Get_Fundamental_Ratios_FinViz.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "QdGiamnJfYcI"
   },
   "outputs": [],
   "source": [
    "# For data manipulation\n",
    "import pandas as pd\n",
    "\n",
    "# To extract fundamental data\n",
    "from bs4 import BeautifulSoup as bs\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functions to Parse Data from FinViz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hkmMDS-UfYcp"
   },
   "outputs": [],
   "source": [
    "def fundamental_metric(soup, metric):\n",
    "    return soup.find(text = metric).find_next(class_='snapshot-td2').text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3l--xuxIfYcY"
   },
   "outputs": [],
   "source": [
    "def get_fundamental_data(df):\n",
    "    for symbol in df.index:\n",
    "        try:\n",
    "            url = (\"http://finviz.com/quote.ashx?t=\" + symbol.lower())\n",
    "            soup = bs(requests.get(url).content) \n",
    "            for m in df.columns:                \n",
    "                df.loc[symbol,m] = fundamental_metric(soup,m)                \n",
    "        except Exception as e:\n",
    "            print (symbol, 'not found')\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# List of Stocks and Ratios You are Interested In"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Y2w5UquOfYc2"
   },
   "outputs": [],
   "source": [
    "stock_list = ['AMZN','GOOG','PG','KO','IBM','DG','XOM','KO','PEP','MT','NL','GSB','LPL']\n",
    "\n",
    "metric = ['P/B',\n",
    "'P/E',\n",
    "'Forward P/E',\n",
    "'PEG',\n",
    "'Debt/Eq',\n",
    "'EPS (ttm)',\n",
    "'Dividend %',\n",
    "'ROE',\n",
    "'ROI',\n",
    "'EPS Q/Q',\n",
    "'Insider Own'\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Initialize Pandas DataFrame to Store the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>P/B</th>\n",
       "      <th>P/E</th>\n",
       "      <th>Forward P/E</th>\n",
       "      <th>PEG</th>\n",
       "      <th>Debt/Eq</th>\n",
       "      <th>EPS (ttm)</th>\n",
       "      <th>Dividend %</th>\n",
       "      <th>ROE</th>\n",
       "      <th>ROI</th>\n",
       "      <th>EPS Q/Q</th>\n",
       "      <th>Insider Own</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>18.61</td>\n",
       "      <td>101.14</td>\n",
       "      <td>58.32</td>\n",
       "      <td>3.12</td>\n",
       "      <td>0.67</td>\n",
       "      <td>23.02</td>\n",
       "      <td>-</td>\n",
       "      <td>21.10%</td>\n",
       "      <td>11.70%</td>\n",
       "      <td>12.70%</td>\n",
       "      <td>11.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>4.16</td>\n",
       "      <td>24.74</td>\n",
       "      <td>21.07</td>\n",
       "      <td>1.56</td>\n",
       "      <td>-</td>\n",
       "      <td>49.16</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>19.30%</td>\n",
       "      <td>5.66%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>6.67</td>\n",
       "      <td>66.12</td>\n",
       "      <td>22.97</td>\n",
       "      <td>8.38</td>\n",
       "      <td>0.63</td>\n",
       "      <td>1.81</td>\n",
       "      <td>2.64%</td>\n",
       "      <td>9.60%</td>\n",
       "      <td>4.90%</td>\n",
       "      <td>16.10%</td>\n",
       "      <td>0.10%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO</th>\n",
       "      <td>10.24</td>\n",
       "      <td>21.94</td>\n",
       "      <td>20.44</td>\n",
       "      <td>4.83</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.07</td>\n",
       "      <td>3.61%</td>\n",
       "      <td>48.80%</td>\n",
       "      <td>12.20%</td>\n",
       "      <td>134.00%</td>\n",
       "      <td>0.30%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>4.97</td>\n",
       "      <td>10.88</td>\n",
       "      <td>8.73</td>\n",
       "      <td>3.28</td>\n",
       "      <td>3.02</td>\n",
       "      <td>10.73</td>\n",
       "      <td>5.55%</td>\n",
       "      <td>51.70%</td>\n",
       "      <td>11.40%</td>\n",
       "      <td>-5.00%</td>\n",
       "      <td>0.10%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DG</th>\n",
       "      <td>6.76</td>\n",
       "      <td>26.91</td>\n",
       "      <td>21.59</td>\n",
       "      <td>2.49</td>\n",
       "      <td>0.43</td>\n",
       "      <td>6.64</td>\n",
       "      <td>0.81%</td>\n",
       "      <td>25.70%</td>\n",
       "      <td>18.90%</td>\n",
       "      <td>17.00%</td>\n",
       "      <td>0.10%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XOM</th>\n",
       "      <td>0.91</td>\n",
       "      <td>12.86</td>\n",
       "      <td>21.55</td>\n",
       "      <td>2.27</td>\n",
       "      <td>0.25</td>\n",
       "      <td>3.19</td>\n",
       "      <td>8.50%</td>\n",
       "      <td>7.50%</td>\n",
       "      <td>2.30%</td>\n",
       "      <td>-17.30%</td>\n",
       "      <td>0.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO</th>\n",
       "      <td>10.24</td>\n",
       "      <td>21.94</td>\n",
       "      <td>20.44</td>\n",
       "      <td>4.83</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.07</td>\n",
       "      <td>3.61%</td>\n",
       "      <td>48.80%</td>\n",
       "      <td>12.20%</td>\n",
       "      <td>134.00%</td>\n",
       "      <td>0.30%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP</th>\n",
       "      <td>12.34</td>\n",
       "      <td>25.21</td>\n",
       "      <td>21.10</td>\n",
       "      <td>4.56</td>\n",
       "      <td>2.17</td>\n",
       "      <td>5.19</td>\n",
       "      <td>2.92%</td>\n",
       "      <td>51.30%</td>\n",
       "      <td>17.80%</td>\n",
       "      <td>-69.70%</td>\n",
       "      <td>0.10%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>0.24</td>\n",
       "      <td>-</td>\n",
       "      <td>6.19</td>\n",
       "      <td>-</td>\n",
       "      <td>0.37</td>\n",
       "      <td>-2.42</td>\n",
       "      <td>2.20%</td>\n",
       "      <td>-6.00%</td>\n",
       "      <td>-2.10%</td>\n",
       "      <td>-259.00%</td>\n",
       "      <td>44.80%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>0.42</td>\n",
       "      <td>4.94</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.53</td>\n",
       "      <td>6.11%</td>\n",
       "      <td>8.50%</td>\n",
       "      <td>-0.70%</td>\n",
       "      <td>78.20%</td>\n",
       "      <td>82.98%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GSB</th>\n",
       "      <td>-</td>\n",
       "      <td>11.06</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.76%</td>\n",
       "      <td>350.00%</td>\n",
       "      <td>123.00%</td>\n",
       "      <td>15.00%</td>\n",
       "      <td>6.60%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LPL</th>\n",
       "      <td>0.34</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>1.20</td>\n",
       "      <td>-3.23</td>\n",
       "      <td>-</td>\n",
       "      <td>-21.70%</td>\n",
       "      <td>-10.90%</td>\n",
       "      <td>-</td>\n",
       "      <td>51.10%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        P/B     P/E Forward P/E   PEG Debt/Eq EPS (ttm) Dividend %      ROE  \\\n",
       "AMZN  18.61  101.14       58.32  3.12    0.67     23.02          -   21.10%   \n",
       "GOOG   4.16   24.74       21.07  1.56       -     49.16          -        -   \n",
       "PG     6.67   66.12       22.97  8.38    0.63      1.81      2.64%    9.60%   \n",
       "KO    10.24   21.94       20.44  4.83    2.25      2.07      3.61%   48.80%   \n",
       "IBM    4.97   10.88        8.73  3.28    3.02     10.73      5.55%   51.70%   \n",
       "DG     6.76   26.91       21.59  2.49    0.43      6.64      0.81%   25.70%   \n",
       "XOM    0.91   12.86       21.55  2.27    0.25      3.19      8.50%    7.50%   \n",
       "KO    10.24   21.94       20.44  4.83    2.25      2.07      3.61%   48.80%   \n",
       "PEP   12.34   25.21       21.10  4.56    2.17      5.19      2.92%   51.30%   \n",
       "MT     0.24       -        6.19     -    0.37     -2.42      2.20%   -6.00%   \n",
       "NL     0.42    4.94           -     -    0.00      0.53      6.11%    8.50%   \n",
       "GSB       -   11.06           -     -       -      0.72      0.76%  350.00%   \n",
       "LPL    0.34       -           -     -    1.20     -3.23          -  -21.70%   \n",
       "\n",
       "          ROI   EPS Q/Q Insider Own  \n",
       "AMZN   11.70%    12.70%      11.20%  \n",
       "GOOG        -    19.30%       5.66%  \n",
       "PG      4.90%    16.10%       0.10%  \n",
       "KO     12.20%   134.00%       0.30%  \n",
       "IBM    11.40%    -5.00%       0.10%  \n",
       "DG     18.90%    17.00%       0.10%  \n",
       "XOM     2.30%   -17.30%       0.20%  \n",
       "KO     12.20%   134.00%       0.30%  \n",
       "PEP    17.80%   -69.70%       0.10%  \n",
       "MT     -2.10%  -259.00%      44.80%  \n",
       "NL     -0.70%    78.20%      82.98%  \n",
       "GSB   123.00%    15.00%       6.60%  \n",
       "LPL   -10.90%         -      51.10%  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(index=stock_list,columns=metric)\n",
    "df = get_fundamental_data(df)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Remove % Sign and Convert Values to Numeric Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P/B</th>\n",
       "      <th>P/E</th>\n",
       "      <th>Forward P/E</th>\n",
       "      <th>PEG</th>\n",
       "      <th>Debt/Eq</th>\n",
       "      <th>EPS (ttm)</th>\n",
       "      <th>Dividend %</th>\n",
       "      <th>ROE</th>\n",
       "      <th>ROI</th>\n",
       "      <th>EPS Q/Q</th>\n",
       "      <th>Insider Own</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AMZN</th>\n",
       "      <td>18.61</td>\n",
       "      <td>101.14</td>\n",
       "      <td>58.32</td>\n",
       "      <td>3.12</td>\n",
       "      <td>0.67</td>\n",
       "      <td>23.02</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.1</td>\n",
       "      <td>11.7</td>\n",
       "      <td>12.7</td>\n",
       "      <td>11.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG</th>\n",
       "      <td>4.16</td>\n",
       "      <td>24.74</td>\n",
       "      <td>21.07</td>\n",
       "      <td>1.56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.3</td>\n",
       "      <td>5.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>6.67</td>\n",
       "      <td>66.12</td>\n",
       "      <td>22.97</td>\n",
       "      <td>8.38</td>\n",
       "      <td>0.63</td>\n",
       "      <td>1.81</td>\n",
       "      <td>2.64</td>\n",
       "      <td>9.6</td>\n",
       "      <td>4.9</td>\n",
       "      <td>16.1</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO</th>\n",
       "      <td>10.24</td>\n",
       "      <td>21.94</td>\n",
       "      <td>20.44</td>\n",
       "      <td>4.83</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.07</td>\n",
       "      <td>3.61</td>\n",
       "      <td>48.8</td>\n",
       "      <td>12.2</td>\n",
       "      <td>134.0</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBM</th>\n",
       "      <td>4.97</td>\n",
       "      <td>10.88</td>\n",
       "      <td>8.73</td>\n",
       "      <td>3.28</td>\n",
       "      <td>3.02</td>\n",
       "      <td>10.73</td>\n",
       "      <td>5.55</td>\n",
       "      <td>51.7</td>\n",
       "      <td>11.4</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DG</th>\n",
       "      <td>6.76</td>\n",
       "      <td>26.91</td>\n",
       "      <td>21.59</td>\n",
       "      <td>2.49</td>\n",
       "      <td>0.43</td>\n",
       "      <td>6.64</td>\n",
       "      <td>0.81</td>\n",
       "      <td>25.7</td>\n",
       "      <td>18.9</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XOM</th>\n",
       "      <td>0.91</td>\n",
       "      <td>12.86</td>\n",
       "      <td>21.55</td>\n",
       "      <td>2.27</td>\n",
       "      <td>0.25</td>\n",
       "      <td>3.19</td>\n",
       "      <td>8.50</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-17.3</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO</th>\n",
       "      <td>10.24</td>\n",
       "      <td>21.94</td>\n",
       "      <td>20.44</td>\n",
       "      <td>4.83</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2.07</td>\n",
       "      <td>3.61</td>\n",
       "      <td>48.8</td>\n",
       "      <td>12.2</td>\n",
       "      <td>134.0</td>\n",
       "      <td>0.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP</th>\n",
       "      <td>12.34</td>\n",
       "      <td>25.21</td>\n",
       "      <td>21.10</td>\n",
       "      <td>4.56</td>\n",
       "      <td>2.17</td>\n",
       "      <td>5.19</td>\n",
       "      <td>2.92</td>\n",
       "      <td>51.3</td>\n",
       "      <td>17.8</td>\n",
       "      <td>-69.7</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MT</th>\n",
       "      <td>0.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.37</td>\n",
       "      <td>-2.42</td>\n",
       "      <td>2.20</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>-259.0</td>\n",
       "      <td>44.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>0.42</td>\n",
       "      <td>4.94</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.53</td>\n",
       "      <td>6.11</td>\n",
       "      <td>8.5</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>78.2</td>\n",
       "      <td>82.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GSB</th>\n",
       "      <td>NaN</td>\n",
       "      <td>11.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.76</td>\n",
       "      <td>350.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LPL</th>\n",
       "      <td>0.34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.20</td>\n",
       "      <td>-3.23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-21.7</td>\n",
       "      <td>-10.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>51.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        P/B     P/E  Forward P/E   PEG  Debt/Eq  EPS (ttm)  Dividend %    ROE  \\\n",
       "AMZN  18.61  101.14        58.32  3.12     0.67      23.02         NaN   21.1   \n",
       "GOOG   4.16   24.74        21.07  1.56      NaN      49.16         NaN    NaN   \n",
       "PG     6.67   66.12        22.97  8.38     0.63       1.81        2.64    9.6   \n",
       "KO    10.24   21.94        20.44  4.83     2.25       2.07        3.61   48.8   \n",
       "IBM    4.97   10.88         8.73  3.28     3.02      10.73        5.55   51.7   \n",
       "DG     6.76   26.91        21.59  2.49     0.43       6.64        0.81   25.7   \n",
       "XOM    0.91   12.86        21.55  2.27     0.25       3.19        8.50    7.5   \n",
       "KO    10.24   21.94        20.44  4.83     2.25       2.07        3.61   48.8   \n",
       "PEP   12.34   25.21        21.10  4.56     2.17       5.19        2.92   51.3   \n",
       "MT     0.24     NaN         6.19   NaN     0.37      -2.42        2.20   -6.0   \n",
       "NL     0.42    4.94          NaN   NaN     0.00       0.53        6.11    8.5   \n",
       "GSB     NaN   11.06          NaN   NaN      NaN       0.72        0.76  350.0   \n",
       "LPL    0.34     NaN          NaN   NaN     1.20      -3.23         NaN  -21.7   \n",
       "\n",
       "        ROI  EPS Q/Q  Insider Own  \n",
       "AMZN   11.7     12.7        11.20  \n",
       "GOOG    NaN     19.3         5.66  \n",
       "PG      4.9     16.1         0.10  \n",
       "KO     12.2    134.0         0.30  \n",
       "IBM    11.4     -5.0         0.10  \n",
       "DG     18.9     17.0         0.10  \n",
       "XOM     2.3    -17.3         0.20  \n",
       "KO     12.2    134.0         0.30  \n",
       "PEP    17.8    -69.7         0.10  \n",
       "MT     -2.1   -259.0        44.80  \n",
       "NL     -0.7     78.2        82.98  \n",
       "GSB   123.0     15.0         6.60  \n",
       "LPL   -10.9      NaN        51.10  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Dividend %'] = df['Dividend %'].str.replace('%', '')\n",
    "df['ROE'] = df['ROE'].str.replace('%', '')\n",
    "df['ROI'] = df['ROI'].str.replace('%', '')\n",
    "df['EPS Q/Q'] = df['EPS Q/Q'].str.replace('%', '')\n",
    "df['Insider Own'] = df['Insider Own'].str.replace('%', '')\n",
    "df = df.apply(pd.to_numeric, errors='coerce')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HDL1Nks2fYdP"
   },
   "source": [
    "# Filter Good Companies\n",
    "\n",
    "### 1. Companies which are quoted at low valuations\n",
    "P/E < 15 and P/B < 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 311
    },
    "colab_type": "code",
    "id": "UkBAV9AHfYdT",
    "outputId": "20aa07e9-8bd4-49f6-a07d-7e6fc91a0784"
   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P/B</th>\n",
       "      <th>P/E</th>\n",
       "      <th>Forward P/E</th>\n",
       "      <th>PEG</th>\n",
       "      <th>Debt/Eq</th>\n",
       "      <th>EPS (ttm)</th>\n",
       "      <th>Dividend %</th>\n",
       "      <th>ROE</th>\n",
       "      <th>ROI</th>\n",
       "      <th>EPS Q/Q</th>\n",
       "      <th>Insider Own</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>XOM</th>\n",
       "      <td>0.91</td>\n",
       "      <td>12.86</td>\n",
       "      <td>21.55</td>\n",
       "      <td>2.27</td>\n",
       "      <td>0.25</td>\n",
       "      <td>3.19</td>\n",
       "      <td>8.50</td>\n",
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       "      <th>NL</th>\n",
       "      <td>0.42</td>\n",
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       "      <td>0.00</td>\n",
       "      <td>0.53</td>\n",
       "      <td>6.11</td>\n",
       "      <td>8.5</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>78.2</td>\n",
       "      <td>82.98</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      P/B    P/E  Forward P/E   PEG  Debt/Eq  EPS (ttm)  Dividend %  ROE  ROI  \\\n",
       "XOM  0.91  12.86        21.55  2.27     0.25       3.19        8.50  7.5  2.3   \n",
       "NL   0.42   4.94          NaN   NaN     0.00       0.53        6.11  8.5 -0.7   \n",
       "\n",
       "     EPS Q/Q  Insider Own  \n",
       "XOM    -17.3         0.20  \n",
       "NL      78.2        82.98  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered = df[(df['P/E'].astype(float)<15) & (df['P/B'].astype(float) < 1)]\n",
    "df_filtered"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Yvn_jxcQfYdf"
   },
   "source": [
    "### 2. Further filter companies which have demonstrated earning power \n",
    "EPS Q/Q > 10%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    "colab_type": "code",
    "id": "jptN2AwufYdi",
    "outputId": "4fe4f580-8aeb-4859-a692-684d4513703b"
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   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P/B</th>\n",
       "      <th>P/E</th>\n",
       "      <th>Forward P/E</th>\n",
       "      <th>PEG</th>\n",
       "      <th>Debt/Eq</th>\n",
       "      <th>EPS (ttm)</th>\n",
       "      <th>Dividend %</th>\n",
       "      <th>ROE</th>\n",
       "      <th>ROI</th>\n",
       "      <th>EPS Q/Q</th>\n",
       "      <th>Insider Own</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NL</th>\n",
       "      <td>0.42</td>\n",
       "      <td>4.94</td>\n",
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       "      <td>0.0</td>\n",
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      "text/plain": [
       "     P/B   P/E  Forward P/E  PEG  Debt/Eq  EPS (ttm)  Dividend %  ROE  ROI  \\\n",
       "NL  0.42  4.94          NaN  NaN      0.0       0.53        6.11  8.5 -0.7   \n",
       "\n",
       "    EPS Q/Q  Insider Own  \n",
       "NL     78.2        82.98  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered = df_filtered[df_filtered['EPS Q/Q'].astype(float) > 10]\n",
    "df_filtered"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mpRquAcLfYd9"
   },
   "source": [
    "### Management having substantial ownership in the business\n",
    "Insider Own > 30%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 141
    },
    "colab_type": "code",
    "id": "OT3niWUafYeI",
    "outputId": "bb70c961-2d6d-49aa-cc49-f182a2b7f301"
   },
   "outputs": [
    {
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       "      <td>0.24</td>\n",
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       "      <th>NL</th>\n",
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       "      <td>0.34</td>\n",
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      "text/plain": [
       "      P/B   P/E  Forward P/E  PEG  Debt/Eq  EPS (ttm)  Dividend %   ROE   ROI  \\\n",
       "MT   0.24   NaN         6.19  NaN     0.37      -2.42        2.20  -6.0  -2.1   \n",
       "NL   0.42  4.94          NaN  NaN     0.00       0.53        6.11   8.5  -0.7   \n",
       "LPL  0.34   NaN          NaN  NaN     1.20      -3.23         NaN -21.7 -10.9   \n",
       "\n",
       "     EPS Q/Q  Insider Own  \n",
       "MT    -259.0        44.80  \n",
       "NL      78.2        82.98  \n",
       "LPL      NaN        51.10  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[df['Insider Own'].astype(float) > 30]\n",
    "df"
   ]
  }
 ],
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