I4OjvT5sSk4bX4VF59Uz8UnNUy5bXsiAuEIrT2+kYFE1xAt0eBieAZIKWgs99BUXcy86mLeONzHrvYBTqwv5YsXL+HtJ9en7W+nbyjEM28d5YmdR3nmzaMM+MMsqivlxnMW8u6Vs2dkevYzd27mL1uPcGJ9KX/9wnlpfzxR2Ao62ADo84X4yr1v8ODrbayYW8Geo4PYlOKbV5zMe1bNSfifzbbDfby8r4sil7nPgPW12B39Gg0oStwO3A5bSv6JDfhDscCjptSd9Hzufz2yk1/+bex0SjBssK9zkF1tA+xs7+dAp5dg2BgVLGjCowKHcMSIf/l4xQFRDpvi4pPque70eZy9qCbtn8TFzNBas/1IP4/v6OCvOzrY2dYPwMLaEi5aZmY8TptfFVstleh99g6FOBjLTHhHBBRt/f4RWa8ip5151cU0VRczf5YZVMyrLmberGLmVBaNeFM3DM1Db7Rx0+Nvsa/Ty4q5FfzTJUs4Z3FNSl6v+zu9PLmzgyd2dvDagR4ihqam1MX5S+p456mNnLu4dkb/9nu8QS6+6Vmaa4r50yfOnLHHFYWp4IMNGFk8unxOBf/v/SuYW5X+tHumDZ9Ouf7MBexq62dX+wB7jw0Sipi/e5fdxrxZxRQ57TjsCqfNhsOucNhtOG1q1HkbTrvCET3GabfhsI283jHqNm6njbMW1cQtZhX5paV7iCd3dvDkrqO8vK+LUERTUeRk/ZJaLlxWz3mLa6kodhKOGBzp9UenN7wjshSHuoYYCIxszlVb5mZedTHzRwcVs4qpLU0+sxWOGPx502F+9ORuDvf6WNtczb+8fQlrFlQTjhgMRWuCfEFzOtQXMqdBB/xh+n0h+v0h+nwh+n1h+v0h+n0hDnYNxfYpWdpQxoXL6rhwWT0r51ZmNLjed2wQQ+u4jcBEgQkOQetr0HAKFKd++nfawYZS6lLgR4Ad+F+t9XdHXa+i118GDAEf1Vpvmug+M9XUyx+KpCzrkCs2H+rhqptfImJoGis8LG0oY2ljOUsbyljWaO5UmmxTKyEmMxgI89xbx3hy11Ge3nWULm8Qu03RUO6hvd8fa7IG0Vql6qJRAUVJNGNRlHTPj0QFwhH+8GoLP3lqD52DAZx2FQvCJ2NTUF7kpKLISbnHSW2Zm3MX13DhsvoZqR8SYlK+Xmh5BQ6+AAdfhCObwQjD+34Np1yV8oebVrChlLIDbwEXA63Aa8B1Wusdw465DPgMZrCxFviR1nrCEn3pIDqzDvf6KHU5pKmPyIiIodnS0suTOzs43Oujqep4ZmJedTEN5Z6Mfvr3BSP88bVDdAwEKHKa06Eepz02NWqed1DmcZjBRZGTEpe9oD60TJvWEAlCODDsawDCweNfw/6xl0UC5rHxjne4oHYp1C2DmhPBWaAdUrWGoW7o2Q/d+6B1gxlcdGwDNNicMGc1zDsD5p8F89aBpzzlw5go2Ejk48LpwB6t9b7onf0BuALYMeyYK4BbtRm5vKyUqlRKNWqt26Y59uS1bwN/74w/7IyIhCAwYJ6CgxDoP/59YNA8xlkEzuJRX4uY4ywy/+BsdrA5oif78e+V3aymE4mLBep6nPPDKAWocc5nGa1BG2CEwIiYn4QiIfOr9T2YY1c2IPpVqeOXKZv5N2Wzg7JjVzZOs9k47UR79Drv8cfrjZ4yqAj4aCKrpgPRU29ah5N6WgN6nPPDxPs71Yb5/8bfB/5+8/+Ov888BfrN/z0jgofAqIBi2HWpYnOCw23erxEtolc2qGo2Aw/rVDJ62f/o15uO/7OZ6EP4mNdsnNfwlI4ZPqzoa1BHhr0eI9HLDPD1RAOLaHDRc8D8XVicxTD3bbD+X2H+mTDnNHBlNtuWSLAxB2gZ9n0rZvZismPmADMfbDz+77D3qRl/2Iyxu8FdBu5SQEHIFz0NHX8RCiFEKjmLwV1ufjp2lYLDY76Z2avMbIPDY/5vcrjGfh33Ok+cy6Kn4ZfZXWCLTvtGQuab7dEdcHSX+fXYLnjzEfONOp/ZnFA5D6qboWmt+bV6oRlwzToB0rAh4nQkEmzEC79Gh32JHINS6kbgRoB58+Yl8NBTcPF/wNlfSM99Z5rNEQ0sysAVDTAcE/Q2iIRGBR/hkZ9Ora962KdVkaTxshXDXxLjZT4yU5ydEDUsA2a3MmHO49kw6xOv9XysT1/oYZ/AIiM/jRmR6Cc1Y5IHF+mhhn2aHnUeGPfvVCkzoPCUg7vC/Jotb2R2J9QuMU8nD7s8HIDO3SOz3GOyFZrjP4d4P5sE3tbiZkCmcEw8KpoFtNmHZQyjl7nLoGJu9LWYGxIJNlqBpmHfzwWOTOEYtNa/An4FZs1GUiNNVEN2t+eeUXaneUrD3JwQQmQthxsalmd6FGKYRJYgvAYsVko1K6VcwLXAA6OOeQC4XpnWAX0ZqdcQQgghRNaZNLOhtQ4rpf4ReAxz6etvtNbblVKfiF5/M/Aw5kqUPZhLX/8ufUMWQgghRC5JaPG61vphzIBi+GU3DzuvgU+ndmhCCCGEyAfSyUkIIYQQaSXBhhBCCCHSSoINIYQQQqSVBBtCCCGESCsJNoQQQgiRVhJsCCGEECKtJNgQQgghRFpJsCGEEEKItJJgQwghhBBpJcGGEEIIIdJKgg0hhBBCpJUEG0IIIYRIK2XuoZaBB1bqGHAwTXdfA3Sm6b4zSZ5X7snn55Yu+fozk+eVW/L1eaXTfK11bbwrMhZspJNSaoPWek2mx5Fq8rxyTz4/t3TJ15+ZPK/ckq/PK1NkGkUIIYQQaSXBhhBCCCHSKl+DjV9legBpIs8r9+Tzc0uXfP2ZyfPKLfn6vDIiL2s2hBBCCJE98jWzIYQQQogsIcGGEEIIIdJLa532E9AEPA3sBLYDn4teXg08DuyOfq2KXn4xsBF4I/r1gmH3dVr08j3Aj4lOBcV5zO8ALcDgqMu/COwAXgeexFwXHO/2buCP0cd5BVgw7LpHgV7giTx7Xt+LPo/dQGuOPa9zgU1AGLhq1HURYEv0uXTm2POKexywEngp+jxeB67Jkddv3J9HnMeM+/Od6Pec4ddvNjyvdLx+Z+p5zfTrd6aeV8Zfv9lympkHgUZgdfR8GfAWcFL0xfHl6OVfBv47en4VMDt6fjlweNh9vQqcASjgEeAd4zzmuujjjv4nfz5QHD3/SeCP49z+U8DN0fPXDj8OuBB4V/QPOy+eF3Am8AJgB+ZEXwDrc+h5LQBOBW5l7D+rwRz+O4x7HHAisDh6fjbQBlTmwOs37s8jzmPG/flO9HvO8Os3o8+L9L1+Z+p5jXsc6Xn9ztTzyvjrN1tOmXlQuB8z6nwTaBz2h/RmnGMV0IUZ0TcCu4Zddx3wy0kea9w/pugf4wvjXPcYcEb0vAMzolbDrl8PPJgvzyv6gtoIFAHFwAZgWa48r2HH/Hb0i3+8+8yl55XA73Wr9c8r3aep/tyS+HlM+vON93tO5O982PUpe/1mw/NKx+t3Jp/XRMeN99i59Lyix2bF6zdTpxmv2VBKLYj+0F8B6rXWbQDRr3VxbvI+YLPWOoAZsbcOu641etlU3YAZrcYzBzPNhtY6DPQBs8a7o1x/XlrrlzBTym3R02Na65059Lwm4lFKbVBKvayUuhJy6vc16XFKqdMBF7B3GmNIyDR/bolKxc93Jl+/yYwpLc8rTa/fZMaUytfDaKl+/SZqRl7nM/n6zSTHTD6YUqoUuAf4vNa6Xyk12fEnA/8NXGJdFOcwPcWxfAhYA5w33iGJPlY+PC+l1CJgGTA3etnjSqm3A/9JbjyviczTWh9RSi0EnlJK7cX8RJIzz2u845RSjcBtwEe01sZUxpCoFPydJ/xQcS5L9uc7k6/flI8p2ftI0+t3WmNK8j4mkurXb6LS/jqfyddvps1YZkMp5cR8Qd+utf5z9OKO6A/b+qEfHXb8XOBe4HqttRXxtXL8xUT0/BGllF0ptSV6+o8ExnIR8BXg3Vakq5T6jnUfwx6rKXqdA6gAuvP4eb0HeFlrPai1HsRM1/44h57XuLTWR6Jf9wF/w3xx58zzindc9PJy4CHgq1rrlyd7vOlI0d/5ePc9+ucW9+c7yX1k8vWbDc8rHa/fmXxe40rD63dGn1c2vH6zwkzM1WBGiLcCPxx1+fcZWdjzvej5Ssw5rPfFua/XMIt7rIKdyyZ57NGFeasw01UTzo8Bn2ZkIdZdo65fDzyYL88LuAazOt8BODFTsffnyvMadvxvGTaHClQRnafF3MWxH7g1V57XeMdhpl2fxPx0lzOv3/F+Hsn+fEf/nhP9Ox92/XpS+PrN9PMiTa/fmXpe4x1Hml6/M/j7yvjrN1tOM/MgcDZm+ul1zCVMW4DLMOdQn8RcsvQkUB09/quAd9ixW4C66HVrgG3RX+BPGX/J4fcwI1Mj+vUb0cufADqG3e8D49zeA/wJc8nTq8DCYdc9BxwDAtHntS/XnxdmFfsvMZeV7c/B39fborfzYhaCbY9efibm0rWt0THk2vOKexzwISA0amwrc+D1G/fnEecx4/58x/s9Z8HrN6PPi/S9fmfqec3063emnlfGX7/ZcpJ25UIIIYRIK+kgKoQQQoi0kmBDCCGEEGklwYYQQggh0kqCDSGEEEKklQQbQgghhEgrCTaEEEIIkVYSbAghhBAirf5/vZLoi4V6kJcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 648x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "finra = quandl.get(\"FINRA/FNYX_GME\", trim_start = \"2020-12-01\")\n",
    "plt.figure(figsize=(9,7))\n",
    "plt.plot(finra)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exemplo de como verificar cotação vs. volume"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.reddit.com/r/wallstreetbets/comments/l81luf/hey_sec_heres_your_market_manipulation_rh_working/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OBS.: Nesse ponto tentar pegar os dados de short interest de vários outros papéis e compará-los no mesmo gráfico"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. yahoofinancials"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A biblioteca *yahoofinancials* é uma das melhores formas de se obter dados fundamentalistas direto do Yahoo Finance, em poucas linhas de código"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A grande desvantagem é que os dados são retornados em elementos JSON, que por natureza são difcíceis de se realizar o parse, e consequentemente torna o processamento e a análise posterior um pouco mais difícil"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Referências para trabalhar com JSONs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://towardsdatascience.com/how-to-parse-json-data-with-python-pandas-f84fbd0b1025\n",
    "    \n",
    "https://stackoverflow.com/questions/16729574/how-to-get-a-value-from-a-cell-of-a-dataframe\n",
    "    \n",
    "https://stackoverflow.com/questions/42354001/python-json-object-must-be-str-bytes-or-bytearray-not-dict\n",
    "    \n",
    "https://stackoverflow.com/questions/21104592/json-to-pandas-dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting yahoofinancials\n",
      "  Downloading yahoofinancials-1.6.tar.gz (27 kB)\n",
      "Requirement already satisfied: beautifulsoup4 in c:\\programdata\\anaconda3\\lib\\site-packages (from yahoofinancials) (4.9.3)\n",
      "Requirement already satisfied: pytz in c:\\programdata\\anaconda3\\lib\\site-packages (from yahoofinancials) (2020.1)\n",
      "Requirement already satisfied: soupsieve>1.2; python_version >= \"3.0\" in c:\\programdata\\anaconda3\\lib\\site-packages (from beautifulsoup4->yahoofinancials) (2.0.1)\n",
      "Building wheels for collected packages: yahoofinancials\n",
      "  Building wheel for yahoofinancials (setup.py): started\n",
      "  Building wheel for yahoofinancials (setup.py): finished with status 'done'\n",
      "  Created wheel for yahoofinancials: filename=yahoofinancials-1.6-py3-none-any.whl size=15195 sha256=e0c2ac737f8dd5c336dc101036356d2cc2b3e1a1ab832d81369b044eec0154c4\n",
      "  Stored in directory: c:\\users\\victo\\appdata\\local\\pip\\cache\\wheels\\6a\\90\\0c\\08c7ac2ce60b9ac91529417d471e59244f9f96848c86f14809\n",
      "Successfully built yahoofinancials\n",
      "Installing collected packages: yahoofinancials\n",
      "Successfully installed yahoofinancials-1.6\n"
     ]
    }
   ],
   "source": [
    "! pip install yahoofinancials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from yahoofinancials import YahooFinancials\n",
    "\n",
    "ticker = 'GME'\n",
    "yahoo_financials = YahooFinancials(ticker)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vamos verificar os dados anuais pra ver se bate com o Yahoo Finance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "balance_sheet_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'balance')\n",
    "income_statement_data_qt = yahoo_financials.get_financial_stmts('quarterly', 'income')\n",
    "all_statement_data_qt =  yahoo_financials.get_financial_stmts('quarterly', ['income', 'cash', 'balance'])\n",
    "GME_earnings_data = yahoo_financials.get_stock_earnings_data()\n",
    "GME_net_income = yahoo_financials.get_net_income()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "balance_sheet_data_qt = yahoo_financials.get_financial_stmts('annual', 'balance')\n",
    "income_statement_data_qt = yahoo_financials.get_financial_stmts('annual', 'income')\n",
    "\n",
    "# Outra opção de obter o dado de statment é usando todos os statements: income, cash e balance\n",
    "all_statement_data_qt =  yahoo_financials.get_financial_stmts('annual', ['income', 'cash', 'balance'])\n",
    "\n",
    "GME_earnings_data = yahoo_financials.get_stock_earnings_data()\n",
    "GME_net_income = yahoo_financials.get_net_income()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos fazer um teste: que tipo são esses dados nos outputs?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(all_statement_data_qt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'incomeStatementHistory': {'GME': [{'2020-02-01': {'researchDevelopment': None,\n",
       "     'effectOfAccountingCharges': None,\n",
       "     'incomeBeforeTax': -426800000,\n",
       "     'minorityInterest': None,\n",
       "     'netIncome': -470900000,\n",
       "     'sellingGeneralAdministrative': 1893600000,\n",
       "     'grossProfit': 1908700000,\n",
       "     'ebit': 15100000,\n",
       "     'operatingIncome': 15100000,\n",
       "     'otherOperatingExpenses': None,\n",
       "     'interestExpense': -38500000,\n",
       "     'extraordinaryItems': None,\n",
       "     'nonRecurring': None,\n",
       "     'otherItems': None,\n",
       "     'incomeTaxExpense': 37600000,\n",
       "     'totalRevenue': 6466000000,\n",
       "     'totalOperatingExpenses': 6450900000,\n",
       "     'costOfRevenue': 4557300000,\n",
       "     'totalOtherIncomeExpenseNet': -441900000,\n",
       "     'discontinuedOperations': -6500000,\n",
       "     'netIncomeFromContinuingOps': -464400000,\n",
       "     'netIncomeApplicableToCommonShares': -470900000}},\n",
       "   {'2019-02-02': {'researchDevelopment': None,\n",
       "     'effectOfAccountingCharges': None,\n",
       "     'incomeBeforeTax': -753100000,\n",
       "     'minorityInterest': None,\n",
       "     'netIncome': -673000000,\n",
       "     'sellingGeneralAdministrative': 1997200000,\n",
       "     'grossProfit': 2308100000,\n",
       "     'ebit': 310900000,\n",
       "     'operatingIncome': 310900000,\n",
       "     'otherOperatingExpenses': None,\n",
       "     'interestExpense': -56800000,\n",
       "     'extraordinaryItems': None,\n",
       "     'nonRecurring': None,\n",
       "     'otherItems': None,\n",
       "     'incomeTaxExpense': 41700000,\n",
       "     'totalRevenue': 8285300000,\n",
       "     'totalOperatingExpenses': 7974400000,\n",
       "     'costOfRevenue': 5977200000,\n",
       "     'totalOtherIncomeExpenseNet': -1064000000,\n",
       "     'discontinuedOperations': 121800000,\n",
       "     'netIncomeFromContinuingOps': -794800000,\n",
       "     'netIncomeApplicableToCommonShares': -673000000}},\n",
       "   {'2018-02-03': {'researchDevelopment': None,\n",
       "     'effectOfAccountingCharges': None,\n",
       "     'incomeBeforeTax': 383900000,\n",
       "     'minorityInterest': None,\n",
       "     'netIncome': 34700000,\n",
       "     'sellingGeneralAdministrative': 2040700000,\n",
       "     'grossProfit': 2484900000,\n",
       "     'ebit': 444200000,\n",
       "     'operatingIncome': 444200000,\n",
       "     'otherOperatingExpenses': None,\n",
       "     'interestExpense': -56800000,\n",
       "     'extraordinaryItems': None,\n",
       "     'nonRecurring': None,\n",
       "     'otherItems': None,\n",
       "     'incomeTaxExpense': 153500000,\n",
       "     'totalRevenue': 8547100000,\n",
       "     'totalOperatingExpenses': 8102900000,\n",
       "     'costOfRevenue': 6062200000,\n",
       "     'totalOtherIncomeExpenseNet': -60300000,\n",
       "     'discontinuedOperations': -195700000,\n",
       "     'netIncomeFromContinuingOps': 230400000,\n",
       "     'netIncomeApplicableToCommonShares': 34700000}},\n",
       "   {'2017-01-28': {'researchDevelopment': None,\n",
       "     'effectOfAccountingCharges': None,\n",
       "     'incomeBeforeTax': 428700000,\n",
       "     'minorityInterest': None,\n",
       "     'netIncome': 353200000,\n",
       "     'sellingGeneralAdministrative': 1861900000,\n",
       "     'grossProfit': 2499900000,\n",
       "     'ebit': 501300000,\n",
       "     'operatingIncome': 501300000,\n",
       "     'otherOperatingExpenses': None,\n",
       "     'interestExpense': -53800000,\n",
       "     'extraordinaryItems': None,\n",
       "     'nonRecurring': None,\n",
       "     'otherItems': None,\n",
       "     'incomeTaxExpense': 124200000,\n",
       "     'totalRevenue': 7965000000,\n",
       "     'totalOperatingExpenses': 7463700000,\n",
       "     'costOfRevenue': 5465100000,\n",
       "     'totalOtherIncomeExpenseNet': -72600000,\n",
       "     'discontinuedOperations': 48700000,\n",
       "     'netIncomeFromContinuingOps': 304500000,\n",
       "     'netIncomeApplicableToCommonShares': 353200000}}]},\n",
       " 'cashflowStatementHistory': {'GME': [{'2020-02-01': {'changeToLiabilities': -792800000,\n",
       "     'totalCashflowsFromInvestingActivities': -60900000,\n",
       "     'netBorrowings': -404500000,\n",
       "     'totalCashFromFinancingActivities': -644700000,\n",
       "     'changeToOperatingActivities': 7700000,\n",
       "     'netIncome': -470900000,\n",
       "     'changeInCash': -1127000000,\n",
       "     'repurchaseOfStock': -199700000,\n",
       "     'effectOfExchangeRate': -6900000,\n",
       "     'totalCashFromOperatingActivities': -414500000,\n",
       "     'depreciation': 96200000,\n",
       "     'otherCashflowsFromInvestingActivities': 12400000,\n",
       "     'dividendsPaid': -40500000,\n",
       "     'changeToInventory': 361100000,\n",
       "     'changeToAccountReceivables': -10900000,\n",
       "     'changeToNetincome': 471000000,\n",
       "     'capitalExpenditures': -78500000}},\n",
       "   {'2019-02-02': {'changeToLiabilities': -26000000,\n",
       "     'totalCashflowsFromInvestingActivities': 635500000,\n",
       "     'netBorrowings': -12200000,\n",
       "     'totalCashFromFinancingActivities': -174700000,\n",
       "     'changeToOperatingActivities': 7100000,\n",
       "     'netIncome': -673000000,\n",
       "     'changeInCash': 771400000,\n",
       "     'repurchaseOfStock': -5100000,\n",
       "     'effectOfExchangeRate': -24700000,\n",
       "     'totalCashFromOperatingActivities': 325100000,\n",
       "     'depreciation': 106800000,\n",
       "     'otherCashflowsFromInvestingActivities': 729200000,\n",
       "     'dividendsPaid': -157400000,\n",
       "     'changeToInventory': 12600000,\n",
       "     'changeToAccountReceivables': -34400000,\n",
       "     'changeToNetincome': 950700000,\n",
       "     'capitalExpenditures': -93700000}},\n",
       "   {'2018-02-03': {'changeToLiabilities': 146100000,\n",
       "     'totalCashflowsFromInvestingActivities': -60600000,\n",
       "     'netBorrowings': -21800000,\n",
       "     'totalCashFromFinancingActivities': -202500000,\n",
       "     'changeToOperatingActivities': -16000000,\n",
       "     'netIncome': 34700000,\n",
       "     'changeInCash': 194400000,\n",
       "     'repurchaseOfStock': -25500000,\n",
       "     'effectOfExchangeRate': 28000000,\n",
       "     'totalCashFromOperatingActivities': 434900000,\n",
       "     'depreciation': 123500000,\n",
       "     'otherCashflowsFromInvestingActivities': 2800000,\n",
       "     'dividendsPaid': -155200000,\n",
       "     'changeToInventory': -197200000,\n",
       "     'changeToAccountReceivables': 35700000,\n",
       "     'changeToNetincome': 332800000,\n",
       "     'capitalExpenditures': -113400000}},\n",
       "   {'2017-01-28': {'changeToLiabilities': 64100000,\n",
       "     'totalCashflowsFromInvestingActivities': -577400000,\n",
       "     'netBorrowings': 474600000,\n",
       "     'totalCashFromFinancingActivities': 238700000,\n",
       "     'changeToOperatingActivities': -9700000,\n",
       "     'netIncome': 353200000,\n",
       "     'changeInCash': 217300000,\n",
       "     'repurchaseOfStock': -71500000,\n",
       "     'effectOfExchangeRate': 21100000,\n",
       "     'totalCashFromOperatingActivities': 537100000,\n",
       "     'depreciation': 138200000,\n",
       "     'otherCashflowsFromInvestingActivities': 6500000,\n",
       "     'dividendsPaid': -155500000,\n",
       "     'changeToInventory': 14700000,\n",
       "     'changeToAccountReceivables': -43900000,\n",
       "     'otherCashflowsFromFinancingActivities': -8900000,\n",
       "     'changeToNetincome': 69600000,\n",
       "     'capitalExpenditures': -142700000}}]},\n",
       " 'balanceSheetHistory': {'GME': [{'2020-02-01': {'totalLiab': 2208200000,\n",
       "     'totalStockholderEquity': 611500000,\n",
       "     'otherCurrentLiab': 423000000,\n",
       "     'totalAssets': 2819700000,\n",
       "     'commonStock': 100000,\n",
       "     'otherCurrentAssets': 13500000,\n",
       "     'retainedEarnings': 690200000,\n",
       "     'otherLiab': 21400000,\n",
       "     'treasuryStock': -78800000,\n",
       "     'otherAssets': 143100000,\n",
       "     'cash': 499400000,\n",
       "     'totalCurrentLiabilities': 1237700000,\n",
       "     'deferredLongTermAssetCharges': 83000000,\n",
       "     'otherStockholderEquity': -78800000,\n",
       "     'propertyPlantEquipment': 1042900000,\n",
       "     'totalCurrentAssets': 1633700000,\n",
       "     'netTangibleAssets': 611500000,\n",
       "     'netReceivables': 141900000,\n",
       "     'longTermDebt': 419800000,\n",
       "     'inventory': 859700000,\n",
       "     'accountsPayable': 380800000}},\n",
       "   {'2019-02-02': {'intangibleAssets': 33500000,\n",
       "     'capitalSurplus': 27700000,\n",
       "     'totalLiab': 2708100000,\n",
       "     'totalStockholderEquity': 1336200000,\n",
       "     'otherCurrentLiab': 549500000,\n",
       "     'totalAssets': 4044300000,\n",
       "     'commonStock': 100000,\n",
       "     'otherCurrentAssets': 3700000,\n",
       "     'retainedEarnings': 1362700000,\n",
       "     'otherLiab': 55400000,\n",
       "     'goodWill': 363900000,\n",
       "     'treasuryStock': -54300000,\n",
       "     'otherAssets': 231400000,\n",
       "     'cash': 1624400000,\n",
       "     'totalCurrentLiabilities': 2181100000,\n",
       "     'deferredLongTermAssetCharges': 147300000,\n",
       "     'shortLongTermDebt': 349200000,\n",
       "     'otherStockholderEquity': -54300000,\n",
       "     'propertyPlantEquipment': 321300000,\n",
       "     'totalCurrentAssets': 3127700000,\n",
       "     'netTangibleAssets': 972300000,\n",
       "     'netReceivables': 134200000,\n",
       "     'longTermDebt': 471600000,\n",
       "     'inventory': 1250500000,\n",
       "     'accountsPayable': 1051900000}},\n",
       "   {'2018-02-03': {'intangibleAssets': 92500000,\n",
       "     'capitalSurplus': 22100000,\n",
       "     'totalLiab': 2827100000,\n",
       "     'totalStockholderEquity': 2214500000,\n",
       "     'otherCurrentLiab': 711600000,\n",
       "     'totalAssets': 5041600000,\n",
       "     'commonStock': 100000,\n",
       "     'otherCurrentAssets': 662500000,\n",
       "     'retainedEarnings': 2180100000,\n",
       "     'otherLiab': 78400000,\n",
       "     'goodWill': 1350500000,\n",
       "     'treasuryStock': 12200000,\n",
       "     'otherAssets': 229200000,\n",
       "     'cash': 854200000,\n",
       "     'totalCurrentLiabilities': 1930800000,\n",
       "     'deferredLongTermAssetCharges': 158200000,\n",
       "     'otherStockholderEquity': 12200000,\n",
       "     'propertyPlantEquipment': 351000000,\n",
       "     'totalCurrentAssets': 3018400000,\n",
       "     'netTangibleAssets': 771500000,\n",
       "     'netReceivables': 138600000,\n",
       "     'longTermDebt': 817900000,\n",
       "     'inventory': 1250300000,\n",
       "     'accountsPayable': 892300000}},\n",
       "   {'2017-01-28': {'intangibleAssets': 507200000,\n",
       "     'totalLiab': 2721800000,\n",
       "     'totalStockholderEquity': 2254100000,\n",
       "     'otherCurrentLiab': 816400000,\n",
       "     'totalAssets': 4975900000,\n",
       "     'commonStock': 100000,\n",
       "     'otherCurrentAssets': 13300000,\n",
       "     'retainedEarnings': 2301300000,\n",
       "     'otherLiab': 145300000,\n",
       "     'goodWill': 1725200000,\n",
       "     'treasuryStock': -47300000,\n",
       "     'otherAssets': 131800000,\n",
       "     'cash': 669400000,\n",
       "     'totalCurrentLiabilities': 1761500000,\n",
       "     'deferredLongTermAssetCharges': 59000000,\n",
       "     'otherStockholderEquity': -47300000,\n",
       "     'propertyPlantEquipment': 471000000,\n",
       "     'totalCurrentAssets': 2140700000,\n",
       "     'netTangibleAssets': 21700000,\n",
       "     'netReceivables': 220900000,\n",
       "     'longTermDebt': 815000000,\n",
       "     'inventory': 1121500000,\n",
       "     'accountsPayable': 616600000}}]}}"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_statement_data_qt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Verifique que esses dados são do tipo \"JSON\", por isso vem no formato de dicionário. Por causa disso, teremos que trabalhar com métodos específicos para tratar JSON"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As principais funções para se trabalhar com JSON são:\n",
    "\n",
    "json.loads take a string as input and returns a dictionary as output.\n",
    "\n",
    "json.dumps take a dictionary as input and returns a string as output.\n",
    "\n",
    "Além disso, na package pandas, a função pd.json_normalize pega um JSON de input e transforma num pandas Data Frame de output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "#data = json.dumps(data)\n",
    "#data = json.loads(data)\n",
    "\n",
    "incomeStatementHistory = pd.json_normalize(all_statement_data_qt['incomeStatementHistory'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[{'2020-02-01': {'researchDevelopment': None, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 GME\n",
       "0  [{'2020-02-01': {'researchDevelopment': None, ..."
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "incomeStatementHistory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "dictionary = incomeStatementHistory.iloc[0]\n",
    "\n",
    "string = list(dictionary[[0]])\n",
    "\n",
    "stringa = string[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'2020-02-01': {'researchDevelopment': None,\n",
       "   'effectOfAccountingCharges': None,\n",
       "   'incomeBeforeTax': -426800000,\n",
       "   'minorityInterest': None,\n",
       "   'netIncome': -470900000,\n",
       "   'sellingGeneralAdministrative': 1893600000,\n",
       "   'grossProfit': 1908700000,\n",
       "   'ebit': 15100000,\n",
       "   'operatingIncome': 15100000,\n",
       "   'otherOperatingExpenses': None,\n",
       "   'interestExpense': -38500000,\n",
       "   'extraordinaryItems': None,\n",
       "   'nonRecurring': None,\n",
       "   'otherItems': None,\n",
       "   'incomeTaxExpense': 37600000,\n",
       "   'totalRevenue': 6466000000,\n",
       "   'totalOperatingExpenses': 6450900000,\n",
       "   'costOfRevenue': 4557300000,\n",
       "   'totalOtherIncomeExpenseNet': -441900000,\n",
       "   'discontinuedOperations': -6500000,\n",
       "   'netIncomeFromContinuingOps': -464400000,\n",
       "   'netIncomeApplicableToCommonShares': -470900000}},\n",
       " {'2019-02-02': {'researchDevelopment': None,\n",
       "   'effectOfAccountingCharges': None,\n",
       "   'incomeBeforeTax': -753100000,\n",
       "   'minorityInterest': None,\n",
       "   'netIncome': -673000000,\n",
       "   'sellingGeneralAdministrative': 1997200000,\n",
       "   'grossProfit': 2308100000,\n",
       "   'ebit': 310900000,\n",
       "   'operatingIncome': 310900000,\n",
       "   'otherOperatingExpenses': None,\n",
       "   'interestExpense': -56800000,\n",
       "   'extraordinaryItems': None,\n",
       "   'nonRecurring': None,\n",
       "   'otherItems': None,\n",
       "   'incomeTaxExpense': 41700000,\n",
       "   'totalRevenue': 8285300000,\n",
       "   'totalOperatingExpenses': 7974400000,\n",
       "   'costOfRevenue': 5977200000,\n",
       "   'totalOtherIncomeExpenseNet': -1064000000,\n",
       "   'discontinuedOperations': 121800000,\n",
       "   'netIncomeFromContinuingOps': -794800000,\n",
       "   'netIncomeApplicableToCommonShares': -673000000}},\n",
       " {'2018-02-03': {'researchDevelopment': None,\n",
       "   'effectOfAccountingCharges': None,\n",
       "   'incomeBeforeTax': 383900000,\n",
       "   'minorityInterest': None,\n",
       "   'netIncome': 34700000,\n",
       "   'sellingGeneralAdministrative': 2040700000,\n",
       "   'grossProfit': 2484900000,\n",
       "   'ebit': 444200000,\n",
       "   'operatingIncome': 444200000,\n",
       "   'otherOperatingExpenses': None,\n",
       "   'interestExpense': -56800000,\n",
       "   'extraordinaryItems': None,\n",
       "   'nonRecurring': None,\n",
       "   'otherItems': None,\n",
       "   'incomeTaxExpense': 153500000,\n",
       "   'totalRevenue': 8547100000,\n",
       "   'totalOperatingExpenses': 8102900000,\n",
       "   'costOfRevenue': 6062200000,\n",
       "   'totalOtherIncomeExpenseNet': -60300000,\n",
       "   'discontinuedOperations': -195700000,\n",
       "   'netIncomeFromContinuingOps': 230400000,\n",
       "   'netIncomeApplicableToCommonShares': 34700000}},\n",
       " {'2017-01-28': {'researchDevelopment': None,\n",
       "   'effectOfAccountingCharges': None,\n",
       "   'incomeBeforeTax': 428700000,\n",
       "   'minorityInterest': None,\n",
       "   'netIncome': 353200000,\n",
       "   'sellingGeneralAdministrative': 1861900000,\n",
       "   'grossProfit': 2499900000,\n",
       "   'ebit': 501300000,\n",
       "   'operatingIncome': 501300000,\n",
       "   'otherOperatingExpenses': None,\n",
       "   'interestExpense': -53800000,\n",
       "   'extraordinaryItems': None,\n",
       "   'nonRecurring': None,\n",
       "   'otherItems': None,\n",
       "   'incomeTaxExpense': 124200000,\n",
       "   'totalRevenue': 7965000000,\n",
       "   'totalOperatingExpenses': 7463700000,\n",
       "   'costOfRevenue': 5465100000,\n",
       "   'totalOtherIncomeExpenseNet': -72600000,\n",
       "   'discontinuedOperations': 48700000,\n",
       "   'netIncomeFromContinuingOps': 304500000,\n",
       "   'netIncomeApplicableToCommonShares': 353200000}}]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stringa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observe que aqui obtivemos uma lista contendo vários dicionários, onde cada trimestre possui os resultados representados em um dicionário"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Se quisermos trabalhar com um trimestre ou ano específico, precisaremos filtrar, e só em seguida criar um data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "string_b = stringa[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'2020-02-01': {'researchDevelopment': None,\n",
       "  'effectOfAccountingCharges': None,\n",
       "  'incomeBeforeTax': -426800000,\n",
       "  'minorityInterest': None,\n",
       "  'netIncome': -470900000,\n",
       "  'sellingGeneralAdministrative': 1893600000,\n",
       "  'grossProfit': 1908700000,\n",
       "  'ebit': 15100000,\n",
       "  'operatingIncome': 15100000,\n",
       "  'otherOperatingExpenses': None,\n",
       "  'interestExpense': -38500000,\n",
       "  'extraordinaryItems': None,\n",
       "  'nonRecurring': None,\n",
       "  'otherItems': None,\n",
       "  'incomeTaxExpense': 37600000,\n",
       "  'totalRevenue': 6466000000,\n",
       "  'totalOperatingExpenses': 6450900000,\n",
       "  'costOfRevenue': 4557300000,\n",
       "  'totalOtherIncomeExpenseNet': -441900000,\n",
       "  'discontinuedOperations': -6500000,\n",
       "  'netIncomeFromContinuingOps': -464400000,\n",
       "  'netIncomeApplicableToCommonShares': -470900000}}"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "string_b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Agora enfim podemos transformar isso num data frame e em seguida seguir com a análise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "string_df = pd.json_normalize(string_b['2020-02-01'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>researchDevelopment</th>\n",
       "      <th>effectOfAccountingCharges</th>\n",
       "      <th>incomeBeforeTax</th>\n",
       "      <th>minorityInterest</th>\n",
       "      <th>netIncome</th>\n",
       "      <th>sellingGeneralAdministrative</th>\n",
       "      <th>grossProfit</th>\n",
       "      <th>ebit</th>\n",
       "      <th>operatingIncome</th>\n",
       "      <th>otherOperatingExpenses</th>\n",
       "      <th>...</th>\n",
       "      <th>nonRecurring</th>\n",
       "      <th>otherItems</th>\n",
       "      <th>incomeTaxExpense</th>\n",
       "      <th>totalRevenue</th>\n",
       "      <th>totalOperatingExpenses</th>\n",
       "      <th>costOfRevenue</th>\n",
       "      <th>totalOtherIncomeExpenseNet</th>\n",
       "      <th>discontinuedOperations</th>\n",
       "      <th>netIncomeFromContinuingOps</th>\n",
       "      <th>netIncomeApplicableToCommonShares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-426800000</td>\n",
       "      <td>None</td>\n",
       "      <td>-470900000</td>\n",
       "      <td>1893600000</td>\n",
       "      <td>1908700000</td>\n",
       "      <td>15100000</td>\n",
       "      <td>15100000</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>37600000</td>\n",
       "      <td>6466000000</td>\n",
       "      <td>6450900000</td>\n",
       "      <td>4557300000</td>\n",
       "      <td>-441900000</td>\n",
       "      <td>-6500000</td>\n",
       "      <td>-464400000</td>\n",
       "      <td>-470900000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  researchDevelopment effectOfAccountingCharges  incomeBeforeTax  \\\n",
       "0                None                      None       -426800000   \n",
       "\n",
       "  minorityInterest  netIncome  sellingGeneralAdministrative  grossProfit  \\\n",
       "0             None -470900000                    1893600000   1908700000   \n",
       "\n",
       "       ebit  operatingIncome otherOperatingExpenses  ...  nonRecurring  \\\n",
       "0  15100000         15100000                   None  ...          None   \n",
       "\n",
       "  otherItems incomeTaxExpense totalRevenue  totalOperatingExpenses  \\\n",
       "0       None         37600000   6466000000              6450900000   \n",
       "\n",
       "   costOfRevenue  totalOtherIncomeExpenseNet  discontinuedOperations  \\\n",
       "0     4557300000                  -441900000                -6500000   \n",
       "\n",
       "   netIncomeFromContinuingOps  netIncomeApplicableToCommonShares  \n",
       "0                  -464400000                         -470900000  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "string_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Uma outra forma mais fácil de obter todas as estatísticas principais de uma só vez:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'GME': {'annualHoldingsTurnover': None, 'enterpriseToRevenue': 4.529, 'beta3Year': None, 'profitMargins': -0.053239997, 'enterpriseToEbitda': -180.657, '52WeekChange': 81.27848, 'morningStarRiskRating': None, 'forwardEps': -0.17, 'revenueQuarterlyGrowth': None, 'sharesOutstanding': 69747000, 'fundInceptionDate': '-', 'annualReportExpenseRatio': None, 'totalAssets': None, 'bookValue': 5.095, 'sharesShort': 61782730, 'sharesPercentSharesOut': 0.8858, 'fundFamily': None, 'lastFiscalYearEnd': 1580515200, 'heldPercentInstitutions': 1.2204499, 'netIncomeToCommon': -270000000, 'trailingEps': -4.224, 'lastDividendValue': 0.38, 'SandP52WeekChange': 0.14322305, 'priceToBook': 48.086384, 'heldPercentInsiders': 0.27334, 'nextFiscalYearEnd': 1643673600, 'yield': None, 'mostRecentQuarter': 1604102400, 'shortRatio': 2.81, 'sharesShortPreviousMonthDate': '2020-12-15', 'floatShares': 46888789, 'beta': 1.433298, 'enterpriseValue': 23376961536, 'priceHint': 2, 'threeYearAverageReturn': None, 'lastSplitDate': '2007-03-19', 'lastSplitFactor': '2:1', 'legalType': None, 'lastDividendDate': '2019-03-14', 'morningStarOverallRating': None, 'earningsQuarterlyGrowth': None, 'priceToSalesTrailing12Months': None, 'dateShortInterest': 1610668800, 'pegRatio': 0.18, 'ytdReturn': None, 'forwardPE': -1441.1771, 'maxAge': 1, 'lastCapGain': None, 'shortPercentOfFloat': 2.2642, 'sharesShortPriorMonth': 68127116, 'impliedSharesOutstanding': None, 'category': None, 'fiveYearAverageReturn': None}}\n"
     ]
    }
   ],
   "source": [
    "yahoo_financials = YahooFinancials('GME')\n",
    "print(yahoo_financials.get_key_statistics_data())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "key_statistics = yahoo_financials.get_key_statistics_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos transformar esse JSON em um data frame?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "key_statistics_df = pd.json_normalize(key_statistics['GME'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>annualHoldingsTurnover</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>enterpriseToRevenue</th>\n",
       "      <td>4.529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta3Year</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>profitMargins</th>\n",
       "      <td>-0.05324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>enterpriseToEbitda</th>\n",
       "      <td>-180.657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52WeekChange</th>\n",
       "      <td>81.2785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>morningStarRiskRating</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>forwardEps</th>\n",
       "      <td>-0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revenueQuarterlyGrowth</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharesOutstanding</th>\n",
       "      <td>69747000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fundInceptionDate</th>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>annualReportExpenseRatio</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalAssets</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bookValue</th>\n",
       "      <td>5.095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharesShort</th>\n",
       "      <td>61782730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharesPercentSharesOut</th>\n",
       "      <td>0.8858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fundFamily</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastFiscalYearEnd</th>\n",
       "      <td>1580515200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heldPercentInstitutions</th>\n",
       "      <td>1.22045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>netIncomeToCommon</th>\n",
       "      <td>-270000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trailingEps</th>\n",
       "      <td>-4.224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastDividendValue</th>\n",
       "      <td>0.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SandP52WeekChange</th>\n",
       "      <td>0.143223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>priceToBook</th>\n",
       "      <td>48.0864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>heldPercentInsiders</th>\n",
       "      <td>0.27334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nextFiscalYearEnd</th>\n",
       "      <td>1643673600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>yield</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mostRecentQuarter</th>\n",
       "      <td>1604102400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shortRatio</th>\n",
       "      <td>2.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharesShortPreviousMonthDate</th>\n",
       "      <td>2020-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>floatShares</th>\n",
       "      <td>46888789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>beta</th>\n",
       "      <td>1.4333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>enterpriseValue</th>\n",
       "      <td>23376961536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>priceHint</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>threeYearAverageReturn</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastSplitDate</th>\n",
       "      <td>2007-03-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastSplitFactor</th>\n",
       "      <td>2:1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>legalType</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastDividendDate</th>\n",
       "      <td>2019-03-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>morningStarOverallRating</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>earningsQuarterlyGrowth</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>priceToSalesTrailing12Months</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dateShortInterest</th>\n",
       "      <td>1610668800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pegRatio</th>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ytdReturn</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>forwardPE</th>\n",
       "      <td>-1441.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>maxAge</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastCapGain</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shortPercentOfFloat</th>\n",
       "      <td>2.2642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sharesShortPriorMonth</th>\n",
       "      <td>68127116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>impliedSharesOutstanding</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fiveYearAverageReturn</th>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        0\n",
       "annualHoldingsTurnover               None\n",
       "enterpriseToRevenue                 4.529\n",
       "beta3Year                            None\n",
       "profitMargins                    -0.05324\n",
       "enterpriseToEbitda               -180.657\n",
       "52WeekChange                      81.2785\n",
       "morningStarRiskRating                None\n",
       "forwardEps                          -0.17\n",
       "revenueQuarterlyGrowth               None\n",
       "sharesOutstanding                69747000\n",
       "fundInceptionDate                       -\n",
       "annualReportExpenseRatio             None\n",
       "totalAssets                          None\n",
       "bookValue                           5.095\n",
       "sharesShort                      61782730\n",
       "sharesPercentSharesOut             0.8858\n",
       "fundFamily                           None\n",
       "lastFiscalYearEnd              1580515200\n",
       "heldPercentInstitutions           1.22045\n",
       "netIncomeToCommon              -270000000\n",
       "trailingEps                        -4.224\n",
       "lastDividendValue                    0.38\n",
       "SandP52WeekChange                0.143223\n",
       "priceToBook                       48.0864\n",
       "heldPercentInsiders               0.27334\n",
       "nextFiscalYearEnd              1643673600\n",
       "yield                                None\n",
       "mostRecentQuarter              1604102400\n",
       "shortRatio                           2.81\n",
       "sharesShortPreviousMonthDate   2020-12-15\n",
       "floatShares                      46888789\n",
       "beta                               1.4333\n",
       "enterpriseValue               23376961536\n",
       "priceHint                               2\n",
       "threeYearAverageReturn               None\n",
       "lastSplitDate                  2007-03-19\n",
       "lastSplitFactor                       2:1\n",
       "legalType                            None\n",
       "lastDividendDate               2019-03-14\n",
       "morningStarOverallRating             None\n",
       "earningsQuarterlyGrowth              None\n",
       "priceToSalesTrailing12Months         None\n",
       "dateShortInterest              1610668800\n",
       "pegRatio                             0.18\n",
       "ytdReturn                            None\n",
       "forwardPE                        -1441.18\n",
       "maxAge                                  1\n",
       "lastCapGain                          None\n",
       "shortPercentOfFloat                2.2642\n",
       "sharesShortPriorMonth            68127116\n",
       "impliedSharesOutstanding             None\n",
       "category                             None\n",
       "fiveYearAverageReturn                None"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "key_statistics_df.transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vamos usar agora um pouco de webscraping para obter as informações de short interest direto da internet?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://www.marketbeat.com/short-interest/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = requests.request(\"POST\", url)\n",
    "\n",
    "tables = pd.read_html(response.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[                                              Company  \\\n",
       " 0                          CHTRCharter Communications   \n",
       " 1                                       VIACViacomCBS   \n",
       " 2                                              AONAON   \n",
       " 3                                   ADIAnalog Devices   \n",
       " 4                                         MRNAModerna   \n",
       " 5                                 DDDuPont de Nemours   \n",
       " 6                           PLTRPalantir Technologies   \n",
       " 7                                            SNAPSnap   \n",
       " 8               IFFInternational Flavors & Fragrances   \n",
       " 9                                     BYNDBeyond Meat   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                       KRThe Kroger   \n",
       " 12                                      CLXThe Clorox   \n",
       " 13                                      SNOWSnowflake   \n",
       " 14                              BBBYBed Bath & Beyond   \n",
       " 15                                       SPWRSunPower   \n",
       " 16                                     DISCADiscovery   \n",
       " 17                            PTONPeloton Interactive   \n",
       " 18                                     ATUSAltice USA   \n",
       " 19                         LGNDLigand Pharmaceuticals   \n",
       " 20                                       DASHDoorDash   \n",
       " 21                                         ABNBAirbnb   \n",
       " 22                             PANWPalo Alto Networks   \n",
       " 23                                SPCEVirgin Galactic   \n",
       " 24                                   IRMIron Mountain   \n",
       " 25                                        DDOGDatadog   \n",
       " 26                                        PENPenumbra   \n",
       " 27                                           FUTUFutu   \n",
       " 28                              MPCMarathon Petroleum   \n",
       " 29                    WLTWWillis Towers Watson Public   \n",
       " 30                                         FUBOfuboTV   \n",
       " 31                                    MACThe Macerich   \n",
       " 32              CHKPCheck Point Software Technologies   \n",
       " 33                                               RHRH   \n",
       " 34                                            MMacy's   \n",
       " 35                                  EXPEExpedia Group   \n",
       " 36                                       FTCHFarfetch   \n",
       " 37                              STXSeagate Technology   \n",
       " 38                                          VMWVMware   \n",
       " 39                                         IRBTiRobot   \n",
       " 40                                   CGCCanopy Growth   \n",
       " 41                                      SIRISirius XM   \n",
       " 42                                       LMNDLemonade   \n",
       " 43                          NUANNuance Communications   \n",
       " 44                          KEYSKeysight Technologies   \n",
       " 45                                 ENPHEnphase Energy   \n",
       " 46                                        ESTCElastic   \n",
       " 47                                 ONON Semiconductor   \n",
       " 48                                         NKLANikola   \n",
       " 49                         OLLIOllie's Bargain Outlet   \n",
       " 50                                           LYFTLyft   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                         Shares Sold Short (1/15/2021)  \\\n",
       " 0                                            10620000   \n",
       " 1                                           121250000   \n",
       " 2                                            22570000   \n",
       " 3                                            30400000   \n",
       " 4                                            24800000   \n",
       " 5                                            46490000   \n",
       " 6                                            98950000   \n",
       " 7                                            65420000   \n",
       " 8                                            29980000   \n",
       " 9                                            15440000   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                           76140000   \n",
       " 12                                           12730000   \n",
       " 13                                            9270000   \n",
       " 14                                           74890000   \n",
       " 15                                           46520000   \n",
       " 16                                           58070000   \n",
       " 17                                           15170000   \n",
       " 18                                           57460000   \n",
       " 19                                           10010000   \n",
       " 20                                            9810000   \n",
       " 21                                            9180000   \n",
       " 22                                            4810000   \n",
       " 23                                           38600000   \n",
       " 24                                           49800000   \n",
       " 25                                           16110000   \n",
       " 26                                            6060000   \n",
       " 27                                           16060000   \n",
       " 28                                           35060000   \n",
       " 29                                            7570000   \n",
       " 30                                           39170000   \n",
       " 31                                           78540000   \n",
       " 32                                           10870000   \n",
       " 33                                            2920000   \n",
       " 34                                           88790000   \n",
       " 35                                           10860000   \n",
       " 36                                           21740000   \n",
       " 37                                           19700000   \n",
       " 38                                            9210000   \n",
       " 39                                           10550000   \n",
       " 40                                           31910000   \n",
       " 41                                          198670000   \n",
       " 42                                            8490000   \n",
       " 43                                           27360000   \n",
       " 44                                            8590000   \n",
       " 45                                            6430000   \n",
       " 46                                            8050000   \n",
       " 47                                           34890000   \n",
       " 48                                           52610000   \n",
       " 49                                           12190000   \n",
       " 50                                           25510000   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                               Dollar VolumeSold Short  \\\n",
       " 0                                       $6.95 billion   \n",
       " 1                                       $6.14 billion   \n",
       " 2                                       $4.66 billion   \n",
       " 3                                       $4.54 billion   \n",
       " 4                                       $3.96 billion   \n",
       " 5                                       $3.77 billion   \n",
       " 6                                       $3.53 billion   \n",
       " 7                                       $3.48 billion   \n",
       " 8                                       $3.45 billion   \n",
       " 9                                       $2.78 billion   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                      $2.69 billion   \n",
       " 12                                      $2.67 billion   \n",
       " 13                                      $2.53 billion   \n",
       " 14                                      $2.52 billion   \n",
       " 15                                      $2.46 billion   \n",
       " 16                                      $2.38 billion   \n",
       " 17                                      $2.21 billion   \n",
       " 18                                      $2.10 billion   \n",
       " 19                                      $1.92 billion   \n",
       " 20                                      $1.80 billion   \n",
       " 21                                      $1.72 billion   \n",
       " 22                                      $1.70 billion   \n",
       " 23                                      $1.66 billion   \n",
       " 24                                      $1.66 billion   \n",
       " 25                                      $1.61 billion   \n",
       " 26                                      $1.60 billion   \n",
       " 27                                      $1.59 billion   \n",
       " 28                                      $1.57 billion   \n",
       " 29                                      $1.56 billion   \n",
       " 30                                      $1.56 billion   \n",
       " 31                                      $1.49 billion   \n",
       " 32                                      $1.44 billion   \n",
       " 33                                      $1.39 billion   \n",
       " 34                                      $1.38 billion   \n",
       " 35                                      $1.38 billion   \n",
       " 36                                      $1.32 billion   \n",
       " 37                                      $1.31 billion   \n",
       " 38                                      $1.29 billion   \n",
       " 39                                      $1.29 billion   \n",
       " 40                                      $1.29 billion   \n",
       " 41                                      $1.27 billion   \n",
       " 42                                      $1.27 billion   \n",
       " 43                                      $1.26 billion   \n",
       " 44                                      $1.25 billion   \n",
       " 45                                      $1.25 billion   \n",
       " 46                                      $1.23 billion   \n",
       " 47                                      $1.23 billion   \n",
       " 48                                      $1.22 billion   \n",
       " 49                                      $1.19 billion   \n",
       " 50                                      $1.18 billion   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                        Shares Sold Short (12/31/2020)  \\\n",
       " 0                                            10630000   \n",
       " 1                                           117920000   \n",
       " 2                                            21470000   \n",
       " 3                                            28260000   \n",
       " 4                                            23390000   \n",
       " 5                                            23670000   \n",
       " 6                                            90740000   \n",
       " 7                                            63160000   \n",
       " 8                                            19880000   \n",
       " 9                                            13690000   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                           73390000   \n",
       " 12                                           12280000   \n",
       " 13                                           10650000   \n",
       " 14                                           76180000   \n",
       " 15                                           43350000   \n",
       " 16                                           54610000   \n",
       " 17                                           17290000   \n",
       " 18                                           51610000   \n",
       " 19                                            9910000   \n",
       " 20                                            8820000   \n",
       " 21                                            7960000   \n",
       " 22                                            5360000   \n",
       " 23                                           43740000   \n",
       " 24                                           49690000   \n",
       " 25                                           15350000   \n",
       " 26                                            5930000   \n",
       " 27                                           13600000   \n",
       " 28                                           31890000   \n",
       " 29                                            6620000   \n",
       " 30                                           33860000   \n",
       " 31                                           80640000   \n",
       " 32                                           11430000   \n",
       " 33                                            2780000   \n",
       " 34                                          108650000   \n",
       " 35                                           13050000   \n",
       " 36                                           21020000   \n",
       " 37                                           16980000   \n",
       " 38                                            9280000   \n",
       " 39                                           10260000   \n",
       " 40                                           32380000   \n",
       " 41                                          191080000   \n",
       " 42                                            8280000   \n",
       " 43                                           24710000   \n",
       " 44                                            9410000   \n",
       " 45                                            8300000   \n",
       " 46                                            7520000   \n",
       " 47                                           31090000   \n",
       " 48                                           54440000   \n",
       " 49                                           12730000   \n",
       " 50                                           24520000   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                                                Change  \\\n",
       " 0                                              -10000   \n",
       " 1                                             3330000   \n",
       " 2                                             1100000   \n",
       " 3                                             2140000   \n",
       " 4                                             1410000   \n",
       " 5                                            22820000   \n",
       " 6                                             8210000   \n",
       " 7                                             2260000   \n",
       " 8                                            10100000   \n",
       " 9                                             1750000   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                            2750000   \n",
       " 12                                             450000   \n",
       " 13                                           -1380000   \n",
       " 14                                           -1290000   \n",
       " 15                                            3170000   \n",
       " 16                                            3460000   \n",
       " 17                                           -2120000   \n",
       " 18                                            5850000   \n",
       " 19                                             100000   \n",
       " 20                                             990000   \n",
       " 21                                            1220000   \n",
       " 22                                            -550000   \n",
       " 23                                           -5140000   \n",
       " 24                                             110000   \n",
       " 25                                             760000   \n",
       " 26                                             130000   \n",
       " 27                                            2460000   \n",
       " 28                                            3170000   \n",
       " 29                                             950000   \n",
       " 30                                            5310000   \n",
       " 31                                           -2100000   \n",
       " 32                                            -560000   \n",
       " 33                                             140000   \n",
       " 34                                          -19860000   \n",
       " 35                                           -2190000   \n",
       " 36                                             720000   \n",
       " 37                                            2720000   \n",
       " 38                                             -70000   \n",
       " 39                                             290000   \n",
       " 40                                            -470000   \n",
       " 41                                            7590000   \n",
       " 42                                             210000   \n",
       " 43                                            2650000   \n",
       " 44                                            -820000   \n",
       " 45                                           -1870000   \n",
       " 46                                             530000   \n",
       " 47                                            3800000   \n",
       " 48                                           -1830000   \n",
       " 49                                            -540000   \n",
       " 50                                             990000   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                                              % Change  \\\n",
       " 0                                               -0.1%   \n",
       " 1                                                2.8%   \n",
       " 2                                                5.1%   \n",
       " 3                                                7.6%   \n",
       " 4                                                6.0%   \n",
       " 5                                               96.4%   \n",
       " 6                                                0.0%   \n",
       " 7                                                3.6%   \n",
       " 8                                               50.8%   \n",
       " 9                                               12.8%   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                               3.8%   \n",
       " 12                                               3.7%   \n",
       " 13                                               0.0%   \n",
       " 14                                              -1.7%   \n",
       " 15                                               7.3%   \n",
       " 16                                               6.3%   \n",
       " 17                                             -12.3%   \n",
       " 18                                              11.3%   \n",
       " 19                                               1.0%   \n",
       " 20                                               0.0%   \n",
       " 21                                               0.0%   \n",
       " 22                                             -10.3%   \n",
       " 23                                             -11.8%   \n",
       " 24                                               0.2%   \n",
       " 25                                               5.0%   \n",
       " 26                                               2.2%   \n",
       " 27                                              18.1%   \n",
       " 28                                               9.9%   \n",
       " 29                                              14.4%   \n",
       " 30                                               0.0%   \n",
       " 31                                              -2.6%   \n",
       " 32                                              -4.9%   \n",
       " 33                                               5.0%   \n",
       " 34                                             -18.3%   \n",
       " 35                                             -16.8%   \n",
       " 36                                               3.4%   \n",
       " 37                                              16.0%   \n",
       " 38                                              -0.8%   \n",
       " 39                                               2.8%   \n",
       " 40                                              -1.5%   \n",
       " 41                                               4.0%   \n",
       " 42                                               0.0%   \n",
       " 43                                              10.7%   \n",
       " 44                                              -8.7%   \n",
       " 45                                             -22.5%   \n",
       " 46                                               7.1%   \n",
       " 47                                              12.2%   \n",
       " 48                                               0.0%   \n",
       " 49                                              -4.2%   \n",
       " 50                                               4.0%   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                                               % Float  \\\n",
       " 0                                                7.9%   \n",
       " 1                                               22.4%   \n",
       " 2                                               10.0%   \n",
       " 3                                                8.3%   \n",
       " 4                                                7.6%   \n",
       " 5                                                6.4%   \n",
       " 6                                                9.7%   \n",
       " 7                                                7.0%   \n",
       " 8                                               28.1%   \n",
       " 9                                               42.9%   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                              10.1%   \n",
       " 12                                              10.1%   \n",
       " 13                                              19.9%   \n",
       " 14                                              65.5%   \n",
       " 15                                              57.5%   \n",
       " 16                                              37.6%   \n",
       " 17                                               6.2%   \n",
       " 18                                              23.8%   \n",
       " 19                                              64.9%   \n",
       " 20                                               7.9%   \n",
       " 21                                              11.3%   \n",
       " 22                                               5.1%   \n",
       " 23                                              72.0%   \n",
       " 24                                              17.5%   \n",
       " 25                                               8.8%   \n",
       " 26                                              17.8%   \n",
       " 27                                              25.7%   \n",
       " 28                                               5.4%   \n",
       " 29                                               5.9%   \n",
       " 30                                              71.9%   \n",
       " 31                                              56.9%   \n",
       " 32                                               9.9%   \n",
       " 33                                              16.0%   \n",
       " 34                                              28.8%   \n",
       " 35                                               9.2%   \n",
       " 36                                              10.5%   \n",
       " 37                                               7.7%   \n",
       " 38                                              11.7%   \n",
       " 39                                              38.5%   \n",
       " 40                                              14.0%   \n",
       " 41                                              18.4%   \n",
       " 42                                              30.9%   \n",
       " 43                                               9.7%   \n",
       " 44                                               5.3%   \n",
       " 45                                               5.5%   \n",
       " 46                                              12.7%   \n",
       " 47                                               8.6%   \n",
       " 48                                              35.7%   \n",
       " 49                                              21.5%   \n",
       " 50                                              10.4%   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                                         Days to Cover  \\\n",
       " 0                                                 9.3   \n",
       " 1                                                 9.3   \n",
       " 2                                                13.8   \n",
       " 3                                                11.4   \n",
       " 4                                                 1.1   \n",
       " 5                                                 5.6   \n",
       " 6                                                 1.5   \n",
       " 7                                                 2.3   \n",
       " 8                                                10.4   \n",
       " 9                                                 3.2   \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " 11                                                6.4   \n",
       " 12                                                  8   \n",
       " 13                                                2.1   \n",
       " 14                                                5.7   \n",
       " 15                                                5.2   \n",
       " 16                                                7.7   \n",
       " 17                                                1.3   \n",
       " 18                                                8.4   \n",
       " 19                                               21.5   \n",
       " 20                                                2.2   \n",
       " 21                                                0.8   \n",
       " 22                                                4.1   \n",
       " 23                                                2.3   \n",
       " 24                                               12.6   \n",
       " 25                                                4.4   \n",
       " 26                                                7.2   \n",
       " 27                                                3.7   \n",
       " 28                                                  5   \n",
       " 29                                                7.6   \n",
       " 30                                                2.1   \n",
       " 31                                               11.1   \n",
       " 32                                                9.7   \n",
       " 33                                                5.3   \n",
       " 34                                                2.9   \n",
       " 35                                                3.6   \n",
       " 36                                                3.7   \n",
       " 37                                                5.4   \n",
       " 38                                                6.1   \n",
       " 39                                               11.2   \n",
       " 40                                                4.7   \n",
       " 41                                                7.6   \n",
       " 42                                                2.4   \n",
       " 43                                                8.2   \n",
       " 44                                                6.3   \n",
       " 45                                                1.7   \n",
       " 46                                                  9   \n",
       " 47                                                4.9   \n",
       " 48                                                2.5   \n",
       " 49                                                9.4   \n",
       " 50                                                2.6   \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       " \n",
       "                                     Avg. Daily Volume  \n",
       " 0                                             1140000  \n",
       " 1                                            13090000  \n",
       " 2                                             1630000  \n",
       " 3                                             2670000  \n",
       " 4                                            23300000  \n",
       " 5                                             8300000  \n",
       " 6                                            67870000  \n",
       " 7                                            28910000  \n",
       " 8                                             2890000  \n",
       " 9                                             4840000  \n",
       " 10  (adsbygoogle = window.adsbygoogle || []).push(...  \n",
       " 11                                           11980000  \n",
       " 12                                            1590000  \n",
       " 13                                            4460000  \n",
       " 14                                           13100000  \n",
       " 15                                            8970000  \n",
       " 16                                            7500000  \n",
       " 17                                           11850000  \n",
       " 18                                            6840000  \n",
       " 19                                             464800  \n",
       " 20                                            4470000  \n",
       " 21                                           11320000  \n",
       " 22                                            1160000  \n",
       " 23                                           16850000  \n",
       " 24                                            3960000  \n",
       " 25                                            3640000  \n",
       " 26                                             840400  \n",
       " 27                                            4300000  \n",
       " 28                                            6960000  \n",
       " 29                                             999400  \n",
       " 30                                           18410000  \n",
       " 31                                            7100000  \n",
       " 32                                            1120000  \n",
       " 33                                             555500  \n",
       " 34                                           30130000  \n",
       " 35                                            3020000  \n",
       " 36                                            5850000  \n",
       " 37                                            3620000  \n",
       " 38                                            1520000  \n",
       " 39                                             944300  \n",
       " 40                                            6810000  \n",
       " 41                                           26300000  \n",
       " 42                                            3590000  \n",
       " 43                                            3350000  \n",
       " 44                                            1360000  \n",
       " 45                                            3700000  \n",
       " 46                                             893900  \n",
       " 47                                            7150000  \n",
       " 48                                           20640000  \n",
       " 49                                            1300000  \n",
       " 50                                            9870000  \n",
       " 51  (adsbygoogle = window.adsbygoogle || []).push(...  ]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "pld_table = tables[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company</th>\n",
       "      <th>Shares Sold Short (1/15/2021)</th>\n",
       "      <th>Dollar VolumeSold Short</th>\n",
       "      <th>Shares Sold Short (12/31/2020)</th>\n",
       "      <th>Change</th>\n",
       "      <th>% Change</th>\n",
       "      <th>% Float</th>\n",
       "      <th>Days to Cover</th>\n",
       "      <th>Avg. Daily Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHTRCharter Communications</td>\n",
       "      <td>10620000</td>\n",
       "      <td>$6.95 billion</td>\n",
       "      <td>10630000</td>\n",
       "      <td>-10000</td>\n",
       "      <td>-0.1%</td>\n",
       "      <td>7.9%</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>VIACViacomCBS</td>\n",
       "      <td>121250000</td>\n",
       "      <td>$6.14 billion</td>\n",
       "      <td>117920000</td>\n",
       "      <td>3330000</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>22.4%</td>\n",
       "      <td>9.3</td>\n",
       "      <td>13090000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AONAON</td>\n",
       "      <td>22570000</td>\n",
       "      <td>$4.66 billion</td>\n",
       "      <td>21470000</td>\n",
       "      <td>1100000</td>\n",
       "      <td>5.1%</td>\n",
       "      <td>10.0%</td>\n",
       "      <td>13.8</td>\n",
       "      <td>1630000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADIAnalog Devices</td>\n",
       "      <td>30400000</td>\n",
       "      <td>$4.54 billion</td>\n",
       "      <td>28260000</td>\n",
       "      <td>2140000</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>8.3%</td>\n",
       "      <td>11.4</td>\n",
       "      <td>2670000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MRNAModerna</td>\n",
       "      <td>24800000</td>\n",
       "      <td>$3.96 billion</td>\n",
       "      <td>23390000</td>\n",
       "      <td>1410000</td>\n",
       "      <td>6.0%</td>\n",
       "      <td>7.6%</td>\n",
       "      <td>1.1</td>\n",
       "      <td>23300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>DDDuPont de Nemours</td>\n",
       "      <td>46490000</td>\n",
       "      <td>$3.77 billion</td>\n",
       "      <td>23670000</td>\n",
       "      <td>22820000</td>\n",
       "      <td>96.4%</td>\n",
       "      <td>6.4%</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PLTRPalantir Technologies</td>\n",
       "      <td>98950000</td>\n",
       "      <td>$3.53 billion</td>\n",
       "      <td>90740000</td>\n",
       "      <td>8210000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>1.5</td>\n",
       "      <td>67870000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SNAPSnap</td>\n",
       "      <td>65420000</td>\n",
       "      <td>$3.48 billion</td>\n",
       "      <td>63160000</td>\n",
       "      <td>2260000</td>\n",
       "      <td>3.6%</td>\n",
       "      <td>7.0%</td>\n",
       "      <td>2.3</td>\n",
       "      <td>28910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>IFFInternational Flavors &amp; Fragrances</td>\n",
       "      <td>29980000</td>\n",
       "      <td>$3.45 billion</td>\n",
       "      <td>19880000</td>\n",
       "      <td>10100000</td>\n",
       "      <td>50.8%</td>\n",
       "      <td>28.1%</td>\n",
       "      <td>10.4</td>\n",
       "      <td>2890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BYNDBeyond Meat</td>\n",
       "      <td>15440000</td>\n",
       "      <td>$2.78 billion</td>\n",
       "      <td>13690000</td>\n",
       "      <td>1750000</td>\n",
       "      <td>12.8%</td>\n",
       "      <td>42.9%</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>KRThe Kroger</td>\n",
       "      <td>76140000</td>\n",
       "      <td>$2.69 billion</td>\n",
       "      <td>73390000</td>\n",
       "      <td>2750000</td>\n",
       "      <td>3.8%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>6.4</td>\n",
       "      <td>11980000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>CLXThe Clorox</td>\n",
       "      <td>12730000</td>\n",
       "      <td>$2.67 billion</td>\n",
       "      <td>12280000</td>\n",
       "      <td>450000</td>\n",
       "      <td>3.7%</td>\n",
       "      <td>10.1%</td>\n",
       "      <td>8</td>\n",
       "      <td>1590000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SNOWSnowflake</td>\n",
       "      <td>9270000</td>\n",
       "      <td>$2.53 billion</td>\n",
       "      <td>10650000</td>\n",
       "      <td>-1380000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>19.9%</td>\n",
       "      <td>2.1</td>\n",
       "      <td>4460000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>BBBYBed Bath &amp; Beyond</td>\n",
       "      <td>74890000</td>\n",
       "      <td>$2.52 billion</td>\n",
       "      <td>76180000</td>\n",
       "      <td>-1290000</td>\n",
       "      <td>-1.7%</td>\n",
       "      <td>65.5%</td>\n",
       "      <td>5.7</td>\n",
       "      <td>13100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SPWRSunPower</td>\n",
       "      <td>46520000</td>\n",
       "      <td>$2.46 billion</td>\n",
       "      <td>43350000</td>\n",
       "      <td>3170000</td>\n",
       "      <td>7.3%</td>\n",
       "      <td>57.5%</td>\n",
       "      <td>5.2</td>\n",
       "      <td>8970000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DISCADiscovery</td>\n",
       "      <td>58070000</td>\n",
       "      <td>$2.38 billion</td>\n",
       "      <td>54610000</td>\n",
       "      <td>3460000</td>\n",
       "      <td>6.3%</td>\n",
       "      <td>37.6%</td>\n",
       "      <td>7.7</td>\n",
       "      <td>7500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PTONPeloton Interactive</td>\n",
       "      <td>15170000</td>\n",
       "      <td>$2.21 billion</td>\n",
       "      <td>17290000</td>\n",
       "      <td>-2120000</td>\n",
       "      <td>-12.3%</td>\n",
       "      <td>6.2%</td>\n",
       "      <td>1.3</td>\n",
       "      <td>11850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ATUSAltice USA</td>\n",
       "      <td>57460000</td>\n",
       "      <td>$2.10 billion</td>\n",
       "      <td>51610000</td>\n",
       "      <td>5850000</td>\n",
       "      <td>11.3%</td>\n",
       "      <td>23.8%</td>\n",
       "      <td>8.4</td>\n",
       "      <td>6840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>LGNDLigand Pharmaceuticals</td>\n",
       "      <td>10010000</td>\n",
       "      <td>$1.92 billion</td>\n",
       "      <td>9910000</td>\n",
       "      <td>100000</td>\n",
       "      <td>1.0%</td>\n",
       "      <td>64.9%</td>\n",
       "      <td>21.5</td>\n",
       "      <td>464800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>DASHDoorDash</td>\n",
       "      <td>9810000</td>\n",
       "      <td>$1.80 billion</td>\n",
       "      <td>8820000</td>\n",
       "      <td>990000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>7.9%</td>\n",
       "      <td>2.2</td>\n",
       "      <td>4470000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ABNBAirbnb</td>\n",
       "      <td>9180000</td>\n",
       "      <td>$1.72 billion</td>\n",
       "      <td>7960000</td>\n",
       "      <td>1220000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>11.3%</td>\n",
       "      <td>0.8</td>\n",
       "      <td>11320000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>PANWPalo Alto Networks</td>\n",
       "      <td>4810000</td>\n",
       "      <td>$1.70 billion</td>\n",
       "      <td>5360000</td>\n",
       "      <td>-550000</td>\n",
       "      <td>-10.3%</td>\n",
       "      <td>5.1%</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1160000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>SPCEVirgin Galactic</td>\n",
       "      <td>38600000</td>\n",
       "      <td>$1.66 billion</td>\n",
       "      <td>43740000</td>\n",
       "      <td>-5140000</td>\n",
       "      <td>-11.8%</td>\n",
       "      <td>72.0%</td>\n",
       "      <td>2.3</td>\n",
       "      <td>16850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>IRMIron Mountain</td>\n",
       "      <td>49800000</td>\n",
       "      <td>$1.66 billion</td>\n",
       "      <td>49690000</td>\n",
       "      <td>110000</td>\n",
       "      <td>0.2%</td>\n",
       "      <td>17.5%</td>\n",
       "      <td>12.6</td>\n",
       "      <td>3960000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>DDOGDatadog</td>\n",
       "      <td>16110000</td>\n",
       "      <td>$1.61 billion</td>\n",
       "      <td>15350000</td>\n",
       "      <td>760000</td>\n",
       "      <td>5.0%</td>\n",
       "      <td>8.8%</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>PENPenumbra</td>\n",
       "      <td>6060000</td>\n",
       "      <td>$1.60 billion</td>\n",
       "      <td>5930000</td>\n",
       "      <td>130000</td>\n",
       "      <td>2.2%</td>\n",
       "      <td>17.8%</td>\n",
       "      <td>7.2</td>\n",
       "      <td>840400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>FUTUFutu</td>\n",
       "      <td>16060000</td>\n",
       "      <td>$1.59 billion</td>\n",
       "      <td>13600000</td>\n",
       "      <td>2460000</td>\n",
       "      <td>18.1%</td>\n",
       "      <td>25.7%</td>\n",
       "      <td>3.7</td>\n",
       "      <td>4300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>MPCMarathon Petroleum</td>\n",
       "      <td>35060000</td>\n",
       "      <td>$1.57 billion</td>\n",
       "      <td>31890000</td>\n",
       "      <td>3170000</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>5.4%</td>\n",
       "      <td>5</td>\n",
       "      <td>6960000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>WLTWWillis Towers Watson Public</td>\n",
       "      <td>7570000</td>\n",
       "      <td>$1.56 billion</td>\n",
       "      <td>6620000</td>\n",
       "      <td>950000</td>\n",
       "      <td>14.4%</td>\n",
       "      <td>5.9%</td>\n",
       "      <td>7.6</td>\n",
       "      <td>999400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>FUBOfuboTV</td>\n",
       "      <td>39170000</td>\n",
       "      <td>$1.56 billion</td>\n",
       "      <td>33860000</td>\n",
       "      <td>5310000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>71.9%</td>\n",
       "      <td>2.1</td>\n",
       "      <td>18410000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>MACThe Macerich</td>\n",
       "      <td>78540000</td>\n",
       "      <td>$1.49 billion</td>\n",
       "      <td>80640000</td>\n",
       "      <td>-2100000</td>\n",
       "      <td>-2.6%</td>\n",
       "      <td>56.9%</td>\n",
       "      <td>11.1</td>\n",
       "      <td>7100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>CHKPCheck Point Software Technologies</td>\n",
       "      <td>10870000</td>\n",
       "      <td>$1.44 billion</td>\n",
       "      <td>11430000</td>\n",
       "      <td>-560000</td>\n",
       "      <td>-4.9%</td>\n",
       "      <td>9.9%</td>\n",
       "      <td>9.7</td>\n",
       "      <td>1120000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>RHRH</td>\n",
       "      <td>2920000</td>\n",
       "      <td>$1.39 billion</td>\n",
       "      <td>2780000</td>\n",
       "      <td>140000</td>\n",
       "      <td>5.0%</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>5.3</td>\n",
       "      <td>555500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>MMacy's</td>\n",
       "      <td>88790000</td>\n",
       "      <td>$1.38 billion</td>\n",
       "      <td>108650000</td>\n",
       "      <td>-19860000</td>\n",
       "      <td>-18.3%</td>\n",
       "      <td>28.8%</td>\n",
       "      <td>2.9</td>\n",
       "      <td>30130000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>EXPEExpedia Group</td>\n",
       "      <td>10860000</td>\n",
       "      <td>$1.38 billion</td>\n",
       "      <td>13050000</td>\n",
       "      <td>-2190000</td>\n",
       "      <td>-16.8%</td>\n",
       "      <td>9.2%</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3020000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>FTCHFarfetch</td>\n",
       "      <td>21740000</td>\n",
       "      <td>$1.32 billion</td>\n",
       "      <td>21020000</td>\n",
       "      <td>720000</td>\n",
       "      <td>3.4%</td>\n",
       "      <td>10.5%</td>\n",
       "      <td>3.7</td>\n",
       "      <td>5850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>STXSeagate Technology</td>\n",
       "      <td>19700000</td>\n",
       "      <td>$1.31 billion</td>\n",
       "      <td>16980000</td>\n",
       "      <td>2720000</td>\n",
       "      <td>16.0%</td>\n",
       "      <td>7.7%</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3620000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>VMWVMware</td>\n",
       "      <td>9210000</td>\n",
       "      <td>$1.29 billion</td>\n",
       "      <td>9280000</td>\n",
       "      <td>-70000</td>\n",
       "      <td>-0.8%</td>\n",
       "      <td>11.7%</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>IRBTiRobot</td>\n",
       "      <td>10550000</td>\n",
       "      <td>$1.29 billion</td>\n",
       "      <td>10260000</td>\n",
       "      <td>290000</td>\n",
       "      <td>2.8%</td>\n",
       "      <td>38.5%</td>\n",
       "      <td>11.2</td>\n",
       "      <td>944300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>CGCCanopy Growth</td>\n",
       "      <td>31910000</td>\n",
       "      <td>$1.29 billion</td>\n",
       "      <td>32380000</td>\n",
       "      <td>-470000</td>\n",
       "      <td>-1.5%</td>\n",
       "      <td>14.0%</td>\n",
       "      <td>4.7</td>\n",
       "      <td>6810000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SIRISirius XM</td>\n",
       "      <td>198670000</td>\n",
       "      <td>$1.27 billion</td>\n",
       "      <td>191080000</td>\n",
       "      <td>7590000</td>\n",
       "      <td>4.0%</td>\n",
       "      <td>18.4%</td>\n",
       "      <td>7.6</td>\n",
       "      <td>26300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>LMNDLemonade</td>\n",
       "      <td>8490000</td>\n",
       "      <td>$1.27 billion</td>\n",
       "      <td>8280000</td>\n",
       "      <td>210000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>30.9%</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3590000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>NUANNuance Communications</td>\n",
       "      <td>27360000</td>\n",
       "      <td>$1.26 billion</td>\n",
       "      <td>24710000</td>\n",
       "      <td>2650000</td>\n",
       "      <td>10.7%</td>\n",
       "      <td>9.7%</td>\n",
       "      <td>8.2</td>\n",
       "      <td>3350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>KEYSKeysight Technologies</td>\n",
       "      <td>8590000</td>\n",
       "      <td>$1.25 billion</td>\n",
       "      <td>9410000</td>\n",
       "      <td>-820000</td>\n",
       "      <td>-8.7%</td>\n",
       "      <td>5.3%</td>\n",
       "      <td>6.3</td>\n",
       "      <td>1360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ENPHEnphase Energy</td>\n",
       "      <td>6430000</td>\n",
       "      <td>$1.25 billion</td>\n",
       "      <td>8300000</td>\n",
       "      <td>-1870000</td>\n",
       "      <td>-22.5%</td>\n",
       "      <td>5.5%</td>\n",
       "      <td>1.7</td>\n",
       "      <td>3700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>ESTCElastic</td>\n",
       "      <td>8050000</td>\n",
       "      <td>$1.23 billion</td>\n",
       "      <td>7520000</td>\n",
       "      <td>530000</td>\n",
       "      <td>7.1%</td>\n",
       "      <td>12.7%</td>\n",
       "      <td>9</td>\n",
       "      <td>893900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>ONON Semiconductor</td>\n",
       "      <td>34890000</td>\n",
       "      <td>$1.23 billion</td>\n",
       "      <td>31090000</td>\n",
       "      <td>3800000</td>\n",
       "      <td>12.2%</td>\n",
       "      <td>8.6%</td>\n",
       "      <td>4.9</td>\n",
       "      <td>7150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>NKLANikola</td>\n",
       "      <td>52610000</td>\n",
       "      <td>$1.22 billion</td>\n",
       "      <td>54440000</td>\n",
       "      <td>-1830000</td>\n",
       "      <td>0.0%</td>\n",
       "      <td>35.7%</td>\n",
       "      <td>2.5</td>\n",
       "      <td>20640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>OLLIOllie's Bargain Outlet</td>\n",
       "      <td>12190000</td>\n",
       "      <td>$1.19 billion</td>\n",
       "      <td>12730000</td>\n",
       "      <td>-540000</td>\n",
       "      <td>-4.2%</td>\n",
       "      <td>21.5%</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>LYFTLyft</td>\n",
       "      <td>25510000</td>\n",
       "      <td>$1.18 billion</td>\n",
       "      <td>24520000</td>\n",
       "      <td>990000</td>\n",
       "      <td>4.0%</td>\n",
       "      <td>10.4%</td>\n",
       "      <td>2.6</td>\n",
       "      <td>9870000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Company  \\\n",
       "0                          CHTRCharter Communications   \n",
       "1                                       VIACViacomCBS   \n",
       "2                                              AONAON   \n",
       "3                                   ADIAnalog Devices   \n",
       "4                                         MRNAModerna   \n",
       "5                                 DDDuPont de Nemours   \n",
       "6                           PLTRPalantir Technologies   \n",
       "7                                            SNAPSnap   \n",
       "8               IFFInternational Flavors & Fragrances   \n",
       "9                                     BYNDBeyond Meat   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                       KRThe Kroger   \n",
       "12                                      CLXThe Clorox   \n",
       "13                                      SNOWSnowflake   \n",
       "14                              BBBYBed Bath & Beyond   \n",
       "15                                       SPWRSunPower   \n",
       "16                                     DISCADiscovery   \n",
       "17                            PTONPeloton Interactive   \n",
       "18                                     ATUSAltice USA   \n",
       "19                         LGNDLigand Pharmaceuticals   \n",
       "20                                       DASHDoorDash   \n",
       "21                                         ABNBAirbnb   \n",
       "22                             PANWPalo Alto Networks   \n",
       "23                                SPCEVirgin Galactic   \n",
       "24                                   IRMIron Mountain   \n",
       "25                                        DDOGDatadog   \n",
       "26                                        PENPenumbra   \n",
       "27                                           FUTUFutu   \n",
       "28                              MPCMarathon Petroleum   \n",
       "29                    WLTWWillis Towers Watson Public   \n",
       "30                                         FUBOfuboTV   \n",
       "31                                    MACThe Macerich   \n",
       "32              CHKPCheck Point Software Technologies   \n",
       "33                                               RHRH   \n",
       "34                                            MMacy's   \n",
       "35                                  EXPEExpedia Group   \n",
       "36                                       FTCHFarfetch   \n",
       "37                              STXSeagate Technology   \n",
       "38                                          VMWVMware   \n",
       "39                                         IRBTiRobot   \n",
       "40                                   CGCCanopy Growth   \n",
       "41                                      SIRISirius XM   \n",
       "42                                       LMNDLemonade   \n",
       "43                          NUANNuance Communications   \n",
       "44                          KEYSKeysight Technologies   \n",
       "45                                 ENPHEnphase Energy   \n",
       "46                                        ESTCElastic   \n",
       "47                                 ONON Semiconductor   \n",
       "48                                         NKLANikola   \n",
       "49                         OLLIOllie's Bargain Outlet   \n",
       "50                                           LYFTLyft   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                        Shares Sold Short (1/15/2021)  \\\n",
       "0                                            10620000   \n",
       "1                                           121250000   \n",
       "2                                            22570000   \n",
       "3                                            30400000   \n",
       "4                                            24800000   \n",
       "5                                            46490000   \n",
       "6                                            98950000   \n",
       "7                                            65420000   \n",
       "8                                            29980000   \n",
       "9                                            15440000   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                           76140000   \n",
       "12                                           12730000   \n",
       "13                                            9270000   \n",
       "14                                           74890000   \n",
       "15                                           46520000   \n",
       "16                                           58070000   \n",
       "17                                           15170000   \n",
       "18                                           57460000   \n",
       "19                                           10010000   \n",
       "20                                            9810000   \n",
       "21                                            9180000   \n",
       "22                                            4810000   \n",
       "23                                           38600000   \n",
       "24                                           49800000   \n",
       "25                                           16110000   \n",
       "26                                            6060000   \n",
       "27                                           16060000   \n",
       "28                                           35060000   \n",
       "29                                            7570000   \n",
       "30                                           39170000   \n",
       "31                                           78540000   \n",
       "32                                           10870000   \n",
       "33                                            2920000   \n",
       "34                                           88790000   \n",
       "35                                           10860000   \n",
       "36                                           21740000   \n",
       "37                                           19700000   \n",
       "38                                            9210000   \n",
       "39                                           10550000   \n",
       "40                                           31910000   \n",
       "41                                          198670000   \n",
       "42                                            8490000   \n",
       "43                                           27360000   \n",
       "44                                            8590000   \n",
       "45                                            6430000   \n",
       "46                                            8050000   \n",
       "47                                           34890000   \n",
       "48                                           52610000   \n",
       "49                                           12190000   \n",
       "50                                           25510000   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                              Dollar VolumeSold Short  \\\n",
       "0                                       $6.95 billion   \n",
       "1                                       $6.14 billion   \n",
       "2                                       $4.66 billion   \n",
       "3                                       $4.54 billion   \n",
       "4                                       $3.96 billion   \n",
       "5                                       $3.77 billion   \n",
       "6                                       $3.53 billion   \n",
       "7                                       $3.48 billion   \n",
       "8                                       $3.45 billion   \n",
       "9                                       $2.78 billion   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                      $2.69 billion   \n",
       "12                                      $2.67 billion   \n",
       "13                                      $2.53 billion   \n",
       "14                                      $2.52 billion   \n",
       "15                                      $2.46 billion   \n",
       "16                                      $2.38 billion   \n",
       "17                                      $2.21 billion   \n",
       "18                                      $2.10 billion   \n",
       "19                                      $1.92 billion   \n",
       "20                                      $1.80 billion   \n",
       "21                                      $1.72 billion   \n",
       "22                                      $1.70 billion   \n",
       "23                                      $1.66 billion   \n",
       "24                                      $1.66 billion   \n",
       "25                                      $1.61 billion   \n",
       "26                                      $1.60 billion   \n",
       "27                                      $1.59 billion   \n",
       "28                                      $1.57 billion   \n",
       "29                                      $1.56 billion   \n",
       "30                                      $1.56 billion   \n",
       "31                                      $1.49 billion   \n",
       "32                                      $1.44 billion   \n",
       "33                                      $1.39 billion   \n",
       "34                                      $1.38 billion   \n",
       "35                                      $1.38 billion   \n",
       "36                                      $1.32 billion   \n",
       "37                                      $1.31 billion   \n",
       "38                                      $1.29 billion   \n",
       "39                                      $1.29 billion   \n",
       "40                                      $1.29 billion   \n",
       "41                                      $1.27 billion   \n",
       "42                                      $1.27 billion   \n",
       "43                                      $1.26 billion   \n",
       "44                                      $1.25 billion   \n",
       "45                                      $1.25 billion   \n",
       "46                                      $1.23 billion   \n",
       "47                                      $1.23 billion   \n",
       "48                                      $1.22 billion   \n",
       "49                                      $1.19 billion   \n",
       "50                                      $1.18 billion   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                       Shares Sold Short (12/31/2020)  \\\n",
       "0                                            10630000   \n",
       "1                                           117920000   \n",
       "2                                            21470000   \n",
       "3                                            28260000   \n",
       "4                                            23390000   \n",
       "5                                            23670000   \n",
       "6                                            90740000   \n",
       "7                                            63160000   \n",
       "8                                            19880000   \n",
       "9                                            13690000   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                           73390000   \n",
       "12                                           12280000   \n",
       "13                                           10650000   \n",
       "14                                           76180000   \n",
       "15                                           43350000   \n",
       "16                                           54610000   \n",
       "17                                           17290000   \n",
       "18                                           51610000   \n",
       "19                                            9910000   \n",
       "20                                            8820000   \n",
       "21                                            7960000   \n",
       "22                                            5360000   \n",
       "23                                           43740000   \n",
       "24                                           49690000   \n",
       "25                                           15350000   \n",
       "26                                            5930000   \n",
       "27                                           13600000   \n",
       "28                                           31890000   \n",
       "29                                            6620000   \n",
       "30                                           33860000   \n",
       "31                                           80640000   \n",
       "32                                           11430000   \n",
       "33                                            2780000   \n",
       "34                                          108650000   \n",
       "35                                           13050000   \n",
       "36                                           21020000   \n",
       "37                                           16980000   \n",
       "38                                            9280000   \n",
       "39                                           10260000   \n",
       "40                                           32380000   \n",
       "41                                          191080000   \n",
       "42                                            8280000   \n",
       "43                                           24710000   \n",
       "44                                            9410000   \n",
       "45                                            8300000   \n",
       "46                                            7520000   \n",
       "47                                           31090000   \n",
       "48                                           54440000   \n",
       "49                                           12730000   \n",
       "50                                           24520000   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                                               Change  \\\n",
       "0                                              -10000   \n",
       "1                                             3330000   \n",
       "2                                             1100000   \n",
       "3                                             2140000   \n",
       "4                                             1410000   \n",
       "5                                            22820000   \n",
       "6                                             8210000   \n",
       "7                                             2260000   \n",
       "8                                            10100000   \n",
       "9                                             1750000   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                            2750000   \n",
       "12                                             450000   \n",
       "13                                           -1380000   \n",
       "14                                           -1290000   \n",
       "15                                            3170000   \n",
       "16                                            3460000   \n",
       "17                                           -2120000   \n",
       "18                                            5850000   \n",
       "19                                             100000   \n",
       "20                                             990000   \n",
       "21                                            1220000   \n",
       "22                                            -550000   \n",
       "23                                           -5140000   \n",
       "24                                             110000   \n",
       "25                                             760000   \n",
       "26                                             130000   \n",
       "27                                            2460000   \n",
       "28                                            3170000   \n",
       "29                                             950000   \n",
       "30                                            5310000   \n",
       "31                                           -2100000   \n",
       "32                                            -560000   \n",
       "33                                             140000   \n",
       "34                                          -19860000   \n",
       "35                                           -2190000   \n",
       "36                                             720000   \n",
       "37                                            2720000   \n",
       "38                                             -70000   \n",
       "39                                             290000   \n",
       "40                                            -470000   \n",
       "41                                            7590000   \n",
       "42                                             210000   \n",
       "43                                            2650000   \n",
       "44                                            -820000   \n",
       "45                                           -1870000   \n",
       "46                                             530000   \n",
       "47                                            3800000   \n",
       "48                                           -1830000   \n",
       "49                                            -540000   \n",
       "50                                             990000   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                                             % Change  \\\n",
       "0                                               -0.1%   \n",
       "1                                                2.8%   \n",
       "2                                                5.1%   \n",
       "3                                                7.6%   \n",
       "4                                                6.0%   \n",
       "5                                               96.4%   \n",
       "6                                                0.0%   \n",
       "7                                                3.6%   \n",
       "8                                               50.8%   \n",
       "9                                               12.8%   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                               3.8%   \n",
       "12                                               3.7%   \n",
       "13                                               0.0%   \n",
       "14                                              -1.7%   \n",
       "15                                               7.3%   \n",
       "16                                               6.3%   \n",
       "17                                             -12.3%   \n",
       "18                                              11.3%   \n",
       "19                                               1.0%   \n",
       "20                                               0.0%   \n",
       "21                                               0.0%   \n",
       "22                                             -10.3%   \n",
       "23                                             -11.8%   \n",
       "24                                               0.2%   \n",
       "25                                               5.0%   \n",
       "26                                               2.2%   \n",
       "27                                              18.1%   \n",
       "28                                               9.9%   \n",
       "29                                              14.4%   \n",
       "30                                               0.0%   \n",
       "31                                              -2.6%   \n",
       "32                                              -4.9%   \n",
       "33                                               5.0%   \n",
       "34                                             -18.3%   \n",
       "35                                             -16.8%   \n",
       "36                                               3.4%   \n",
       "37                                              16.0%   \n",
       "38                                              -0.8%   \n",
       "39                                               2.8%   \n",
       "40                                              -1.5%   \n",
       "41                                               4.0%   \n",
       "42                                               0.0%   \n",
       "43                                              10.7%   \n",
       "44                                              -8.7%   \n",
       "45                                             -22.5%   \n",
       "46                                               7.1%   \n",
       "47                                              12.2%   \n",
       "48                                               0.0%   \n",
       "49                                              -4.2%   \n",
       "50                                               4.0%   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                                              % Float  \\\n",
       "0                                                7.9%   \n",
       "1                                               22.4%   \n",
       "2                                               10.0%   \n",
       "3                                                8.3%   \n",
       "4                                                7.6%   \n",
       "5                                                6.4%   \n",
       "6                                                9.7%   \n",
       "7                                                7.0%   \n",
       "8                                               28.1%   \n",
       "9                                               42.9%   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                              10.1%   \n",
       "12                                              10.1%   \n",
       "13                                              19.9%   \n",
       "14                                              65.5%   \n",
       "15                                              57.5%   \n",
       "16                                              37.6%   \n",
       "17                                               6.2%   \n",
       "18                                              23.8%   \n",
       "19                                              64.9%   \n",
       "20                                               7.9%   \n",
       "21                                              11.3%   \n",
       "22                                               5.1%   \n",
       "23                                              72.0%   \n",
       "24                                              17.5%   \n",
       "25                                               8.8%   \n",
       "26                                              17.8%   \n",
       "27                                              25.7%   \n",
       "28                                               5.4%   \n",
       "29                                               5.9%   \n",
       "30                                              71.9%   \n",
       "31                                              56.9%   \n",
       "32                                               9.9%   \n",
       "33                                              16.0%   \n",
       "34                                              28.8%   \n",
       "35                                               9.2%   \n",
       "36                                              10.5%   \n",
       "37                                               7.7%   \n",
       "38                                              11.7%   \n",
       "39                                              38.5%   \n",
       "40                                              14.0%   \n",
       "41                                              18.4%   \n",
       "42                                              30.9%   \n",
       "43                                               9.7%   \n",
       "44                                               5.3%   \n",
       "45                                               5.5%   \n",
       "46                                              12.7%   \n",
       "47                                               8.6%   \n",
       "48                                              35.7%   \n",
       "49                                              21.5%   \n",
       "50                                              10.4%   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                                        Days to Cover  \\\n",
       "0                                                 9.3   \n",
       "1                                                 9.3   \n",
       "2                                                13.8   \n",
       "3                                                11.4   \n",
       "4                                                 1.1   \n",
       "5                                                 5.6   \n",
       "6                                                 1.5   \n",
       "7                                                 2.3   \n",
       "8                                                10.4   \n",
       "9                                                 3.2   \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "11                                                6.4   \n",
       "12                                                  8   \n",
       "13                                                2.1   \n",
       "14                                                5.7   \n",
       "15                                                5.2   \n",
       "16                                                7.7   \n",
       "17                                                1.3   \n",
       "18                                                8.4   \n",
       "19                                               21.5   \n",
       "20                                                2.2   \n",
       "21                                                0.8   \n",
       "22                                                4.1   \n",
       "23                                                2.3   \n",
       "24                                               12.6   \n",
       "25                                                4.4   \n",
       "26                                                7.2   \n",
       "27                                                3.7   \n",
       "28                                                  5   \n",
       "29                                                7.6   \n",
       "30                                                2.1   \n",
       "31                                               11.1   \n",
       "32                                                9.7   \n",
       "33                                                5.3   \n",
       "34                                                2.9   \n",
       "35                                                3.6   \n",
       "36                                                3.7   \n",
       "37                                                5.4   \n",
       "38                                                6.1   \n",
       "39                                               11.2   \n",
       "40                                                4.7   \n",
       "41                                                7.6   \n",
       "42                                                2.4   \n",
       "43                                                8.2   \n",
       "44                                                6.3   \n",
       "45                                                1.7   \n",
       "46                                                  9   \n",
       "47                                                4.9   \n",
       "48                                                2.5   \n",
       "49                                                9.4   \n",
       "50                                                2.6   \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "\n",
       "                                    Avg. Daily Volume  \n",
       "0                                             1140000  \n",
       "1                                            13090000  \n",
       "2                                             1630000  \n",
       "3                                             2670000  \n",
       "4                                            23300000  \n",
       "5                                             8300000  \n",
       "6                                            67870000  \n",
       "7                                            28910000  \n",
       "8                                             2890000  \n",
       "9                                             4840000  \n",
       "10  (adsbygoogle = window.adsbygoogle || []).push(...  \n",
       "11                                           11980000  \n",
       "12                                            1590000  \n",
       "13                                            4460000  \n",
       "14                                           13100000  \n",
       "15                                            8970000  \n",
       "16                                            7500000  \n",
       "17                                           11850000  \n",
       "18                                            6840000  \n",
       "19                                             464800  \n",
       "20                                            4470000  \n",
       "21                                           11320000  \n",
       "22                                            1160000  \n",
       "23                                           16850000  \n",
       "24                                            3960000  \n",
       "25                                            3640000  \n",
       "26                                             840400  \n",
       "27                                            4300000  \n",
       "28                                            6960000  \n",
       "29                                             999400  \n",
       "30                                           18410000  \n",
       "31                                            7100000  \n",
       "32                                            1120000  \n",
       "33                                             555500  \n",
       "34                                           30130000  \n",
       "35                                            3020000  \n",
       "36                                            5850000  \n",
       "37                                            3620000  \n",
       "38                                            1520000  \n",
       "39                                             944300  \n",
       "40                                            6810000  \n",
       "41                                           26300000  \n",
       "42                                            3590000  \n",
       "43                                            3350000  \n",
       "44                                            1360000  \n",
       "45                                            3700000  \n",
       "46                                             893900  \n",
       "47                                            7150000  \n",
       "48                                           20640000  \n",
       "49                                            1300000  \n",
       "50                                            9870000  \n",
       "51  (adsbygoogle = window.adsbygoogle || []).push(...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pld_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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