wsb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pulling data from:  https://api.quiverquant.com/beta/live/wsbcomments?date_from=20180901\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Puts</th>\n",
       "      <th>Calls</th>\n",
       "      <th>Time</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>Datetime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592759000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2019-11-01 07:19:19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ATVI</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592825000</td>\n",
       "      <td>-0.2230</td>\n",
       "      <td>2019-11-01 07:20:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BABA</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592866000</td>\n",
       "      <td>0.5719</td>\n",
       "      <td>2019-11-01 07:21:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GLD</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572593101000</td>\n",
       "      <td>0.3182</td>\n",
       "      <td>2019-11-01 07:25:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PINS</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572593120000</td>\n",
       "      <td>0.5562</td>\n",
       "      <td>2019-11-01 07:25:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319415</th>\n",
       "      <td>PINS</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592290000</td>\n",
       "      <td>0.2263</td>\n",
       "      <td>2019-11-01 07:11:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319416</th>\n",
       "      <td>BABA</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1572592354000</td>\n",
       "      <td>0.5994</td>\n",
       "      <td>2019-11-01 07:12:34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319417</th>\n",
       "      <td>AMD</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592510000</td>\n",
       "      <td>0.7184</td>\n",
       "      <td>2019-11-01 07:15:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319418</th>\n",
       "      <td>SPY</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592602000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2019-11-01 07:16:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3319419</th>\n",
       "      <td>MFG</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1572592647000</td>\n",
       "      <td>-0.7506</td>\n",
       "      <td>2019-11-01 07:17:27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3319420 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Ticker  Puts  Calls           Time  Sentiment            Datetime\n",
       "0         AAPL     0      0  1572592759000     0.0000 2019-11-01 07:19:19\n",
       "1         ATVI     3      0  1572592825000    -0.2230 2019-11-01 07:20:25\n",
       "2         BABA     0      0  1572592866000     0.5719 2019-11-01 07:21:06\n",
       "3          GLD     0      0  1572593101000     0.3182 2019-11-01 07:25:01\n",
       "4         PINS     0      0  1572593120000     0.5562 2019-11-01 07:25:20\n",
       "...        ...   ...    ...            ...        ...                 ...\n",
       "3319415   PINS     0      0  1572592290000     0.2263 2019-11-01 07:11:30\n",
       "3319416   BABA     1      2  1572592354000     0.5994 2019-11-01 07:12:34\n",
       "3319417    AMD     0      0  1572592510000     0.7184 2019-11-01 07:15:10\n",
       "3319418    SPY     0      0  1572592602000     0.0000 2019-11-01 07:16:42\n",
       "3319419    MFG     0      0  1572592647000    -0.7506 2019-11-01 07:17:27\n",
       "\n",
       "[3319420 rows x 6 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import quiverquant\n",
    "import pandas as pd\n",
    "\n",
    "#My Quiver API token. Replace this with a string of your own.\n",
    "token = load_obj(\"APIToken\")\n",
    "\n",
    "quiver = quiverquant.quiver(token)\n",
    "df = quiver.wallstreetbetsComments(date_from=\"20180901\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Date</th>\n",
       "      <th>Mentions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AA</td>\n",
       "      <td>2018-09-07</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AA</td>\n",
       "      <td>2018-10-09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AA</td>\n",
       "      <td>2018-10-18</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AA</td>\n",
       "      <td>2018-11-28</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AA</td>\n",
       "      <td>2019-01-04</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267796</th>\n",
       "      <td>ZYXI</td>\n",
       "      <td>2019-08-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267797</th>\n",
       "      <td>ZYXI</td>\n",
       "      <td>2020-01-09</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267798</th>\n",
       "      <td>ZYXI</td>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267799</th>\n",
       "      <td>ZYXI</td>\n",
       "      <td>2020-05-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267800</th>\n",
       "      <td>ZYXI</td>\n",
       "      <td>2020-06-17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>267801 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Ticker        Date  Mentions\n",
       "0          AA  2018-09-07         1\n",
       "1          AA  2018-10-09         1\n",
       "2          AA  2018-10-18         1\n",
       "3          AA  2018-11-28         1\n",
       "4          AA  2019-01-04         1\n",
       "...       ...         ...       ...\n",
       "267796   ZYXI  2019-08-01         1\n",
       "267797   ZYXI  2020-01-09         1\n",
       "267798   ZYXI  2020-02-24         1\n",
       "267799   ZYXI  2020-05-06         1\n",
       "267800   ZYXI  2020-06-17         1\n",
       "\n",
       "[267801 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Date\"] = df[\"Datetime\"].dt.date\n",
    "dfDay = df.groupby([\"Ticker\",\"Date\"]).count().reset_index()\n",
    "dfDay = dfDay.rename(columns={\"Puts\": \"Mentions\"})\n",
    "dfDay = dfDay[[\"Ticker\", \"Date\", \"Mentions\"]]\n",
    "dfDay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Mentions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-09-03</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2018-09-03</td>\n",
       "      <td>LEN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2018-09-03</td>\n",
       "      <td>LOW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2018-09-03</td>\n",
       "      <td>MDB</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2018-09-03</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102910</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>FREE</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102909</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>FR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102908</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>FOX</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102916</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>FSK</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103834</th>\n",
       "      <td>2021-02-22</td>\n",
       "      <td>ZYNE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>103835 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date Ticker  Mentions\n",
       "0      2018-09-03   AAPL         3\n",
       "22     2018-09-03    LEN         2\n",
       "23     2018-09-03    LOW         1\n",
       "24     2018-09-03    MDB         1\n",
       "25     2018-09-03   MSFT         2\n",
       "...           ...    ...       ...\n",
       "102910 2021-02-22   FREE        11\n",
       "102909 2021-02-22     FR         1\n",
       "102908 2021-02-22    FOX         3\n",
       "102916 2021-02-22    FSK         1\n",
       "103834 2021-02-22   ZYNE         1\n",
       "\n",
       "[103835 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDay[\"Date\"] = pd.to_datetime(dfDay[\"Date\"])\n",
    "dfWeek = dfDay.groupby([pd.Grouper(key='Date', freq='W-MON'), 'Ticker'])['Mentions'].sum().reset_index().sort_values('Date')\n",
    "dfWeek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf\n",
    "import datetime as dt\n",
    "dfLarge = dfWeek[dfWeek[\"Mentions\"]>1]\n",
    "\n",
    "dfLarge = dfLarge.sort_values(\"Date\", ascending=True)\n",
    "dates = dfLarge[\"Date\"].unique()\n",
    "\n",
    "\n",
    "capital = 100000\n",
    "started = False\n",
    "startedDFW = False\n",
    "\n",
    "for date in dates[:-2]:\n",
    "    dfW = dfLarge[dfLarge[\"Date\"]==date]\n",
    "    dfW = dfW.sort_values(\"Mentions\", ascending=False).head(5)\n",
    "    dfW['prop'] = dfW['Mentions']/dfW[\"Mentions\"].sum()\n",
    "    dfW['buy'] = capital*dfW['prop']\n",
    "    buyDate = date+pd.Timedelta(days=6)\n",
    "    dfW['buyDate'] = [buyDate]*len(dfW['buy'])\n",
    "    if not startedDFW:\n",
    "        dfWs = dfW\n",
    "        startedDFW = True\n",
    "    else:\n",
    "        dfWs = pd.concat([dfWs, dfW])\n",
    "    sellDate = date+pd.Timedelta(days=15)\n",
    "\n",
    "    startedWeek = False\n",
    "    print(date)\n",
    "    for index, row in dfW.iterrows():\n",
    "        ticker = row[\"Ticker\"]\n",
    "        print(ticker)\n",
    "        try:\n",
    "            ytStock = yf.download(ticker, start=str(buyDate.date()), end=str(sellDate.date()), interval=\"1d\").reset_index()\n",
    "            shares = row[\"buy\"]/ytStock[\"Adj Close\"].values[0]\n",
    "            ytStock = ytStock.iloc[1:]\n",
    "\n",
    "        except:\n",
    "            print(\"Error\")\n",
    "            ytStock = yf.download(\"SPY\", start=str(buyDate.date()), end=str(sellDate.date()), interval=\"1d\").reset_index()\n",
    "            shares = row[\"buy\"]/ytStock[\"Adj Close\"].values[0]\n",
    "            ytStock = ytStock.iloc[1:]\n",
    "\n",
    "        ytStock[\"OpenAmount\"] = ytStock[\"Open\"]*shares\n",
    "        ytStock[\"CloseAmount\"] = ytStock[\"Adj Close\"]*shares\n",
    "        ytStock[\"Ticker\"] = [ticker]*len(ytStock[\"OpenAmount\"])\n",
    "        ytStock = ytStock.fillna(method='ffill')\n",
    "        ytStock = ytStock.fillna(method='bfill')\n",
    "        ytStock = ytStock.dropna()\n",
    "        if not startedWeek:\n",
    "            dfCombined = ytStock\n",
    "            startedWeek = True\n",
    "        else:\n",
    "            dfCombined = pd.concat([dfCombined, ytStock])\n",
    "        \n",
    "        if not started:\n",
    "            dfAll = ytStock\n",
    "            started = True\n",
    "        else:\n",
    "            dfAll = pd.concat([dfAll, ytStock])\n",
    "            \n",
    "    capital = 0\n",
    "    for ticker in dfCombined[\"Ticker\"].unique():\n",
    "        dfT = dfCombined[dfCombined[\"Ticker\"]==ticker]\n",
    "        capital+=dfT[\"CloseAmount\"].values[-1]\n",
    "    print(\"Week end capital: \", capital)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>OpenAmount</th>\n",
       "      <th>CloseAmount</th>\n",
       "      <th>Fund</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-09-11</td>\n",
       "      <td>2254.264027</td>\n",
       "      <td>2319.250008</td>\n",
       "      <td>2238.429993</td>\n",
       "      <td>2315.728027</td>\n",
       "      <td>2315.578598</td>\n",
       "      <td>105633000</td>\n",
       "      <td>98602.876081</td>\n",
       "      <td>99282.779572</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-09-12</td>\n",
       "      <td>2321.538002</td>\n",
       "      <td>2334.080002</td>\n",
       "      <td>2288.359936</td>\n",
       "      <td>2321.088001</td>\n",
       "      <td>2320.937626</td>\n",
       "      <td>126806363</td>\n",
       "      <td>98141.567929</td>\n",
       "      <td>99321.659858</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>2330.533997</td>\n",
       "      <td>2344.220013</td>\n",
       "      <td>2309.516029</td>\n",
       "      <td>2321.141987</td>\n",
       "      <td>2320.990498</td>\n",
       "      <td>100055038</td>\n",
       "      <td>99531.099307</td>\n",
       "      <td>100259.117586</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-09-14</td>\n",
       "      <td>2325.042053</td>\n",
       "      <td>2331.866028</td>\n",
       "      <td>2288.213974</td>\n",
       "      <td>2303.799938</td>\n",
       "      <td>2303.647877</td>\n",
       "      <td>83332550</td>\n",
       "      <td>100660.744792</td>\n",
       "      <td>101092.077546</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-09-17</td>\n",
       "      <td>2287.587975</td>\n",
       "      <td>2293.333942</td>\n",
       "      <td>2216.266037</td>\n",
       "      <td>2239.028034</td>\n",
       "      <td>2238.878071</td>\n",
       "      <td>75012413</td>\n",
       "      <td>100323.973803</td>\n",
       "      <td>99874.491212</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>599</th>\n",
       "      <td>2021-02-10</td>\n",
       "      <td>172.580000</td>\n",
       "      <td>185.980000</td>\n",
       "      <td>167.669999</td>\n",
       "      <td>173.120000</td>\n",
       "      <td>173.120000</td>\n",
       "      <td>295784000</td>\n",
       "      <td>291311.772160</td>\n",
       "      <td>293176.574373</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>2021-02-11</td>\n",
       "      <td>171.500001</td>\n",
       "      <td>177.300003</td>\n",
       "      <td>168.760004</td>\n",
       "      <td>172.140001</td>\n",
       "      <td>172.140001</td>\n",
       "      <td>154264600</td>\n",
       "      <td>287004.383414</td>\n",
       "      <td>286948.420054</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601</th>\n",
       "      <td>2021-02-12</td>\n",
       "      <td>171.719998</td>\n",
       "      <td>177.570000</td>\n",
       "      <td>168.609998</td>\n",
       "      <td>174.050000</td>\n",
       "      <td>174.050000</td>\n",
       "      <td>128979800</td>\n",
       "      <td>287221.285067</td>\n",
       "      <td>292418.399412</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>602</th>\n",
       "      <td>2021-02-17</td>\n",
       "      <td>99.240000</td>\n",
       "      <td>102.479998</td>\n",
       "      <td>91.940002</td>\n",
       "      <td>93.999999</td>\n",
       "      <td>93.999999</td>\n",
       "      <td>273156400</td>\n",
       "      <td>291268.591431</td>\n",
       "      <td>277727.075341</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>603</th>\n",
       "      <td>2021-02-18</td>\n",
       "      <td>94.220002</td>\n",
       "      <td>96.809798</td>\n",
       "      <td>88.070002</td>\n",
       "      <td>92.934401</td>\n",
       "      <td>92.934401</td>\n",
       "      <td>363457792</td>\n",
       "      <td>288406.686481</td>\n",
       "      <td>284455.689746</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>603 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date         Open         High          Low        Close  \\\n",
       "0   2018-09-11  2254.264027  2319.250008  2238.429993  2315.728027   \n",
       "1   2018-09-12  2321.538002  2334.080002  2288.359936  2321.088001   \n",
       "2   2018-09-13  2330.533997  2344.220013  2309.516029  2321.141987   \n",
       "3   2018-09-14  2325.042053  2331.866028  2288.213974  2303.799938   \n",
       "4   2018-09-17  2287.587975  2293.333942  2216.266037  2239.028034   \n",
       "..         ...          ...          ...          ...          ...   \n",
       "599 2021-02-10   172.580000   185.980000   167.669999   173.120000   \n",
       "600 2021-02-11   171.500001   177.300003   168.760004   172.140001   \n",
       "601 2021-02-12   171.719998   177.570000   168.609998   174.050000   \n",
       "602 2021-02-17    99.240000   102.479998    91.940002    93.999999   \n",
       "603 2021-02-18    94.220002    96.809798    88.070002    92.934401   \n",
       "\n",
       "       Adj Close     Volume     OpenAmount    CloseAmount Fund  \n",
       "0    2315.578598  105633000   98602.876081   99282.779572  WSB  \n",
       "1    2320.937626  126806363   98141.567929   99321.659858  WSB  \n",
       "2    2320.990498  100055038   99531.099307  100259.117586  WSB  \n",
       "3    2303.647877   83332550  100660.744792  101092.077546  WSB  \n",
       "4    2238.878071   75012413  100323.973803   99874.491212  WSB  \n",
       "..           ...        ...            ...            ...  ...  \n",
       "599   173.120000  295784000  291311.772160  293176.574373  WSB  \n",
       "600   172.140001  154264600  287004.383414  286948.420054  WSB  \n",
       "601   174.050000  128979800  287221.285067  292418.399412  WSB  \n",
       "602    93.999999  273156400  291268.591431  277727.075341  WSB  \n",
       "603    92.934401  363457792  288406.686481  284455.689746  WSB  \n",
       "\n",
       "[603 rows x 10 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfDay = dfAll.groupby(\"Date\").sum().reset_index()\n",
    "dfDay = dfDay[dfDay[\"Date\"]!=pd.to_datetime(\"2020-8-31\")]\n",
    "dfDay[\"Fund\"] = [\"WSB\"]*len(dfDay[\"Close\"])\n",
    "dfDay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>OpenAmount</th>\n",
       "      <th>CloseAmount</th>\n",
       "      <th>Fund</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-09-11</td>\n",
       "      <td>2254.264027</td>\n",
       "      <td>2319.250008</td>\n",
       "      <td>2238.429993</td>\n",
       "      <td>2315.728027</td>\n",
       "      <td>2315.578598</td>\n",
       "      <td>105633000</td>\n",
       "      <td>98602.876081</td>\n",
       "      <td>99282.779572</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-09-12</td>\n",
       "      <td>2321.538002</td>\n",
       "      <td>2334.080002</td>\n",
       "      <td>2288.359936</td>\n",
       "      <td>2321.088001</td>\n",
       "      <td>2320.937626</td>\n",
       "      <td>126806363</td>\n",
       "      <td>98141.567929</td>\n",
       "      <td>99321.659858</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>2330.533997</td>\n",
       "      <td>2344.220013</td>\n",
       "      <td>2309.516029</td>\n",
       "      <td>2321.141987</td>\n",
       "      <td>2320.990498</td>\n",
       "      <td>100055038</td>\n",
       "      <td>99531.099307</td>\n",
       "      <td>100259.117586</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-09-14</td>\n",
       "      <td>2325.042053</td>\n",
       "      <td>2331.866028</td>\n",
       "      <td>2288.213974</td>\n",
       "      <td>2303.799938</td>\n",
       "      <td>2303.647877</td>\n",
       "      <td>83332550</td>\n",
       "      <td>100660.744792</td>\n",
       "      <td>101092.077546</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-09-17</td>\n",
       "      <td>2287.587975</td>\n",
       "      <td>2293.333942</td>\n",
       "      <td>2216.266037</td>\n",
       "      <td>2239.028034</td>\n",
       "      <td>2238.878071</td>\n",
       "      <td>75012413</td>\n",
       "      <td>100323.973803</td>\n",
       "      <td>99874.491212</td>\n",
       "      <td>WSB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>2021-02-10</td>\n",
       "      <td>392.119995</td>\n",
       "      <td>392.279999</td>\n",
       "      <td>387.500000</td>\n",
       "      <td>390.079987</td>\n",
       "      <td>390.079987</td>\n",
       "      <td>59154400</td>\n",
       "      <td>135653.497000</td>\n",
       "      <td>134947.758205</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>2021-02-11</td>\n",
       "      <td>391.239990</td>\n",
       "      <td>391.690002</td>\n",
       "      <td>388.100006</td>\n",
       "      <td>390.709991</td>\n",
       "      <td>390.709991</td>\n",
       "      <td>42755400</td>\n",
       "      <td>135349.060243</td>\n",
       "      <td>135165.707727</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <td>2021-02-12</td>\n",
       "      <td>389.850006</td>\n",
       "      <td>392.899994</td>\n",
       "      <td>389.769989</td>\n",
       "      <td>392.640015</td>\n",
       "      <td>392.640015</td>\n",
       "      <td>50505700</td>\n",
       "      <td>134868.196705</td>\n",
       "      <td>135833.397206</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>2021-02-16</td>\n",
       "      <td>393.959991</td>\n",
       "      <td>394.170013</td>\n",
       "      <td>391.529999</td>\n",
       "      <td>392.299988</td>\n",
       "      <td>392.299988</td>\n",
       "      <td>50700800</td>\n",
       "      <td>136290.041785</td>\n",
       "      <td>135715.765276</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>2021-02-17</td>\n",
       "      <td>390.420013</td>\n",
       "      <td>392.660004</td>\n",
       "      <td>389.329987</td>\n",
       "      <td>392.390015</td>\n",
       "      <td>392.390015</td>\n",
       "      <td>52290600</td>\n",
       "      <td>135065.390135</td>\n",
       "      <td>135746.909971</td>\n",
       "      <td>S&amp;P 500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1215 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date         Open         High          Low        Close  \\\n",
       "0   2018-09-11  2254.264027  2319.250008  2238.429993  2315.728027   \n",
       "1   2018-09-12  2321.538002  2334.080002  2288.359936  2321.088001   \n",
       "2   2018-09-13  2330.533997  2344.220013  2309.516029  2321.141987   \n",
       "3   2018-09-14  2325.042053  2331.866028  2288.213974  2303.799938   \n",
       "4   2018-09-17  2287.587975  2293.333942  2216.266037  2239.028034   \n",
       "..         ...          ...          ...          ...          ...   \n",
       "607 2021-02-10   392.119995   392.279999   387.500000   390.079987   \n",
       "608 2021-02-11   391.239990   391.690002   388.100006   390.709991   \n",
       "609 2021-02-12   389.850006   392.899994   389.769989   392.640015   \n",
       "610 2021-02-16   393.959991   394.170013   391.529999   392.299988   \n",
       "611 2021-02-17   390.420013   392.660004   389.329987   392.390015   \n",
       "\n",
       "       Adj Close     Volume     OpenAmount    CloseAmount     Fund  \n",
       "0    2315.578598  105633000   98602.876081   99282.779572      WSB  \n",
       "1    2320.937626  126806363   98141.567929   99321.659858      WSB  \n",
       "2    2320.990498  100055038   99531.099307  100259.117586      WSB  \n",
       "3    2303.647877   83332550  100660.744792  101092.077546      WSB  \n",
       "4    2238.878071   75012413  100323.973803   99874.491212      WSB  \n",
       "..           ...        ...            ...            ...      ...  \n",
       "607   390.079987   59154400  135653.497000  134947.758205  S&P 500  \n",
       "608   390.709991   42755400  135349.060243  135165.707727  S&P 500  \n",
       "609   392.640015   50505700  134868.196705  135833.397206  S&P 500  \n",
       "610   392.299988   50700800  136290.041785  135715.765276  S&P 500  \n",
       "611   392.390015   52290600  135065.390135  135746.909971  S&P 500  \n",
       "\n",
       "[1215 rows x 10 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfSPY = yf.download(\"SPY\", start=\"2018-9-12\", end=\"2021-02-18\", interval=\"1d\").reset_index()\n",
    "dfSPY[\"Fund\"] = [\"S&P 500\"] * len(dfSPY[\"Open\"])\n",
    "shares = 100000/dfSPY[\"Open\"].values[0]\n",
    "dfSPY[\"OpenAmount\"] = dfSPY[\"Open\"]*shares\n",
    "dfSPY[\"CloseAmount\"] = dfSPY[\"Close\"]*shares\n",
    "dfCombined = pd.concat([dfDay, dfSPY])\n",
    "dfCombined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "data": [
        {
         "hovertemplate": "<b>%{x}</b><br>$%{y:.0f}<extra></extra>",
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          "2018-11-01T00:00:00",
          "2018-11-02T00:00:00",
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          "2018-11-06T00:00:00",
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          "2018-12-03T00:00:00",
          "2018-12-04T00:00:00",
          "2018-12-06T00:00:00",
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       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('8b0a2b56-68cb-4ca7-b3f3-ad5344c7d6e9');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
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       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "import plotly \n",
    "#dfCombined = dfCombined[dfCombined[\"Date\"]>\"2021-01-28\"]\n",
    "fig = px.line(dfCombined, x=\"Date\", y=\"CloseAmount\", title='WSB', color=\"Fund\", \n",
    "             color_discrete_sequence=[\"rgb(229, 81, 39)\",\"rgb(118, 213, 232)\" ])\n",
    "\n",
    "wsbReturn = (capital-100000)/100000*100\n",
    "\n",
    "\n",
    "fig.update_layout(title=\"<b>+\"+str(round(wsbReturn, 2))+\"% Return</b><br>Aug 2018 - Feb 2021\", titlefont=dict(color='rgb(229, 81, 39)', size=20), plot_bgcolor='rgb(32,36,44)', paper_bgcolor='rgb(32,36,44)')\n",
    "fig.update_xaxes(title_text=\"\",color='white', showgrid=False, tickfont=dict(size=10))\n",
    "fig.update_yaxes(title_text=\"$\", color='white', showgrid=False, titlefont=dict(size=20),gridcolor=\"rgb(228,49,34)\")\n",
    "fig.update_layout(\n",
    "    legend=dict(\n",
    "        title=dict(text=\"\",font=dict(color='white')),\n",
    "        x=.85, y=1.15,\n",
    "        font=dict(\n",
    "            color='white',\n",
    "            size=15\n",
    "        )\n",
    "    )\n",
    ")\n",
    "fig.update_traces(line=dict(width=3))\n",
    "for i in range(0, len(fig.data)):\n",
    "    fig.data[i].hovertemplate = \"<b>%{x}</b><br>$%{y:.0f}<extra></extra>\"\n",
    "\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
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       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('b4d45ecd-c877-4008-a1c1-964d9986fbe7');\n",
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       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
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       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
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       "    x.observe(outputEl, {childList: true});\n",
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       "                });\n",
       "            </script>\n",
       "        </div>"
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     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "\n",
    "fig = go.Figure(px.bar(dfWs, x=\"buyDate\", y=\"buy\", color='Ticker',text='Ticker',color_discrete_sequence=px.colors.qualitative.Light24))\n",
    "\n",
    "fig.update_layout(title=\"Portfolio by Week\", titlefont=dict(color='rgb(235,60,92)'), plot_bgcolor='rgb(32,36,44)', paper_bgcolor='rgb(32,36,44)')\n",
    "fig.update_xaxes(title_text=\"\",color='white', showgrid=False, fixedrange=False)\n",
    "fig.update_yaxes(title_text=\"$\",color='white', showgrid=False,  fixedrange=False,gridwidth=1,gridcolor=\"rgb(109,177,174)\")\n",
    "fig.update_layout(\n",
    "    legend=dict(\n",
    "        title=dict(text=\"Ticker\",font=dict(color=\"white\")),\n",
    "        \n",
    "        font=dict(\n",
    "            color='white'\n",
    "        ),\n",
    "        \n",
    "    )\n",
    ")\n",
    "\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
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