z_score_dev.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CB: Altman's z-score is based on Fisher's discriminant analysis (linear classifier/separator).  (See e.g. wiki)\n",
    "# It is used as an indicator for financial health, or as a determiner of likelihood of bankruptcy.\n",
    "# It is a weighted linear combination of factors.  We can construct many such scores.\n",
    "# The weights can be calculated by past scores of businesses which did or did not go bankrupt.\n",
    "# Thus, industry-specific scores may be appropriate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We can use data from yfinance\n",
    "import yfinance as yf\n",
    "from pandas import DataFrame as df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "tick = yf.Ticker('GME')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Dividends</th>\n",
       "      <th>Stock Splits</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-04-25</th>\n",
       "      <td>135.410004</td>\n",
       "      <td>139.710007</td>\n",
       "      <td>133.279999</td>\n",
       "      <td>135.949997</td>\n",
       "      <td>1534800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-26</th>\n",
       "      <td>135.639999</td>\n",
       "      <td>136.800003</td>\n",
       "      <td>126.160004</td>\n",
       "      <td>127.599998</td>\n",
       "      <td>1545700</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-27</th>\n",
       "      <td>127.269997</td>\n",
       "      <td>132.679993</td>\n",
       "      <td>124.580002</td>\n",
       "      <td>129.839996</td>\n",
       "      <td>1305900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>130.279999</td>\n",
       "      <td>132.600006</td>\n",
       "      <td>120.500000</td>\n",
       "      <td>129.309998</td>\n",
       "      <td>1767500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-29</th>\n",
       "      <td>127.300003</td>\n",
       "      <td>130.889999</td>\n",
       "      <td>123.010002</td>\n",
       "      <td>125.070000</td>\n",
       "      <td>1284200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-05-02</th>\n",
       "      <td>123.650002</td>\n",
       "      <td>125.389999</td>\n",
       "      <td>112.699997</td>\n",
       "      <td>119.570000</td>\n",
       "      <td>2543000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-03</th>\n",
       "      <td>118.480003</td>\n",
       "      <td>124.430000</td>\n",
       "      <td>114.419998</td>\n",
       "      <td>120.430000</td>\n",
       "      <td>1828200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-04</th>\n",
       "      <td>119.209999</td>\n",
       "      <td>127.750000</td>\n",
       "      <td>115.720001</td>\n",
       "      <td>127.080002</td>\n",
       "      <td>1662800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-05</th>\n",
       "      <td>123.940002</td>\n",
       "      <td>124.680000</td>\n",
       "      <td>115.120003</td>\n",
       "      <td>119.129997</td>\n",
       "      <td>1753900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-06</th>\n",
       "      <td>117.279999</td>\n",
       "      <td>120.559998</td>\n",
       "      <td>110.230003</td>\n",
       "      <td>114.699997</td>\n",
       "      <td>1786800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-09</th>\n",
       "      <td>110.779999</td>\n",
       "      <td>110.779999</td>\n",
       "      <td>98.080002</td>\n",
       "      <td>98.790001</td>\n",
       "      <td>3316200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-10</th>\n",
       "      <td>102.980003</td>\n",
       "      <td>106.059998</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>93.500000</td>\n",
       "      <td>4150800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-11</th>\n",
       "      <td>93.470001</td>\n",
       "      <td>95.269997</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>81.330002</td>\n",
       "      <td>4170300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-12</th>\n",
       "      <td>83.040001</td>\n",
       "      <td>108.059998</td>\n",
       "      <td>77.769997</td>\n",
       "      <td>89.570000</td>\n",
       "      <td>10034900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-05-13</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>106.779999</td>\n",
       "      <td>95.040001</td>\n",
       "      <td>98.389999</td>\n",
       "      <td>5974000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-16</th>\n",
       "      <td>98.800003</td>\n",
       "      <td>99.180000</td>\n",
       "      <td>90.779999</td>\n",
       "      <td>91.800003</td>\n",
       "      <td>2895500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-17</th>\n",
       "      <td>93.900002</td>\n",
       "      <td>100.379997</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>100.379997</td>\n",
       "      <td>2611200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-18</th>\n",
       "      <td>96.379997</td>\n",
       "      <td>99.839996</td>\n",
       "      <td>90.169998</td>\n",
       "      <td>91.480003</td>\n",
       "      <td>2890000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-19</th>\n",
       "      <td>91.220001</td>\n",
       "      <td>101.980003</td>\n",
       "      <td>90.160004</td>\n",
       "      <td>99.190002</td>\n",
       "      <td>3180100</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-20</th>\n",
       "      <td>99.809998</td>\n",
       "      <td>102.410004</td>\n",
       "      <td>89.750000</td>\n",
       "      <td>95.660004</td>\n",
       "      <td>2488100</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-23</th>\n",
       "      <td>96.570000</td>\n",
       "      <td>97.279999</td>\n",
       "      <td>91.500000</td>\n",
       "      <td>96.129997</td>\n",
       "      <td>1748500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-24</th>\n",
       "      <td>94.050003</td>\n",
       "      <td>94.139999</td>\n",
       "      <td>86.699997</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>2192496</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                  Open        High         Low       Close    Volume  \\\n",
       "Date                                                                   \n",
       "2022-04-25  135.410004  139.710007  133.279999  135.949997   1534800   \n",
       "2022-04-26  135.639999  136.800003  126.160004  127.599998   1545700   \n",
       "2022-04-27  127.269997  132.679993  124.580002  129.839996   1305900   \n",
       "2022-04-28  130.279999  132.600006  120.500000  129.309998   1767500   \n",
       "2022-04-29  127.300003  130.889999  123.010002  125.070000   1284200   \n",
       "2022-05-02  123.650002  125.389999  112.699997  119.570000   2543000   \n",
       "2022-05-03  118.480003  124.430000  114.419998  120.430000   1828200   \n",
       "2022-05-04  119.209999  127.750000  115.720001  127.080002   1662800   \n",
       "2022-05-05  123.940002  124.680000  115.120003  119.129997   1753900   \n",
       "2022-05-06  117.279999  120.559998  110.230003  114.699997   1786800   \n",
       "2022-05-09  110.779999  110.779999   98.080002   98.790001   3316200   \n",
       "2022-05-10  102.980003  106.059998   88.000000   93.500000   4150800   \n",
       "2022-05-11   93.470001   95.269997   80.000000   81.330002   4170300   \n",
       "2022-05-12   83.040001  108.059998   77.769997   89.570000  10034900   \n",
       "2022-05-13   99.000000  106.779999   95.040001   98.389999   5974000   \n",
       "2022-05-16   98.800003   99.180000   90.779999   91.800003   2895500   \n",
       "2022-05-17   93.900002  100.379997   91.199997  100.379997   2611200   \n",
       "2022-05-18   96.379997   99.839996   90.169998   91.480003   2890000   \n",
       "2022-05-19   91.220001  101.980003   90.160004   99.190002   3180100   \n",
       "2022-05-20   99.809998  102.410004   89.750000   95.660004   2488100   \n",
       "2022-05-23   96.570000   97.279999   91.500000   96.129997   1748500   \n",
       "2022-05-24   94.050003   94.139999   86.699997   89.150002   2192496   \n",
       "\n",
       "            Dividends  Stock Splits  \n",
       "Date                                 \n",
       "2022-04-25          0             0  \n",
       "2022-04-26          0             0  \n",
       "2022-04-27          0             0  \n",
       "2022-04-28          0             0  \n",
       "2022-04-29          0             0  \n",
       "2022-05-02          0             0  \n",
       "2022-05-03          0             0  \n",
       "2022-05-04          0             0  \n",
       "2022-05-05          0             0  \n",
       "2022-05-06          0             0  \n",
       "2022-05-09          0             0  \n",
       "2022-05-10          0             0  \n",
       "2022-05-11          0             0  \n",
       "2022-05-12          0             0  \n",
       "2022-05-13          0             0  \n",
       "2022-05-16          0             0  \n",
       "2022-05-17          0             0  \n",
       "2022-05-18          0             0  \n",
       "2022-05-19          0             0  \n",
       "2022-05-20          0             0  \n",
       "2022-05-23          0             0  \n",
       "2022-05-24          0             0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tick.history()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yfinance.Ticker object <GME>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tick"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2022-01-29</th>\n",
       "      <th>2021-01-30</th>\n",
       "      <th>2020-02-01</th>\n",
       "      <th>2019-02-02</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Capital Surplus</th>\n",
       "      <td>1.577500e+09</td>\n",
       "      <td>1.100000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.770000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Liab</th>\n",
       "      <td>1.896800e+09</td>\n",
       "      <td>2.035900e+09</td>\n",
       "      <td>2.208200e+09</td>\n",
       "      <td>2.708100e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Stockholder Equity</th>\n",
       "      <td>1.602500e+09</td>\n",
       "      <td>4.367000e+08</td>\n",
       "      <td>6.115000e+08</td>\n",
       "      <td>1.336200e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Current Liab</th>\n",
       "      <td>4.262000e+08</td>\n",
       "      <td>4.252000e+08</td>\n",
       "      <td>4.230000e+08</td>\n",
       "      <td>5.495000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Assets</th>\n",
       "      <td>3.499300e+09</td>\n",
       "      <td>2.472600e+09</td>\n",
       "      <td>2.819700e+09</td>\n",
       "      <td>4.044300e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Common Stock</th>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>1.000000e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Current Assets</th>\n",
       "      <td>3.690000e+07</td>\n",
       "      <td>1.125000e+08</td>\n",
       "      <td>1.350000e+07</td>\n",
       "      <td>3.700000e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Retained Earnings</th>\n",
       "      <td>9.360000e+07</td>\n",
       "      <td>4.749000e+08</td>\n",
       "      <td>6.902000e+08</td>\n",
       "      <td>1.362700e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Liab</th>\n",
       "      <td>1.079000e+08</td>\n",
       "      <td>2.050000e+07</td>\n",
       "      <td>2.140000e+07</td>\n",
       "      <td>5.540000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Treasury Stock</th>\n",
       "      <td>-6.870000e+07</td>\n",
       "      <td>-4.930000e+07</td>\n",
       "      <td>-7.880000e+07</td>\n",
       "      <td>-5.430000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Assets</th>\n",
       "      <td>1.503000e+08</td>\n",
       "      <td>5.810000e+07</td>\n",
       "      <td>1.431000e+08</td>\n",
       "      <td>2.314000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cash</th>\n",
       "      <td>1.271400e+09</td>\n",
       "      <td>5.085000e+08</td>\n",
       "      <td>4.994000e+08</td>\n",
       "      <td>1.624400e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Current Liabilities</th>\n",
       "      <td>1.354700e+09</td>\n",
       "      <td>1.342700e+09</td>\n",
       "      <td>1.237700e+09</td>\n",
       "      <td>2.181100e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deferred Long Term Asset Charges</th>\n",
       "      <td>1.630000e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.300000e+07</td>\n",
       "      <td>1.473000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Short Long Term Debt</th>\n",
       "      <td>4.100000e+06</td>\n",
       "      <td>1.217000e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.492000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Stockholder Equity</th>\n",
       "      <td>-6.870000e+07</td>\n",
       "      <td>-4.930000e+07</td>\n",
       "      <td>-7.880000e+07</td>\n",
       "      <td>-5.430000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Property Plant Equipment</th>\n",
       "      <td>7.502000e+08</td>\n",
       "      <td>8.633000e+08</td>\n",
       "      <td>1.042900e+09</td>\n",
       "      <td>3.213000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Current Assets</th>\n",
       "      <td>2.598800e+09</td>\n",
       "      <td>1.551200e+09</td>\n",
       "      <td>1.633700e+09</td>\n",
       "      <td>3.127700e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Tangible Assets</th>\n",
       "      <td>1.602500e+09</td>\n",
       "      <td>4.367000e+08</td>\n",
       "      <td>6.115000e+08</td>\n",
       "      <td>9.723000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Receivables</th>\n",
       "      <td>3.097000e+08</td>\n",
       "      <td>1.081000e+08</td>\n",
       "      <td>2.084000e+08</td>\n",
       "      <td>1.342000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Long Term Debt</th>\n",
       "      <td>4.050000e+07</td>\n",
       "      <td>2.160000e+08</td>\n",
       "      <td>4.198000e+08</td>\n",
       "      <td>4.716000e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inventory</th>\n",
       "      <td>9.150000e+08</td>\n",
       "      <td>6.025000e+08</td>\n",
       "      <td>8.597000e+08</td>\n",
       "      <td>1.250500e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accounts Payable</th>\n",
       "      <td>4.710000e+08</td>\n",
       "      <td>3.418000e+08</td>\n",
       "      <td>3.808000e+08</td>\n",
       "      <td>1.051900e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intangible Assets</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.350000e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Good Will</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.639000e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    2022-01-29    2021-01-30    2020-02-01  \\\n",
       "Capital Surplus                   1.577500e+09  1.100000e+07           NaN   \n",
       "Total Liab                        1.896800e+09  2.035900e+09  2.208200e+09   \n",
       "Total Stockholder Equity          1.602500e+09  4.367000e+08  6.115000e+08   \n",
       "Other Current Liab                4.262000e+08  4.252000e+08  4.230000e+08   \n",
       "Total Assets                      3.499300e+09  2.472600e+09  2.819700e+09   \n",
       "Common Stock                      1.000000e+05  1.000000e+05  1.000000e+05   \n",
       "Other Current Assets              3.690000e+07  1.125000e+08  1.350000e+07   \n",
       "Retained Earnings                 9.360000e+07  4.749000e+08  6.902000e+08   \n",
       "Other Liab                        1.079000e+08  2.050000e+07  2.140000e+07   \n",
       "Treasury Stock                   -6.870000e+07 -4.930000e+07 -7.880000e+07   \n",
       "Other Assets                      1.503000e+08  5.810000e+07  1.431000e+08   \n",
       "Cash                              1.271400e+09  5.085000e+08  4.994000e+08   \n",
       "Total Current Liabilities         1.354700e+09  1.342700e+09  1.237700e+09   \n",
       "Deferred Long Term Asset Charges  1.630000e+07           NaN  8.300000e+07   \n",
       "Short Long Term Debt              4.100000e+06  1.217000e+08           NaN   \n",
       "Other Stockholder Equity         -6.870000e+07 -4.930000e+07 -7.880000e+07   \n",
       "Property Plant Equipment          7.502000e+08  8.633000e+08  1.042900e+09   \n",
       "Total Current Assets              2.598800e+09  1.551200e+09  1.633700e+09   \n",
       "Net Tangible Assets               1.602500e+09  4.367000e+08  6.115000e+08   \n",
       "Net Receivables                   3.097000e+08  1.081000e+08  2.084000e+08   \n",
       "Long Term Debt                    4.050000e+07  2.160000e+08  4.198000e+08   \n",
       "Inventory                         9.150000e+08  6.025000e+08  8.597000e+08   \n",
       "Accounts Payable                  4.710000e+08  3.418000e+08  3.808000e+08   \n",
       "Intangible Assets                          NaN           NaN           NaN   \n",
       "Good Will                                  NaN           NaN           NaN   \n",
       "\n",
       "                                    2019-02-02  \n",
       "Capital Surplus                   2.770000e+07  \n",
       "Total Liab                        2.708100e+09  \n",
       "Total Stockholder Equity          1.336200e+09  \n",
       "Other Current Liab                5.495000e+08  \n",
       "Total Assets                      4.044300e+09  \n",
       "Common Stock                      1.000000e+05  \n",
       "Other Current Assets              3.700000e+06  \n",
       "Retained Earnings                 1.362700e+09  \n",
       "Other Liab                        5.540000e+07  \n",
       "Treasury Stock                   -5.430000e+07  \n",
       "Other Assets                      2.314000e+08  \n",
       "Cash                              1.624400e+09  \n",
       "Total Current Liabilities         2.181100e+09  \n",
       "Deferred Long Term Asset Charges  1.473000e+08  \n",
       "Short Long Term Debt              3.492000e+08  \n",
       "Other Stockholder Equity         -5.430000e+07  \n",
       "Property Plant Equipment          3.213000e+08  \n",
       "Total Current Assets              3.127700e+09  \n",
       "Net Tangible Assets               9.723000e+08  \n",
       "Net Receivables                   1.342000e+08  \n",
       "Long Term Debt                    4.716000e+08  \n",
       "Inventory                         1.250500e+09  \n",
       "Accounts Payable                  1.051900e+09  \n",
       "Intangible Assets                 3.350000e+07  \n",
       "Good Will                         3.639000e+08  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tick.balance_sheet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2022-01-29</th>\n",
       "      <th>2021-01-30</th>\n",
       "      <th>2020-02-01</th>\n",
       "      <th>2019-02-02</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Research Development</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Effect Of Accounting Charges</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income Before Tax</th>\n",
       "      <td>-3.954e+08</td>\n",
       "      <td>-2.699e+08</td>\n",
       "      <td>-4.268e+08</td>\n",
       "      <td>-7.531e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minority Interest</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Income</th>\n",
       "      <td>-3.813e+08</td>\n",
       "      <td>-2.153e+08</td>\n",
       "      <td>-4.709e+08</td>\n",
       "      <td>-6.73e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Selling General Administrative</th>\n",
       "      <td>1.6134e+09</td>\n",
       "      <td>1.4486e+09</td>\n",
       "      <td>1.8247e+09</td>\n",
       "      <td>1.9876e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gross Profit</th>\n",
       "      <td>1.3478e+09</td>\n",
       "      <td>1.2595e+09</td>\n",
       "      <td>1.9087e+09</td>\n",
       "      <td>2.3081e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ebit</th>\n",
       "      <td>-3.392e+08</td>\n",
       "      <td>-2.659e+08</td>\n",
       "      <td>-6.8e+06</td>\n",
       "      <td>3.205e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Operating Income</th>\n",
       "      <td>-3.392e+08</td>\n",
       "      <td>-2.659e+08</td>\n",
       "      <td>-6.8e+06</td>\n",
       "      <td>3.205e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Operating Expenses</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interest Expense</th>\n",
       "      <td>-2.69e+07</td>\n",
       "      <td>-3.21e+07</td>\n",
       "      <td>-2.72e+07</td>\n",
       "      <td>-5.68e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Extraordinary Items</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Non Recurring</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Items</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income Tax Expense</th>\n",
       "      <td>-1.41e+07</td>\n",
       "      <td>-5.53e+07</td>\n",
       "      <td>3.76e+07</td>\n",
       "      <td>4.17e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Revenue</th>\n",
       "      <td>6.0107e+09</td>\n",
       "      <td>5.0898e+09</td>\n",
       "      <td>6.466e+09</td>\n",
       "      <td>8.2853e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Operating Expenses</th>\n",
       "      <td>6.3499e+09</td>\n",
       "      <td>5.3557e+09</td>\n",
       "      <td>6.4728e+09</td>\n",
       "      <td>7.9648e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cost Of Revenue</th>\n",
       "      <td>4.6629e+09</td>\n",
       "      <td>3.8303e+09</td>\n",
       "      <td>4.5573e+09</td>\n",
       "      <td>5.9772e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total Other Income Expense Net</th>\n",
       "      <td>-5.62e+07</td>\n",
       "      <td>-4e+06</td>\n",
       "      <td>-4.2e+08</td>\n",
       "      <td>-1.0736e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Discontinued Operations</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-700000</td>\n",
       "      <td>-6.5e+06</td>\n",
       "      <td>1.218e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Income From Continuing Ops</th>\n",
       "      <td>-3.813e+08</td>\n",
       "      <td>-2.146e+08</td>\n",
       "      <td>-4.644e+08</td>\n",
       "      <td>-7.948e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Net Income Applicable To Common Shares</th>\n",
       "      <td>-3.813e+08</td>\n",
       "      <td>-2.153e+08</td>\n",
       "      <td>-4.709e+08</td>\n",
       "      <td>-6.73e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        2022-01-29  2021-01-30  2020-02-01  \\\n",
       "Research Development                          None        None        None   \n",
       "Effect Of Accounting Charges                  None        None        None   \n",
       "Income Before Tax                       -3.954e+08  -2.699e+08  -4.268e+08   \n",
       "Minority Interest                             None        None        None   \n",
       "Net Income                              -3.813e+08  -2.153e+08  -4.709e+08   \n",
       "Selling General Administrative          1.6134e+09  1.4486e+09  1.8247e+09   \n",
       "Gross Profit                            1.3478e+09  1.2595e+09  1.9087e+09   \n",
       "Ebit                                    -3.392e+08  -2.659e+08    -6.8e+06   \n",
       "Operating Income                        -3.392e+08  -2.659e+08    -6.8e+06   \n",
       "Other Operating Expenses                      None        None        None   \n",
       "Interest Expense                         -2.69e+07   -3.21e+07   -2.72e+07   \n",
       "Extraordinary Items                           None        None        None   \n",
       "Non Recurring                                 None        None        None   \n",
       "Other Items                                   None        None        None   \n",
       "Income Tax Expense                       -1.41e+07   -5.53e+07    3.76e+07   \n",
       "Total Revenue                           6.0107e+09  5.0898e+09   6.466e+09   \n",
       "Total Operating Expenses                6.3499e+09  5.3557e+09  6.4728e+09   \n",
       "Cost Of Revenue                         4.6629e+09  3.8303e+09  4.5573e+09   \n",
       "Total Other Income Expense Net           -5.62e+07      -4e+06    -4.2e+08   \n",
       "Discontinued Operations                        NaN     -700000    -6.5e+06   \n",
       "Net Income From Continuing Ops          -3.813e+08  -2.146e+08  -4.644e+08   \n",
       "Net Income Applicable To Common Shares  -3.813e+08  -2.153e+08  -4.709e+08   \n",
       "\n",
       "                                        2019-02-02  \n",
       "Research Development                          None  \n",
       "Effect Of Accounting Charges                  None  \n",
       "Income Before Tax                       -7.531e+08  \n",
       "Minority Interest                             None  \n",
       "Net Income                               -6.73e+08  \n",
       "Selling General Administrative          1.9876e+09  \n",
       "Gross Profit                            2.3081e+09  \n",
       "Ebit                                     3.205e+08  \n",
       "Operating Income                         3.205e+08  \n",
       "Other Operating Expenses                      None  \n",
       "Interest Expense                         -5.68e+07  \n",
       "Extraordinary Items                           None  \n",
       "Non Recurring                                 None  \n",
       "Other Items                                   None  \n",
       "Income Tax Expense                        4.17e+07  \n",
       "Total Revenue                           8.2853e+09  \n",
       "Total Operating Expenses                7.9648e+09  \n",
       "Cost Of Revenue                         5.9772e+09  \n",
       "Total Other Income Expense Net         -1.0736e+09  \n",
       "Discontinued Operations                  1.218e+08  \n",
       "Net Income From Continuing Ops          -7.948e+08  \n",
       "Net Income Applicable To Common Shares   -6.73e+08  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tick.financials"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Z-score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3499300000.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For Working Capital (one of the factors) we need to grab total assets and total liabilities.\n",
    "current_assets = tick.balance_sheet.loc['Total Assets'][0]\n",
    "current_assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1896800000.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_liabilities = tick.balance_sheet.loc['Total Liab'][0]\n",
    "current_liabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1602500000.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "working_capital = current_assets - current_liabilities\n",
    "working_capital"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-339200000.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We also need EBIT: Earnings Before Interest and Taxes\n",
    "ebit = tick.financials.loc['Ebit'][0]\n",
    "ebit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6010700000.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sales i.e. revenue\n",
    "sales = tick.financials.loc['Total Revenue'][0]\n",
    "sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93600000.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Retained earnings\n",
    "retained_earnings = tick.balance_sheet.loc['Retained Earnings'][0]\n",
    "retained_earnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7303717888"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Market Capitalization\n",
    "market_cap = tick.info['marketCap']\n",
    "market_cap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example of an Altman-like z-score for manufacturing as outlined here:\n",
    "# https://www.investopedia.com/terms/a/altman.asp\n",
    "# https://en.wikipedia.org/wiki/Altman_Z-score\n",
    "# Altman-like because some of these metrics might be debated (e.g. sales vs. revenue, etc.).\n",
    "# We can come up with many scores like this, details and coefficients to be fine-tuned for particular use cases.\n",
    "\n",
    "# Plug in from above\n",
    "def z_altman(tick):\n",
    "    '''\n",
    "    Altman z-score, tuned for manufacturing companies.\n",
    "    \n",
    "    Takes a yfinance ticker and returns a z-score.\n",
    "    '''\n",
    "    \n",
    "    # Get numbers\n",
    "    current_assets = tick.balance_sheet.loc['Total Assets'][0]\n",
    "    current_liabilities = tick.balance_sheet.loc['Total Liab'][0]\n",
    "    ebit = tick.financials.loc['Ebit'][0]\n",
    "    sales = tick.financials.loc['Total Revenue'][0]\n",
    "    retained_earnings = tick.balance_sheet.loc['Retained Earnings'][0]\n",
    "    market_cap = tick.info['marketCap']\n",
    "    \n",
    "    # Calculate working capital\n",
    "    working_capital = current_assets - current_liabilities\n",
    "    \n",
    "    # Calculate ratios\n",
    "    working_capital_to_assets = working_capital / current_assets\n",
    "    retained_earnings_to_assets = retained_earnings / current_assets\n",
    "    ebit_to_assets = ebit / current_assets\n",
    "    market_cap_to_liabilities = market_cap / current_liabilities\n",
    "    sales_to_assets = sales / current_assets\n",
    "    \n",
    "    # Multiply by weights\n",
    "    z_score = (\n",
    "        (1.2 * working_capital_to_assets) +\n",
    "        (1.4 * retained_earnings_to_assets) + \n",
    "        (3.3 * ebit_to_assets) +\n",
    "        (0.6 * market_cap_to_liabilities) +\n",
    "        (1.0 * sales_to_assets)\n",
    "    )\n",
    "    \n",
    "    return z_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.29511955100652"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z_altman(tick)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "yfinance.Tickers object <GME,TSLA>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Handle multiple tickers\n",
    "ticks = yf.Tickers(['GME','TSLA'])\n",
    "ticks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-339200000.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# E.g.\n",
    "ticks.tickers['GME'].financials.loc['Ebit'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#yf.Tickers??"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['GME', 'TSLA']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ticks.symbols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-339200000.0\n",
      "GME\n",
      "6523000000.0\n",
      "TSLA\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'GME': -339200000.0, 'TSLA': 6523000000.0}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores_dict = dict()\n",
    "for stock in ticks.tickers:\n",
    "    print(ticks.tickers[stock].financials.loc['Ebit'][0])\n",
    "    print(stock)\n",
    "    scores_dict[stock] = ticks.tickers[stock].financials.loc['Ebit'][0]\n",
    "scores_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adjust function\n",
    "def z_altman_multi(ticks):\n",
    "    '''\n",
    "    Altman z-score, tuned for manufacturing companies.\n",
    "    \n",
    "    Takes a yfinance.Tickers object (multiple tickers) and returns a score dictionary.\n",
    "    '''\n",
    "    \n",
    "    scores_dict = dict()\n",
    "    \n",
    "    # Loop over ticks\n",
    "    for stock in ticks.tickers:\n",
    "        \n",
    "        # Get numbers\n",
    "        current_assets = ticks.tickers[stock].balance_sheet.loc['Total Assets'][0]\n",
    "        current_liabilities = ticks.tickers[stock].balance_sheet.loc['Total Liab'][0]\n",
    "        ebit = ticks.tickers[stock].financials.loc['Ebit'][0]\n",
    "        sales = ticks.tickers[stock].financials.loc['Total Revenue'][0]\n",
    "        retained_earnings = ticks.tickers[stock].balance_sheet.loc['Retained Earnings'][0]\n",
    "        market_cap = ticks.tickers[stock].info['marketCap']\n",
    "\n",
    "        # Calculate working capital\n",
    "        working_capital = current_assets - current_liabilities\n",
    "\n",
    "        # Calculate ratios\n",
    "        working_capital_to_assets = working_capital / current_assets\n",
    "        retained_earnings_to_assets = retained_earnings / current_assets\n",
    "        ebit_to_assets = ebit / current_assets\n",
    "        market_cap_to_liabilities = market_cap / current_liabilities\n",
    "        sales_to_assets = sales / current_assets\n",
    "\n",
    "        # Multiply by weights\n",
    "        z_score = (\n",
    "            (1.2 * working_capital_to_assets) +\n",
    "            (1.4 * retained_earnings_to_assets) + \n",
    "            (3.3 * ebit_to_assets) +\n",
    "            (0.6 * market_cap_to_liabilities) +\n",
    "            (1.0 * sales_to_assets)\n",
    "        )\n",
    "        \n",
    "        # Add score to dict\n",
    "        scores_dict[stock] = z_score\n",
    "    \n",
    "    return scores_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check a bunch, examine scores. \n",
    "list_of_stocks = yf.Tickers(\n",
    "    ['GME','TSLA','COST','AAPL',\n",
    "     'IBM','F','GOOG','MMM','BA',\n",
    "     'LMT','GM','AMC','QS','TDOC',\n",
    "     'NVDA','FB','DE','ZM','Z',\n",
    "     'DELL','HPE','GE','INTC','NOC',\n",
    "     'PRLB','COST','MSFT','COIN','ROKU',\n",
    "     'VICI','XOM','PSX','CVX'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([('GME', 4.137560674583069), ('TSLA', 14.61230959859679), ('COST', 7.175560451191021), ('AAPL', 7.038652937717932), ('IBM', 3.0237557442555283), ('F', 1.2319392195711252), ('GOOG', 10.79696165235446), ('MMM', 4.602694523275302), ('BA', 0.9285875451865), ('LMT', 4.449333040371847), ('GM', 1.4080125025382866), ('AMC', -0.8237133981669874), ('QS', 25.161468370595266), ('TDOC', 2.905725400924926), ('NVDA', 16.33915169457314), ('FB', 10.291847994840625), ('DE', 2.5896149709996372), ('ZM', 11.393658182055113), ('Z', 2.2307228176263925), ('DELL', 1.3076092828566763), ('HPE', 1.1827458363878098), ('GE', 1.583454406672066), ('INTC', 3.541145075833152), ('NOC', 3.6188018215234683), ('PRLB', 9.862687792321633), ('MSFT', 7.876750573772894), ('COIN', 2.406030772217069), ('ROKU', 7.427480981806268), ('VICI', 3.2325795643823687), ('XOM', 4.7916045286519084), ('PSX', 3.644345514313662), ('CVX', 4.485656173340259)])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can sometimes fail, time out. \n",
    "scores = z_altman_multi(list_of_stocks)\n",
    "scores.items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('QS', 25.161468370595266),\n",
       " ('NVDA', 16.33915169457314),\n",
       " ('TSLA', 14.61230959859679),\n",
       " ('ZM', 11.393658182055113),\n",
       " ('GOOG', 10.79696165235446),\n",
       " ('FB', 10.291847994840625),\n",
       " ('PRLB', 9.862687792321633),\n",
       " ('MSFT', 7.876750573772894),\n",
       " ('ROKU', 7.427480981806268),\n",
       " ('COST', 7.175560451191021),\n",
       " ('AAPL', 7.038652937717932),\n",
       " ('XOM', 4.7916045286519084),\n",
       " ('MMM', 4.602694523275302),\n",
       " ('CVX', 4.485656173340259),\n",
       " ('LMT', 4.449333040371847),\n",
       " ('GME', 4.137560674583069),\n",
       " ('PSX', 3.644345514313662),\n",
       " ('NOC', 3.6188018215234683),\n",
       " ('INTC', 3.541145075833152),\n",
       " ('VICI', 3.2325795643823687),\n",
       " ('IBM', 3.0237557442555283),\n",
       " ('TDOC', 2.905725400924926),\n",
       " ('DE', 2.5896149709996372),\n",
       " ('COIN', 2.406030772217069),\n",
       " ('Z', 2.2307228176263925),\n",
       " ('GE', 1.583454406672066),\n",
       " ('GM', 1.4080125025382866),\n",
       " ('DELL', 1.3076092828566763),\n",
       " ('F', 1.2319392195711252),\n",
       " ('HPE', 1.1827458363878098),\n",
       " ('BA', 0.9285875451865),\n",
       " ('AMC', -0.8237133981669874)]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_scores = sorted(scores.items(), reverse = True, key=lambda kv: kv[1])\n",
    "sorted_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Some of the scores seem to be outliers.\n",
    "# We could create a new tech score with different weights.  What might such a z_score look like?\n",
    "def z_tech():\n",
    "    \n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now lets plot the scores against another metric, like the market cap, \n",
    "# to check in on the usefulness of the score.\n",
    "# Ultimately we can combine data into a pandas df. \n",
    "# (Perhaps this could be done more directly from yf.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_m_caps(ticks):\n",
    "\n",
    "    cap_dict = dict()\n",
    "    \n",
    "    for stock in ticks.tickers:\n",
    "        market_cap = ticks.tickers[stock].info['marketCap']\n",
    "        \n",
    "        cap_dict[stock] = market_cap\n",
    "        \n",
    "    return cap_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GME</td>\n",
       "      <td>6805621760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TSLA</td>\n",
       "      <td>650780016640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>COST</td>\n",
       "      <td>194003566592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2271754584064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBM</td>\n",
       "      <td>119927619584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>49925545984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>1393876140032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MMM</td>\n",
       "      <td>82940346368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BA</td>\n",
       "      <td>70641336320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>LMT</td>\n",
       "      <td>117826863104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GM</td>\n",
       "      <td>51344629760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AMC</td>\n",
       "      <td>5333498880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>QS</td>\n",
       "      <td>4657414656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TDOC</td>\n",
       "      <td>5241248768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NVDA</td>\n",
       "      <td>402557665280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>FB</td>\n",
       "      <td>490601676800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DE</td>\n",
       "      <td>96313688064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZM</td>\n",
       "      <td>26742071296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Z</td>\n",
       "      <td>10372258816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>DELL</td>\n",
       "      <td>30593593344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>HPE</td>\n",
       "      <td>18315110400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GE</td>\n",
       "      <td>82635038720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>INTC</td>\n",
       "      <td>169390555136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NOC</td>\n",
       "      <td>69752651776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>PRLB</td>\n",
       "      <td>1260292992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>1896215347200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>COIN</td>\n",
       "      <td>17324685312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ROKU</td>\n",
       "      <td>12656995328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>VICI</td>\n",
       "      <td>18207987712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>XOM</td>\n",
       "      <td>398903246848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>PSX</td>\n",
       "      <td>41098964992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CVX</td>\n",
       "      <td>323504963584</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0              1\n",
       "0    GME     6805621760\n",
       "1   TSLA   650780016640\n",
       "2   COST   194003566592\n",
       "3   AAPL  2271754584064\n",
       "4    IBM   119927619584\n",
       "5      F    49925545984\n",
       "6   GOOG  1393876140032\n",
       "7    MMM    82940346368\n",
       "8     BA    70641336320\n",
       "9    LMT   117826863104\n",
       "10    GM    51344629760\n",
       "11   AMC     5333498880\n",
       "12    QS     4657414656\n",
       "13  TDOC     5241248768\n",
       "14  NVDA   402557665280\n",
       "15    FB   490601676800\n",
       "16    DE    96313688064\n",
       "17    ZM    26742071296\n",
       "18     Z    10372258816\n",
       "19  DELL    30593593344\n",
       "20   HPE    18315110400\n",
       "21    GE    82635038720\n",
       "22  INTC   169390555136\n",
       "23   NOC    69752651776\n",
       "24  PRLB     1260292992\n",
       "25  MSFT  1896215347200\n",
       "26  COIN    17324685312\n",
       "27  ROKU    12656995328\n",
       "28  VICI    18207987712\n",
       "29   XOM   398903246848\n",
       "30   PSX    41098964992\n",
       "31   CVX   323504963584"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "market_caps_df = df(get_m_caps(list_of_stocks).items())\n",
    "market_caps_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>2271754584064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>1896215347200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>1393876140032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TSLA</td>\n",
       "      <td>650780016640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FB</td>\n",
       "      <td>490601676800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NVDA</td>\n",
       "      <td>402557665280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>XOM</td>\n",
       "      <td>398903246848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CVX</td>\n",
       "      <td>323504963584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>COST</td>\n",
       "      <td>194003566592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>INTC</td>\n",
       "      <td>169390555136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>IBM</td>\n",
       "      <td>119927619584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>LMT</td>\n",
       "      <td>117826863104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>DE</td>\n",
       "      <td>96313688064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>MMM</td>\n",
       "      <td>82940346368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>GE</td>\n",
       "      <td>82635038720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BA</td>\n",
       "      <td>70641336320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NOC</td>\n",
       "      <td>69752651776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>GM</td>\n",
       "      <td>51344629760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>F</td>\n",
       "      <td>49925545984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>PSX</td>\n",
       "      <td>41098964992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>DELL</td>\n",
       "      <td>30593593344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ZM</td>\n",
       "      <td>26742071296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>HPE</td>\n",
       "      <td>18315110400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>VICI</td>\n",
       "      <td>18207987712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>COIN</td>\n",
       "      <td>17324685312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ROKU</td>\n",
       "      <td>12656995328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Z</td>\n",
       "      <td>10372258816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>GME</td>\n",
       "      <td>6805621760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>AMC</td>\n",
       "      <td>5333498880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>TDOC</td>\n",
       "      <td>5241248768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>QS</td>\n",
       "      <td>4657414656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>PRLB</td>\n",
       "      <td>1260292992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0              1\n",
       "0   AAPL  2271754584064\n",
       "1   MSFT  1896215347200\n",
       "2   GOOG  1393876140032\n",
       "3   TSLA   650780016640\n",
       "4     FB   490601676800\n",
       "5   NVDA   402557665280\n",
       "6    XOM   398903246848\n",
       "7    CVX   323504963584\n",
       "8   COST   194003566592\n",
       "9   INTC   169390555136\n",
       "10   IBM   119927619584\n",
       "11   LMT   117826863104\n",
       "12    DE    96313688064\n",
       "13   MMM    82940346368\n",
       "14    GE    82635038720\n",
       "15    BA    70641336320\n",
       "16   NOC    69752651776\n",
       "17    GM    51344629760\n",
       "18     F    49925545984\n",
       "19   PSX    41098964992\n",
       "20  DELL    30593593344\n",
       "21    ZM    26742071296\n",
       "22   HPE    18315110400\n",
       "23  VICI    18207987712\n",
       "24  COIN    17324685312\n",
       "25  ROKU    12656995328\n",
       "26     Z    10372258816\n",
       "27   GME     6805621760\n",
       "28   AMC     5333498880\n",
       "29  TDOC     5241248768\n",
       "30    QS     4657414656\n",
       "31  PRLB     1260292992"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_market_caps_df = df(sorted(get_m_caps(list_of_stocks).items(), reverse = True, key=lambda kv: kv[1]))\n",
    "sorted_market_caps_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GME</td>\n",
       "      <td>4.137561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TSLA</td>\n",
       "      <td>14.612310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>COST</td>\n",
       "      <td>7.175560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>7.038653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBM</td>\n",
       "      <td>3.023756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>1.231939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>10.796962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MMM</td>\n",
       "      <td>4.602695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BA</td>\n",
       "      <td>0.928588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>LMT</td>\n",
       "      <td>4.449333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GM</td>\n",
       "      <td>1.408013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AMC</td>\n",
       "      <td>-0.823713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>QS</td>\n",
       "      <td>25.161468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TDOC</td>\n",
       "      <td>2.905725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NVDA</td>\n",
       "      <td>16.339152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>FB</td>\n",
       "      <td>10.291848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DE</td>\n",
       "      <td>2.589615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZM</td>\n",
       "      <td>11.393658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Z</td>\n",
       "      <td>2.230723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>DELL</td>\n",
       "      <td>1.307609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>HPE</td>\n",
       "      <td>1.182746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GE</td>\n",
       "      <td>1.583454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>INTC</td>\n",
       "      <td>3.541145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NOC</td>\n",
       "      <td>3.618802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>PRLB</td>\n",
       "      <td>9.862688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>7.876751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>COIN</td>\n",
       "      <td>2.406031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ROKU</td>\n",
       "      <td>7.427481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>VICI</td>\n",
       "      <td>3.232580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>XOM</td>\n",
       "      <td>4.791605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>PSX</td>\n",
       "      <td>3.644346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CVX</td>\n",
       "      <td>4.485656</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0          1\n",
       "0    GME   4.137561\n",
       "1   TSLA  14.612310\n",
       "2   COST   7.175560\n",
       "3   AAPL   7.038653\n",
       "4    IBM   3.023756\n",
       "5      F   1.231939\n",
       "6   GOOG  10.796962\n",
       "7    MMM   4.602695\n",
       "8     BA   0.928588\n",
       "9    LMT   4.449333\n",
       "10    GM   1.408013\n",
       "11   AMC  -0.823713\n",
       "12    QS  25.161468\n",
       "13  TDOC   2.905725\n",
       "14  NVDA  16.339152\n",
       "15    FB  10.291848\n",
       "16    DE   2.589615\n",
       "17    ZM  11.393658\n",
       "18     Z   2.230723\n",
       "19  DELL   1.307609\n",
       "20   HPE   1.182746\n",
       "21    GE   1.583454\n",
       "22  INTC   3.541145\n",
       "23   NOC   3.618802\n",
       "24  PRLB   9.862688\n",
       "25  MSFT   7.876751\n",
       "26  COIN   2.406031\n",
       "27  ROKU   7.427481\n",
       "28  VICI   3.232580\n",
       "29   XOM   4.791605\n",
       "30   PSX   3.644346\n",
       "31   CVX   4.485656"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scores_df = df(scores.items())\n",
    "scores_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas import merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>z_score</th>\n",
       "      <th>m_cap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GME</td>\n",
       "      <td>4.137561</td>\n",
       "      <td>6805621760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TSLA</td>\n",
       "      <td>14.612310</td>\n",
       "      <td>650780016640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>COST</td>\n",
       "      <td>7.175560</td>\n",
       "      <td>194003566592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AAPL</td>\n",
       "      <td>7.038653</td>\n",
       "      <td>2271754584064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBM</td>\n",
       "      <td>3.023756</td>\n",
       "      <td>119927619584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F</td>\n",
       "      <td>1.231939</td>\n",
       "      <td>49925545984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>GOOG</td>\n",
       "      <td>10.796962</td>\n",
       "      <td>1393876140032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MMM</td>\n",
       "      <td>4.602695</td>\n",
       "      <td>82940346368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BA</td>\n",
       "      <td>0.928588</td>\n",
       "      <td>70641336320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>LMT</td>\n",
       "      <td>4.449333</td>\n",
       "      <td>117826863104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>GM</td>\n",
       "      <td>1.408013</td>\n",
       "      <td>51344629760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AMC</td>\n",
       "      <td>-0.823713</td>\n",
       "      <td>5333498880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>QS</td>\n",
       "      <td>25.161468</td>\n",
       "      <td>4657414656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>TDOC</td>\n",
       "      <td>2.905725</td>\n",
       "      <td>5241248768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NVDA</td>\n",
       "      <td>16.339152</td>\n",
       "      <td>402557665280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>FB</td>\n",
       "      <td>10.291848</td>\n",
       "      <td>490601676800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DE</td>\n",
       "      <td>2.589615</td>\n",
       "      <td>96313688064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZM</td>\n",
       "      <td>11.393658</td>\n",
       "      <td>26742071296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Z</td>\n",
       "      <td>2.230723</td>\n",
       "      <td>10372258816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>DELL</td>\n",
       "      <td>1.307609</td>\n",
       "      <td>30593593344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>HPE</td>\n",
       "      <td>1.182746</td>\n",
       "      <td>18315110400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>GE</td>\n",
       "      <td>1.583454</td>\n",
       "      <td>82635038720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>INTC</td>\n",
       "      <td>3.541145</td>\n",
       "      <td>169390555136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NOC</td>\n",
       "      <td>3.618802</td>\n",
       "      <td>69752651776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>PRLB</td>\n",
       "      <td>9.862688</td>\n",
       "      <td>1260292992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>MSFT</td>\n",
       "      <td>7.876751</td>\n",
       "      <td>1896215347200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>COIN</td>\n",
       "      <td>2.406031</td>\n",
       "      <td>17324685312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ROKU</td>\n",
       "      <td>7.427481</td>\n",
       "      <td>12656995328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>VICI</td>\n",
       "      <td>3.232580</td>\n",
       "      <td>18207987712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>XOM</td>\n",
       "      <td>4.791605</td>\n",
       "      <td>398903246848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>PSX</td>\n",
       "      <td>3.644346</td>\n",
       "      <td>41098964992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CVX</td>\n",
       "      <td>4.485656</td>\n",
       "      <td>323504963584</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0    z_score          m_cap\n",
       "0    GME   4.137561     6805621760\n",
       "1   TSLA  14.612310   650780016640\n",
       "2   COST   7.175560   194003566592\n",
       "3   AAPL   7.038653  2271754584064\n",
       "4    IBM   3.023756   119927619584\n",
       "5      F   1.231939    49925545984\n",
       "6   GOOG  10.796962  1393876140032\n",
       "7    MMM   4.602695    82940346368\n",
       "8     BA   0.928588    70641336320\n",
       "9    LMT   4.449333   117826863104\n",
       "10    GM   1.408013    51344629760\n",
       "11   AMC  -0.823713     5333498880\n",
       "12    QS  25.161468     4657414656\n",
       "13  TDOC   2.905725     5241248768\n",
       "14  NVDA  16.339152   402557665280\n",
       "15    FB  10.291848   490601676800\n",
       "16    DE   2.589615    96313688064\n",
       "17    ZM  11.393658    26742071296\n",
       "18     Z   2.230723    10372258816\n",
       "19  DELL   1.307609    30593593344\n",
       "20   HPE   1.182746    18315110400\n",
       "21    GE   1.583454    82635038720\n",
       "22  INTC   3.541145   169390555136\n",
       "23   NOC   3.618802    69752651776\n",
       "24  PRLB   9.862688     1260292992\n",
       "25  MSFT   7.876751  1896215347200\n",
       "26  COIN   2.406031    17324685312\n",
       "27  ROKU   7.427481    12656995328\n",
       "28  VICI   3.232580    18207987712\n",
       "29   XOM   4.791605   398903246848\n",
       "30   PSX   3.644346    41098964992\n",
       "31   CVX   4.485656   323504963584"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stocks_df = merge(scores_df,market_caps_df, on = 0)\n",
    "stocks_df.rename(columns={'1_x':'z_score','1_y':'m_cap'}, inplace=True)\n",
    "stocks_df"
   ]
  }
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