yahoo_market_v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "from selenium import webdriver\n",
    "import chromedriver_binary\n",
    "import string\n",
    "\n",
    "pd.options.display.float_format = '{:.0f}'.format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "is_link = 'https://finance.yahoo.com/quote/AAPL/financials?p=AAPL'\n",
    "bs_link = 'https://finance.yahoo.com/quote/AAPL/balance-sheet?p=AAPL'\n",
    "cf_link = 'https://finance.yahoo.com/quote/AAPL/cash-flow?p=AAPL'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ticker = input('Enter your company ticker symbol here: ')\n",
    "# link = f'https://finance.yahoo.com/quote/{ticker}/financials?p={ticker}'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "driver = webdriver.Chrome()\n",
    "driver.get(is_link)\n",
    "html = driver.execute_script('return document.body.innerHTML;')\n",
    "soup = BeautifulSoup(html,'lxml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "close_price = [entry.text for entry in soup.find_all('span', {'class':'Trsdu(0.3s) Fw(b) Fz(36px) Mb(-4px) D(ib)'})]\n",
    "after_hours_price = [entry.text for entry in soup.find_all('span', {'class':'C($primaryColor) Fz(24px) Fw(b)'})]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['309.51']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "close_price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = soup.find_all('div', class_='D(tbr)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "headers = []\n",
    "temp_list = []\n",
    "label_list = []\n",
    "final = []\n",
    "index = 0\n",
    "\n",
    "#create headers\n",
    "for item in features[0].find_all('div', class_='D(ib)'):\n",
    "    headers.append(item.text)\n",
    "\n",
    "#statement contents\n",
    "while index <= len(features)-1:\n",
    "    #filter for each line of the statement\n",
    "    temp = features[index].find_all('div', class_='D(tbc)')\n",
    "    for line in temp:\n",
    "        #each item adding to a temporary list\n",
    "        temp_list.append(line.text)\n",
    "    #temp_list added to final list\n",
    "    final.append(temp_list)\n",
    "    #clear temp_list\n",
    "    temp_list = []\n",
    "    index+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(final[1:])\n",
    "df.columns = headers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#function to make all values numerical (or - for NaNs)\n",
    "def convert_to_numeric(column):\n",
    "\n",
    "    first_col = [i.replace(',','') for i in column]\n",
    "    second_col = [i.replace('-','') for i in first_col]\n",
    "    final_col = pd.to_numeric(second_col)\n",
    "    \n",
    "    return final_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "for column in headers[1:]:\n",
    "    \n",
    "    df[column] = convert_to_numeric(df[column])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_df = df.fillna('-')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Breakdown</th>\n",
       "      <th>ttm</th>\n",
       "      <th>9/30/2019</th>\n",
       "      <th>9/30/2018</th>\n",
       "      <th>9/30/2017</th>\n",
       "      <th>9/30/2016</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Total Revenue</td>\n",
       "      <td>267683000</td>\n",
       "      <td>260174000</td>\n",
       "      <td>265595000</td>\n",
       "      <td>229234000</td>\n",
       "      <td>215639000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cost of Revenue</td>\n",
       "      <td>166105000</td>\n",
       "      <td>161782000</td>\n",
       "      <td>163756000</td>\n",
       "      <td>141048000</td>\n",
       "      <td>131376000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Gross Profit</td>\n",
       "      <td>101578000</td>\n",
       "      <td>98392000</td>\n",
       "      <td>101839000</td>\n",
       "      <td>88186000</td>\n",
       "      <td>84263000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Operating Expenses</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Research Development</td>\n",
       "      <td>16766000</td>\n",
       "      <td>16217000</td>\n",
       "      <td>14236000</td>\n",
       "      <td>11581000</td>\n",
       "      <td>10045000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Selling General and Administrative</td>\n",
       "      <td>18659000</td>\n",
       "      <td>18245000</td>\n",
       "      <td>16705000</td>\n",
       "      <td>15261000</td>\n",
       "      <td>14194000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Total Operating Expenses</td>\n",
       "      <td>35425000</td>\n",
       "      <td>34462000</td>\n",
       "      <td>30941000</td>\n",
       "      <td>26842000</td>\n",
       "      <td>24239000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Operating Income or Loss</td>\n",
       "      <td>66153000</td>\n",
       "      <td>63930000</td>\n",
       "      <td>70898000</td>\n",
       "      <td>61344000</td>\n",
       "      <td>60024000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Interest Expense</td>\n",
       "      <td>-</td>\n",
       "      <td>3576000</td>\n",
       "      <td>3240000</td>\n",
       "      <td>2323000</td>\n",
       "      <td>1456000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Total Other Income/Expenses Net</td>\n",
       "      <td>628000</td>\n",
       "      <td>1807000</td>\n",
       "      <td>441000</td>\n",
       "      <td>133000</td>\n",
       "      <td>1195000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Income Before Tax</td>\n",
       "      <td>67749000</td>\n",
       "      <td>65737000</td>\n",
       "      <td>72903000</td>\n",
       "      <td>64089000</td>\n",
       "      <td>61372000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Income Tax Expense</td>\n",
       "      <td>10222000</td>\n",
       "      <td>10481000</td>\n",
       "      <td>13372000</td>\n",
       "      <td>15738000</td>\n",
       "      <td>15685000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Income from Continuing Operations</td>\n",
       "      <td>57527000</td>\n",
       "      <td>55256000</td>\n",
       "      <td>59531000</td>\n",
       "      <td>48351000</td>\n",
       "      <td>45687000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Net Income</td>\n",
       "      <td>57527000</td>\n",
       "      <td>55256000</td>\n",
       "      <td>59531000</td>\n",
       "      <td>48351000</td>\n",
       "      <td>45687000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Net Income available to common shareholders</td>\n",
       "      <td>57527000</td>\n",
       "      <td>55256000</td>\n",
       "      <td>59531000</td>\n",
       "      <td>48351000</td>\n",
       "      <td>45687000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Reported EPS</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Basic</td>\n",
       "      <td>-</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Diluted</td>\n",
       "      <td>-</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Weighted average shares outstanding</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Basic</td>\n",
       "      <td>-</td>\n",
       "      <td>4617834</td>\n",
       "      <td>4955377</td>\n",
       "      <td>5217242</td>\n",
       "      <td>5470820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Diluted</td>\n",
       "      <td>-</td>\n",
       "      <td>4648913</td>\n",
       "      <td>5000109</td>\n",
       "      <td>5251692</td>\n",
       "      <td>5500281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>EBITDA</td>\n",
       "      <td>-</td>\n",
       "      <td>76477000</td>\n",
       "      <td>87046000</td>\n",
       "      <td>76569000</td>\n",
       "      <td>73333000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Breakdown       ttm 9/30/2019 9/30/2018  \\\n",
       "0                                 Total Revenue 267683000 260174000 265595000   \n",
       "1                               Cost of Revenue 166105000 161782000 163756000   \n",
       "2                                  Gross Profit 101578000  98392000 101839000   \n",
       "3                            Operating Expenses         -         -         -   \n",
       "4                          Research Development  16766000  16217000  14236000   \n",
       "5            Selling General and Administrative  18659000  18245000  16705000   \n",
       "6                      Total Operating Expenses  35425000  34462000  30941000   \n",
       "7                      Operating Income or Loss  66153000  63930000  70898000   \n",
       "8                              Interest Expense         -   3576000   3240000   \n",
       "9               Total Other Income/Expenses Net    628000   1807000    441000   \n",
       "10                            Income Before Tax  67749000  65737000  72903000   \n",
       "11                           Income Tax Expense  10222000  10481000  13372000   \n",
       "12            Income from Continuing Operations  57527000  55256000  59531000   \n",
       "13                                   Net Income  57527000  55256000  59531000   \n",
       "14  Net Income available to common shareholders  57527000  55256000  59531000   \n",
       "15                                 Reported EPS         -         -         -   \n",
       "16                                        Basic         -        12        12   \n",
       "17                                      Diluted         -        12        12   \n",
       "18          Weighted average shares outstanding         -         -         -   \n",
       "19                                        Basic         -   4617834   4955377   \n",
       "20                                      Diluted         -   4648913   5000109   \n",
       "21                                       EBITDA         -  76477000  87046000   \n",
       "\n",
       "   9/30/2017 9/30/2016  \n",
       "0  229234000 215639000  \n",
       "1  141048000 131376000  \n",
       "2   88186000  84263000  \n",
       "3          -         -  \n",
       "4   11581000  10045000  \n",
       "5   15261000  14194000  \n",
       "6   26842000  24239000  \n",
       "7   61344000  60024000  \n",
       "8    2323000   1456000  \n",
       "9     133000   1195000  \n",
       "10  64089000  61372000  \n",
       "11  15738000  15685000  \n",
       "12  48351000  45687000  \n",
       "13  48351000  45687000  \n",
       "14  48351000  45687000  \n",
       "15         -         -  \n",
       "16         9         8  \n",
       "17         9         8  \n",
       "18         -         -  \n",
       "19   5217242   5470820  \n",
       "20   5251692   5500281  \n",
       "21  76569000  73333000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ratios\n",
    "# value a company\n",
    "# investment analysis - quantitative financial analysis, look at trends in all of their metrics\n",
    "# sales growth obvious, but like for Amazon, their cash flow from payables/receivables\n",
    "# what's the intrinsic value of apple and other companies? make it generalizable so I can apply this \n",
    "# make a formula to make a projection baseline for companies and their Free Cash Flow and discount it back"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}