Investment Portfolio Python Notebook_03_2018_blog example.ipynb

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   "source": [
    "**References:**  \n",
    "\n",
    "https://www.datacamp.com/community/tutorials/finance-python-trading\n",
    "\n",
    "https://github.com/datacamp/datacamp-community-tutorials/blob/master/Python%20Finance%20Tutorial%20For%20Beginners/Python%20For%20Finance%20Beginners%20Tutorial.ipynb\n",
    "\n",
    "https://pypi.python.org/pypi/fix-yahoo-finance\n",
    "\n",
    "http://www.learndatasci.com/python-finance-part-yahoo-finance-api-pandas-matplotlib/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import initial libraries\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.2.2\n"
     ]
    },
    {
     "data": {
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       "<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
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       "<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
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     "output_type": "display_data"
    }
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   "source": [
    "# Imports in order to be able to use Plotly offline.\n",
    "from plotly import __version__\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "print(__version__) # requires version >= 1.9.0\n",
    "\n",
    "init_notebook_mode(connected=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>JNJ</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>MCD</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>MTCH</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>NFLX</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013-08-14</td>\n",
       "      <td>WMT</td>\n",
       "      <td>125</td>\n",
       "      <td>68.30</td>\n",
       "      <td>8537.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>FB</td>\n",
       "      <td>150</td>\n",
       "      <td>53.32</td>\n",
       "      <td>7998.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>TWTR</td>\n",
       "      <td>225</td>\n",
       "      <td>36.38</td>\n",
       "      <td>8185.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Acquisition Date Ticker  Quantity  Unit Cost  Cost Basis Start of Year\n",
       "0       2013-02-07   AAPL       125      65.40     8175.00    2017-12-29\n",
       "1       2014-02-27    JNJ       100      81.90     8190.00    2017-12-29\n",
       "2       2013-06-04    MCD       100      84.99     8499.00    2017-12-29\n",
       "3       2015-12-14   MTCH       600      13.63     8178.00    2017-12-29\n",
       "4       2016-01-14   NFLX        75     108.71     8153.25    2017-12-29\n",
       "5       2013-08-14    WMT       125      68.30     8537.50    2017-12-29\n",
       "6       2013-12-13     FB       150      53.32     7998.00    2017-12-29\n",
       "7       2015-01-05   TWTR       225      36.38     8185.50    2017-12-29"
      ]
     },
     "execution_count": 3,
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    }
   ],
   "source": [
    "# Import the Sample worksheet with acquisition dates and initial cost basis:\n",
    "\n",
    "portfolio_df = pd.read_excel('Sample stocks acquisition dates_costs.xlsx', sheetname='Sample')\n",
    "\n",
    "portfolio_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8 entries, 0 to 7\n",
      "Data columns (total 6 columns):\n",
      "Acquisition Date    8 non-null datetime64[ns]\n",
      "Ticker              8 non-null object\n",
      "Quantity            8 non-null int64\n",
      "Unit Cost           8 non-null float64\n",
      "Cost Basis          8 non-null float64\n",
      "Start of Year       8 non-null datetime64[ns]\n",
      "dtypes: datetime64[ns](2), float64(2), int64(1), object(1)\n",
      "memory usage: 456.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "# Confirm that you have 8 values for each column.\n",
    "\n",
    "portfolio_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Date Ranges for SP 500 and for all tickers\n",
    "# Modify these date ranges each week.\n",
    "\n",
    "# The below will pull back stock prices from 2010 until end date specified.\n",
    "start_sp = datetime.datetime(2013, 1, 1)\n",
    "end_sp = datetime.datetime(2018, 3, 9)\n",
    "\n",
    "# This variable is used for YTD performance.\n",
    "end_of_last_year = datetime.datetime(2017, 12, 29)\n",
    "\n",
    "# These are separate if for some reason want different date range than SP.\n",
    "stocks_start = datetime.datetime(2013, 1, 1)\n",
    "stocks_end = datetime.datetime(2018, 3, 9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Kevin\\Anaconda2\\lib\\site-packages\\fix_yahoo_finance\\__init__.py:43: DeprecationWarning:\n",
      "\n",
      "\n",
      "    Auto-overriding of pandas_datareader's get_data_yahoo() is deprecated and no longer available.\n",
      "    Use pdr_override() to explicitly override it.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 downloaded"
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       "      <th></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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>1426.189941</td>\n",
       "      <td>1462.430054</td>\n",
       "      <td>1426.189941</td>\n",
       "      <td>1462.420044</td>\n",
       "      <td>1462.420044</td>\n",
       "      <td>-92367296</td>\n",
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       "      <th>2013-01-03</th>\n",
       "      <td>1462.420044</td>\n",
       "      <td>1465.469971</td>\n",
       "      <td>1455.530029</td>\n",
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       "      <th>2013-01-04</th>\n",
       "      <td>1459.369995</td>\n",
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       "      <td>1458.989990</td>\n",
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       "      <th>2013-01-07</th>\n",
       "      <td>1466.469971</td>\n",
       "      <td>1466.469971</td>\n",
       "      <td>1456.619995</td>\n",
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       "    <tr>\n",
       "      <th>2013-01-08</th>\n",
       "      <td>1461.890015</td>\n",
       "      <td>1461.890015</td>\n",
       "      <td>1451.640015</td>\n",
       "      <td>1457.150024</td>\n",
       "      <td>1457.150024</td>\n",
       "      <td>-693367296</td>\n",
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      "text/plain": [
       "                   Open         High          Low        Close    Adj Close  \\\n",
       "Date                                                                          \n",
       "2013-01-02  1426.189941  1462.430054  1426.189941  1462.420044  1462.420044   \n",
       "2013-01-03  1462.420044  1465.469971  1455.530029  1459.369995  1459.369995   \n",
       "2013-01-04  1459.369995  1467.939941  1458.989990  1466.469971  1466.469971   \n",
       "2013-01-07  1466.469971  1466.469971  1456.619995  1461.890015  1461.890015   \n",
       "2013-01-08  1461.890015  1461.890015  1451.640015  1457.150024  1457.150024   \n",
       "\n",
       "               Volume  \n",
       "Date                   \n",
       "2013-01-02  -92367296  \n",
       "2013-01-03 -465237296  \n",
       "2013-01-04 -870677296  \n",
       "2013-01-07 -989997296  \n",
       "2013-01-08 -693367296  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Leveraged from the helpful Datacamp Python Finance trading blog post.\n",
    "\n",
    "from pandas_datareader import data as pdr\n",
    "import fix_yahoo_finance as yf\n",
    "yf.pdr_override() # <== that's all it takes :-)\n",
    "\n",
    "sp500 = pdr.get_data_yahoo('^GSPC', \n",
    "                           start_sp,\n",
    "                             end_sp)\n",
    "                          \n",
    "sp500.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "      <th></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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-03-05</th>\n",
       "      <td>2681.060059</td>\n",
       "      <td>2728.090088</td>\n",
       "      <td>2675.750000</td>\n",
       "      <td>2720.939941</td>\n",
       "      <td>2720.939941</td>\n",
       "      <td>-584157296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-06</th>\n",
       "      <td>2730.179932</td>\n",
       "      <td>2732.080078</td>\n",
       "      <td>2711.260010</td>\n",
       "      <td>2728.120117</td>\n",
       "      <td>2728.120117</td>\n",
       "      <td>-924277296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-07</th>\n",
       "      <td>2710.179932</td>\n",
       "      <td>2730.600098</td>\n",
       "      <td>2701.739990</td>\n",
       "      <td>2726.800049</td>\n",
       "      <td>2726.800049</td>\n",
       "      <td>-901697296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-08</th>\n",
       "      <td>2732.750000</td>\n",
       "      <td>2740.449951</td>\n",
       "      <td>2722.649902</td>\n",
       "      <td>2738.969971</td>\n",
       "      <td>2738.969971</td>\n",
       "      <td>-1082647296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-09</th>\n",
       "      <td>2752.909912</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>2751.540039</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>-930867296</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Open         High          Low        Close    Adj Close  \\\n",
       "Date                                                                          \n",
       "2018-03-05  2681.060059  2728.090088  2675.750000  2720.939941  2720.939941   \n",
       "2018-03-06  2730.179932  2732.080078  2711.260010  2728.120117  2728.120117   \n",
       "2018-03-07  2710.179932  2730.600098  2701.739990  2726.800049  2726.800049   \n",
       "2018-03-08  2732.750000  2740.449951  2722.649902  2738.969971  2738.969971   \n",
       "2018-03-09  2752.909912  2786.570068  2751.540039  2786.570068  2786.570068   \n",
       "\n",
       "                Volume  \n",
       "Date                    \n",
       "2018-03-05  -584157296  \n",
       "2018-03-06  -924277296  \n",
       "2018-03-07  -901697296  \n",
       "2018-03-08 -1082647296  \n",
       "2018-03-09  -930867296  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp500.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a dataframe with only the Adj Close column as that's all we need for this analysis.\n",
    "\n",
    "sp_500_adj_close = sp500[['Adj Close']].reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "      <th>1301</th>\n",
       "      <td>2018-03-05</td>\n",
       "      <td>2720.939941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1302</th>\n",
       "      <td>2018-03-06</td>\n",
       "      <td>2728.120117</td>\n",
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       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>2018-03-07</td>\n",
       "      <td>2726.800049</td>\n",
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       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>2018-03-08</td>\n",
       "      <td>2738.969971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1305</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
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      "text/plain": [
       "           Date    Adj Close\n",
       "1301 2018-03-05  2720.939941\n",
       "1302 2018-03-06  2728.120117\n",
       "1303 2018-03-07  2726.800049\n",
       "1304 2018-03-08  2738.969971\n",
       "1305 2018-03-09  2786.570068"
      ]
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     "execution_count": 9,
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   ],
   "source": [
    "sp_500_adj_close.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date    Adj Close\n",
       "1258 2017-12-29  2673.610107"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adj Close for the EOY in 2017 in order to run comparisons versus stocks YTD performances.\n",
    "\n",
    "sp_500_adj_close_start = sp_500_adj_close[sp_500_adj_close['Date']==end_of_last_year]\n",
    "sp_500_adj_close_start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([u'AAPL', u'JNJ', u'MCD', u'MTCH', u'NFLX', u'WMT', u'FB', u'TWTR'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a dynamic list of tickers to pull from Yahoo Finance API based on the imported file with tickers.\n",
    "tickers = portfolio_df['Ticker'].unique()\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 downloaded"
     ]
    }
   ],
   "source": [
    "# Stock comparison code\n",
    "\n",
    "def get(tickers, startdate, enddate):\n",
    "    def data(ticker):\n",
    "        return (pdr.get_data_yahoo(ticker, start=startdate, end=enddate))\n",
    "    datas = map(data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['Ticker', 'Date']))\n",
    "               \n",
    "all_data = get(tickers, stocks_start, stocks_end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">AAPL</th>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>79.117142</td>\n",
       "      <td>79.285713</td>\n",
       "      <td>77.375717</td>\n",
       "      <td>78.432854</td>\n",
       "      <td>56.532833</td>\n",
       "      <td>140129500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>78.268570</td>\n",
       "      <td>78.524284</td>\n",
       "      <td>77.285713</td>\n",
       "      <td>77.442856</td>\n",
       "      <td>55.819256</td>\n",
       "      <td>88241300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>76.709999</td>\n",
       "      <td>76.947144</td>\n",
       "      <td>75.118568</td>\n",
       "      <td>75.285713</td>\n",
       "      <td>54.264439</td>\n",
       "      <td>148583400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-07</th>\n",
       "      <td>74.571426</td>\n",
       "      <td>75.614288</td>\n",
       "      <td>73.599998</td>\n",
       "      <td>74.842857</td>\n",
       "      <td>53.945240</td>\n",
       "      <td>121039100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-08</th>\n",
       "      <td>75.601425</td>\n",
       "      <td>75.984283</td>\n",
       "      <td>74.464287</td>\n",
       "      <td>75.044289</td>\n",
       "      <td>54.090424</td>\n",
       "      <td>114676800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Open       High        Low      Close  Adj Close  \\\n",
       "Ticker Date                                                                \n",
       "AAPL   2013-01-02  79.117142  79.285713  77.375717  78.432854  56.532833   \n",
       "       2013-01-03  78.268570  78.524284  77.285713  77.442856  55.819256   \n",
       "       2013-01-04  76.709999  76.947144  75.118568  75.285713  54.264439   \n",
       "       2013-01-07  74.571426  75.614288  73.599998  74.842857  53.945240   \n",
       "       2013-01-08  75.601425  75.984283  74.464287  75.044289  54.090424   \n",
       "\n",
       "                      Volume  \n",
       "Ticker Date                   \n",
       "AAPL   2013-01-02  140129500  \n",
       "       2013-01-03   88241300  \n",
       "       2013-01-04  148583400  \n",
       "       2013-01-07  121039100  \n",
       "       2013-01-08  114676800  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>56.532833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>55.819256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>54.264439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-07</td>\n",
       "      <td>53.945240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-08</td>\n",
       "      <td>54.090424</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker       Date  Adj Close\n",
       "0   AAPL 2013-01-02  56.532833\n",
       "1   AAPL 2013-01-03  55.819256\n",
       "2   AAPL 2013-01-04  54.264439\n",
       "3   AAPL 2013-01-07  53.945240\n",
       "4   AAPL 2013-01-08  54.090424"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Also only pulling the ticker, date and adj. close columns for our tickers.\n",
    "\n",
    "adj_close = all_data[['Adj Close']].reset_index()\n",
    "adj_close.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>168.542831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2564</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>138.831009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3870</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>171.037949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4449</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>31.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5755</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>191.960007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ticker       Date   Adj Close\n",
       "1258   AAPL 2017-12-29  168.542831\n",
       "2564    JNJ 2017-12-29  138.831009\n",
       "3870    MCD 2017-12-29  171.037949\n",
       "4449   MTCH 2017-12-29   31.309999\n",
       "5755   NFLX 2017-12-29  191.960007"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grabbing the ticker close from the end of last year\n",
    "adj_close_start = adj_close[adj_close['Date']==end_of_last_year]\n",
    "adj_close_start.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1305</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2611</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4496</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5802</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7108</th>\n",
       "      <td>WMT</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>88.720001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8414</th>\n",
       "      <td>FB</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>185.229996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9505</th>\n",
       "      <td>TWTR</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>35.349998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ticker       Date   Adj Close\n",
       "1305   AAPL 2018-03-09  179.979996\n",
       "2611    JNJ 2018-03-09  133.800003\n",
       "3917    MCD 2018-03-09  157.240005\n",
       "4496   MTCH 2018-03-09   44.790001\n",
       "5802   NFLX 2018-03-09  331.440002\n",
       "7108    WMT 2018-03-09   88.720001\n",
       "8414     FB 2018-03-09  185.229996\n",
       "9505   TWTR 2018-03-09   35.349998"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grab the latest stock close price\n",
    "\n",
    "adj_close_latest = adj_close[adj_close['Date']==stocks_end]\n",
    "adj_close_latest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Adj Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCD</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MTCH</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date   Adj Close\n",
       "Ticker                       \n",
       "AAPL   2018-03-09  179.979996\n",
       "JNJ    2018-03-09  133.800003\n",
       "MCD    2018-03-09  157.240005\n",
       "MTCH   2018-03-09   44.790001\n",
       "NFLX   2018-03-09  331.440002"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adj_close_latest.set_index('Ticker', inplace=True)\n",
    "adj_close_latest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ</th>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCD</th>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MTCH</th>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year\n",
       "Ticker                                                                \n",
       "AAPL         2013-02-07       125      65.40     8175.00    2017-12-29\n",
       "JNJ          2014-02-27       100      81.90     8190.00    2017-12-29\n",
       "MCD          2013-06-04       100      84.99     8499.00    2017-12-29\n",
       "MTCH         2015-12-14       600      13.63     8178.00    2017-12-29\n",
       "NFLX         2016-01-14        75     108.71     8153.25    2017-12-29"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_df.set_index(['Ticker'], inplace=True)\n",
    "\n",
    "portfolio_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr 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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ</th>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCD</th>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MTCH</th>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "Ticker                                                                   \n",
       "AAPL         2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "JNJ          2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "MCD          2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "MTCH         2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "NFLX         2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "             Date   Adj Close  \n",
       "Ticker                         \n",
       "AAPL   2018-03-09  179.979996  \n",
       "JNJ    2018-03-09  133.800003  \n",
       "MCD    2018-03-09  157.240005  \n",
       "MTCH   2018-03-09   44.790001  \n",
       "NFLX   2018-03-09  331.440002  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the portfolio dataframe with the adj close dataframe; they are being joined by their indexes.\n",
    "\n",
    "merged_portfolio = pd.merge(portfolio_df, adj_close_latest, left_index=True, right_index=True)\n",
    "merged_portfolio.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ</th>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCD</th>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MTCH</th>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WMT</th>\n",
       "      <td>2013-08-14</td>\n",
       "      <td>125</td>\n",
       "      <td>68.30</td>\n",
       "      <td>8537.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>88.720001</td>\n",
       "      <td>0.298975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB</th>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>150</td>\n",
       "      <td>53.32</td>\n",
       "      <td>7998.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>185.229996</td>\n",
       "      <td>2.473931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TWTR</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>225</td>\n",
       "      <td>36.38</td>\n",
       "      <td>8185.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>35.349998</td>\n",
       "      <td>-0.028312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "Ticker                                                                   \n",
       "AAPL         2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "JNJ          2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "MCD          2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "MTCH         2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "NFLX         2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "WMT          2013-08-14       125      68.30     8537.50    2017-12-29   \n",
       "FB           2013-12-13       150      53.32     7998.00    2017-12-29   \n",
       "TWTR         2015-01-05       225      36.38     8185.50    2017-12-29   \n",
       "\n",
       "             Date   Adj Close  ticker return  \n",
       "Ticker                                        \n",
       "AAPL   2018-03-09  179.979996       1.751988  \n",
       "JNJ    2018-03-09  133.800003       0.633700  \n",
       "MCD    2018-03-09  157.240005       0.850100  \n",
       "MTCH   2018-03-09   44.790001       2.286134  \n",
       "NFLX   2018-03-09  331.440002       2.048846  \n",
       "WMT    2018-03-09   88.720001       0.298975  \n",
       "FB     2018-03-09  185.229996       2.473931  \n",
       "TWTR   2018-03-09   35.349998      -0.028312  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The below creates a new column which is the ticker return; takes the latest adjusted close for each position\n",
    "# and divides that by the initial share cost.\n",
    "\n",
    "merged_portfolio['ticker return'] = merged_portfolio['Adj Close'] / merged_portfolio['Unit Cost'] - 1\n",
    "\n",
    "merged_portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "merged_portfolio.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Date_x</th>\n",
       "      <th>Adj Close_x</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>Date_y</th>\n",
       "      <th>Adj Close_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>1509.390015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>1854.290039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>1631.380005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>2021.939941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>1921.839966</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "      Date_x  Adj Close_x  ticker return     Date_y  Adj Close_y  \n",
       "0 2018-03-09   179.979996       1.751988 2013-02-07  1509.390015  \n",
       "1 2018-03-09   133.800003       0.633700 2014-02-27  1854.290039  \n",
       "2 2018-03-09   157.240005       0.850100 2013-06-04  1631.380005  \n",
       "3 2018-03-09    44.790001       2.286134 2015-12-14  2021.939941  \n",
       "4 2018-03-09   331.440002       2.048846 2016-01-14  1921.839966  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Here we are merging the new dataframe with the sp500 adjusted closes since the sp start price based on \n",
    "# each ticker's acquisition date and sp500 close date.\n",
    "\n",
    "merged_portfolio_sp = pd.merge(merged_portfolio, sp_500_adj_close, left_on='Acquisition Date', right_on='Date')\n",
    "# .set_index('Ticker')\n",
    "\n",
    "merged_portfolio_sp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \n",
       "0  2018-03-09        179.979996       1.751988           1509.390015  \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039  \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005  \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941  \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We will delete the additional date column which is created from this merge.\n",
    "# We then rename columns to Latest Date and then reflect Ticker Adj Close and SP 500 Initial Close.\n",
    "\n",
    "del merged_portfolio_sp['Date_y']\n",
    "\n",
    "merged_portfolio_sp.rename(columns={'Date_x': 'Latest Date', 'Adj Close_x': 'Ticker Adj Close'\n",
    "                                    , 'Adj Close_y': 'SP 500 Initial Close'}, inplace=True)\n",
    "\n",
    "merged_portfolio_sp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>Equiv SP Shares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>5.416095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>4.416785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>5.209700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>4.044631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>4.242419</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "   Equiv SP Shares  \n",
       "0         5.416095  \n",
       "1         4.416785  \n",
       "2         5.209700  \n",
       "3         4.044631  \n",
       "4         4.242419  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This new column determines what SP 500 equivalent purchase would have been at purchase date of stock.\n",
    "merged_portfolio_sp['Equiv SP Shares'] = merged_portfolio_sp['Cost Basis'] / merged_portfolio_sp['SP 500 Initial Close']\n",
    "merged_portfolio_sp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>Equiv SP Shares</th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>5.416095</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>4.416785</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>5.209700</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>4.044631</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>4.242419</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "   Equiv SP Shares       Date    Adj Close  \n",
       "0         5.416095 2018-03-09  2786.570068  \n",
       "1         4.416785 2018-03-09  2786.570068  \n",
       "2         5.209700 2018-03-09  2786.570068  \n",
       "3         4.044631 2018-03-09  2786.570068  \n",
       "4         4.242419 2018-03-09  2786.570068  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We are joining the developing dataframe with the sp500 closes again, this time with the latest close for SP.\n",
    "merged_portfolio_sp_latest = pd.merge(merged_portfolio_sp, sp_500_adj_close, left_on='Latest Date', right_on='Date')\n",
    "\n",
    "merged_portfolio_sp_latest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>Equiv SP Shares</th>\n",
       "      <th>SP 500 Latest Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>5.416095</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>4.416785</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>5.209700</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>4.044631</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>4.242419</td>\n",
       "      <td>2786.570068</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "   Equiv SP Shares  SP 500 Latest Close  \n",
       "0         5.416095          2786.570068  \n",
       "1         4.416785          2786.570068  \n",
       "2         5.209700          2786.570068  \n",
       "3         4.044631          2786.570068  \n",
       "4         4.242419          2786.570068  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Once again need to delete the new Date column added as it's redundant to Latest Date.  \n",
    "# Modify Adj Close from the sp dataframe to distinguish it by calling it the SP 500 Latest Close.\n",
    "\n",
    "del merged_portfolio_sp_latest['Date']\n",
    "\n",
    "merged_portfolio_sp_latest.rename(columns={'Adj Close': 'SP 500 Latest Close'}, inplace=True)\n",
    "\n",
    "merged_portfolio_sp_latest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>Equiv SP Shares</th>\n",
       "      <th>SP 500 Latest Close</th>\n",
       "      <th>SP Return</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>5.416095</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.846156</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.49950</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.49950</td>\n",
       "      <td>6917.328742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>4.416785</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.502769</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.00030</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.00030</td>\n",
       "      <td>4117.680232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>5.209700</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.708106</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.00050</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.00050</td>\n",
       "      <td>6018.193379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>4.044631</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.378167</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.00060</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.00060</td>\n",
       "      <td>3092.646350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>4.242419</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.449949</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.00015</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.75015</td>\n",
       "      <td>3668.547241</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "   Equiv SP Shares  SP 500 Latest Close  SP Return  Abs. Return Compare  \\\n",
       "0         5.416095          2786.570068   0.846156             0.905831   \n",
       "1         4.416785          2786.570068   0.502769             0.130930   \n",
       "2         5.209700          2786.570068   0.708106             0.141994   \n",
       "3         4.044631          2786.570068   0.378167             1.907967   \n",
       "4         4.242419          2786.570068   0.449949             1.598897   \n",
       "\n",
       "   Ticker Share Value  SP 500 Value  Abs Value Compare  Stock Gain / (Loss)  \\\n",
       "0         22497.49950  15092.328742        7405.170758          14322.49950   \n",
       "1         13380.00030  12307.680232        1072.320068           5190.00030   \n",
       "2         15724.00050  14517.193379        1206.807121           7225.00050   \n",
       "3         26874.00060  11270.646350       15603.354250          18696.00060   \n",
       "4         24858.00015  11821.797241       13036.202909          16704.75015   \n",
       "\n",
       "   SP 500 Gain / (Loss)  \n",
       "0           6917.328742  \n",
       "1           4117.680232  \n",
       "2           6018.193379  \n",
       "3           3092.646350  \n",
       "4           3668.547241  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Percent return of SP from acquisition date of position through latest trading day.\n",
    "merged_portfolio_sp_latest['SP Return'] = merged_portfolio_sp_latest['SP 500 Latest Close'] / merged_portfolio_sp_latest['SP 500 Initial Close'] - 1\n",
    "\n",
    "# This is a new column which takes the tickers return and subtracts the sp 500 equivalent range return.\n",
    "merged_portfolio_sp_latest['Abs. Return Compare'] = merged_portfolio_sp_latest['ticker return'] - merged_portfolio_sp_latest['SP Return']\n",
    "\n",
    "# This is a new column where we calculate the ticker's share value by multiplying the original quantity by the latest close.\n",
    "merged_portfolio_sp_latest['Ticker Share Value'] = merged_portfolio_sp_latest['Quantity'] * merged_portfolio_sp_latest['Ticker Adj Close']\n",
    "\n",
    "# We calculate the equivalent SP 500 Value if we take the original SP shares * the latest SP 500 share price.\n",
    "merged_portfolio_sp_latest['SP 500 Value'] = merged_portfolio_sp_latest['Equiv SP Shares'] * merged_portfolio_sp_latest['SP 500 Latest Close']\n",
    "\n",
    "# This is a new column where we take the current market value for the shares and subtract the SP 500 value.\n",
    "merged_portfolio_sp_latest['Abs Value Compare'] = merged_portfolio_sp_latest['Ticker Share Value'] - merged_portfolio_sp_latest['SP 500 Value']\n",
    "\n",
    "# This column calculates profit / loss for stock position.\n",
    "merged_portfolio_sp_latest['Stock Gain / (Loss)'] = merged_portfolio_sp_latest['Ticker Share Value'] - merged_portfolio_sp_latest['Cost Basis']\n",
    "\n",
    "# This column calculates profit / loss for SP 500.\n",
    "merged_portfolio_sp_latest['SP 500 Gain / (Loss)'] = merged_portfolio_sp_latest['SP 500 Value'] - merged_portfolio_sp_latest['Cost Basis']\n",
    "\n",
    "merged_portfolio_sp_latest.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>SP 500 Latest Close</th>\n",
       "      <th>SP Return</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.846156</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.49950</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.49950</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>168.542831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.502769</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.00030</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.00030</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>138.831009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.708106</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.00050</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.00050</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>171.037949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.378167</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.00060</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.00060</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>31.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>...</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.449949</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.00015</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.75015</td>\n",
       "      <td>3668.547241</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>191.960007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "      ...      SP 500 Latest Close  SP Return  Abs. Return Compare  \\\n",
       "0     ...              2786.570068   0.846156             0.905831   \n",
       "1     ...              2786.570068   0.502769             0.130930   \n",
       "2     ...              2786.570068   0.708106             0.141994   \n",
       "3     ...              2786.570068   0.378167             1.907967   \n",
       "4     ...              2786.570068   0.449949             1.598897   \n",
       "\n",
       "   Ticker Share Value  SP 500 Value  Abs Value Compare  Stock Gain / (Loss)  \\\n",
       "0         22497.49950  15092.328742        7405.170758          14322.49950   \n",
       "1         13380.00030  12307.680232        1072.320068           5190.00030   \n",
       "2         15724.00050  14517.193379        1206.807121           7225.00050   \n",
       "3         26874.00060  11270.646350       15603.354250          18696.00060   \n",
       "4         24858.00015  11821.797241       13036.202909          16704.75015   \n",
       "\n",
       "   SP 500 Gain / (Loss)       Date   Adj Close  \n",
       "0           6917.328742 2017-12-29  168.542831  \n",
       "1           4117.680232 2017-12-29  138.831009  \n",
       "2           6018.193379 2017-12-29  171.037949  \n",
       "3           3092.646350 2017-12-29   31.309999  \n",
       "4           3668.547241 2017-12-29  191.960007  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the overall dataframe with the adj close start of year dataframe for YTD tracking of tickers.\n",
    "# Should not need to do the outer join;\n",
    "\n",
    "merged_portfolio_sp_latest_YTD = pd.merge(merged_portfolio_sp_latest, adj_close_start, on='Ticker')\n",
    "# , how='outer'\n",
    "\n",
    "merged_portfolio_sp_latest_YTD.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
       "    .dataframe tbody tr 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>Ticker</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>Equiv SP Shares</th>\n",
       "      <th>SP 500 Latest Close</th>\n",
       "      <th>SP Return</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Ticker Start Year Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>5.416095</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.846156</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.49950</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.49950</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>168.542831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>4.416785</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.502769</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.00030</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.00030</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>138.831009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>5.209700</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.708106</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.00050</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.00050</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>171.037949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>4.044631</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.378167</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.00060</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.00060</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>31.309999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>4.242419</td>\n",
       "      <td>2786.570068</td>\n",
       "      <td>0.449949</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.00015</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.75015</td>\n",
       "      <td>3668.547241</td>\n",
       "      <td>191.960007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "   Equiv SP Shares  SP 500 Latest Close  SP Return  Abs. Return Compare  \\\n",
       "0         5.416095          2786.570068   0.846156             0.905831   \n",
       "1         4.416785          2786.570068   0.502769             0.130930   \n",
       "2         5.209700          2786.570068   0.708106             0.141994   \n",
       "3         4.044631          2786.570068   0.378167             1.907967   \n",
       "4         4.242419          2786.570068   0.449949             1.598897   \n",
       "\n",
       "   Ticker Share Value  SP 500 Value  Abs Value Compare  Stock Gain / (Loss)  \\\n",
       "0         22497.49950  15092.328742        7405.170758          14322.49950   \n",
       "1         13380.00030  12307.680232        1072.320068           5190.00030   \n",
       "2         15724.00050  14517.193379        1206.807121           7225.00050   \n",
       "3         26874.00060  11270.646350       15603.354250          18696.00060   \n",
       "4         24858.00015  11821.797241       13036.202909          16704.75015   \n",
       "\n",
       "   SP 500 Gain / (Loss)  Ticker Start Year Close  \n",
       "0           6917.328742               168.542831  \n",
       "1           4117.680232               138.831009  \n",
       "2           6018.193379               171.037949  \n",
       "3           3092.646350                31.309999  \n",
       "4           3668.547241               191.960007  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Deleting date again as it's an unnecessary column.  Explaining that new column is the Ticker Start of Year Close.\n",
    "\n",
    "del merged_portfolio_sp_latest_YTD['Date']\n",
    "\n",
    "merged_portfolio_sp_latest_YTD.rename(columns={'Adj Close': 'Ticker Start Year Close'}, inplace=True)\n",
    "\n",
    "merged_portfolio_sp_latest_YTD.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>SP Return</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Ticker Start Year Close</th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.846156</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.49950</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.49950</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>168.542831</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.502769</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.00030</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.00030</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>138.831009</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>0.708106</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.00050</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.00050</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>171.037949</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>0.378167</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.00060</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.00060</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>31.309999</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>...</td>\n",
       "      <td>0.449949</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.00015</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.75015</td>\n",
       "      <td>3668.547241</td>\n",
       "      <td>191.960007</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2673.610107</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "      ...       SP Return  Abs. Return Compare  Ticker Share Value  \\\n",
       "0     ...        0.846156             0.905831         22497.49950   \n",
       "1     ...        0.502769             0.130930         13380.00030   \n",
       "2     ...        0.708106             0.141994         15724.00050   \n",
       "3     ...        0.378167             1.907967         26874.00060   \n",
       "4     ...        0.449949             1.598897         24858.00015   \n",
       "\n",
       "   SP 500 Value  Abs Value Compare  Stock Gain / (Loss)  SP 500 Gain / (Loss)  \\\n",
       "0  15092.328742        7405.170758          14322.49950           6917.328742   \n",
       "1  12307.680232        1072.320068           5190.00030           4117.680232   \n",
       "2  14517.193379        1206.807121           7225.00050           6018.193379   \n",
       "3  11270.646350       15603.354250          18696.00060           3092.646350   \n",
       "4  11821.797241       13036.202909          16704.75015           3668.547241   \n",
       "\n",
       "   Ticker Start Year Close       Date    Adj Close  \n",
       "0               168.542831 2017-12-29  2673.610107  \n",
       "1               138.831009 2017-12-29  2673.610107  \n",
       "2               171.037949 2017-12-29  2673.610107  \n",
       "3                31.309999 2017-12-29  2673.610107  \n",
       "4               191.960007 2017-12-29  2673.610107  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Join the SP 500 start of year with current dataframe for SP 500 ytd comparisons to tickers.\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp = pd.merge(merged_portfolio_sp_latest_YTD, sp_500_adj_close_start\n",
    "                                             , left_on='Start of Year', right_on='Date')\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticker</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Ticker Start Year Close</th>\n",
       "      <th>SP Start Year Close</th>\n",
       "      <th>Share YTD</th>\n",
       "      <th>SP 500 YTD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.49950</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.49950</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>168.542831</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.067859</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.00030</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.00030</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>138.831009</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.036238</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.00050</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.00050</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>171.037949</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.080672</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.00060</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.00060</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>31.309999</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.430533</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>...</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.00015</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.75015</td>\n",
       "      <td>3668.547241</td>\n",
       "      <td>191.960007</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.726610</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "\n",
       "      ...      Abs. Return Compare  Ticker Share Value  SP 500 Value  \\\n",
       "0     ...                 0.905831         22497.49950  15092.328742   \n",
       "1     ...                 0.130930         13380.00030  12307.680232   \n",
       "2     ...                 0.141994         15724.00050  14517.193379   \n",
       "3     ...                 1.907967         26874.00060  11270.646350   \n",
       "4     ...                 1.598897         24858.00015  11821.797241   \n",
       "\n",
       "   Abs Value Compare  Stock Gain / (Loss)  SP 500 Gain / (Loss)  \\\n",
       "0        7405.170758          14322.49950           6917.328742   \n",
       "1        1072.320068           5190.00030           4117.680232   \n",
       "2        1206.807121           7225.00050           6018.193379   \n",
       "3       15603.354250          18696.00060           3092.646350   \n",
       "4       13036.202909          16704.75015           3668.547241   \n",
       "\n",
       "   Ticker Start Year Close  SP Start Year Close  Share YTD  SP 500 YTD  \n",
       "0               168.542831          2673.610107   0.067859     0.04225  \n",
       "1               138.831009          2673.610107  -0.036238     0.04225  \n",
       "2               171.037949          2673.610107  -0.080672     0.04225  \n",
       "3                31.309999          2673.610107   0.430533     0.04225  \n",
       "4               191.960007          2673.610107   0.726610     0.04225  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Deleting another unneeded Date column.\n",
    "\n",
    "del merged_portfolio_sp_latest_YTD_sp['Date']\n",
    "\n",
    "# Renaming so that it's clear this column is SP 500 start of year close.\n",
    "merged_portfolio_sp_latest_YTD_sp.rename(columns={'Adj Close': 'SP Start Year Close'}, inplace=True)\n",
    "\n",
    "# YTD return for portfolio position.\n",
    "merged_portfolio_sp_latest_YTD_sp['Share YTD'] = merged_portfolio_sp_latest_YTD_sp['Ticker Adj Close'] / merged_portfolio_sp_latest_YTD_sp['Ticker Start Year Close'] - 1\n",
    "\n",
    "# YTD return for SP to run compares.\n",
    "merged_portfolio_sp_latest_YTD_sp['SP 500 YTD'] = merged_portfolio_sp_latest_YTD_sp['SP 500 Latest Close'] / merged_portfolio_sp_latest_YTD_sp['SP Start Year Close'] - 1\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>Abs. Return Compare</th>\n",
       "      <th>Ticker Share Value</th>\n",
       "      <th>SP 500 Value</th>\n",
       "      <th>Abs Value Compare</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Ticker Start Year Close</th>\n",
       "      <th>SP Start Year Close</th>\n",
       "      <th>Share YTD</th>\n",
       "      <th>SP 500 YTD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>0.905831</td>\n",
       "      <td>22497.499500</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>7405.170758</td>\n",
       "      <td>14322.499500</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>168.542831</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.067859</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FB</td>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>150</td>\n",
       "      <td>53.32</td>\n",
       "      <td>7998.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>185.229996</td>\n",
       "      <td>2.473931</td>\n",
       "      <td>1775.319946</td>\n",
       "      <td>...</td>\n",
       "      <td>1.904315</td>\n",
       "      <td>27784.499400</td>\n",
       "      <td>12553.786406</td>\n",
       "      <td>15230.712994</td>\n",
       "      <td>19786.499400</td>\n",
       "      <td>4555.786406</td>\n",
       "      <td>176.460007</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.049700</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>0.130930</td>\n",
       "      <td>13380.000300</td>\n",
       "      <td>12307.680232</td>\n",
       "      <td>1072.320068</td>\n",
       "      <td>5190.000300</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>138.831009</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.036238</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>0.141994</td>\n",
       "      <td>15724.000500</td>\n",
       "      <td>14517.193379</td>\n",
       "      <td>1206.807121</td>\n",
       "      <td>7225.000500</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>171.037949</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.080672</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>1.907967</td>\n",
       "      <td>26874.000600</td>\n",
       "      <td>11270.646350</td>\n",
       "      <td>15603.354250</td>\n",
       "      <td>18696.000600</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>31.309999</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.430533</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>...</td>\n",
       "      <td>1.598897</td>\n",
       "      <td>24858.000150</td>\n",
       "      <td>11821.797241</td>\n",
       "      <td>13036.202909</td>\n",
       "      <td>16704.750150</td>\n",
       "      <td>3668.547241</td>\n",
       "      <td>191.960007</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.726610</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>TWTR</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>225</td>\n",
       "      <td>36.38</td>\n",
       "      <td>8185.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>35.349998</td>\n",
       "      <td>-0.028312</td>\n",
       "      <td>2020.579956</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.407406</td>\n",
       "      <td>7953.749550</td>\n",
       "      <td>11288.575453</td>\n",
       "      <td>-3334.825903</td>\n",
       "      <td>-231.750450</td>\n",
       "      <td>3103.075453</td>\n",
       "      <td>24.010000</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.472303</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>WMT</td>\n",
       "      <td>2013-08-14</td>\n",
       "      <td>125</td>\n",
       "      <td>68.30</td>\n",
       "      <td>8537.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>88.720001</td>\n",
       "      <td>0.298975</td>\n",
       "      <td>1685.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.354393</td>\n",
       "      <td>11090.000125</td>\n",
       "      <td>14115.630058</td>\n",
       "      <td>-3025.629933</td>\n",
       "      <td>2552.500125</td>\n",
       "      <td>5578.130058</td>\n",
       "      <td>98.164749</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.096213</td>\n",
       "      <td>0.04225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "6     FB       2013-12-13       150      53.32     7998.00    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "4   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "7   TWTR       2015-01-05       225      36.38     8185.50    2017-12-29   \n",
       "5    WMT       2013-08-14       125      68.30     8537.50    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "6  2018-03-09        185.229996       2.473931           1775.319946   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "4  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "7  2018-03-09         35.349998      -0.028312           2020.579956   \n",
       "5  2018-03-09         88.720001       0.298975           1685.390015   \n",
       "\n",
       "      ...      Abs. Return Compare  Ticker Share Value  SP 500 Value  \\\n",
       "0     ...                 0.905831        22497.499500  15092.328742   \n",
       "6     ...                 1.904315        27784.499400  12553.786406   \n",
       "1     ...                 0.130930        13380.000300  12307.680232   \n",
       "2     ...                 0.141994        15724.000500  14517.193379   \n",
       "3     ...                 1.907967        26874.000600  11270.646350   \n",
       "4     ...                 1.598897        24858.000150  11821.797241   \n",
       "7     ...                -0.407406         7953.749550  11288.575453   \n",
       "5     ...                -0.354393        11090.000125  14115.630058   \n",
       "\n",
       "   Abs Value Compare  Stock Gain / (Loss)  SP 500 Gain / (Loss)  \\\n",
       "0        7405.170758         14322.499500           6917.328742   \n",
       "6       15230.712994         19786.499400           4555.786406   \n",
       "1        1072.320068          5190.000300           4117.680232   \n",
       "2        1206.807121          7225.000500           6018.193379   \n",
       "3       15603.354250         18696.000600           3092.646350   \n",
       "4       13036.202909         16704.750150           3668.547241   \n",
       "7       -3334.825903          -231.750450           3103.075453   \n",
       "5       -3025.629933          2552.500125           5578.130058   \n",
       "\n",
       "   Ticker Start Year Close  SP Start Year Close  Share YTD  SP 500 YTD  \n",
       "0               168.542831          2673.610107   0.067859     0.04225  \n",
       "6               176.460007          2673.610107   0.049700     0.04225  \n",
       "1               138.831009          2673.610107  -0.036238     0.04225  \n",
       "2               171.037949          2673.610107  -0.080672     0.04225  \n",
       "3                31.309999          2673.610107   0.430533     0.04225  \n",
       "4               191.960007          2673.610107   0.726610     0.04225  \n",
       "7                24.010000          2673.610107   0.472303     0.04225  \n",
       "5                98.164749          2673.610107  -0.096213     0.04225  \n",
       "\n",
       "[8 rows x 23 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_portfolio_sp_latest_YTD_sp = merged_portfolio_sp_latest_YTD_sp.sort_values(by='Ticker', ascending=True)\n",
    "merged_portfolio_sp_latest_YTD_sp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>Stock Gain / (Loss)</th>\n",
       "      <th>SP 500 Gain / (Loss)</th>\n",
       "      <th>Ticker Start Year Close</th>\n",
       "      <th>SP Start Year Close</th>\n",
       "      <th>Share YTD</th>\n",
       "      <th>SP 500 YTD</th>\n",
       "      <th>Cum Invst</th>\n",
       "      <th>Cum Ticker Returns</th>\n",
       "      <th>Cum SP Returns</th>\n",
       "      <th>Cum Ticker ROI Mult</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>14322.4995</td>\n",
       "      <td>6917.328742</td>\n",
       "      <td>168.542831</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.067859</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>22497.4995</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>2.751988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FB</td>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>150</td>\n",
       "      <td>53.32</td>\n",
       "      <td>7998.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>185.229996</td>\n",
       "      <td>2.473931</td>\n",
       "      <td>1775.319946</td>\n",
       "      <td>...</td>\n",
       "      <td>19786.4994</td>\n",
       "      <td>4555.786406</td>\n",
       "      <td>176.460007</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.049700</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>16173.0</td>\n",
       "      <td>50281.9989</td>\n",
       "      <td>27646.115147</td>\n",
       "      <td>3.109009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>5190.0003</td>\n",
       "      <td>4117.680232</td>\n",
       "      <td>138.831009</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.036238</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>24363.0</td>\n",
       "      <td>63661.9992</td>\n",
       "      <td>39953.795379</td>\n",
       "      <td>2.613061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>7225.0005</td>\n",
       "      <td>6018.193379</td>\n",
       "      <td>171.037949</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.080672</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>32862.0</td>\n",
       "      <td>79385.9997</td>\n",
       "      <td>54470.988759</td>\n",
       "      <td>2.415739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>18696.0006</td>\n",
       "      <td>3092.646350</td>\n",
       "      <td>31.309999</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.430533</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>41040.0</td>\n",
       "      <td>106260.0003</td>\n",
       "      <td>65741.635109</td>\n",
       "      <td>2.589181</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40      8175.0    2017-12-29   \n",
       "6     FB       2013-12-13       150      53.32      7998.0    2017-12-29   \n",
       "1    JNJ       2014-02-27       100      81.90      8190.0    2017-12-29   \n",
       "2    MCD       2013-06-04       100      84.99      8499.0    2017-12-29   \n",
       "3   MTCH       2015-12-14       600      13.63      8178.0    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "6  2018-03-09        185.229996       2.473931           1775.319946   \n",
       "1  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "2  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "3  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "\n",
       "          ...           Stock Gain / (Loss)  SP 500 Gain / (Loss)  \\\n",
       "0         ...                    14322.4995           6917.328742   \n",
       "6         ...                    19786.4994           4555.786406   \n",
       "1         ...                     5190.0003           4117.680232   \n",
       "2         ...                     7225.0005           6018.193379   \n",
       "3         ...                    18696.0006           3092.646350   \n",
       "\n",
       "   Ticker Start Year Close  SP Start Year Close  Share YTD  SP 500 YTD  \\\n",
       "0               168.542831          2673.610107   0.067859     0.04225   \n",
       "6               176.460007          2673.610107   0.049700     0.04225   \n",
       "1               138.831009          2673.610107  -0.036238     0.04225   \n",
       "2               171.037949          2673.610107  -0.080672     0.04225   \n",
       "3                31.309999          2673.610107   0.430533     0.04225   \n",
       "\n",
       "   Cum Invst  Cum Ticker Returns  Cum SP Returns  Cum Ticker ROI Mult  \n",
       "0     8175.0          22497.4995    15092.328742             2.751988  \n",
       "6    16173.0          50281.9989    27646.115147             3.109009  \n",
       "1    24363.0          63661.9992    39953.795379             2.613061  \n",
       "2    32862.0          79385.9997    54470.988759             2.415739  \n",
       "3    41040.0         106260.0003    65741.635109             2.589181  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cumulative sum of original investment\n",
    "merged_portfolio_sp_latest_YTD_sp['Cum Invst'] = merged_portfolio_sp_latest_YTD_sp['Cost Basis'].cumsum()\n",
    "\n",
    "# Cumulative sum of Ticker Share Value (latest FMV based on initial quantity purchased).\n",
    "merged_portfolio_sp_latest_YTD_sp['Cum Ticker Returns'] = merged_portfolio_sp_latest_YTD_sp['Ticker Share Value'].cumsum()\n",
    "\n",
    "# Cumulative sum of SP Share Value (latest FMV driven off of initial SP equiv purchase).\n",
    "merged_portfolio_sp_latest_YTD_sp['Cum SP Returns'] = merged_portfolio_sp_latest_YTD_sp['SP 500 Value'].cumsum()\n",
    "\n",
    "# Cumulative CoC multiple return for stock investments\n",
    "merged_portfolio_sp_latest_YTD_sp['Cum Ticker ROI Mult'] = merged_portfolio_sp_latest_YTD_sp['Cum Ticker Returns'] / merged_portfolio_sp_latest_YTD_sp['Cum Invst']\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assessing Where Positions are At versus Highest Close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>56.532833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>55.819256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>54.264439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-07</td>\n",
       "      <td>53.945240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-08</td>\n",
       "      <td>54.090424</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker       Date  Adj Close\n",
       "0   AAPL 2013-01-02  56.532833\n",
       "1   AAPL 2013-01-03  55.819256\n",
       "2   AAPL 2013-01-04  54.264439\n",
       "3   AAPL 2013-01-07  53.945240\n",
       "4   AAPL 2013-01-08  54.090424"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Referencing the adj_close dataframe from above\n",
    "\n",
    "adj_close.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL</th>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ</th>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCD</th>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MTCH</th>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX</th>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year\n",
       "Ticker                                                                \n",
       "AAPL         2013-02-07       125      65.40     8175.00    2017-12-29\n",
       "JNJ          2014-02-27       100      81.90     8190.00    2017-12-29\n",
       "MCD          2013-06-04       100      84.99     8499.00    2017-12-29\n",
       "MTCH         2015-12-14       600      13.63     8178.00    2017-12-29\n",
       "NFLX         2016-01-14        75     108.71     8153.25    2017-12-29"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>Adj Close</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>56.532833</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.4</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>55.819256</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.4</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>54.264439</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.4</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-07</td>\n",
       "      <td>53.945240</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.4</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-08</td>\n",
       "      <td>54.090424</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.4</td>\n",
       "      <td>8175.0</td>\n",
       "      <td>2017-12-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker       Date  Adj Close Acquisition Date  Quantity  Unit Cost  \\\n",
       "0   AAPL 2013-01-02  56.532833       2013-02-07       125       65.4   \n",
       "1   AAPL 2013-01-03  55.819256       2013-02-07       125       65.4   \n",
       "2   AAPL 2013-01-04  54.264439       2013-02-07       125       65.4   \n",
       "3   AAPL 2013-01-07  53.945240       2013-02-07       125       65.4   \n",
       "4   AAPL 2013-01-08  54.090424       2013-02-07       125       65.4   \n",
       "\n",
       "   Cost Basis Start of Year  \n",
       "0      8175.0    2017-12-29  \n",
       "1      8175.0    2017-12-29  \n",
       "2      8175.0    2017-12-29  \n",
       "3      8175.0    2017-12-29  \n",
       "4      8175.0    2017-12-29  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Need to factor in that some positions were purchased much more recently than others.\n",
    "# Join adj_close dataframe with portfolio in order to have acquisition date.\n",
    "\n",
    "portfolio_df.reset_index(inplace=True)\n",
    "\n",
    "adj_close_acq_date = pd.merge(adj_close, portfolio_df, on='Ticker')\n",
    "\n",
    "adj_close_acq_date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# delete_columns = ['Quantity', 'Unit Cost', 'Cost Basis', 'Start of Year']\n",
    "\n",
    "del adj_close_acq_date['Quantity']\n",
    "del adj_close_acq_date['Unit Cost']\n",
    "del adj_close_acq_date['Cost Basis']\n",
    "del adj_close_acq_date['Start of Year']\n",
    "\n",
    "# Sort by these columns in this order in order to make it clearer where compare for each position should begin.\n",
    "adj_close_acq_date.sort_values(by=['Ticker', 'Acquisition Date', 'Date'], ascending=[True, True, True], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Date Delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>56.532833</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>-3110400000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-03</td>\n",
       "      <td>55.819256</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>-3024000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-04</td>\n",
       "      <td>54.264439</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>-2937600000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-07</td>\n",
       "      <td>53.945240</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>-2678400000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-01-08</td>\n",
       "      <td>54.090424</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>-2592000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker       Date  Adj Close Acquisition Date        Date Delta\n",
       "0   AAPL 2013-01-02  56.532833       2013-02-07 -3110400000000000\n",
       "1   AAPL 2013-01-03  55.819256       2013-02-07 -3024000000000000\n",
       "2   AAPL 2013-01-04  54.264439       2013-02-07 -2937600000000000\n",
       "3   AAPL 2013-01-07  53.945240       2013-02-07 -2678400000000000\n",
       "4   AAPL 2013-01-08  54.090424       2013-02-07 -2592000000000000"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Anything less than 0 means that the stock close was prior to acquisition.\n",
    "adj_close_acq_date['Date Delta'] = adj_close_acq_date['Date'] - adj_close_acq_date['Acquisition Date']\n",
    "\n",
    "adj_close_acq_date['Date Delta'] = adj_close_acq_date[['Date Delta']].apply(pd.to_numeric)  \n",
    "\n",
    "adj_close_acq_date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
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       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Date Delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>50.250072</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-08</td>\n",
       "      <td>50.975567</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>86400000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-11</td>\n",
       "      <td>51.506813</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>345600000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-12</td>\n",
       "      <td>50.215736</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>432000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-13</td>\n",
       "      <td>50.120209</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>518400000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Ticker       Date  Adj Close Acquisition Date       Date Delta\n",
       "25   AAPL 2013-02-07  50.250072       2013-02-07                0\n",
       "26   AAPL 2013-02-08  50.975567       2013-02-07   86400000000000\n",
       "27   AAPL 2013-02-11  51.506813       2013-02-07  345600000000000\n",
       "28   AAPL 2013-02-12  50.215736       2013-02-07  432000000000000\n",
       "29   AAPL 2013-02-13  50.120209       2013-02-07  518400000000000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Modified the dataframe being evaluated to look at highest close which occurred after Acquisition Date (aka, not prior to purchase).\n",
    "\n",
    "adj_close_acq_date_modified = adj_close_acq_date[adj_close_acq_date['Date Delta']>=0]\n",
    "\n",
    "adj_close_acq_date_modified.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
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       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Acquisition Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>179.979996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FB</td>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>193.089996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>147.197433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>177.238724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>44.790001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>331.440002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>TWTR</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>52.869999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WMT</td>\n",
       "      <td>2013-08-14</td>\n",
       "      <td>108.900742</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date   Adj Close\n",
       "0   AAPL       2013-02-07  179.979996\n",
       "1     FB       2013-12-13  193.089996\n",
       "2    JNJ       2014-02-27  147.197433\n",
       "3    MCD       2013-06-04  177.238724\n",
       "4   MTCH       2015-12-14   44.790001\n",
       "5   NFLX       2016-01-14  331.440002\n",
       "6   TWTR       2015-01-05   52.869999\n",
       "7    WMT       2013-08-14  108.900742"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This pivot table will index on the Ticker and Acquisition Date, and find the max adjusted close.\n",
    "\n",
    "adj_close_pivot = adj_close_acq_date_modified.pivot_table(index=['Ticker', 'Acquisition Date'], values='Adj Close', aggfunc=np.max)\n",
    "\n",
    "adj_close_pivot.reset_index(inplace=True)\n",
    "\n",
    "adj_close_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\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>Acquisition Date</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>2018-03-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FB</td>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>193.089996</td>\n",
       "      <td>2018-02-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>147.197433</td>\n",
       "      <td>2018-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>177.238724</td>\n",
       "      <td>2018-01-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2018-03-09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date   Adj Close       Date\n",
       "0   AAPL       2013-02-07  179.979996 2018-03-09\n",
       "1     FB       2013-12-13  193.089996 2018-02-01\n",
       "2    JNJ       2014-02-27  147.197433 2018-01-22\n",
       "3    MCD       2013-06-04  177.238724 2018-01-26\n",
       "4   MTCH       2015-12-14   44.790001 2018-03-09"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the adj close pivot table with the adj_close table in order to grab the date of the Adj Close High (good to know).\n",
    "\n",
    "adj_close_pivot_merged = pd.merge(adj_close_pivot, adj_close\n",
    "                                             , on=['Ticker', 'Adj Close'])\n",
    "\n",
    "adj_close_pivot_merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr 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>Ticker</th>\n",
       "      <th>Acquisition Date</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Unit Cost</th>\n",
       "      <th>Cost Basis</th>\n",
       "      <th>Start of Year</th>\n",
       "      <th>Latest Date</th>\n",
       "      <th>Ticker Adj Close</th>\n",
       "      <th>ticker return</th>\n",
       "      <th>SP 500 Initial Close</th>\n",
       "      <th>...</th>\n",
       "      <th>SP Start Year Close</th>\n",
       "      <th>Share YTD</th>\n",
       "      <th>SP 500 YTD</th>\n",
       "      <th>Cum Invst</th>\n",
       "      <th>Cum Ticker Returns</th>\n",
       "      <th>Cum SP Returns</th>\n",
       "      <th>Cum Ticker ROI Mult</th>\n",
       "      <th>Closing High Adj Close</th>\n",
       "      <th>Closing High Adj Close Date</th>\n",
       "      <th>Pct off High</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2013-02-07</td>\n",
       "      <td>125</td>\n",
       "      <td>65.40</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>1.751988</td>\n",
       "      <td>1509.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.067859</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>8175.00</td>\n",
       "      <td>22497.499500</td>\n",
       "      <td>15092.328742</td>\n",
       "      <td>2.751988</td>\n",
       "      <td>179.979996</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FB</td>\n",
       "      <td>2013-12-13</td>\n",
       "      <td>150</td>\n",
       "      <td>53.32</td>\n",
       "      <td>7998.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>185.229996</td>\n",
       "      <td>2.473931</td>\n",
       "      <td>1775.319946</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.049700</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>16173.00</td>\n",
       "      <td>50281.998900</td>\n",
       "      <td>27646.115147</td>\n",
       "      <td>3.109009</td>\n",
       "      <td>193.089996</td>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>-0.040706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>JNJ</td>\n",
       "      <td>2014-02-27</td>\n",
       "      <td>100</td>\n",
       "      <td>81.90</td>\n",
       "      <td>8190.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>133.800003</td>\n",
       "      <td>0.633700</td>\n",
       "      <td>1854.290039</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.036238</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>24363.00</td>\n",
       "      <td>63661.999200</td>\n",
       "      <td>39953.795379</td>\n",
       "      <td>2.613061</td>\n",
       "      <td>147.197433</td>\n",
       "      <td>2018-01-22</td>\n",
       "      <td>-0.091017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MCD</td>\n",
       "      <td>2013-06-04</td>\n",
       "      <td>100</td>\n",
       "      <td>84.99</td>\n",
       "      <td>8499.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>157.240005</td>\n",
       "      <td>0.850100</td>\n",
       "      <td>1631.380005</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.080672</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>32862.00</td>\n",
       "      <td>79385.999700</td>\n",
       "      <td>54470.988759</td>\n",
       "      <td>2.415739</td>\n",
       "      <td>177.238724</td>\n",
       "      <td>2018-01-26</td>\n",
       "      <td>-0.112835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MTCH</td>\n",
       "      <td>2015-12-14</td>\n",
       "      <td>600</td>\n",
       "      <td>13.63</td>\n",
       "      <td>8178.00</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2.286134</td>\n",
       "      <td>2021.939941</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.430533</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>41040.00</td>\n",
       "      <td>106260.000300</td>\n",
       "      <td>65741.635109</td>\n",
       "      <td>2.589181</td>\n",
       "      <td>44.790001</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NFLX</td>\n",
       "      <td>2016-01-14</td>\n",
       "      <td>75</td>\n",
       "      <td>108.71</td>\n",
       "      <td>8153.25</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2.048846</td>\n",
       "      <td>1921.839966</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.726610</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>49193.25</td>\n",
       "      <td>131118.000450</td>\n",
       "      <td>77563.432349</td>\n",
       "      <td>2.665366</td>\n",
       "      <td>331.440002</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>TWTR</td>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>225</td>\n",
       "      <td>36.38</td>\n",
       "      <td>8185.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>35.349998</td>\n",
       "      <td>-0.028312</td>\n",
       "      <td>2020.579956</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>0.472303</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>57378.75</td>\n",
       "      <td>139071.750000</td>\n",
       "      <td>88852.007802</td>\n",
       "      <td>2.423750</td>\n",
       "      <td>52.869999</td>\n",
       "      <td>2015-04-07</td>\n",
       "      <td>-0.331379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>WMT</td>\n",
       "      <td>2013-08-14</td>\n",
       "      <td>125</td>\n",
       "      <td>68.30</td>\n",
       "      <td>8537.50</td>\n",
       "      <td>2017-12-29</td>\n",
       "      <td>2018-03-09</td>\n",
       "      <td>88.720001</td>\n",
       "      <td>0.298975</td>\n",
       "      <td>1685.390015</td>\n",
       "      <td>...</td>\n",
       "      <td>2673.610107</td>\n",
       "      <td>-0.096213</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>65916.25</td>\n",
       "      <td>150161.750125</td>\n",
       "      <td>102967.637860</td>\n",
       "      <td>2.278069</td>\n",
       "      <td>108.900742</td>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>-0.185313</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticker Acquisition Date  Quantity  Unit Cost  Cost Basis Start of Year  \\\n",
       "0   AAPL       2013-02-07       125      65.40     8175.00    2017-12-29   \n",
       "1     FB       2013-12-13       150      53.32     7998.00    2017-12-29   \n",
       "2    JNJ       2014-02-27       100      81.90     8190.00    2017-12-29   \n",
       "3    MCD       2013-06-04       100      84.99     8499.00    2017-12-29   \n",
       "4   MTCH       2015-12-14       600      13.63     8178.00    2017-12-29   \n",
       "5   NFLX       2016-01-14        75     108.71     8153.25    2017-12-29   \n",
       "6   TWTR       2015-01-05       225      36.38     8185.50    2017-12-29   \n",
       "7    WMT       2013-08-14       125      68.30     8537.50    2017-12-29   \n",
       "\n",
       "  Latest Date  Ticker Adj Close  ticker return  SP 500 Initial Close  \\\n",
       "0  2018-03-09        179.979996       1.751988           1509.390015   \n",
       "1  2018-03-09        185.229996       2.473931           1775.319946   \n",
       "2  2018-03-09        133.800003       0.633700           1854.290039   \n",
       "3  2018-03-09        157.240005       0.850100           1631.380005   \n",
       "4  2018-03-09         44.790001       2.286134           2021.939941   \n",
       "5  2018-03-09        331.440002       2.048846           1921.839966   \n",
       "6  2018-03-09         35.349998      -0.028312           2020.579956   \n",
       "7  2018-03-09         88.720001       0.298975           1685.390015   \n",
       "\n",
       "       ...       SP Start Year Close  Share YTD  SP 500 YTD  Cum Invst  \\\n",
       "0      ...               2673.610107   0.067859     0.04225    8175.00   \n",
       "1      ...               2673.610107   0.049700     0.04225   16173.00   \n",
       "2      ...               2673.610107  -0.036238     0.04225   24363.00   \n",
       "3      ...               2673.610107  -0.080672     0.04225   32862.00   \n",
       "4      ...               2673.610107   0.430533     0.04225   41040.00   \n",
       "5      ...               2673.610107   0.726610     0.04225   49193.25   \n",
       "6      ...               2673.610107   0.472303     0.04225   57378.75   \n",
       "7      ...               2673.610107  -0.096213     0.04225   65916.25   \n",
       "\n",
       "   Cum Ticker Returns  Cum SP Returns  Cum Ticker ROI Mult  \\\n",
       "0        22497.499500    15092.328742             2.751988   \n",
       "1        50281.998900    27646.115147             3.109009   \n",
       "2        63661.999200    39953.795379             2.613061   \n",
       "3        79385.999700    54470.988759             2.415739   \n",
       "4       106260.000300    65741.635109             2.589181   \n",
       "5       131118.000450    77563.432349             2.665366   \n",
       "6       139071.750000    88852.007802             2.423750   \n",
       "7       150161.750125   102967.637860             2.278069   \n",
       "\n",
       "   Closing High Adj Close  Closing High Adj Close Date  Pct off High  \n",
       "0              179.979996                   2018-03-09      0.000000  \n",
       "1              193.089996                   2018-02-01     -0.040706  \n",
       "2              147.197433                   2018-01-22     -0.091017  \n",
       "3              177.238724                   2018-01-26     -0.112835  \n",
       "4               44.790001                   2018-03-09      0.000000  \n",
       "5              331.440002                   2018-03-09      0.000000  \n",
       "6               52.869999                   2015-04-07     -0.331379  \n",
       "7              108.900742                   2018-01-29     -0.185313  \n",
       "\n",
       "[8 rows x 30 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Merge the Adj Close pivot table with the master dataframe to have the closing high since you have owned the stock.\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp_closing_high = pd.merge(merged_portfolio_sp_latest_YTD_sp, adj_close_pivot_merged\n",
    "                                             , on=['Ticker', 'Acquisition Date'])\n",
    "\n",
    "# Renaming so that it's clear that the new columns are two year closing high and two year closing high date.\n",
    "merged_portfolio_sp_latest_YTD_sp_closing_high.rename(columns={'Adj Close': 'Closing High Adj Close', 'Date': 'Closing High Adj Close Date'}, inplace=True)\n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp_closing_high['Pct off High'] = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker Adj Close'] / merged_portfolio_sp_latest_YTD_sp_closing_high['Closing High Adj Close'] - 1 \n",
    "\n",
    "merged_portfolio_sp_latest_YTD_sp_closing_high"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Not needed for this blog post -- this is if you have multiple positions for the same ticker with different acquisition dates.\n",
    "# merged_portfolio_sp_latest_YTD_sp_closing_high['Counts'] = merged_portfolio_sp_latest_YTD_sp_closing_high.index\n",
    "\n",
    "# merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker #'] = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'].map(str) + ' ' + merged_portfolio_sp_latest_YTD_sp_closing_high['Counts'].map(str)\n",
    "\n",
    "# merged_portfolio_sp_latest_YTD_sp_closing_high.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## YTD and Trailing Stop Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "name": "Ticker YTD",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          0.0678591010495131,
          0.04969958433697652,
          -0.036238344993948624,
          -0.08067182798128625,
          0.43053345354626193,
          0.7266096578127337,
          0.47230312369845895,
          -0.09621323434545737
         ]
        },
        {
         "name": "SP500 YTD",
         "type": "scatter",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          0.04224997530651531,
          0.04224997530651531,
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          0.04224997530651531,
          0.04224997530651531,
          0.04224997530651531
         ]
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "x": 0.8,
         "y": 1
        },
        "title": "YTD Return vs S&P 500 YTD",
        "xaxis": {
         "title": "Ticker"
        },
        "yaxis": {
         "tickformat": ".2%",
         "title": "Returns"
        }
       }
      },
      "text/html": [
       "<div id=\"5af40a2f-ec35-4a3b-852d-02f6a55166b3\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"5af40a2f-ec35-4a3b-852d-02f6a55166b3\", [{\"y\": [0.0678591010495131, 0.04969958433697652, -0.036238344993948624, -0.08067182798128625, 0.43053345354626193, 0.7266096578127337, 0.47230312369845895, -0.09621323434545737], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker YTD\"}, {\"y\": [0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"SP500 YTD\"}], {\"barmode\": \"group\", \"title\": \"YTD Return vs S&P 500 YTD\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"Returns\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"5af40a2f-ec35-4a3b-852d-02f6a55166b3\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"5af40a2f-ec35-4a3b-852d-02f6a55166b3\", [{\"y\": [0.0678591010495131, 0.04969958433697652, -0.036238344993948624, -0.08067182798128625, 0.43053345354626193, 0.7266096578127337, 0.47230312369845895, -0.09621323434545737], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker YTD\"}, {\"y\": [0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531, 0.04224997530651531], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"SP500 YTD\"}], {\"barmode\": \"group\", \"title\": \"YTD Return vs S&P 500 YTD\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"Returns\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ploty is an outstanding resource for interactive charts.\n",
    "\n",
    "trace1 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp['Share YTD'][0:10],\n",
    "    name = 'Ticker YTD')\n",
    "\n",
    "trace2 = go.Scatter(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp['SP 500 YTD'][0:10],\n",
    "    name = 'SP500 YTD')\n",
    "    \n",
    "data = [trace1, trace2]\n",
    "\n",
    "layout = go.Layout(title = 'YTD Return vs S&P 500 YTD'\n",
    "    , barmode = 'group'\n",
    "    , yaxis=dict(title='Returns', tickformat=\".2%\")\n",
    "    , xaxis=dict(title='Ticker')\n",
    "    , legend=dict(x=.8,y=1)\n",
    "    )\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "name": "Pct off High",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          0,
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         ]
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "x": 0.8,
         "y": 1
        },
        "title": "Adj Close % off of High",
        "xaxis": {
         "title": "Ticker"
        },
        "yaxis": {
         "tickformat": ".2%",
         "title": "% Below Adj Close High"
        }
       }
      },
      "text/html": [
       "<div id=\"4e7e93ef-5a27-451e-9134-c689a12057bf\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"4e7e93ef-5a27-451e-9134-c689a12057bf\", [{\"y\": [0.0, -0.040706407182275695, -0.09101673668453181, -0.11283492991068922, 0.0, 0.0, -0.3313788789744445, -0.18531316343097093], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Pct off High\"}], {\"barmode\": \"group\", \"title\": \"Adj Close % off of High\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"% Below Adj Close High\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"4e7e93ef-5a27-451e-9134-c689a12057bf\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"4e7e93ef-5a27-451e-9134-c689a12057bf\", [{\"y\": [0.0, -0.040706407182275695, -0.09101673668453181, -0.11283492991068922, 0.0, 0.0, -0.3313788789744445, -0.18531316343097093], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Pct off High\"}], {\"barmode\": \"group\", \"title\": \"Adj Close % off of High\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"% Below Adj Close High\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "# Current Share Price versus Closing High Since Purchased\n",
    "\n",
    "trace1 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Pct off High'][0:10],\n",
    "    name = 'Pct off High')\n",
    "    \n",
    "data = [trace1]\n",
    "\n",
    "layout = go.Layout(title = 'Adj Close % off of High'\n",
    "    , barmode = 'group'\n",
    "    , yaxis=dict(title='% Below Adj Close High', tickformat=\".2%\")\n",
    "    , xaxis=dict(title='Ticker')\n",
    "    , legend=dict(x=.8,y=1)\n",
    "    )\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total Return Comparison Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "name": "Ticker Total Return",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          1.751987706422018,
          2.4739309077269316,
          0.6336996703296702,
          0.8501000705965409,
          2.2861336023477623,
          2.0488455707846565,
          -0.028312314458493804,
          0.29897512445095176
         ]
        },
        {
         "name": "SP500 Total Return",
         "type": "scatter",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          0.8461564210095824,
          0.56961570463874,
          0.5027692590651942,
          0.7081060571169622,
          0.3781665871943918,
          0.44994906823578873,
          0.37909418517462523,
          0.6533680888099958
         ]
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "x": 0.8,
         "y": 1
        },
        "title": "Total Return vs S&P 500",
        "xaxis": {
         "tickformat": ".2%",
         "title": "Ticker"
        },
        "yaxis": {
         "tickformat": ".2%",
         "title": "Returns"
        }
       }
      },
      "text/html": [
       "<div id=\"8d8f6df9-f82d-4700-9ed5-f41dd9b98452\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"8d8f6df9-f82d-4700-9ed5-f41dd9b98452\", [{\"y\": [1.751987706422018, 2.4739309077269316, 0.6336996703296702, 0.8501000705965409, 2.2861336023477623, 2.0488455707846565, -0.028312314458493804, 0.29897512445095176], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker Total Return\"}, {\"y\": [0.8461564210095824, 0.56961570463874, 0.5027692590651942, 0.7081060571169622, 0.3781665871943918, 0.44994906823578873, 0.37909418517462523, 0.6533680888099958], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"SP500 Total Return\"}], {\"barmode\": \"group\", \"title\": \"Total Return vs S&P 500\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"tickformat\": \".2%\", \"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"Returns\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"8d8f6df9-f82d-4700-9ed5-f41dd9b98452\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"8d8f6df9-f82d-4700-9ed5-f41dd9b98452\", [{\"y\": [1.751987706422018, 2.4739309077269316, 0.6336996703296702, 0.8501000705965409, 2.2861336023477623, 2.0488455707846565, -0.028312314458493804, 0.29897512445095176], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker Total Return\"}, {\"y\": [0.8461564210095824, 0.56961570463874, 0.5027692590651942, 0.7081060571169622, 0.3781665871943918, 0.44994906823578873, 0.37909418517462523, 0.6533680888099958], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"SP500 Total Return\"}], {\"barmode\": \"group\", \"title\": \"Total Return vs S&P 500\", \"legend\": {\"y\": 1, \"x\": 0.8}, \"xaxis\": {\"tickformat\": \".2%\", \"title\": \"Ticker\"}, \"yaxis\": {\"tickformat\": \".2%\", \"title\": \"Returns\"}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace1 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['ticker return'][0:10],\n",
    "    name = 'Ticker Total Return')\n",
    "\n",
    "trace2 = go.Scatter(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['SP Return'][0:10],\n",
    "    name = 'SP500 Total Return')\n",
    "    \n",
    "data = [trace1, trace2]\n",
    "\n",
    "layout = go.Layout(title = 'Total Return vs S&P 500'\n",
    "    , barmode = 'group'\n",
    "    , yaxis=dict(title='Returns', tickformat=\".2%\")\n",
    "    , xaxis=dict(title='Ticker', tickformat=\".2%\")\n",
    "    , legend=dict(x=.8,y=1)\n",
    "    )\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Cumulative Returns Over Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "name": "Ticker Total Return ($)",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          14322.499500000002,
          19786.4994,
          5190.000299999999,
          7225.0005,
          18696.000600000003,
          16704.75015,
          -231.75045000000136,
          2552.5001249999987
         ]
        },
        {
         "name": "SP 500 Total Return ($)",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          6917.3287417533365,
          4555.786405700643,
          4117.680231743942,
          6018.193379437062,
          3092.6463500757372,
          3668.5472405934443,
          3103.075452746897,
          5578.130058215338
         ]
        },
        {
         "name": "Ticker Total Return %",
         "type": "scatter",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          1.751987706422018,
          2.4739309077269316,
          0.6336996703296702,
          0.8501000705965409,
          2.2861336023477623,
          2.0488455707846565,
          -0.028312314458493804,
          0.29897512445095176
         ],
         "yaxis": "y2"
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "x": 0.75,
         "y": 1
        },
        "title": "Gain / (Loss) Total Return vs S&P 500",
        "xaxis": {
         "title": "Ticker"
        },
        "yaxis": {
         "title": "Gain / (Loss) ($)"
        },
        "yaxis2": {
         "overlaying": "y",
         "side": "right",
         "tickformat": ".2%",
         "title": "Ticker Return"
        }
       }
      },
      "text/html": [
       "<div id=\"53942214-c05d-475f-8190-4b90a7bd9dd7\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"53942214-c05d-475f-8190-4b90a7bd9dd7\", [{\"y\": [14322.499500000002, 19786.4994, 5190.000299999999, 7225.0005, 18696.000600000003, 16704.75015, -231.75045000000136, 2552.5001249999987], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker Total Return ($)\"}, {\"y\": [6917.3287417533365, 4555.786405700643, 4117.680231743942, 6018.193379437062, 3092.6463500757372, 3668.5472405934443, 3103.075452746897, 5578.130058215338], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"SP 500 Total Return ($)\"}, {\"y\": [1.751987706422018, 2.4739309077269316, 0.6336996703296702, 0.8501000705965409, 2.2861336023477623, 2.0488455707846565, -0.028312314458493804, 0.29897512445095176], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"Ticker Total Return %\", \"yaxis\": \"y2\"}], {\"title\": \"Gain / (Loss) Total Return vs S&P 500\", \"yaxis\": {\"title\": \"Gain / (Loss) ($)\"}, \"barmode\": \"group\", \"yaxis2\": {\"overlaying\": \"y\", \"tickformat\": \".2%\", \"side\": \"right\", \"title\": \"Ticker Return\"}, \"xaxis\": {\"title\": \"Ticker\"}, \"legend\": {\"y\": 1, \"x\": 0.75}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"53942214-c05d-475f-8190-4b90a7bd9dd7\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"53942214-c05d-475f-8190-4b90a7bd9dd7\", [{\"y\": [14322.499500000002, 19786.4994, 5190.000299999999, 7225.0005, 18696.000600000003, 16704.75015, -231.75045000000136, 2552.5001249999987], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Ticker Total Return ($)\"}, {\"y\": [6917.3287417533365, 4555.786405700643, 4117.680231743942, 6018.193379437062, 3092.6463500757372, 3668.5472405934443, 3103.075452746897, 5578.130058215338], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"SP 500 Total Return ($)\"}, {\"y\": [1.751987706422018, 2.4739309077269316, 0.6336996703296702, 0.8501000705965409, 2.2861336023477623, 2.0488455707846565, -0.028312314458493804, 0.29897512445095176], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"Ticker Total Return %\", \"yaxis\": \"y2\"}], {\"title\": \"Gain / (Loss) Total Return vs S&P 500\", \"yaxis\": {\"title\": \"Gain / (Loss) ($)\"}, \"barmode\": \"group\", \"yaxis2\": {\"overlaying\": \"y\", \"tickformat\": \".2%\", \"side\": \"right\", \"title\": \"Ticker Return\"}, \"xaxis\": {\"title\": \"Ticker\"}, \"legend\": {\"y\": 1, \"x\": 0.75}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace1 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Stock Gain / (Loss)'][0:10],\n",
    "    name = 'Ticker Total Return ($)')\n",
    "\n",
    "trace2 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['SP 500 Gain / (Loss)'][0:10],\n",
    "    name = 'SP 500 Total Return ($)')\n",
    "\n",
    "trace3 = go.Scatter(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'][0:10],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['ticker return'][0:10],\n",
    "    name = 'Ticker Total Return %',\n",
    "    yaxis='y2')\n",
    "\n",
    "data = [trace1, trace2, trace3]\n",
    "\n",
    "layout = go.Layout(title = 'Gain / (Loss) Total Return vs S&P 500'\n",
    "    , barmode = 'group'\n",
    "    , yaxis=dict(title='Gain / (Loss) ($)')\n",
    "    , yaxis2=dict(title='Ticker Return', overlaying='y', side='right', tickformat=\".2%\")\n",
    "    , xaxis=dict(title='Ticker')\n",
    "    , legend=dict(x=.75,y=1)\n",
    "    )\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "name": "Cum Invst",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          8175.000000000001,
          16173,
          24363,
          32862,
          41040,
          49193.25,
          57378.75,
          65916.25
         ]
        },
        {
         "name": "Cum SP500 Returns",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          15092.328741753337,
          27646.11514745398,
          39953.79537919792,
          54470.98875863499,
          65741.63510871073,
          77563.43234930417,
          88852.00780205107,
          102967.6378602664
         ]
        },
        {
         "name": "Cum Ticker Returns",
         "type": "bar",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          22497.4995,
          50281.998900000006,
          63661.999200000006,
          79385.9997,
          106260.0003,
          131118.00045,
          139071.75,
          150161.750125
         ]
        },
        {
         "name": "Cum ROI Mult",
         "type": "scatter",
         "x": [
          "AAPL",
          "FB",
          "JNJ",
          "MCD",
          "MTCH",
          "NFLX",
          "TWTR",
          "WMT"
         ],
         "y": [
          2.7519877064220184,
          3.109008773882397,
          2.6130607560645243,
          2.415738533868906,
          2.589181293859649,
          2.6653656843164457,
          2.4237500816940067,
          2.2780687633929415
         ],
         "yaxis": "y2"
        }
       ],
       "layout": {
        "barmode": "group",
        "legend": {
         "x": 0.4,
         "y": 1
        },
        "title": "Total Cumulative Investments Over Time",
        "xaxis": {
         "title": "Ticker"
        },
        "yaxis": {
         "title": "Returns"
        },
        "yaxis2": {
         "overlaying": "y",
         "side": "right",
         "title": "Cum ROI Mult"
        }
       }
      },
      "text/html": [
       "<div id=\"e9b7b83a-2fc4-4e97-9bb6-b4ee168723ea\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"e9b7b83a-2fc4-4e97-9bb6-b4ee168723ea\", [{\"y\": [8175.000000000001, 16173.0, 24363.0, 32862.0, 41040.0, 49193.25, 57378.75, 65916.25], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum Invst\"}, {\"y\": [15092.328741753337, 27646.11514745398, 39953.79537919792, 54470.98875863499, 65741.63510871073, 77563.43234930417, 88852.00780205107, 102967.6378602664], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum SP500 Returns\"}, {\"y\": [22497.4995, 50281.998900000006, 63661.999200000006, 79385.9997, 106260.0003, 131118.00045, 139071.75, 150161.750125], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum Ticker Returns\"}, {\"y\": [2.7519877064220184, 3.109008773882397, 2.6130607560645243, 2.415738533868906, 2.589181293859649, 2.6653656843164457, 2.4237500816940067, 2.2780687633929415], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"Cum ROI Mult\", \"yaxis\": \"y2\"}], {\"title\": \"Total Cumulative Investments Over Time\", \"yaxis\": {\"title\": \"Returns\"}, \"barmode\": \"group\", \"yaxis2\": {\"overlaying\": \"y\", \"side\": \"right\", \"title\": \"Cum ROI Mult\"}, \"xaxis\": {\"title\": \"Ticker\"}, \"legend\": {\"y\": 1, \"x\": 0.4}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"e9b7b83a-2fc4-4e97-9bb6-b4ee168723ea\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"e9b7b83a-2fc4-4e97-9bb6-b4ee168723ea\", [{\"y\": [8175.000000000001, 16173.0, 24363.0, 32862.0, 41040.0, 49193.25, 57378.75, 65916.25], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum Invst\"}, {\"y\": [15092.328741753337, 27646.11514745398, 39953.79537919792, 54470.98875863499, 65741.63510871073, 77563.43234930417, 88852.00780205107, 102967.6378602664], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum SP500 Returns\"}, {\"y\": [22497.4995, 50281.998900000006, 63661.999200000006, 79385.9997, 106260.0003, 131118.00045, 139071.75, 150161.750125], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"bar\", \"name\": \"Cum Ticker Returns\"}, {\"y\": [2.7519877064220184, 3.109008773882397, 2.6130607560645243, 2.415738533868906, 2.589181293859649, 2.6653656843164457, 2.4237500816940067, 2.2780687633929415], \"x\": [\"AAPL\", \"FB\", \"JNJ\", \"MCD\", \"MTCH\", \"NFLX\", \"TWTR\", \"WMT\"], \"type\": \"scatter\", \"name\": \"Cum ROI Mult\", \"yaxis\": \"y2\"}], {\"title\": \"Total Cumulative Investments Over Time\", \"yaxis\": {\"title\": \"Returns\"}, \"barmode\": \"group\", \"yaxis2\": {\"overlaying\": \"y\", \"side\": \"right\", \"title\": \"Cum ROI Mult\"}, \"xaxis\": {\"title\": \"Ticker\"}, \"legend\": {\"y\": 1, \"x\": 0.4}}, {\"linkText\": \"Export to plot.ly\", \"showLink\": true})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace1 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Cum Invst'],\n",
    "    # mode = 'lines+markers',\n",
    "    name = 'Cum Invst')\n",
    "\n",
    "trace2 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Cum SP Returns'],\n",
    "    # mode = 'lines+markers',\n",
    "    name = 'Cum SP500 Returns')\n",
    "\n",
    "trace3 = go.Bar(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Cum Ticker Returns'],\n",
    "    # mode = 'lines+markers',\n",
    "    name = 'Cum Ticker Returns')\n",
    "\n",
    "trace4 = go.Scatter(\n",
    "    x = merged_portfolio_sp_latest_YTD_sp_closing_high['Ticker'],\n",
    "    y = merged_portfolio_sp_latest_YTD_sp_closing_high['Cum Ticker ROI Mult'],\n",
    "    # mode = 'lines+markers',\n",
    "    name = 'Cum ROI Mult'\n",
    "    , yaxis='y2')\n",
    "\n",
    "\n",
    "data = [trace1, trace2, trace3, trace4]\n",
    "\n",
    "layout = go.Layout(title = 'Total Cumulative Investments Over Time'\n",
    "    , barmode = 'group'\n",
    "    , yaxis=dict(title='Returns')\n",
    "    , xaxis=dict(title='Ticker')\n",
    "    , legend=dict(x=.4,y=1)\n",
    "    , yaxis2=dict(title='Cum ROI Mult', overlaying='y', side='right')               \n",
    "    )\n",
    "\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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