ratio_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "67acaf53",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests\n",
    "\n",
    "def dow_jones_symbols():\n",
    "    \"\"\"\n",
    "    Returns a list of the 30 stocks in the Dow Jones.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    list\n",
    "        a list of strings that are stock symbols which make up the Dow Jones Industrial Average\n",
    "    \"\"\"\n",
    "\n",
    "    headers = {\n",
    "        'authority': 'quote.cnbc.com',\n",
    "        'accept': '*/*',\n",
    "        'accept-language': 'en-US,en;q=0.9',\n",
    "        'origin': 'https://www.cnbc.com',\n",
    "        'referer': 'https://www.cnbc.com/',\n",
    "        'sec-ch-ua': '\"Not?A_Brand\";v=\"8\", \"Chromium\";v=\"108\", \"Google Chrome\";v=\"108\"',\n",
    "        'sec-ch-ua-mobile': '?0',\n",
    "        'sec-ch-ua-platform': '\"Windows\"',\n",
    "        'sec-fetch-dest': 'empty',\n",
    "        'sec-fetch-mode': 'cors',\n",
    "        'sec-fetch-site': 'same-site',\n",
    "        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36',\n",
    "    }\n",
    "\n",
    "    params = {\n",
    "        'symbols': 'AXP|AMGN|AAPL|BA|CAT|CSCO|CVX|GS|HD|HON|IBM|INTC|JNJ|KO|JPM|MCD|MMM|MRK|MSFT|NKE|PG|TRV|UNH|CRM|VZ|V|WBA|WMT|DIS|DOW',\n",
    "        'requestMethod': 'itv',\n",
    "        'noform': '1',\n",
    "        'partnerId': '2',\n",
    "        'fund': '1',\n",
    "        'exthrs': '1',\n",
    "        'output': 'json',\n",
    "        'events': '1',\n",
    "    }\n",
    "    \n",
    "    response = requests.get(\n",
    "        'https://quote.cnbc.com/quote-html-webservice/restQuote/symbolType/symbol',\n",
    "        params=params,\n",
    "        headers=headers,\n",
    "    )\n",
    "    data = response.json()['FormattedQuoteResult']['FormattedQuote']\n",
    "    \n",
    "    symbols = []\n",
    "    for i in data:\n",
    "        symbol = i['symbol']\n",
    "        symbols.append(symbol)\n",
    "\n",
    "    dj = pd.DataFrame(symbols, columns = ['Symbol'])\n",
    "    dj = dj.sort_values(by=['Symbol'])\n",
    "    dow_jones_list = []\n",
    "    for i in dj['Symbol']:\n",
    "        dow_jones_list.append(i)\n",
    "\n",
    "    return dow_jones_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "07490254",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AAPL',\n",
       " 'AMGN',\n",
       " 'AXP',\n",
       " 'BA',\n",
       " 'CAT',\n",
       " 'CRM',\n",
       " 'CSCO',\n",
       " 'CVX',\n",
       " 'DIS',\n",
       " 'DOW',\n",
       " 'GS',\n",
       " 'HD',\n",
       " 'HON',\n",
       " 'IBM',\n",
       " 'INTC',\n",
       " 'JNJ',\n",
       " 'JPM',\n",
       " 'KO',\n",
       " 'MCD',\n",
       " 'MMM',\n",
       " 'MRK',\n",
       " 'MSFT',\n",
       " 'NKE',\n",
       " 'PG',\n",
       " 'TRV',\n",
       " 'UNH',\n",
       " 'V',\n",
       " 'VZ',\n",
       " 'WBA',\n",
       " 'WMT']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dow_jones_symbols()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6b2bae21",
   "metadata": {},
   "outputs": [],
   "source": [
    "def debt_to_equity(df, symbol=\"\"):\n",
    "    for j in df:\n",
    "        if j == 'ticker' or j == 'items':\n",
    "            continue\n",
    "        df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "        df[j] = pd.to_numeric(df[j])\\\n",
    "\n",
    "    df_columns = []\n",
    "\n",
    "    for col in df.columns:\n",
    "        df_columns.append(col)\n",
    "\n",
    "    df_columns.insert(1, df_columns[-1])\n",
    "    del df_columns[-1]\n",
    "\n",
    "    first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Liabilities'), df_columns[2:]]\n",
    "    second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Equity'), df_columns[2:]]\n",
    "#     print(first_row)\n",
    "#     print(second_row)\n",
    "    third_row = first_row / second_row.values\n",
    "#     print(third_row)\n",
    "    third_row['ticker'] = symbol\n",
    "    third_row['items'] = \"Debt-to-Equity Ratio\"\n",
    "    third_row = third_row[df_columns]\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1be8c18e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "32  Debt-to-Equity Ratio   AAPL       NaN        NaN   4.202777   4.787754   \n",
      "25  Debt-to-Equity Ratio   AMZN  2.042056   2.065402   2.194228   2.115609   \n",
      "46  Debt-to-Equity Ratio   DELL       NaN        NaN        NaN        NaN   \n",
      "41  Debt-to-Equity Ratio   GOOG  0.427735   0.405868   0.390597   0.412533   \n",
      "41  Debt-to-Equity Ratio  GOOGL  0.427735   0.405868   0.390597   0.412533   \n",
      "44  Debt-to-Equity Ratio    HPQ       NaN -17.714777 -22.022655 -17.931406   \n",
      "37  Debt-to-Equity Ratio   META  0.329183   0.332635   0.349949   0.441601   \n",
      "37  Debt-to-Equity Ratio   MSFT       NaN        NaN   1.127298   1.115140   \n",
      "\n",
      "      Q4 2022    Q1 2023   Q2 2023    Q3 2023  \n",
      "32   5.961537   5.112557       NaN        NaN  \n",
      "25        NaN        NaN       NaN        NaN  \n",
      "46 -56.035608 -36.908205 -32.04021 -25.552321  \n",
      "41        NaN        NaN       NaN        NaN  \n",
      "41        NaN        NaN       NaN        NaN  \n",
      "44 -14.223783        NaN       NaN        NaN  \n",
      "37        NaN        NaN       NaN        NaN  \n",
      "37   1.190679   1.072894       NaN        NaN  \n",
      "                   items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "25  Debt-to-Equity Ratio   AMGN       NaN  63.624454  23.511782  16.437722   \n",
      "33  Debt-to-Equity Ratio   ABBV  8.509930   7.795124   8.771787   7.836126   \n",
      "37  Debt-to-Equity Ratio    AZN  1.683177   1.759301   1.687827   1.680737   \n",
      "30  Debt-to-Equity Ratio   GILD  2.225212   2.165554   2.106839   1.967459   \n",
      "35  Debt-to-Equity Ratio    JNJ  1.458938   1.387330   1.327540   1.347538   \n",
      "37  Debt-to-Equity Ratio   MRNA  0.744008   0.616925   0.448040   0.448199   \n",
      "44  Debt-to-Equity Ratio    PFE  1.350725   1.230430   1.239359   1.108882   \n",
      "31  Debt-to-Equity Ratio   REGN  0.355160   0.323073   0.315062   0.291012   \n",
      "\n",
      "      Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "25  16.787763      NaN      NaN      NaN  \n",
      "33        NaN      NaN      NaN      NaN  \n",
      "37        NaN      NaN      NaN      NaN  \n",
      "30        NaN      NaN      NaN      NaN  \n",
      "35        NaN      NaN      NaN      NaN  \n",
      "37        NaN      NaN      NaN      NaN  \n",
      "44        NaN      NaN      NaN      NaN  \n",
      "31        NaN      NaN      NaN      NaN  \n",
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "23  Debt-to-Equity Ratio    AXP        NaN   7.750480   7.835722   7.977235   \n",
      "31  Debt-to-Equity Ratio    BAC  10.736002  11.145598  10.562237  10.401408   \n",
      "31  Debt-to-Equity Ratio      C  10.345201  11.109236  10.963500  10.991660   \n",
      "28  Debt-to-Equity Ratio    COF   6.084845   6.706008   7.243550   7.734236   \n",
      "23  Debt-to-Equity Ratio    DFS   7.222106   6.996129   7.326068   7.531849   \n",
      "30  Debt-to-Equity Ratio    JPM  11.727723  12.832462  12.424456  12.102945   \n",
      "36  Debt-to-Equity Ratio     MA   4.151668   4.283338   4.871172   4.912907   \n",
      "29  Debt-to-Equity Ratio   PYPL   2.488885   2.679319   2.936359   2.771960   \n",
      "19  Debt-to-Equity Ratio    SYF   6.011937   6.099940   6.108191   6.744082   \n",
      "29  Debt-to-Equity Ratio      V        NaN   1.263607   1.273139   1.407068   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "23  8.240986      NaN      NaN      NaN  \n",
      "31       NaN      NaN      NaN      NaN  \n",
      "31       NaN      NaN      NaN      NaN  \n",
      "28       NaN      NaN      NaN      NaN  \n",
      "23       NaN      NaN      NaN      NaN  \n",
      "30       NaN      NaN      NaN      NaN  \n",
      "36       NaN      NaN      NaN      NaN  \n",
      "29       NaN      NaN      NaN      NaN  \n",
      "19       NaN      NaN      NaN      NaN  \n",
      "29  1.402996      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022    Q2 2022   Q3 2022  \\\n",
      "38  Debt-to-Equity Ratio     BA       NaN -9.819392 -10.099879 -8.772078   \n",
      "28  Debt-to-Equity Ratio     AM  1.424136  1.469469   1.504484  1.515371   \n",
      "30  Debt-to-Equity Ratio    HXL  0.897712  0.918628   0.904730  0.921107   \n",
      "33  Debt-to-Equity Ratio    RTX  1.208956  1.199304   1.257449  1.254335   \n",
      "30  Debt-to-Equity Ratio    TDG       NaN -8.308014  -7.499138 -7.323589   \n",
      "26  Debt-to-Equity Ratio    TXT  1.322377  1.300275   1.334804  1.359657   \n",
      "47  Debt-to-Equity Ratio    WWD       NaN  0.815115   0.896199  0.966492   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "38 -9.631871      NaN      NaN      NaN  \n",
      "28       NaN      NaN      NaN      NaN  \n",
      "30       NaN      NaN      NaN      NaN  \n",
      "33       NaN      NaN      NaN      NaN  \n",
      "30 -5.799099      NaN      NaN      NaN  \n",
      "26       NaN      NaN      NaN      NaN  \n",
      "47  1.002104      NaN      NaN      NaN  \n",
      "                   items ticker  Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "33  Debt-to-Equity Ratio    CAT      NaN  3.821330  4.157182  4.189340   \n",
      "40  Debt-to-Equity Ratio     DE      NaN  3.471692  3.448741  3.561393   \n",
      "34  Debt-to-Equity Ratio    TEX  1.58018  1.639138  1.854147  1.876329   \n",
      "34  Debt-to-Equity Ratio    TTC      NaN  1.904464  1.843137  1.672883   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "33  4.163715      NaN      NaN      NaN  \n",
      "40  3.443293      NaN      NaN      NaN  \n",
      "34       NaN      NaN      NaN      NaN  \n",
      "34  1.630178      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022    Q3 2022  \\\n",
      "24  Debt-to-Equity Ratio    CRM       NaN       NaN       NaN        NaN   \n",
      "29  Debt-to-Equity Ratio   ADBE       NaN  0.885735  0.882445   0.860711   \n",
      "43  Debt-to-Equity Ratio   CSCO       NaN       NaN  1.386621   1.296955   \n",
      "41  Debt-to-Equity Ratio   GOOG  0.427735  0.405868  0.390597   0.412533   \n",
      "41  Debt-to-Equity Ratio  GOOGL  0.427735  0.405868  0.390597   0.412533   \n",
      "32  Debt-to-Equity Ratio   INTU       NaN       NaN  0.686630   0.681151   \n",
      "37  Debt-to-Equity Ratio   MSFT       NaN       NaN  1.127298   1.115140   \n",
      "28  Debt-to-Equity Ratio   ORCL       NaN       NaN       NaN -13.493560   \n",
      "32  Debt-to-Equity Ratio    SAP  0.831750  0.916537  0.896772   0.821513   \n",
      "\n",
      "      Q4 2022    Q1 2023    Q2 2023   Q3 2023  \n",
      "24        NaN   0.579965   0.566575  0.548146  \n",
      "29   0.933314        NaN        NaN       NaN  \n",
      "43   1.363463   1.310638        NaN       NaN  \n",
      "41        NaN        NaN        NaN       NaN  \n",
      "41        NaN        NaN        NaN       NaN  \n",
      "32   0.686880   0.685753        NaN       NaN  \n",
      "37   1.190679   1.072894        NaN       NaN  \n",
      "28 -18.571865 -23.180255 -31.256477       NaN  \n",
      "32        NaN        NaN        NaN       NaN  \n",
      "                   items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "45  Debt-to-Equity Ratio   CSCO       NaN        NaN        NaN   1.296955   \n",
      "25  Debt-to-Equity Ratio   AMZN  2.042056   2.065402   2.194228   2.115609   \n",
      "30  Debt-to-Equity Ratio   AVGO       NaN   2.188088   2.421218   2.416651   \n",
      "46  Debt-to-Equity Ratio   DELL       NaN        NaN        NaN        NaN   \n",
      "38  Debt-to-Equity Ratio   FTNT  6.569054  24.922018 -14.470738  -9.403150   \n",
      "37  Debt-to-Equity Ratio   MSFT       NaN        NaN   1.127298   1.115140   \n",
      "30  Debt-to-Equity Ratio   PANW       NaN        NaN  87.144068  31.840237   \n",
      "32  Debt-to-Equity Ratio    RNG  3.793680   9.354839  14.555556 -52.466667   \n",
      "37  Debt-to-Equity Ratio    VMW       NaN        NaN        NaN        NaN   \n",
      "38  Debt-to-Equity Ratio     ZM       NaN        NaN        NaN        NaN   \n",
      "30  Debt-to-Equity Ratio     ZS       NaN        NaN   3.493506   3.746241   \n",
      "\n",
      "      Q4 2022    Q1 2023     Q2 2023    Q3 2023  \n",
      "45   1.363463   1.310638    1.310845        NaN  \n",
      "25        NaN        NaN         NaN        NaN  \n",
      "30   2.225549        NaN         NaN        NaN  \n",
      "46 -56.035608 -36.908205  -32.040210 -25.552321  \n",
      "38        NaN        NaN         NaN        NaN  \n",
      "37   1.190679   1.072894         NaN        NaN  \n",
      "30  57.352381  23.692913         NaN        NaN  \n",
      "32        NaN        NaN         NaN        NaN  \n",
      "37 -33.735160 -67.749392  198.950000  33.895782  \n",
      "38   0.306401   0.337761    0.343406   0.361536  \n",
      "30   3.942408   5.577726         NaN        NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "41  Debt-to-Equity Ratio    CVX       NaN  0.703253  0.679774  0.636848   \n",
      "44  Debt-to-Equity Ratio     BP  2.806793  3.668510  3.490880  3.872415   \n",
      "38  Debt-to-Equity Ratio    COP  0.996674  0.895810  0.866320  0.932334   \n",
      "8   Debt-to-Equity Ratio   ROSN       NaN       NaN       NaN       NaN   \n",
      "33  Debt-to-Equity Ratio   SHEL  1.351506  1.414726  1.351171  1.344807   \n",
      "27  Debt-to-Equity Ratio    XOM  1.010494  1.096569  1.074116  0.988995   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "41  0.617942      NaN      NaN      NaN  \n",
      "44       NaN      NaN      NaN      NaN  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "8        NaN      NaN      NaN      NaN  \n",
      "33       NaN      NaN      NaN      NaN  \n",
      "27       NaN      NaN      NaN      NaN  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "28  Debt-to-Equity Ratio    DIS       NaN   1.262430   1.233693   1.206205   \n",
      "30  Debt-to-Equity Ratio   AAPL       NaN   4.299324   4.202777   4.787754   \n",
      "29  Debt-to-Equity Ratio   CHTR  9.141708  10.935987  13.501265  15.162560   \n",
      "34  Debt-to-Equity Ratio  CMCSA  1.871259   1.894373   1.920745   2.167132   \n",
      "39  Debt-to-Equity Ratio   DISH  2.091518   2.079166   2.012932   1.884226   \n",
      "25  Debt-to-Equity Ratio    FOX       NaN        NaN   1.029091   0.965714   \n",
      "25  Debt-to-Equity Ratio   FOXA       NaN        NaN   1.029091   0.965714   \n",
      "27  Debt-to-Equity Ratio   NFLX  1.813048   1.583846   1.429807   1.316933   \n",
      "33  Debt-to-Equity Ratio   PARA  1.616731   1.561022   1.500922   1.529562   \n",
      "33  Debt-to-Equity Ratio  PARAA  1.616731   1.561022   1.500922   1.529562   \n",
      "\n",
      "     Q4 2022   Q1 2023  Q2 2023  Q3 2023  \n",
      "28  1.143304       NaN      NaN      NaN  \n",
      "30  5.961537       NaN      NaN      NaN  \n",
      "29       NaN       NaN      NaN      NaN  \n",
      "34       NaN       NaN      NaN      NaN  \n",
      "39       NaN       NaN      NaN      NaN  \n",
      "25  0.956522  0.946359      NaN      NaN  \n",
      "25  0.956522  0.946359      NaN      NaN  \n",
      "27       NaN       NaN      NaN      NaN  \n",
      "33       NaN       NaN      NaN      NaN  \n",
      "33       NaN       NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "45  Debt-to-Equity Ratio    DOW  2.467658  2.354608  2.275339  2.287354   \n",
      "34  Debt-to-Equity Ratio    APD       NaN  0.962025  0.967037  1.014732   \n",
      "51  Debt-to-Equity Ratio     DD  0.729164  0.734146  0.740834  0.770404   \n",
      "37  Debt-to-Equity Ratio    EMN  1.720722  1.682165  1.794477  1.783247   \n",
      "32  Debt-to-Equity Ratio    HUN  1.151168  1.171864  1.113669  1.172009   \n",
      "32  Debt-to-Equity Ratio    LIN  0.853185  0.926472  0.963124  0.975205   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "45       NaN      NaN      NaN      NaN  \n",
      "34  1.068853      NaN      NaN      NaN  \n",
      "51       NaN      NaN      NaN      NaN  \n",
      "37       NaN      NaN      NaN      NaN  \n",
      "32       NaN      NaN      NaN      NaN  \n",
      "32       NaN      NaN      NaN      NaN  \n",
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "30  Debt-to-Equity Ratio     GS  12.317941  12.792562  12.584546  12.043792   \n",
      "31  Debt-to-Equity Ratio    BAC  10.736002  11.145598  10.562237  10.401408   \n",
      "33  Debt-to-Equity Ratio     BK   9.327601  10.335463  10.043846   9.769635   \n",
      "26  Debt-to-Equity Ratio    BLK   3.049771   2.823175   2.396317   2.106130   \n",
      "31  Debt-to-Equity Ratio      C  10.345201  11.109236  10.963500  10.991660   \n",
      "25  Debt-to-Equity Ratio     MS  10.268292  10.877756  10.553368  10.484185   \n",
      "18  Debt-to-Equity Ratio   SCHW  10.860258  13.157553  13.322939  14.592533   \n",
      "37  Debt-to-Equity Ratio    UBS  17.416505  18.367983  18.582954  18.939254   \n",
      "36  Debt-to-Equity Ratio    WFC   9.383826   9.821672   9.596073   9.657561   \n",
      "\n",
      "    Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "30      NaN      NaN      NaN      NaN  \n",
      "31      NaN      NaN      NaN      NaN  \n",
      "33      NaN      NaN      NaN      NaN  \n",
      "26      NaN      NaN      NaN      NaN  \n",
      "31      NaN      NaN      NaN      NaN  \n",
      "25      NaN      NaN      NaN      NaN  \n",
      "18      NaN      NaN      NaN      NaN  \n",
      "37      NaN      NaN      NaN      NaN  \n",
      "36      NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "25  Debt-to-Equity Ratio     HD       NaN       NaN       NaN       NaN   \n",
      "25  Debt-to-Equity Ratio   AMZN  2.042056  2.065402  2.194228  2.115609   \n",
      "21  Debt-to-Equity Ratio   FAST  0.413215  0.421706  0.444794  0.463777   \n",
      "30  Debt-to-Equity Ratio    GWW  2.517609  2.360404  2.202635  2.120017   \n",
      "28  Debt-to-Equity Ratio    LOW       NaN       NaN       NaN       NaN   \n",
      "37  Debt-to-Equity Ratio    SHW  7.480509  8.726947  8.911461  7.562741   \n",
      "25  Debt-to-Equity Ratio    TGT       NaN       NaN       NaN       NaN   \n",
      "22  Debt-to-Equity Ratio   TSCO  2.878183  3.294413  3.111285  3.076249   \n",
      "24  Debt-to-Equity Ratio    WMT       NaN       NaN       NaN       NaN   \n",
      "\n",
      "      Q4 2022    Q1 2023     Q2 2023    Q3 2023  \n",
      "25 -43.379717 -45.802224  318.936709  58.218798  \n",
      "25        NaN        NaN         NaN        NaN  \n",
      "21        NaN        NaN         NaN        NaN  \n",
      "30        NaN        NaN         NaN        NaN  \n",
      "28 -10.269103  -8.230624   -6.534826  -4.650373  \n",
      "37        NaN        NaN         NaN        NaN  \n",
      "25   3.195135   3.718953    3.953739   4.047191  \n",
      "22        NaN        NaN         NaN        NaN  \n",
      "24   1.941155   2.200973    2.186827   2.427622  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "37  Debt-to-Equity Ratio    HON  2.471916  2.449605  2.549285  2.404699   \n",
      "40  Debt-to-Equity Ratio     GE  3.933614  3.921446  4.354844  4.746688   \n",
      "32  Debt-to-Equity Ratio   GRMN  0.284593  0.232677  0.332083  0.297550   \n",
      "40  Debt-to-Equity Ratio    JCI       NaN  1.447794  1.599843  1.647235   \n",
      "37  Debt-to-Equity Ratio    MMM  2.128539  2.071333  2.320768  2.279545   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "37       NaN      NaN      NaN      NaN  \n",
      "40       NaN      NaN      NaN      NaN  \n",
      "32       NaN      NaN      NaN      NaN  \n",
      "40  1.591468      NaN      NaN      NaN  \n",
      "37       NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022    Q3 2022  \\\n",
      "49  Debt-to-Equity Ratio    IBM  5.983810  5.996063  5.569272   5.268679   \n",
      "36  Debt-to-Equity Ratio    ACN       NaN       NaN  1.155545   1.155080   \n",
      "29  Debt-to-Equity Ratio   ADBE       NaN  0.885735  0.882445   0.860711   \n",
      "43  Debt-to-Equity Ratio   CSCO       NaN       NaN  1.386621   1.296955   \n",
      "46  Debt-to-Equity Ratio   DELL       NaN       NaN       NaN        NaN   \n",
      "41  Debt-to-Equity Ratio   GOOG  0.427735  0.405868  0.390597   0.412533   \n",
      "41  Debt-to-Equity Ratio  GOOGL  0.427735  0.405868  0.390597   0.412533   \n",
      "37  Debt-to-Equity Ratio    HPE       NaN  1.848361  1.743230   1.798263   \n",
      "37  Debt-to-Equity Ratio   MSFT       NaN       NaN  1.127298   1.115140   \n",
      "28  Debt-to-Equity Ratio   ORCL       NaN       NaN       NaN -13.493560   \n",
      "32  Debt-to-Equity Ratio    SAP  0.831750  0.916537  0.896772   0.821513   \n",
      "\n",
      "      Q4 2022    Q1 2023    Q2 2023    Q3 2023  \n",
      "49        NaN        NaN        NaN        NaN  \n",
      "36   1.138017   1.050751        NaN        NaN  \n",
      "29   0.933314        NaN        NaN        NaN  \n",
      "43   1.363463   1.310638        NaN        NaN  \n",
      "46 -56.035608 -36.908205 -32.040210 -25.552321  \n",
      "41        NaN        NaN        NaN        NaN  \n",
      "41        NaN        NaN        NaN        NaN  \n",
      "37   1.875705        NaN        NaN        NaN  \n",
      "37   1.190679   1.072894        NaN        NaN  \n",
      "28 -18.571865 -23.180255 -31.256477        NaN  \n",
      "32        NaN        NaN        NaN        NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "29  Debt-to-Equity Ratio   INTC  0.765429  0.709936  0.683673  0.750423   \n",
      "45  Debt-to-Equity Ratio   AMAT       NaN  1.138604  1.198722  1.167440   \n",
      "35  Debt-to-Equity Ratio    AMD  0.656529  0.209315  0.223549  0.243280   \n",
      "30  Debt-to-Equity Ratio   AVGO       NaN  2.188088  2.421218  2.416651   \n",
      "48  Debt-to-Equity Ratio     MU       NaN       NaN  0.331299  0.324973   \n",
      "33  Debt-to-Equity Ratio   NVDA       NaN       NaN       NaN       NaN   \n",
      "33  Debt-to-Equity Ratio   QCOM       NaN  2.778346  2.323980  1.929960   \n",
      "35  Debt-to-Equity Ratio    TXN  0.850746  0.803239  0.754400  0.796167   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2023  \n",
      "29       NaN       NaN       NaN       NaN  \n",
      "45  1.191734       NaN       NaN       NaN  \n",
      "35       NaN       NaN       NaN       NaN  \n",
      "30  2.225549       NaN       NaN       NaN  \n",
      "48  0.328130  0.376587       NaN       NaN  \n",
      "33  0.660416  0.717781  0.822817  0.896482  \n",
      "33  1.721035       NaN       NaN       NaN  \n",
      "35       NaN       NaN       NaN       NaN  \n",
      "                   items ticker   Q4 2021    Q1 2022   Q2 2022   Q3 2022  \\\n",
      "35  Debt-to-Equity Ratio    JNJ  1.458938   1.387330  1.327540  1.347538   \n",
      "36  Debt-to-Equity Ratio    ABT  1.100330   1.090652  1.033489  1.040673   \n",
      "37  Debt-to-Equity Ratio    AZN  1.683177   1.759301  1.687827  1.680737   \n",
      "42  Debt-to-Equity Ratio    MDT       NaN        NaN       NaN  0.747250   \n",
      "34  Debt-to-Equity Ratio    MRK  1.768018   1.609104  1.476586  1.408588   \n",
      "33  Debt-to-Equity Ratio   NOVN  2.764398  18.049473  8.338885       NaN   \n",
      "44  Debt-to-Equity Ratio    PFE  1.350725   1.230430  1.239359  1.108882   \n",
      "26  Debt-to-Equity Ratio     PG       NaN        NaN  1.721234  1.643410   \n",
      "42  Debt-to-Equity Ratio    ROG  0.428954   0.426141  0.475158  0.491743   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023  Q3 2023  \n",
      "35       NaN       NaN       NaN      NaN  \n",
      "36       NaN       NaN       NaN      NaN  \n",
      "37       NaN       NaN       NaN      NaN  \n",
      "42  0.731290  0.707023  0.797244      NaN  \n",
      "34       NaN       NaN       NaN      NaN  \n",
      "33       NaN       NaN       NaN      NaN  \n",
      "44       NaN       NaN       NaN      NaN  \n",
      "26  1.515787  1.638276       NaN      NaN  \n",
      "42       NaN       NaN       NaN      NaN  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "30  Debt-to-Equity Ratio    JPM  11.727723  12.832462  12.424456  12.102945   \n",
      "31  Debt-to-Equity Ratio    BAC  10.736002  11.145598  10.562237  10.401408   \n",
      "31  Debt-to-Equity Ratio    BMO        NaN  16.108755  14.879452  14.946771   \n",
      "31  Debt-to-Equity Ratio      C  10.345201  11.109236  10.963500  10.991660   \n",
      "26  Debt-to-Equity Ratio     RY        NaN  16.196242  16.722925  16.729812   \n",
      "40  Debt-to-Equity Ratio     TD        NaN  16.441070  17.360721  16.943027   \n",
      "36  Debt-to-Equity Ratio    WFC   9.383826   9.821672   9.596073   9.657561   \n",
      "\n",
      "      Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "30        NaN      NaN      NaN      NaN  \n",
      "31        NaN      NaN      NaN      NaN  \n",
      "31  15.036473      NaN      NaN      NaN  \n",
      "31        NaN      NaN      NaN      NaN  \n",
      "26  16.741514      NaN      NaN      NaN  \n",
      "40  16.215625      NaN      NaN      NaN  \n",
      "36        NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "35  Debt-to-Equity Ratio     KO  3.102526  2.786033  3.049946  3.054856   \n",
      "35  Debt-to-Equity Ratio   CCEP  3.136215       NaN  2.998683       NaN   \n",
      "43  Debt-to-Equity Ratio   COKE  3.839888  3.261194  2.971175  2.529931   \n",
      "28  Debt-to-Equity Ratio   FIZZ       NaN       NaN       NaN  1.077670   \n",
      "46  Debt-to-Equity Ratio    KDP  1.026189  1.008702  1.025442  1.049239   \n",
      "36  Debt-to-Equity Ratio    KHC  0.894478  0.890742  0.878761  0.869070   \n",
      "44  Debt-to-Equity Ratio   MDLZ  1.373342  1.414474  1.399549  1.553808   \n",
      "38  Debt-to-Equity Ratio   MNST  0.188518  0.192369  0.200617  0.203785   \n",
      "33  Debt-to-Equity Ratio    PEP  4.758088  4.107241  4.018218  3.977657   \n",
      "28  Debt-to-Equity Ratio   PRMW  1.820455  1.819923  1.842600  1.851148   \n",
      "43  Debt-to-Equity Ratio   SBUX       NaN -4.409483 -4.309991 -4.248644   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023  Q3 2023  \n",
      "35       NaN       NaN       NaN      NaN  \n",
      "35       NaN       NaN       NaN      NaN  \n",
      "43       NaN       NaN       NaN      NaN  \n",
      "28  0.953975  0.723485  0.694915      NaN  \n",
      "46       NaN       NaN       NaN      NaN  \n",
      "36       NaN       NaN       NaN      NaN  \n",
      "44       NaN       NaN       NaN      NaN  \n",
      "38       NaN       NaN       NaN      NaN  \n",
      "33       NaN       NaN       NaN      NaN  \n",
      "28       NaN       NaN       NaN      NaN  \n",
      "43 -4.213277       NaN       NaN      NaN  \n",
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "22  Debt-to-Equity Ratio    MCD -12.704847  -9.492405  -8.731240  -8.386841   \n",
      "25  Debt-to-Equity Ratio    CMG   1.896387   2.030459   2.038533   1.929523   \n",
      "36  Debt-to-Equity Ratio    DPZ  -1.396912  -1.398666  -1.399761  -1.381283   \n",
      "40  Debt-to-Equity Ratio   JACK        NaN  -3.237913  -4.600765  -4.729167   \n",
      "32  Debt-to-Equity Ratio   PZZA  -5.707447  -4.955357  -4.344000  -4.029197   \n",
      "38  Debt-to-Equity Ratio    QSR   9.391596   9.118777   9.277326   8.752270   \n",
      "43  Debt-to-Equity Ratio   SBUX        NaN  -4.409483  -4.309991  -4.248644   \n",
      "24  Debt-to-Equity Ratio   SHAK   2.556098   2.622500   2.672457   2.724566   \n",
      "33  Debt-to-Equity Ratio    WEN  10.699541  11.228571  12.040189  11.643021   \n",
      "25  Debt-to-Equity Ratio    YUM  -1.712528  -1.684961  -1.675770  -1.676539   \n",
      "46  Debt-to-Equity Ratio   YUMC   0.874008   0.833599   0.846225   0.822375   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "22       NaN      NaN      NaN      NaN  \n",
      "25       NaN      NaN      NaN      NaN  \n",
      "36       NaN      NaN      NaN      NaN  \n",
      "40 -4.971467      NaN      NaN      NaN  \n",
      "32       NaN      NaN      NaN      NaN  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "43 -4.213277      NaN      NaN      NaN  \n",
      "24       NaN      NaN      NaN      NaN  \n",
      "33       NaN      NaN      NaN      NaN  \n",
      "25       NaN      NaN      NaN      NaN  \n",
      "46       NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "37  Debt-to-Equity Ratio    MMM  2.128539  2.071333  2.320768  2.279545   \n",
      "51  Debt-to-Equity Ratio     DD  0.729164  0.734146  0.740834  0.770404   \n",
      "40  Debt-to-Equity Ratio     GE  3.933614  3.921446  4.354844  4.746688   \n",
      "37  Debt-to-Equity Ratio    HON  2.471916  2.449605  2.549285  2.404699   \n",
      "29  Debt-to-Equity Ratio    ITW  3.435034  3.547892  3.637655  4.053435   \n",
      "35  Debt-to-Equity Ratio    JNJ  1.458938  1.387330  1.327540  1.347538   \n",
      "\n",
      "    Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "37      NaN      NaN      NaN      NaN  \n",
      "51      NaN      NaN      NaN      NaN  \n",
      "40      NaN      NaN      NaN      NaN  \n",
      "37      NaN      NaN      NaN      NaN  \n",
      "29      NaN      NaN      NaN      NaN  \n",
      "35      NaN      NaN      NaN      NaN  \n",
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "34  Debt-to-Equity Ratio    MRK   1.768018   1.609104   1.476586   1.408588   \n",
      "36  Debt-to-Equity Ratio    ABT   1.100330   1.090652   1.033489   1.040673   \n",
      "51  Debt-to-Equity Ratio    BMY   2.041062   2.262635   2.078436   2.005601   \n",
      "35  Debt-to-Equity Ratio    GSK   4.254268   4.542859   4.438195   5.590144   \n",
      "35  Debt-to-Equity Ratio    JNJ   1.458938   1.387330   1.327540   1.347538   \n",
      "38  Debt-to-Equity Ratio    LLY   4.435572   4.028400   4.507782   3.713108   \n",
      "33  Debt-to-Equity Ratio   NOVN   2.764398  18.049473   8.338885        NaN   \n",
      "44  Debt-to-Equity Ratio    PFE   1.350725   1.230430   1.239359   1.108882   \n",
      "32  Debt-to-Equity Ratio    SAN  17.357702  17.431375  18.247243  18.948497   \n",
      "38  Debt-to-Equity Ratio    ZTS   2.059652   1.975526   2.006550   1.932447   \n",
      "\n",
      "    Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "34      NaN      NaN      NaN      NaN  \n",
      "36      NaN      NaN      NaN      NaN  \n",
      "51      NaN      NaN      NaN      NaN  \n",
      "35      NaN      NaN      NaN      NaN  \n",
      "35      NaN      NaN      NaN      NaN  \n",
      "38      NaN      NaN      NaN      NaN  \n",
      "33      NaN      NaN      NaN      NaN  \n",
      "44      NaN      NaN      NaN      NaN  \n",
      "32      NaN      NaN      NaN      NaN  \n",
      "38      NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022    Q3 2022  \\\n",
      "37  Debt-to-Equity Ratio   MSFT       NaN       NaN  1.127298   1.115140   \n",
      "30  Debt-to-Equity Ratio   AAPL       NaN  4.299324  4.202777   4.787754   \n",
      "30  Debt-to-Equity Ratio   AVGO       NaN  2.188088  2.421218   2.416651   \n",
      "24  Debt-to-Equity Ratio    CRM       NaN       NaN       NaN        NaN   \n",
      "43  Debt-to-Equity Ratio   CSCO       NaN       NaN  1.386621   1.296955   \n",
      "41  Debt-to-Equity Ratio   GOOG  0.427735  0.405868  0.390597   0.412533   \n",
      "41  Debt-to-Equity Ratio  GOOGL  0.427735  0.405868  0.390597   0.412533   \n",
      "49  Debt-to-Equity Ratio    IBM  5.983810  5.996063  5.569272   5.268679   \n",
      "28  Debt-to-Equity Ratio   ORCL       NaN       NaN       NaN -13.493560   \n",
      "32  Debt-to-Equity Ratio    SAP  0.831750  0.916537  0.896772   0.821513   \n",
      "\n",
      "      Q4 2022    Q1 2023    Q2 2023   Q3 2023  \n",
      "37   1.190679   1.072894        NaN       NaN  \n",
      "30   5.961537        NaN        NaN       NaN  \n",
      "30   2.225549        NaN        NaN       NaN  \n",
      "24   0.637835   0.579965   0.566575  0.548146  \n",
      "43   1.363463   1.310638        NaN       NaN  \n",
      "41        NaN        NaN        NaN       NaN  \n",
      "41        NaN        NaN        NaN       NaN  \n",
      "49        NaN        NaN        NaN       NaN  \n",
      "28 -18.571865 -23.180255 -31.256477       NaN  \n",
      "32        NaN        NaN        NaN       NaN  \n",
      "                   items ticker     Q4 2021    Q1 2022   Q2 2022   Q3 2022  \\\n",
      "27  Debt-to-Equity Ratio    NKE         NaN        NaN       NaN  1.604970   \n",
      "17  Debt-to-Equity Ratio    ADS    9.424736   8.231922  8.587253  8.153814   \n",
      "38  Debt-to-Equity Ratio   CROX  109.357143  11.808023  8.323171  6.199683   \n",
      "26  Debt-to-Equity Ratio    SKX    0.991715   0.943290  0.954333  0.930905   \n",
      "31  Debt-to-Equity Ratio     UA    1.389181        NaN       NaN       NaN   \n",
      "31  Debt-to-Equity Ratio    UAA    1.389181        NaN       NaN       NaN   \n",
      "32  Debt-to-Equity Ratio    VFC         NaN        NaN       NaN  2.705448   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023  Q3 2023  \n",
      "27  1.638636  1.596890  1.596058      NaN  \n",
      "17       NaN       NaN       NaN      NaN  \n",
      "38       NaN       NaN       NaN      NaN  \n",
      "26       NaN       NaN       NaN      NaN  \n",
      "31  1.575477  1.663968  1.626652      NaN  \n",
      "31  1.575477  1.663968  1.626652      NaN  \n",
      "32  2.779603  2.941229  3.466948      NaN  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "26  Debt-to-Equity Ratio     PG        NaN        NaN   1.721234   1.643410   \n",
      "31  Debt-to-Equity Ratio     CL  23.696223  47.981308  92.517857  25.186495   \n",
      "37  Debt-to-Equity Ratio     EL        NaN        NaN   2.550659   2.473008   \n",
      "35  Debt-to-Equity Ratio    JNJ   1.458938   1.387330   1.327540   1.347538   \n",
      "37  Debt-to-Equity Ratio     OR   0.450153   0.517838   0.553135   0.236248   \n",
      "\n",
      "     Q4 2022   Q1 2023  Q2 2023  Q3 2023  \n",
      "26  1.515787  1.638276      NaN      NaN  \n",
      "31       NaN       NaN      NaN      NaN  \n",
      "37  2.740608  2.623165      NaN      NaN  \n",
      "35       NaN       NaN      NaN      NaN  \n",
      "37       NaN       NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022    Q2 2022    Q3 2022  \\\n",
      "26  Debt-to-Equity Ratio    TRV  3.170250  3.645020   4.096922   4.742841   \n",
      "24  Debt-to-Equity Ratio    AIG  8.038025  9.251555  10.885542  12.400610   \n",
      "24  Debt-to-Equity Ratio    AIZ  5.208089  5.576977   6.114126   7.110759   \n",
      "29  Debt-to-Equity Ratio    ALL  2.949323  3.185335   3.789958   4.526849   \n",
      "30  Debt-to-Equity Ratio     CB  2.350203  2.492010   2.786769   3.158589   \n",
      "24  Debt-to-Equity Ratio   CINF  1.395040  1.501654   1.766228   1.990033   \n",
      "29  Debt-to-Equity Ratio    HIG  3.291767  3.733723   4.089414   4.542339   \n",
      "21  Debt-to-Equity Ratio      L  3.573910  3.774902   4.058480   4.424744   \n",
      "29  Debt-to-Equity Ratio    PGR  2.901547  3.335757   3.667348   4.111262   \n",
      "22  Debt-to-Equity Ratio    WRB  3.817075  3.697888   4.018729   4.212260   \n",
      "\n",
      "    Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "26      NaN      NaN      NaN      NaN  \n",
      "24      NaN      NaN      NaN      NaN  \n",
      "24      NaN      NaN      NaN      NaN  \n",
      "29      NaN      NaN      NaN      NaN  \n",
      "30      NaN      NaN      NaN      NaN  \n",
      "24      NaN      NaN      NaN      NaN  \n",
      "29      NaN      NaN      NaN      NaN  \n",
      "21      NaN      NaN      NaN      NaN  \n",
      "29      NaN      NaN      NaN      NaN  \n",
      "22      NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "21  Debt-to-Equity Ratio    UNH  1.957163  2.040403  2.160835  2.256223   \n",
      "31  Debt-to-Equity Ratio     CI  2.287676  2.311346  2.325852  2.201727   \n",
      "34  Debt-to-Equity Ratio    CVS  2.103550  2.154179  2.062872  2.271112   \n",
      "22  Debt-to-Equity Ratio    ELV  1.702718  1.793218  1.816849  1.862549   \n",
      "25  Debt-to-Equity Ratio    HUM  1.758582  2.022913  2.022595  2.123231   \n",
      "\n",
      "    Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "21      NaN      NaN      NaN      NaN  \n",
      "31      NaN      NaN      NaN      NaN  \n",
      "34      NaN      NaN      NaN      NaN  \n",
      "22      NaN      NaN      NaN      NaN  \n",
      "25      NaN      NaN      NaN      NaN  \n",
      "                   items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "29  Debt-to-Equity Ratio      V        NaN   1.263607   1.273139   1.407068   \n",
      "23  Debt-to-Equity Ratio    AXP   7.501961   7.750480   7.835722   7.977235   \n",
      "31  Debt-to-Equity Ratio    BAC  10.736002  11.145598  10.562237  10.401408   \n",
      "31  Debt-to-Equity Ratio      C  10.345201  11.109236  10.963500  10.991660   \n",
      "28  Debt-to-Equity Ratio    COF   6.084845   6.706008   7.243550   7.734236   \n",
      "23  Debt-to-Equity Ratio    DFS   7.222106   6.996129   7.326068   7.531849   \n",
      "30  Debt-to-Equity Ratio    JPM  11.727723  12.832462  12.424456  12.102945   \n",
      "36  Debt-to-Equity Ratio     MA   4.151668   4.283338   4.871172   4.912907   \n",
      "29  Debt-to-Equity Ratio   PYPL   2.488885   2.679319   2.936359   2.771960   \n",
      "19  Debt-to-Equity Ratio    SYF   6.011937   6.099940   6.108191   6.744082   \n",
      "36  Debt-to-Equity Ratio    WFC   9.383826   9.821672   9.596073   9.657561   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "29  1.402996      NaN      NaN      NaN  \n",
      "23       NaN      NaN      NaN      NaN  \n",
      "31       NaN      NaN      NaN      NaN  \n",
      "31       NaN      NaN      NaN      NaN  \n",
      "28       NaN      NaN      NaN      NaN  \n",
      "23       NaN      NaN      NaN      NaN  \n",
      "30       NaN      NaN      NaN      NaN  \n",
      "36       NaN      NaN      NaN      NaN  \n",
      "29       NaN      NaN      NaN      NaN  \n",
      "19       NaN      NaN      NaN      NaN  \n",
      "36       NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "38  Debt-to-Equity Ratio     VZ  3.482162  3.366133  3.303234  3.288311   \n",
      "30  Debt-to-Equity Ratio   AAPL       NaN  4.299324  4.202777  4.787754   \n",
      "38  Debt-to-Equity Ratio      T  2.316391  2.414628  2.621635  2.484004   \n",
      "38  Debt-to-Equity Ratio    TBB  2.316391  2.414628  2.621635  2.484004   \n",
      "38  Debt-to-Equity Ratio    TBC  2.316391  2.414628  2.621635  2.484004   \n",
      "40  Debt-to-Equity Ratio    TDS  1.276531  1.369799  1.398047  1.452405   \n",
      "34  Debt-to-Equity Ratio   TMUS  1.989248  2.010361  1.990876  2.043464   \n",
      "34  Debt-to-Equity Ratio    USM  1.274247  1.367734  1.387804  1.409239   \n",
      "\n",
      "     Q4 2022  Q1 2023  Q2 2023  Q3 2023  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "30  5.961537      NaN      NaN      NaN  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "38       NaN      NaN      NaN      NaN  \n",
      "40       NaN      NaN      NaN      NaN  \n",
      "34       NaN      NaN      NaN      NaN  \n",
      "34       NaN      NaN      NaN      NaN  \n",
      "                   items ticker   Q4 2021     Q1 2022     Q2 2022     Q3 2022  \\\n",
      "32  Debt-to-Equity Ratio    WBA       NaN    2.674637    2.471143    2.533272   \n",
      "29  Debt-to-Equity Ratio    ABC       NaN  236.925620  103.196364  254.236607   \n",
      "25  Debt-to-Equity Ratio   AMZN  2.042056    2.065402    2.194228    2.115609   \n",
      "34  Debt-to-Equity Ratio    CVS  2.103550    2.154179    2.062872    2.271112   \n",
      "27  Debt-to-Equity Ratio    MCK       NaN         NaN         NaN  -51.006279   \n",
      "24  Debt-to-Equity Ratio    RAD       NaN         NaN         NaN         NaN   \n",
      "\n",
      "       Q4 2022      Q1 2023    Q2 2023    Q3 2023  \n",
      "32    2.565737          NaN        NaN        NaN  \n",
      "29 -267.792453          NaN        NaN        NaN  \n",
      "25         NaN          NaN        NaN        NaN  \n",
      "34         NaN          NaN        NaN        NaN  \n",
      "27  -28.860035   -32.085329 -36.699491        NaN  \n",
      "24   85.151515 -1069.750000 -25.904762 -21.321782  \n",
      "                   items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "24  Debt-to-Equity Ratio    WMT       NaN       NaN       NaN       NaN   \n",
      "25  Debt-to-Equity Ratio   AMZN  2.042056  2.065402  2.194228  2.115609   \n",
      "22  Debt-to-Equity Ratio   COST       NaN       NaN  2.248429  2.197716   \n",
      "34  Debt-to-Equity Ratio    CVS  2.103550  2.154179  2.062872  2.271112   \n",
      "20  Debt-to-Equity Ratio     DG       NaN       NaN       NaN       NaN   \n",
      "32  Debt-to-Equity Ratio     JD  1.376644  1.480435  1.750457  1.731678   \n",
      "29  Debt-to-Equity Ratio    PDD  1.412434  1.201075  1.111991  0.951909   \n",
      "25  Debt-to-Equity Ratio    TGT       NaN       NaN       NaN       NaN   \n",
      "26  Debt-to-Equity Ratio    TJX       NaN       NaN       NaN       NaN   \n",
      "32  Debt-to-Equity Ratio    WBA       NaN  2.674637  2.471143  2.533272   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2023  \n",
      "24  1.941155  2.200973  2.186827  2.427622  \n",
      "25       NaN       NaN       NaN       NaN  \n",
      "22  2.108517  2.075171       NaN       NaN  \n",
      "34       NaN       NaN       NaN       NaN  \n",
      "20  3.204248  3.521469  3.563510  3.759928  \n",
      "32       NaN       NaN       NaN       NaN  \n",
      "29       NaN       NaN       NaN       NaN  \n",
      "25  3.195135  3.718953  3.953739  4.047191  \n",
      "26  3.741129  3.952458  4.019641  4.018358  \n",
      "32  2.565737       NaN       NaN       NaN  \n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from os import path\n",
    "\n",
    "dow_jones_list = dow_jones_symbols()\n",
    "\n",
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = debt_to_equity(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "#     print(competitor_directory)\n",
    "    for symbol in competitor_list:  \n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "        competitor_rows = debt_to_equity(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df, columns=[\"items\",\n",
    "                                 \"ticker\",\n",
    "                                 \"Q4 2021\",\n",
    "                                 \"Q1 2022\",\n",
    "                                 \"Q2 2022\",\n",
    "                                 \"Q3 2022\",\n",
    "                                 \"Q4 2022\",\n",
    "                                 \"Q1 2023\",\n",
    "                                 \"Q2 2023\",\n",
    "                                 \"Q3 2023\"\n",
    "                                ])\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "89d1f5d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def interest_coverage_ratio(df, symbol=\"\"):\n",
    "    try:\n",
    "        for j in df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            df[j] = pd.to_numeric(df[j])\n",
    "\n",
    "        df_columns = []\n",
    "\n",
    "        for col in df.columns:\n",
    "            df_columns.append(col)\n",
    "\n",
    "        df_columns.insert(1, df_columns[-1])\n",
    "        del df_columns[-1]\n",
    "\n",
    "        first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Operating Income'), df_columns[2:]]\n",
    "        second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Interest Expense, Suppl'), df_columns[2:]]\n",
    "    #     print(first_row)\n",
    "    #     print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Interest Coverage Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Interest Coverage Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4939a52e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'DELL', 'GOOG', 'GOOGL', 'HPQ', 'META', 'MSFT']\n",
      "                      items ticker      Q2 2022      Q3 2022    Q4 2022  \\\n",
      "5   Interest Coverage Ratio   AAPL    43.384949    32.094576  30.101572   \n",
      "8   Interest Coverage Ratio   AMZN     5.679795     4.092382        NaN   \n",
      "10  Interest Coverage Ratio   DELL          NaN          NaN   8.402985   \n",
      "6   Interest Coverage Ratio   GOOG   234.373494   169.653465        NaN   \n",
      "6   Interest Coverage Ratio  GOOGL   234.373494   169.653465        NaN   \n",
      "10  Interest Coverage Ratio    HPQ    17.270270    13.250000   5.900000   \n",
      "7   Interest Coverage Ratio   META  2089.500000  1416.000000        NaN   \n",
      "6   Interest Coverage Ratio   MSFT    42.365714    40.385686  41.312500   \n",
      "\n",
      "      Q1 2023      Q4 2021      Q1 2022   Q2 2023   Q3 2023  \n",
      "5   35.908275          NaN          NaN       NaN       NaN  \n",
      "8         NaN     7.178423     7.773305       NaN       NaN  \n",
      "10   5.849057          NaN          NaN  4.261745  2.801471  \n",
      "6         NaN   187.051282   242.096386       NaN       NaN  \n",
      "6         NaN   187.051282   242.096386       NaN       NaN  \n",
      "10        NaN          NaN    22.278689       NaN       NaN  \n",
      "7         NaN  3146.250000  2131.000000       NaN       NaN  \n",
      "6   42.986000          NaN          NaN       NaN       NaN  \n",
      "['ABBV', 'AZN', 'GILD', 'JNJ', 'MRNA', 'PFE', 'REGN']\n",
      "                      items ticker     Q1 2022     Q2 2022     Q3 2022  \\\n",
      "7   Interest Coverage Ratio   AMGN    8.474576    6.634146    7.440217   \n",
      "12  Interest Coverage Ratio   ABBV    8.607664    5.926259    8.219643   \n",
      "14  Interest Coverage Ratio    AZN         NaN         NaN         NaN   \n",
      "6   Interest Coverage Ratio   GILD    0.827731    8.384298   12.388646   \n",
      "16  Interest Coverage Ratio    JNJ  586.200000  153.684211  114.156863   \n",
      "7   Interest Coverage Ratio   MRNA  704.500000  489.400000  145.750000   \n",
      "12  Interest Coverage Ratio    PFE   30.661491   41.303754   30.263666   \n",
      "9   Interest Coverage Ratio   REGN   89.928571   85.384615   81.600000   \n",
      "\n",
      "     Q4 2022     Q4 2021  \n",
      "7   5.373494         NaN  \n",
      "12       NaN    8.748276  \n",
      "14       NaN         NaN  \n",
      "6        NaN    3.949580  \n",
      "16       NaN   80.600000  \n",
      "7        NaN  901.666667  \n",
      "12       NaN   14.481013  \n",
      "9        NaN  188.571429  \n",
      "['BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'V']\n",
      "                      items ticker    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "10  Interest Coverage Ratio    AXP   8.448598   5.792711   3.089196   \n",
      "11  Interest Coverage Ratio     MA  26.818182  26.473684  25.933333   \n",
      "10  Interest Coverage Ratio   PYPL  12.050847  11.072464  12.850575   \n",
      "8   Interest Coverage Ratio      V  35.641791  35.835821  37.369369   \n",
      "\n",
      "      Q4 2022    Q4 2021  \n",
      "10   1.550124        NaN  \n",
      "11        NaN  26.175926  \n",
      "10        NaN  17.796610  \n",
      "8   31.993711        NaN  \n",
      "['AM', 'HXL', 'RTX', 'TDG', 'TXT', 'WWD']\n",
      "                      items ticker     Q1 2022     Q2 2022     Q3 2022  \\\n",
      "7   Interest Coverage Ratio     BA   -1.855556    1.190769   -4.507246   \n",
      "12  Interest Coverage Ratio     AM    2.916823    2.826487    2.880109   \n",
      "7   Interest Coverage Ratio    HXL    3.307692    7.168539    4.533333   \n",
      "9   Interest Coverage Ratio    RTX    3.354037    4.228125    4.539877   \n",
      "10  Interest Coverage Ratio    TDG  227.500000  260.000000  200.666667   \n",
      "8   Interest Coverage Ratio    TXT    6.181818    7.343750    7.612903   \n",
      "9   Interest Coverage Ratio    WWD    4.750000    7.500000    6.444444   \n",
      "\n",
      "     Q4 2022   Q4 2021  \n",
      "7  -0.558544       NaN  \n",
      "12       NaN  2.873011  \n",
      "7        NaN  2.500000  \n",
      "9        NaN  2.329861  \n",
      "10       NaN       NaN  \n",
      "8        NaN  7.272727  \n",
      "9   6.200000       NaN  \n",
      "['DE', 'TEX', 'TTC']\n",
      "                      items ticker    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "10  Interest Coverage Ratio    CAT   8.627907   8.526316   9.326923   \n",
      "11  Interest Coverage Ratio     DE   6.026201  12.903743   9.577703   \n",
      "5   Interest Coverage Ratio    TEX   6.818182   8.666667   8.642857   \n",
      "5   Interest Coverage Ratio    TTC  13.142857  21.375000  18.111111   \n",
      "\n",
      "      Q4 2022   Q4 2021  \n",
      "10   5.508197       NaN  \n",
      "11   9.266476       NaN  \n",
      "5         NaN  6.181818  \n",
      "5   12.500000       NaN  \n",
      "['ADBE', 'CSCO', 'GOOG', 'GOOGL', 'INTU', 'MSFT', 'ORCL', 'SAP']\n",
      "                      items ticker    Q1 2023   Q2 2023   Q3 2023   Q4 2023  \\\n",
      "11  Interest Coverage Ratio    CRM   0.121622  1.986842  5.226667 -0.206349   \n",
      "8   Interest Coverage Ratio   ADBE        NaN       NaN       NaN       NaN   \n",
      "11  Interest Coverage Ratio   CSCO  35.400000       NaN       NaN       NaN   \n",
      "6   Interest Coverage Ratio   GOOG        NaN       NaN       NaN       NaN   \n",
      "6   Interest Coverage Ratio  GOOGL        NaN       NaN       NaN       NaN   \n",
      "8   Interest Coverage Ratio   INTU   1.551020       NaN       NaN       NaN   \n",
      "6   Interest Coverage Ratio   MSFT  42.986000       NaN       NaN       NaN   \n",
      "11  Interest Coverage Ratio   ORCL   3.332910  3.587617       NaN       NaN   \n",
      "13  Interest Coverage Ratio    SAP        NaN       NaN       NaN       NaN   \n",
      "\n",
      "       Q1 2022     Q2 2022     Q3 2022    Q4 2022     Q4 2021  \n",
      "11         NaN         NaN         NaN        NaN         NaN  \n",
      "8    56.428571   54.607143   53.000000  53.750000         NaN  \n",
      "11         NaN   39.625000   40.111111  36.924731         NaN  \n",
      "6   242.096386  234.373494  169.653465        NaN  187.051282  \n",
      "6   242.096386  234.373494  169.653465        NaN  187.051282  \n",
      "8          NaN    2.666667  114.047619  -2.343750         NaN  \n",
      "6          NaN   42.365714   40.385686  41.312500         NaN  \n",
      "11         NaN         NaN    5.730135   6.394886         NaN  \n",
      "13         NaN         NaN         NaN        NaN         NaN  \n",
      "['AMZN', 'AVGO', 'DELL', 'FTNT', 'MSFT', 'PANW', 'RNG', 'VMW', 'ZM', 'ZS']\n",
      "                      items ticker     Q3 2022    Q4 2022    Q1 2023  \\\n",
      "11  Interest Coverage Ratio   CSCO   40.111111  36.924731  35.400000   \n",
      "8   Interest Coverage Ratio   AMZN    4.092382        NaN        NaN   \n",
      "9   Interest Coverage Ratio   AVGO    9.204433   9.817734        NaN   \n",
      "10  Interest Coverage Ratio   DELL         NaN   8.402985   5.849057   \n",
      "9   Interest Coverage Ratio   FTNT   53.200000        NaN        NaN   \n",
      "6   Interest Coverage Ratio   MSFT   40.385686  41.312500  42.986000   \n",
      "8   Interest Coverage Ratio   PANW   -6.857143   2.142857   2.142857   \n",
      "9   Interest Coverage Ratio    RNG -183.000000        NaN        NaN   \n",
      "11  Interest Coverage Ratio    VMW         NaN   9.658228   5.746479   \n",
      "7   Interest Coverage Ratio     ZM         NaN        NaN        NaN   \n",
      "11  Interest Coverage Ratio     ZS   -6.078689  -5.708189 -51.906086   \n",
      "\n",
      "      Q2 2023    Q4 2021     Q1 2022     Q2 2022   Q3 2023  \n",
      "11  30.766355        NaN         NaN         NaN       NaN  \n",
      "8         NaN   7.178423    7.773305    5.679795       NaN  \n",
      "9         NaN        NaN    7.636364    6.552124       NaN  \n",
      "10   4.261745        NaN         NaN         NaN  2.801471  \n",
      "9         NaN  43.000000   30.200000   39.000000       NaN  \n",
      "6         NaN        NaN         NaN   42.365714       NaN  \n",
      "8         NaN        NaN         NaN  -10.571429       NaN  \n",
      "9         NaN  -6.312500 -104.000000 -108.000000       NaN  \n",
      "11   7.648649        NaN         NaN         NaN  5.064935  \n",
      "7         NaN        NaN         NaN         NaN       NaN  \n",
      "11        NaN        NaN         NaN   -5.978063       NaN  \n",
      "['BP', 'COP', 'ROSN', 'SHEL', 'XOM']\n",
      "                      items ticker    Q4 2021    Q1 2022     Q2 2022  \\\n",
      "7   Interest Coverage Ratio    CVX  35.929032  52.713235  105.829457   \n",
      "9   Interest Coverage Ratio     BP        NaN        NaN         NaN   \n",
      "13  Interest Coverage Ratio    COP  16.931507  35.543779   34.464455   \n",
      "7   Interest Coverage Ratio   ROSN        NaN        NaN         NaN   \n",
      "12  Interest Coverage Ratio   SHEL  12.747925  16.306610   34.769784   \n",
      "8   Interest Coverage Ratio    XOM  37.511312  31.797872  106.757732   \n",
      "\n",
      "      Q3 2022  Q2 2014  Q3 2014  Q4 2014   Q1 2015  \n",
      "7   99.492188      NaN      NaN      NaN       NaN  \n",
      "9         NaN      NaN      NaN      NaN       NaN  \n",
      "13  35.100503      NaN      NaN      NaN       NaN  \n",
      "7         NaN      NaN      NaN      NaN -7.230769  \n",
      "12  12.604905      NaN      NaN      NaN       NaN  \n",
      "8   96.043062      NaN      NaN      NaN       NaN  \n",
      "['AAPL', 'CHTR', 'CMCSA', 'DISH', 'FOX', 'FOXA', 'NFLX', 'PARA', 'PARAA']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      items ticker     Q1 2022     Q2 2022    Q3 2022  \\\n",
      "9   Interest Coverage Ratio    DIS    6.072022    3.756684   6.289474   \n",
      "5   Interest Coverage Ratio   AAPL   59.780980   43.384949  32.094576   \n",
      "10  Interest Coverage Ratio   CHTR    2.606604    2.964833   2.476724   \n",
      "15  Interest Coverage Ratio  CMCSA    5.608258    6.577479  -2.526042   \n",
      "12  Interest Coverage Ratio   DISH  110.000000  115.333333  85.400000   \n",
      "9   Interest Coverage Ratio    FOX         NaN    1.752577   7.417582   \n",
      "9   Interest Coverage Ratio   FOXA         NaN    1.752577   7.417582   \n",
      "5   Interest Coverage Ratio   NFLX   10.489362    9.017143   8.861272   \n",
      "9   Interest Coverage Ratio   PARA    2.925000    3.356522   2.450216   \n",
      "9   Interest Coverage Ratio  PARAA    2.925000    3.356522   2.450216   \n",
      "\n",
      "      Q4 2022     Q4 2021    Q1 2023  \n",
      "9         NaN         NaN        NaN  \n",
      "5   30.101572         NaN        NaN  \n",
      "10        NaN    3.015474        NaN  \n",
      "15        NaN    4.304464        NaN  \n",
      "12        NaN  178.500000        NaN  \n",
      "9    7.313953         NaN  10.482759  \n",
      "9    7.313953         NaN  10.482759  \n",
      "5         NaN    3.343915        NaN  \n",
      "9         NaN   11.053942        NaN  \n",
      "9         NaN   11.053942        NaN  \n",
      "['APD', 'DD', 'EMN', 'HUN', 'LIN']\n",
      "                      items ticker    Q4 2021    Q1 2022    Q2 2022  \\\n",
      "10  Interest Coverage Ratio    DOW  11.205882  11.281437  12.193939   \n",
      "9   Interest Coverage Ratio    APD        NaN  16.870968  17.562500   \n",
      "11  Interest Coverage Ratio     DD   3.488889   3.083333   4.614754   \n",
      "15  Interest Coverage Ratio    EMN  11.775510   7.085106   9.466667   \n",
      "11  Interest Coverage Ratio    HUN  45.333333  21.714286  18.312500   \n",
      "8   Interest Coverage Ratio    LIN        NaN        NaN        NaN   \n",
      "\n",
      "      Q3 2022  Q4 2022  \n",
      "10   7.077419      NaN  \n",
      "9   19.000000     19.0  \n",
      "11   4.632812      NaN  \n",
      "15   7.200000      NaN  \n",
      "11   8.625000      NaN  \n",
      "8         NaN      NaN  \n",
      "['BAC', 'BK', 'BLK', 'C', 'MS', 'SCHW', 'UBS', 'WFC']\n",
      "                      items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022\n",
      "10  Interest Coverage Ratio     GS   4.135802   3.361733   1.136991   0.577225\n",
      "9   Interest Coverage Ratio    BLK  40.780000  32.666667  30.888889  30.520000\n",
      "7   Interest Coverage Ratio     MS  15.167702  10.571429   2.495489   0.943470\n",
      "12  Interest Coverage Ratio   SCHW  15.804688  13.522059  13.698795   6.211137\n",
      "['AMZN', 'FAST', 'GWW', 'LOW', 'SHW', 'TGT', 'TSCO', 'WMT']\n",
      "                      items ticker    Q4 2022    Q1 2023    Q2 2023  \\\n",
      "6   Interest Coverage Ratio     HD  14.149560  15.938172  18.923885   \n",
      "8   Interest Coverage Ratio   AMZN        NaN        NaN        NaN   \n",
      "4   Interest Coverage Ratio   FAST        NaN        NaN        NaN   \n",
      "7   Interest Coverage Ratio    GWW        NaN        NaN        NaN   \n",
      "6   Interest Coverage Ratio    LOW   8.328829  13.873950  16.018939   \n",
      "13  Interest Coverage Ratio    SHW        NaN        NaN        NaN   \n",
      "9   Interest Coverage Ratio    TGT        NaN        NaN        NaN   \n",
      "6   Interest Coverage Ratio   TSCO        NaN        NaN        NaN   \n",
      "5   Interest Coverage Ratio    WMT  15.660422  10.808791  14.726514   \n",
      "\n",
      "      Q3 2023     Q4 2021     Q1 2022     Q2 2022    Q3 2022  \n",
      "6   14.886199         NaN         NaN         NaN        NaN  \n",
      "8         NaN    7.178423    7.773305    5.679795   4.092382  \n",
      "4         NaN  150.500000  179.000000  127.666667  94.750000  \n",
      "7         NaN   18.954545   23.217391   24.272727  24.120000  \n",
      "6    3.019608         NaN         NaN         NaN        NaN  \n",
      "13        NaN    3.435294    5.420455    8.118280   8.861386  \n",
      "9         NaN         NaN         NaN         NaN        NaN  \n",
      "6         NaN   41.857143   34.857143   75.000000  51.000000  \n",
      "5    4.614726         NaN         NaN         NaN        NaN  \n",
      "['GE', 'GRMN', 'JCI', 'MMM']\n",
      "                      items ticker    Q4 2021    Q1 2022    Q2 2022  \\\n",
      "14  Interest Coverage Ratio    HON  22.412500  17.705882  19.586207   \n",
      "10  Interest Coverage Ratio     GE  -4.401381  -1.724138   2.159898   \n",
      "7   Interest Coverage Ratio   GRMN        NaN        NaN        NaN   \n",
      "8   Interest Coverage Ratio    JCI        NaN   9.872727   2.875000   \n",
      "10  Interest Coverage Ratio    MMM  13.694915  14.522124   0.859375   \n",
      "\n",
      "      Q3 2022  Q4 2022  \n",
      "14  20.214286      NaN  \n",
      "10  -0.871795      NaN  \n",
      "7         NaN      NaN  \n",
      "8   10.240741     11.1  \n",
      "10  39.207547      NaN  \n",
      "['ACN', 'ADBE', 'CSCO', 'DELL', 'GOOG', 'GOOGL', 'HPE', 'MSFT', 'ORCL', 'SAP']\n",
      "                      items ticker     Q4 2021     Q1 2022     Q2 2022  \\\n",
      "18  Interest Coverage Ratio    IBM    9.465347    2.003215    5.797980   \n",
      "5   Interest Coverage Ratio    ACN         NaN         NaN  187.454545   \n",
      "8   Interest Coverage Ratio   ADBE         NaN   56.428571   54.607143   \n",
      "11  Interest Coverage Ratio   CSCO         NaN         NaN   39.625000   \n",
      "10  Interest Coverage Ratio   DELL         NaN         NaN         NaN   \n",
      "6   Interest Coverage Ratio   GOOG  187.051282  242.096386  234.373494   \n",
      "6   Interest Coverage Ratio  GOOGL  187.051282  242.096386  234.373494   \n",
      "14  Interest Coverage Ratio    HPE         NaN         NaN         NaN   \n",
      "6   Interest Coverage Ratio   MSFT         NaN         NaN   42.365714   \n",
      "11  Interest Coverage Ratio   ORCL         NaN         NaN         NaN   \n",
      "13  Interest Coverage Ratio    SAP         NaN         NaN         NaN   \n",
      "\n",
      "       Q3 2022     Q4 2022     Q1 2023   Q2 2023   Q3 2023  \n",
      "18  -15.257627         NaN         NaN       NaN       NaN  \n",
      "5   208.916667  174.461538  370.428571       NaN       NaN  \n",
      "8    53.000000   53.750000         NaN       NaN       NaN  \n",
      "11   40.111111   36.924731   35.400000       NaN       NaN  \n",
      "10         NaN    8.402985    5.849057  4.261745  2.801471  \n",
      "6   169.653465         NaN         NaN       NaN       NaN  \n",
      "6   169.653465         NaN         NaN       NaN       NaN  \n",
      "14         NaN         NaN         NaN       NaN       NaN  \n",
      "6    40.385686   41.312500   42.986000       NaN       NaN  \n",
      "11    5.730135    6.394886    3.332910  3.587617       NaN  \n",
      "13         NaN         NaN         NaN       NaN       NaN  \n",
      "['AMAT', 'AMD', 'AVGO', 'MU', 'NVDA', 'QCOM', 'TXN']\n",
      "                      items ticker     Q4 2021    Q1 2022    Q2 2022  \\\n",
      "10  Interest Coverage Ratio   INTC   37.231343  43.879032  -7.339450   \n",
      "11  Interest Coverage Ratio   AMAT         NaN  34.666667  32.655172   \n",
      "9   Interest Coverage Ratio    AMD  153.875000  72.692308  21.000000   \n",
      "9   Interest Coverage Ratio   AVGO         NaN   7.636364   6.552124   \n",
      "12  Interest Coverage Ratio     MU         NaN        NaN  46.290909   \n",
      "8   Interest Coverage Ratio   NVDA         NaN        NaN        NaN   \n",
      "8   Interest Coverage Ratio   QCOM         NaN  27.791367  28.014599   \n",
      "7   Interest Coverage Ratio    TXN   51.081633  49.288462  55.571429   \n",
      "\n",
      "      Q3 2022    Q4 2022    Q1 2023   Q2 2023   Q3 2023  \n",
      "10  -1.535088        NaN        NaN       NaN       NaN  \n",
      "11  34.357143  34.982456        NaN       NaN       NaN  \n",
      "9   -2.064516        NaN        NaN       NaN       NaN  \n",
      "9    9.204433   9.817734        NaN       NaN       NaN  \n",
      "12  68.272727  33.800000  -4.098039       NaN       NaN  \n",
      "8         NaN  48.688525  27.470588  7.676923  9.246154  \n",
      "8   63.600000  25.241379        NaN       NaN       NaN  \n",
      "7   50.528302        NaN        NaN       NaN       NaN  \n",
      "['ABT', 'AZN', 'MDT', 'MRK', 'NOVN', 'PFE', 'PG', 'ROG']\n",
      "                      items ticker    Q4 2021     Q1 2022     Q2 2022  \\\n",
      "16  Interest Coverage Ratio    JNJ  80.600000  586.200000  153.684211   \n",
      "9   Interest Coverage Ratio    ABT  18.152672   22.229008   18.000000   \n",
      "14  Interest Coverage Ratio    AZN        NaN         NaN         NaN   \n",
      "15  Interest Coverage Ratio    MDT        NaN         NaN         NaN   \n",
      "8   Interest Coverage Ratio    MRK  17.105263   22.917695   20.520833   \n",
      "14  Interest Coverage Ratio   NOVN        NaN -100.196970  -13.628289   \n",
      "12  Interest Coverage Ratio    PFE  14.481013   30.661491   41.303754   \n",
      "4   Interest Coverage Ratio     PG        NaN         NaN   48.754717   \n",
      "12  Interest Coverage Ratio    ROG  10.636456   19.539293   15.361786   \n",
      "\n",
      "       Q3 2022    Q4 2022    Q1 2023    Q2 2023  Q3 2021  \n",
      "16  114.156863        NaN        NaN        NaN      NaN  \n",
      "9    12.553191        NaN        NaN        NaN      NaN  \n",
      "14         NaN        NaN        NaN        NaN      NaN  \n",
      "15   12.109489  11.685315   9.594595  11.864407      NaN  \n",
      "8    16.442623        NaN        NaN        NaN      NaN  \n",
      "14         NaN        NaN        NaN        NaN      NaN  \n",
      "12   30.263666        NaN        NaN        NaN      NaN  \n",
      "4    36.917431  31.286957  40.154472        NaN      NaN  \n",
      "12    6.140246        NaN        NaN        NaN      NaN  \n",
      "['BAC', 'BMO', 'C', 'RY', 'TD', 'WFC']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022, Q4 2022]\n",
      "Index: []\n",
      "['CCEP', 'COKE', 'FIZZ', 'KDP', 'KHC', 'MDLZ', 'MNST', 'PEP', 'PRMW', 'SBUX']\n",
      "                      items ticker    Q4 2021    Q1 2022    Q2 2022  \\\n",
      "14  Interest Coverage Ratio     KO  13.806061  18.780220  11.338384   \n",
      "5   Interest Coverage Ratio   CCEP        NaN        NaN        NaN   \n",
      "4   Interest Coverage Ratio   COKE  10.875000  16.375000  21.000000   \n",
      "6   Interest Coverage Ratio   FIZZ        NaN        NaN        NaN   \n",
      "14  Interest Coverage Ratio    KDP   5.949580   4.851064   2.268571   \n",
      "8   Interest Coverage Ratio    KHC   0.019868   4.603306   2.324786   \n",
      "9   Interest Coverage Ratio   MDLZ  13.377778  10.604396  10.415730   \n",
      "13  Interest Coverage Ratio   MNST        inf        inf        inf   \n",
      "12  Interest Coverage Ratio    PEP   2.249117  21.987500   8.245763   \n",
      "9   Interest Coverage Ratio   PRMW        NaN        NaN        NaN   \n",
      "10  Interest Coverage Ratio   SBUX        NaN  10.243478   7.974790   \n",
      "\n",
      "       Q3 2022  Q4 2020  Q2 2021     Q4 2022  Q1 2023  Q2 2023  \n",
      "14   15.595960      NaN      NaN         NaN      NaN      NaN  \n",
      "5          NaN      NaN      NaN         NaN      NaN      NaN  \n",
      "4    31.666667      NaN      NaN         NaN      NaN      NaN  \n",
      "6   656.387097      NaN      NaN  328.050725      NaN      NaN  \n",
      "14    1.903382      NaN      NaN         NaN      NaN      NaN  \n",
      "8     3.293860      NaN      NaN         NaN      NaN      NaN  \n",
      "9     5.956140      NaN      NaN         NaN      NaN      NaN  \n",
      "13         inf      NaN      NaN         NaN      NaN      NaN  \n",
      "12   17.336842      NaN      NaN         NaN      NaN      NaN  \n",
      "9          NaN      NaN      NaN         NaN      NaN      NaN  \n",
      "10   10.536585      NaN      NaN    9.568000      NaN      NaN  \n",
      "['CMG', 'DPZ', 'JACK', 'PZZA', 'QSR', 'SBUX', 'SHAK', 'WEN', 'YUM', 'YUMC']\n",
      "                      items ticker     Q4 2021    Q1 2022     Q2 2022  \\\n",
      "11  Interest Coverage Ratio    MCD    8.097973   6.317073    5.756014   \n",
      "7   Interest Coverage Ratio    CMG         NaN        NaN         NaN   \n",
      "6   Interest Coverage Ratio    DPZ    3.655738   3.510638    3.955556   \n",
      "14  Interest Coverage Ratio   JACK         NaN   3.637350    1.439801   \n",
      "10  Interest Coverage Ratio   PZZA    4.750000   3.500000    6.500000   \n",
      "16  Interest Coverage Ratio    QSR    3.924528   4.128440    4.546218   \n",
      "10  Interest Coverage Ratio   SBUX         NaN  10.243478    7.974790   \n",
      "11  Interest Coverage Ratio   SHAK  -18.393768 -42.070423   -2.600000   \n",
      "18  Interest Coverage Ratio    WEN    2.961538   2.884615    3.000000   \n",
      "9   Interest Coverage Ratio    YUM         NaN        NaN         NaN   \n",
      "11  Interest Coverage Ratio   YUMC  647.000000        NaN  105.000000   \n",
      "\n",
      "       Q3 2022  Q4 2022  \n",
      "11    9.032680      NaN  \n",
      "7          NaN      NaN  \n",
      "6     3.911111      NaN  \n",
      "14    2.620604   4.2428  \n",
      "10    2.375000      NaN  \n",
      "16    3.895833      NaN  \n",
      "10   10.536585   9.5680  \n",
      "11  -10.160000      NaN  \n",
      "18    3.062500      NaN  \n",
      "9          NaN      NaN  \n",
      "11  340.000000      NaN  \n",
      "['DD', 'GE', 'HON', 'ITW', 'JNJ']\n",
      "                      items ticker    Q4 2021     Q1 2022     Q2 2022  \\\n",
      "10  Interest Coverage Ratio    MMM  13.694915   14.522124    0.859375   \n",
      "11  Interest Coverage Ratio     DD   3.488889    3.083333    4.614754   \n",
      "10  Interest Coverage Ratio     GE  -4.401381   -1.724138    2.159898   \n",
      "14  Interest Coverage Ratio    HON  22.412500   17.705882   19.586207   \n",
      "5   Interest Coverage Ratio    ITW  17.020408   18.645833   19.702128   \n",
      "16  Interest Coverage Ratio    JNJ  80.600000  586.200000  153.684211   \n",
      "\n",
      "       Q3 2022  \n",
      "10   39.207547  \n",
      "11    4.632812  \n",
      "10   -0.871795  \n",
      "14   20.214286  \n",
      "5    18.903846  \n",
      "16  114.156863  \n",
      "['ABT', 'BMY', 'GSK', 'JNJ', 'LLY', 'NOVN', 'PFE', 'SAN', 'ZTS']\n",
      "                      items ticker    Q4 2021     Q1 2022     Q2 2022  \\\n",
      "8   Interest Coverage Ratio    MRK  17.105263   22.917695   20.520833   \n",
      "9   Interest Coverage Ratio    ABT  18.152672   22.229008   18.000000   \n",
      "15  Interest Coverage Ratio    BMY   8.182663    8.153374    8.274760   \n",
      "11  Interest Coverage Ratio    GSK        NaN         NaN         NaN   \n",
      "16  Interest Coverage Ratio    JNJ  80.600000  586.200000  153.684211   \n",
      "10  Interest Coverage Ratio    LLY  23.666667   28.282353   14.938272   \n",
      "14  Interest Coverage Ratio   NOVN        NaN -100.196970  -13.628289   \n",
      "12  Interest Coverage Ratio    PFE  14.481013   30.661491   41.303754   \n",
      "20  Interest Coverage Ratio    ZTS   9.370370   13.716981   12.641509   \n",
      "\n",
      "       Q3 2022  Q3 2021  \n",
      "8    16.442623      NaN  \n",
      "9    12.553191      NaN  \n",
      "15    8.270903      NaN  \n",
      "11         NaN      NaN  \n",
      "16  114.156863      NaN  \n",
      "10   20.451220      NaN  \n",
      "14         NaN      NaN  \n",
      "12   30.263666      NaN  \n",
      "20   12.584906      NaN  \n",
      "['AAPL', 'AVGO', 'CRM', 'CSCO', 'GOOG', 'GOOGL', 'IBM', 'ORCL', 'SAP']\n",
      "                      items ticker     Q2 2022     Q3 2022    Q4 2022  \\\n",
      "6   Interest Coverage Ratio   MSFT   42.365714   40.385686  41.312500   \n",
      "5   Interest Coverage Ratio   AAPL   43.384949   32.094576  30.101572   \n",
      "9   Interest Coverage Ratio   AVGO    6.552124    9.204433   9.817734   \n",
      "11  Interest Coverage Ratio    CRM         NaN         NaN  -2.563380   \n",
      "11  Interest Coverage Ratio   CSCO   39.625000   40.111111  36.924731   \n",
      "6   Interest Coverage Ratio   GOOG  234.373494  169.653465        NaN   \n",
      "6   Interest Coverage Ratio  GOOGL  234.373494  169.653465        NaN   \n",
      "18  Interest Coverage Ratio    IBM    5.797980  -15.257627        NaN   \n",
      "11  Interest Coverage Ratio   ORCL         NaN    5.730135   6.394886   \n",
      "13  Interest Coverage Ratio    SAP         NaN         NaN        NaN   \n",
      "\n",
      "      Q1 2023     Q1 2022   Q2 2023   Q3 2023     Q4 2021  \n",
      "6   42.986000         NaN       NaN       NaN         NaN  \n",
      "5         NaN   59.780980       NaN       NaN         NaN  \n",
      "9         NaN    7.636364       NaN       NaN         NaN  \n",
      "11   0.121622         NaN  1.986842  5.226667         NaN  \n",
      "11  35.400000         NaN       NaN       NaN         NaN  \n",
      "6         NaN  242.096386       NaN       NaN  187.051282  \n",
      "6         NaN  242.096386       NaN       NaN  187.051282  \n",
      "18        NaN    2.003215       NaN       NaN    9.465347  \n",
      "11   3.332910         NaN  3.587617       NaN         NaN  \n",
      "13        NaN         NaN       NaN       NaN         NaN  \n",
      "['ADS', 'CROX', 'SKX', 'UA', 'UAA', 'VFC']\n",
      "                      items ticker    Q3 2022    Q4 2022    Q1 2023  Q2 2023  \\\n",
      "6   Interest Coverage Ratio    NKE  21.720000  19.064935  21.730769      NaN   \n",
      "11  Interest Coverage Ratio    ADS   1.421053        NaN        NaN      NaN   \n",
      "7   Interest Coverage Ratio   CROX   7.764706        NaN        NaN      NaN   \n",
      "5   Interest Coverage Ratio    SKX  26.000000        NaN        NaN      NaN   \n",
      "9   Interest Coverage Ratio     UA        NaN  -7.666667   5.666667    29.75   \n",
      "9   Interest Coverage Ratio    UAA        NaN  -7.666667   5.666667    29.75   \n",
      "8   Interest Coverage Ratio    VFC  19.852941   6.000000   1.909091    -2.60   \n",
      "\n",
      "      Q4 2021    Q1 2022    Q2 2022  \n",
      "6         NaN        NaN        NaN  \n",
      "11   2.725849   3.822785   0.168421  \n",
      "7   17.777778   6.263158   7.515152  \n",
      "5   23.250000  35.200000  30.800000  \n",
      "9   10.750000        NaN        NaN  \n",
      "9   10.750000        NaN        NaN  \n",
      "8         NaN        NaN        NaN  \n",
      "['CL', 'EL', 'JNJ', 'OR']\n",
      "                      items ticker     Q2 2022     Q3 2022    Q4 2022  \\\n",
      "4   Interest Coverage Ratio     PG   48.754717   36.917431  31.286957   \n",
      "8   Interest Coverage Ratio     CL         NaN         NaN        NaN   \n",
      "7   Interest Coverage Ratio     EL   33.761905   18.000000   1.880952   \n",
      "16  Interest Coverage Ratio    JNJ  153.684211  114.156863        NaN   \n",
      "9   Interest Coverage Ratio     OR         NaN         NaN        NaN   \n",
      "\n",
      "      Q1 2023  Q4 2021  Q1 2022  \n",
      "4   40.154472      NaN      NaN  \n",
      "8         NaN      NaN      NaN  \n",
      "7   14.369565      NaN      NaN  \n",
      "16        NaN     80.6    586.2  \n",
      "9         NaN      NaN      NaN  \n",
      "['AIG', 'AIZ', 'ALL', 'CB', 'CINF', 'HIG', 'L', 'PGR', 'WRB']\n",
      "                      items ticker     Q4 2021    Q1 2022    Q2 2022  \\\n",
      "11  Interest Coverage Ratio    TRV   19.750000  14.586207   8.465909   \n",
      "11  Interest Coverage Ratio    AIG   17.996633  23.186312  17.244361   \n",
      "13  Interest Coverage Ratio    AIZ    7.000000   7.481481   3.592593   \n",
      "15  Interest Coverage Ratio    ALL   16.583333   9.602410 -15.843373   \n",
      "15  Interest Coverage Ratio     CB   18.507937  16.265152  12.970149   \n",
      "12  Interest Coverage Ratio   CINF  132.857143 -26.692308 -79.076923   \n",
      "14  Interest Coverage Ratio    HIG   15.516129   9.758065  11.823529   \n",
      "11  Interest Coverage Ratio      L    5.800000   6.208333   4.364583   \n",
      "14  Interest Coverage Ratio    PGR   24.153846   8.240741  -9.095238   \n",
      "14  Interest Coverage Ratio    WRB   10.405405  21.800000   6.687500   \n",
      "\n",
      "      Q3 2022  \n",
      "11   7.102273  \n",
      "11  14.641844  \n",
      "13   1.346154  \n",
      "15 -10.823529  \n",
      "15   9.393333  \n",
      "12 -40.357143  \n",
      "14   9.620000  \n",
      "11   3.086957  \n",
      "14   3.269841  \n",
      "14   8.656250  \n",
      "['CI', 'CVS', 'ELV', 'HUM']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022\n",
      "10  Interest Coverage Ratio    UNH  12.856148  16.050808  15.271949  14.461240\n",
      "14  Interest Coverage Ratio     CI   5.477816   6.180602   7.594684  12.483553\n",
      "11  Interest Coverage Ratio    CVS   3.519737   5.955631   7.837050  -6.945230\n",
      "15  Interest Coverage Ratio    ELV   8.000000  12.572139  11.302885  11.075117\n",
      "12  Interest Coverage Ratio    HUM   0.670330  14.322222  12.029703  13.843137\n",
      "['AXP', 'BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'WFC']\n",
      "                      items ticker    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "8   Interest Coverage Ratio      V  35.641791  35.835821  37.369369   \n",
      "10  Interest Coverage Ratio    AXP   8.448598   5.792711   3.089196   \n",
      "11  Interest Coverage Ratio     MA  26.818182  26.473684  25.933333   \n",
      "10  Interest Coverage Ratio   PYPL  12.050847  11.072464  12.850575   \n",
      "\n",
      "      Q4 2022    Q4 2021  \n",
      "8   31.993711        NaN  \n",
      "10        NaN   7.897260  \n",
      "11        NaN  26.175926  \n",
      "10        NaN  17.796610  \n",
      "['AAPL', 'T', 'TBB', 'TBC', 'TDS', 'TMUS', 'USM']\n",
      "                      items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022  \\\n",
      "10  Interest Coverage Ratio     VZ  3.118826   9.918575   9.620382   8.424760   \n",
      "5   Interest Coverage Ratio   AAPL       NaN  59.780980  43.384949  32.094576   \n",
      "8   Interest Coverage Ratio      T  3.191822   3.405289   3.299601   4.233803   \n",
      "8   Interest Coverage Ratio    TBB  3.191822   3.405289   3.299601   4.233803   \n",
      "8   Interest Coverage Ratio    TBC  3.191822   3.405289   3.299601   4.233803   \n",
      "9   Interest Coverage Ratio    TDS  0.615385   2.878788   1.575000  -0.239130   \n",
      "9   Interest Coverage Ratio   TMUS  1.274580   2.090278   0.833137   1.548972   \n",
      "9   Interest Coverage Ratio    USM  0.161290   2.151515   1.000000  -0.357143   \n",
      "\n",
      "      Q4 2022  \n",
      "10        NaN  \n",
      "5   30.101572  \n",
      "8         NaN  \n",
      "8         NaN  \n",
      "8         NaN  \n",
      "9         NaN  \n",
      "9         NaN  \n",
      "9         NaN  \n",
      "['ABC', 'AMZN', 'CVS', 'MCK', 'RAD']\n",
      "                      items ticker    Q1 2022    Q2 2022   Q3 2022    Q4 2022  \\\n",
      "14  Interest Coverage Ratio    WBA  14.918605  10.180000  0.932692  -5.982301   \n",
      "12  Interest Coverage Ratio    ABC  11.298246  14.181818  9.327586   7.177419   \n",
      "8   Interest Coverage Ratio   AMZN   7.773305   5.679795  4.092382        NaN   \n",
      "11  Interest Coverage Ratio    CVS   5.955631   7.837050 -6.945230        NaN   \n",
      "9   Interest Coverage Ratio    MCK        NaN        NaN  7.268293  14.720930   \n",
      "8   Interest Coverage Ratio    RAD        NaN        NaN       NaN  -7.478261   \n",
      "\n",
      "     Q4 2021    Q1 2023    Q2 2023  Q3 2023  \n",
      "14       NaN        NaN        NaN      NaN  \n",
      "12       NaN        NaN        NaN      NaN  \n",
      "8   7.178423        NaN        NaN      NaN  \n",
      "11  3.519737        NaN        NaN      NaN  \n",
      "9        NaN  23.022222  20.436364      NaN  \n",
      "8        NaN  -1.833333  -5.584906 -0.22807  \n",
      "['AMZN', 'COST', 'CVS', 'DG', 'JD', 'PDD', 'TGT', 'TJX', 'WBA']\n",
      "                      items ticker    Q4 2022    Q1 2023    Q2 2023  \\\n",
      "5   Interest Coverage Ratio    WMT  15.660422  10.808791  14.726514   \n",
      "8   Interest Coverage Ratio   AMZN        NaN        NaN        NaN   \n",
      "5   Interest Coverage Ratio   COST  52.020833  51.500000        NaN   \n",
      "11  Interest Coverage Ratio    CVS        NaN        NaN        NaN   \n",
      "4   Interest Coverage Ratio     DG  20.435897  18.650000  21.232558   \n",
      "9   Interest Coverage Ratio     JD        NaN        NaN        NaN   \n",
      "7   Interest Coverage Ratio    PDD        NaN        NaN        NaN   \n",
      "9   Interest Coverage Ratio    TGT        NaN        NaN        NaN   \n",
      "7   Interest Coverage Ratio    TJX  60.190476  41.476190  52.238095   \n",
      "14  Interest Coverage Ratio    WBA  -5.982301        NaN        NaN   \n",
      "\n",
      "      Q3 2023    Q4 2021     Q1 2022     Q2 2022     Q3 2022  \n",
      "5    4.614726        NaN         NaN         NaN         NaN  \n",
      "8         NaN   7.178423    7.773305    5.679795    4.092382  \n",
      "5         NaN        NaN         NaN   50.333333   51.171429  \n",
      "11        NaN   3.519737    5.955631    7.837050   -6.945230  \n",
      "4   13.629630        NaN         NaN         NaN         NaN  \n",
      "9         NaN  -0.876957   -3.304348    7.828512   15.120898  \n",
      "7         NaN  22.795380  165.692308  669.000000  745.500000  \n",
      "9         NaN        NaN         NaN         NaN         NaN  \n",
      "7   64.714286        NaN         NaN         NaN         NaN  \n",
      "14        NaN        NaN   14.918605   10.180000    0.932692  \n"
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = interest_coverage_ratio(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "    print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = interest_coverage_ratio(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b55fbc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def operating_margin(df, symbol=\"\"):\n",
    "#     df = pd.DataFrame()\n",
    "    # for i in my_list:\n",
    "#     i= 'AAPL'\n",
    "#     i_csv = DATA_DIR + 'my_resources/'+ i + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "#     i_df = pd.read_csv(i_csv)\n",
    "    try:\n",
    "        for j in df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            df[j] = pd.to_numeric(df[j])\n",
    "\n",
    "        df_columns = []\n",
    "\n",
    "        for col in df.columns:\n",
    "            df_columns.append(col)\n",
    "\n",
    "        df_columns.insert(1, df_columns[-1])\n",
    "        del df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "\n",
    "        first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Operating Income'), df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Revenue'), df_columns[2:]]\n",
    "#         print(first_row)\n",
    "#         print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Operating Margin\"\n",
    "        third_row = third_row[df_columns]\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Operating Margin\"\n",
    "        third_row = third_row[df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f47198c5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'DELL', 'GOOG', 'GOOGL', 'HPQ', 'META', 'MSFT']\n",
      "               items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "5   Operating Margin   AAPL  0.308179  0.278162  0.276152  0.307424       NaN   \n",
      "8   Operating Margin   AMZN  0.027360  0.019866       NaN       NaN  0.025180   \n",
      "10  Operating Margin   DELL       NaN       NaN  0.025367  0.059351       NaN   \n",
      "6   Operating Margin   GOOG  0.279156  0.248003       NaN       NaN  0.290541   \n",
      "6   Operating Margin  GOOGL  0.279156  0.248003       NaN       NaN  0.290541   \n",
      "10  Operating Margin    HPQ  0.077502  0.086743  0.051821       NaN       NaN   \n",
      "7   Operating Margin   META  0.289987  0.204373       NaN       NaN  0.373764   \n",
      "6   Operating Margin   MSFT  0.429980  0.411548  0.395083  0.428814       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2023   Q3 2023  \n",
      "5        NaN       NaN       NaN  \n",
      "8   0.031509       NaN       NaN  \n",
      "10       NaN  0.048061  0.030824  \n",
      "6   0.295452       NaN       NaN  \n",
      "6   0.295452       NaN       NaN  \n",
      "10  0.079810       NaN       NaN  \n",
      "7   0.305432       NaN       NaN  \n",
      "6        NaN       NaN       NaN  \n",
      "['ABBV', 'AZN', 'GILD', 'JNJ', 'MRNA', 'PFE', 'REGN']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "7   Operating Margin   AMGN  0.400769  0.329997  0.411606  0.326071       NaN\n",
      "12  Operating Margin   ABBV  0.348427  0.225948  0.310762       NaN  0.340857\n",
      "14  Operating Margin    AZN  0.077085  0.050042  0.113367       NaN -0.024311\n",
      "6   Operating Margin   GILD  0.029894  0.324121  0.402869       NaN  0.129763\n",
      "16  Operating Margin    JNJ  0.250235  0.243131  0.244714       NaN  0.194969\n",
      "7   Operating Margin   MRNA  0.696835  0.515266  0.346611       NaN  0.750243\n",
      "12  Operating Margin    PFE  0.384747  0.436234  0.415761       NaN  0.193611\n",
      "9   Operating Margin   REGN  0.424621  0.388519  0.416894       NaN  0.533118\n",
      "['BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'V']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "10  Operating Margin    AXP  0.228726  0.187233  0.175693  0.125117       NaN\n",
      "11  Operating Margin     MA  0.570931  0.549027  0.540653       NaN  0.541986\n",
      "10  Operating Margin   PYPL  0.109671  0.112254  0.163307       NaN  0.151778\n",
      "8   Operating Margin      V  0.676583  0.667965  0.570172  0.653268       NaN\n",
      "['AM', 'HXL', 'RTX', 'TDG', 'TXT', 'WWD']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "7   Operating Margin     BA -0.083554  0.046400 -0.175420 -0.017668       NaN\n",
      "12  Operating Margin     AM  0.591118  0.560909  0.596319       NaN  0.588775\n",
      "7   Operating Margin    HXL  0.077061  0.162341  0.111873       NaN  0.063836\n",
      "9   Operating Margin    RTX  0.068720  0.082935  0.087310       NaN  0.039369\n",
      "10  Operating Margin    TDG  0.381072  0.391861  0.430615  0.424503       NaN\n",
      "8   Operating Margin    TXT  0.067977  0.074509  0.076673       NaN  0.072246\n",
      "9   Operating Margin    WWD  0.070111  0.102215  0.094463  0.096875       NaN\n",
      "['DE', 'TEX', 'TTC']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "10  Operating Margin    CAT  0.136507  0.136450  0.161731  0.101223       NaN\n",
      "11  Operating Margin     DE  0.144216  0.184989  0.201035  0.208162       NaN\n",
      "5   Operating Margin    TEX  0.074776  0.096565  0.107939       NaN  0.068687\n",
      "5   Operating Margin    TTC  0.098607  0.136910  0.140396  0.127986       NaN\n",
      "['ADBE', 'CSCO', 'GOOG', 'GOOGL', 'INTU', 'MSFT', 'ORCL', 'SAP']\n",
      "               items ticker   Q1 2023   Q2 2023   Q3 2023   Q4 2023   Q1 2022  \\\n",
      "11  Operating Margin    CRM  0.001214  0.019560  0.050019 -0.001551       NaN   \n",
      "8   Operating Margin   ADBE       NaN       NaN       NaN       NaN  0.370718   \n",
      "11  Operating Margin   CSCO  0.259683       NaN       NaN       NaN       NaN   \n",
      "6   Operating Margin   GOOG       NaN       NaN       NaN       NaN  0.295452   \n",
      "6   Operating Margin  GOOGL       NaN       NaN       NaN       NaN  0.295452   \n",
      "8   Operating Margin   INTU  0.029265       NaN       NaN       NaN       NaN   \n",
      "6   Operating Margin   MSFT  0.428814       NaN       NaN       NaN       NaN   \n",
      "11  Operating Margin   ORCL  0.229183  0.250183       NaN       NaN       NaN   \n",
      "13  Operating Margin    SAP       NaN       NaN       NaN       NaN  0.148792   \n",
      "\n",
      "     Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "11       NaN       NaN       NaN       NaN  \n",
      "8   0.348609  0.334762  0.332597       NaN  \n",
      "11  0.274135  0.281262  0.262097       NaN  \n",
      "6   0.279156  0.248003       NaN  0.290541  \n",
      "6   0.279156  0.248003       NaN  0.290541  \n",
      "8   0.020950  0.425249 -0.031069       NaN  \n",
      "6   0.429980  0.411548  0.395083       NaN  \n",
      "11       NaN  0.363550  0.380236       NaN  \n",
      "13  0.089530  0.158016       NaN  0.183310  \n",
      "['AMZN', 'AVGO', 'DELL', 'FTNT', 'MSFT', 'PANW', 'RNG', 'VMW', 'ZM', 'ZS']\n",
      "               items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023   Q4 2021  \\\n",
      "11  Operating Margin   CSCO  0.281262  0.262097  0.259683  0.242201       NaN   \n",
      "8   Operating Margin   AMZN  0.019866       NaN       NaN       NaN  0.025180   \n",
      "9   Operating Margin   AVGO  0.441517  0.446361       NaN       NaN       NaN   \n",
      "10  Operating Margin   DELL       NaN  0.025367  0.059351  0.048061       NaN   \n",
      "9   Operating Margin   FTNT  0.231304       NaN       NaN       NaN  0.223029   \n",
      "6   Operating Margin   MSFT  0.411548  0.395083  0.428814       NaN       NaN   \n",
      "8   Operating Margin   PANW -0.034607  0.009671  0.009597       NaN       NaN   \n",
      "9   Operating Margin    RNG -0.359528       NaN       NaN       NaN -0.225446   \n",
      "11  Operating Margin    VMW       NaN  0.216086  0.132124  0.169664       NaN   \n",
      "7   Operating Margin     ZM       NaN  0.235294  0.174115  0.111010       NaN   \n",
      "11  Operating Margin     ZS -0.301935 -0.259477 -0.194311       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2023  \n",
      "11       NaN       NaN       NaN  \n",
      "8   0.031509  0.027360       NaN  \n",
      "9   0.403322  0.418857       NaN  \n",
      "10       NaN       NaN  0.030824  \n",
      "9   0.158115  0.189320       NaN  \n",
      "6        NaN  0.429980       NaN  \n",
      "8        NaN -0.056188       NaN  \n",
      "9  -0.222222 -0.221766       NaN  \n",
      "11       NaN       NaN  0.121457  \n",
      "7        NaN       NaN  0.060799  \n",
      "11       NaN -0.328420       NaN  \n",
      "['BP', 'COP', 'ROSN', 'SHEL', 'XOM']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q2 2014  \\\n",
      "7   Operating Margin    CVX  0.121432  0.137038  0.208836  0.200526      NaN   \n",
      "9   Operating Margin     BP  0.067156 -0.372325  0.210282  0.030558      NaN   \n",
      "13  Operating Margin    COP  0.245238  0.434242  0.343651  0.332413      NaN   \n",
      "7   Operating Margin   ROSN       NaN       NaN       NaN       NaN     -inf   \n",
      "12  Operating Margin   SHEL  0.144102  0.137689  0.241508  0.096628      NaN   \n",
      "8   Operating Margin    XOM  0.101962  0.068138  0.186141  0.188458      NaN   \n",
      "\n",
      "    Q3 2014  Q4 2014  Q1 2015  \n",
      "7       NaN      NaN      NaN  \n",
      "9       NaN      NaN      NaN  \n",
      "13      NaN      NaN      NaN  \n",
      "7      -inf     -inf     -inf  \n",
      "12      NaN      NaN      NaN  \n",
      "8       NaN      NaN      NaN  \n",
      "['AAPL', 'CHTR', 'CMCSA', 'DISH', 'FOX', 'FOXA', 'NFLX', 'PARA', 'PARAA']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "9   Operating Margin    DIS  0.100463  0.072991  0.111142  0.030025       NaN   \n",
      "5   Operating Margin   AAPL  0.334729  0.308179  0.278162  0.276152       NaN   \n",
      "10  Operating Margin   CHTR  0.209318  0.241800  0.212030       NaN  0.235998   \n",
      "15  Operating Margin  CMCSA  0.179587  0.212120 -0.081242       NaN  0.158920   \n",
      "12  Operating Margin   DISH  0.126991  0.164371  0.104274       NaN  0.160558   \n",
      "9   Operating Margin    FOX       NaN  0.038280  0.195369  0.207385       NaN   \n",
      "9   Operating Margin   FOXA       NaN  0.038280  0.195369  0.207385       NaN   \n",
      "5   Operating Margin   NFLX  0.250635  0.197992  0.193414       NaN  0.081982   \n",
      "9   Operating Margin   PARA  0.095797  0.099242  0.081839       NaN  0.333000   \n",
      "9   Operating Margin  PARAA  0.095797  0.099242  0.081839       NaN  0.333000   \n",
      "\n",
      "     Q1 2023  \n",
      "9        NaN  \n",
      "5        NaN  \n",
      "10       NaN  \n",
      "15       NaN  \n",
      "12       NaN  \n",
      "9   0.285714  \n",
      "9   0.285714  \n",
      "5        NaN  \n",
      "9        NaN  \n",
      "9        NaN  \n",
      "['APD', 'DD', 'EMN', 'HUN', 'LIN']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q4 2022\n",
      "10  Operating Margin    DOW  0.132623  0.123428  0.128447  0.077719      NaN\n",
      "9   Operating Margin    APD       NaN  0.174683  0.190832  0.196613  0.17563\n",
      "11  Operating Margin     DD  0.110279  0.113012  0.169476  0.178776      NaN\n",
      "15  Operating Margin    EMN  0.214180  0.122697  0.153017  0.119601      NaN\n",
      "11  Operating Margin    HUN  0.294755  0.127250  0.124047  0.068623      NaN\n",
      "8   Operating Margin    LIN  0.161123  0.180246  0.069646  0.183358      NaN\n",
      "['BAC', 'BK', 'BLK', 'C', 'MS', 'SCHW', 'UBS', 'WFC']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "10  Operating Margin     GS  0.362711  0.325185  0.236566  0.203225\n",
      "9   Operating Margin    BLK  0.399334  0.375399  0.368537  0.353978\n",
      "7   Operating Margin     MS  0.328978  0.301149  0.229498  0.204380\n",
      "12  Operating Margin   SCHW  0.418321  0.382488  0.432402  0.451357\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'FAST', 'GWW', 'LOW', 'SHW', 'TGT', 'TSCO', 'WMT']\n",
      "               items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023   Q4 2021  \\\n",
      "6   Operating Margin     HD  0.135082  0.152385  0.164642  0.158160       NaN   \n",
      "8   Operating Margin   AMZN       NaN       NaN       NaN       NaN  0.025180   \n",
      "4   Operating Margin   FAST       NaN       NaN       NaN       NaN  0.196475   \n",
      "7   Operating Margin    GWW       NaN       NaN       NaN       NaN  0.124144   \n",
      "6   Operating Margin    LOW  0.086649  0.139566  0.153916  0.039354       NaN   \n",
      "13  Operating Margin    SHW       NaN       NaN       NaN       NaN  0.061319   \n",
      "9   Operating Margin    TGT  0.067589  0.053476  0.012329  0.038540       NaN   \n",
      "6   Operating Margin   TSCO       NaN       NaN       NaN       NaN  0.088280   \n",
      "5   Operating Margin    WMT  0.043743  0.034739  0.046147  0.017636       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2022  \n",
      "6        NaN       NaN       NaN  \n",
      "8   0.031509  0.027360  0.019866  \n",
      "4   0.210094  0.215289  0.210322  \n",
      "7   0.146422  0.139171  0.152968  \n",
      "6        NaN       NaN       NaN  \n",
      "13  0.095419  0.128576  0.148007  \n",
      "9        NaN       NaN       NaN  \n",
      "6   0.080688  0.134512  0.093549  \n",
      "5        NaN       NaN       NaN  \n",
      "['GE', 'GRMN', 'JCI', 'MMM']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "14  Operating Margin    HON  0.207116  0.179680  0.190327  0.221316       NaN\n",
      "10  Operating Margin     GE -0.219097 -0.041082  0.045642 -0.017816       NaN\n",
      "7   Operating Margin   GRMN  0.226293  0.195226  0.236100  0.209649       NaN\n",
      "8   Operating Margin    JCI       NaN  0.092631  0.026402  0.083611  0.099033\n",
      "10  Operating Margin    MMM  0.187645  0.185865  0.012641  0.482191       NaN\n",
      "['ACN', 'ADBE', 'CSCO', 'DELL', 'GOOG', 'GOOGL', 'HPE', 'MSFT', 'ORCL', 'SAP']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "18  Operating Margin    IBM  0.171788  0.043883  0.110846 -0.319061       NaN   \n",
      "5   Operating Margin    ACN       NaN       NaN  0.137037  0.155146  0.147044   \n",
      "8   Operating Margin   ADBE       NaN  0.370718  0.348609  0.334762  0.332597   \n",
      "11  Operating Margin   CSCO       NaN       NaN  0.274135  0.281262  0.262097   \n",
      "10  Operating Margin   DELL       NaN       NaN       NaN       NaN  0.025367   \n",
      "6   Operating Margin   GOOG  0.290541  0.295452  0.279156  0.248003       NaN   \n",
      "6   Operating Margin  GOOGL  0.290541  0.295452  0.279156  0.248003       NaN   \n",
      "14  Operating Margin    HPE       NaN  0.061916  0.030836  0.062725 -0.045610   \n",
      "6   Operating Margin   MSFT       NaN       NaN  0.429980  0.411548  0.395083   \n",
      "11  Operating Margin   ORCL       NaN       NaN       NaN  0.363550  0.380236   \n",
      "13  Operating Margin    SAP  0.183310  0.148792  0.089530  0.158016       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "18       NaN       NaN       NaN  \n",
      "5   0.164656       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "11  0.259683       NaN       NaN  \n",
      "10  0.059351  0.048061  0.030824  \n",
      "6        NaN       NaN       NaN  \n",
      "6        NaN       NaN       NaN  \n",
      "14       NaN       NaN       NaN  \n",
      "6   0.428814       NaN       NaN  \n",
      "11  0.229183  0.250183       NaN  \n",
      "13       NaN       NaN       NaN  \n",
      "['AMAT', 'AMD', 'AVGO', 'MU', 'NVDA', 'QCOM', 'TXN']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "10  Operating Margin   INTC  0.243034  0.296464 -0.052216 -0.011410       NaN   \n",
      "11  Operating Margin   AMAT       NaN  0.315101  0.303283  0.295092  0.295451   \n",
      "9   Operating Margin    AMD  0.255077  0.160523  0.080153 -0.011500       NaN   \n",
      "9   Operating Margin   AVGO       NaN  0.403322  0.418857  0.441517  0.446361   \n",
      "12  Operating Margin     MU       NaN       NaN  0.326997  0.347605  0.228963   \n",
      "8   Operating Margin   NVDA       NaN       NaN       NaN       NaN  0.388591   \n",
      "8   Operating Margin   QCOM       NaN  0.360859  0.343784  0.407096  0.321194   \n",
      "7   Operating Margin    TXN  0.518005  0.522528  0.522448  0.510971       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "10       NaN       NaN       NaN  \n",
      "11       NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN  \n",
      "12 -0.051163       NaN       NaN  \n",
      "8   0.225386  0.074433  0.101332  \n",
      "8        NaN       NaN       NaN  \n",
      "7        NaN       NaN       NaN  \n",
      "['ABT', 'AZN', 'MDT', 'MRK', 'NOVN', 'PFE', 'PG', 'ROG']\n",
      "               items ticker    Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "16  Operating Margin    JNJ   0.194969  0.250235  0.243131  0.244714   \n",
      "9   Operating Margin    ABT   0.207360  0.244809  0.211069  0.170029   \n",
      "14  Operating Margin    AZN  -0.024311  0.077085  0.050042  0.113367   \n",
      "15  Operating Margin    MDT        NaN       NaN       NaN  0.213706   \n",
      "8   Operating Margin    MRK   0.264404  0.350230  0.337491  0.268200   \n",
      "14  Operating Margin   NOVN -12.354198 -6.859959 -1.345567       NaN   \n",
      "12  Operating Margin    PFE   0.193611  0.384747  0.436234  0.415761   \n",
      "4   Operating Margin     PG        NaN       NaN  0.246647  0.207626   \n",
      "12  Operating Margin    ROG   0.045324  0.080120  0.092852  0.074732   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2021  \n",
      "16       NaN       NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN       NaN  \n",
      "14       NaN       NaN       NaN       NaN  \n",
      "15  0.206577  0.144485  0.184575       NaN  \n",
      "8        NaN       NaN       NaN       NaN  \n",
      "14       NaN       NaN       NaN -8.796472  \n",
      "12       NaN       NaN       NaN       NaN  \n",
      "4   0.184371  0.239618       NaN       NaN  \n",
      "12       NaN       NaN       NaN       NaN  \n",
      "['BAC', 'BMO', 'C', 'RY', 'TD', 'WFC']\n",
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022, Q4 2022]\n",
      "Index: []\n",
      "['CCEP', 'COKE', 'FIZZ', 'KDP', 'KHC', 'MDLZ', 'MNST', 'PEP', 'PRMW', 'SBUX']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q4 2020  \\\n",
      "14  Operating Margin     KO  0.240702  0.325803  0.198234  0.279129      NaN   \n",
      "5   Operating Margin   CCEP  0.126960       NaN  0.116787       NaN  0.09447   \n",
      "4   Operating Margin   COKE  0.062054  0.093305  0.092163  0.116636      NaN   \n",
      "6   Operating Margin   FIZZ       NaN       NaN       NaN  0.157174      NaN   \n",
      "14  Operating Margin    KDP  0.208788  0.296296  0.111705  0.108780      NaN   \n",
      "8   Operating Margin    KHC  0.001789  0.184285  0.083003  0.115450      NaN   \n",
      "9   Operating Margin   MDLZ  0.157221  0.124292  0.127440  0.087466      NaN   \n",
      "13  Operating Margin   MNST  0.289825  0.262673  0.225378  0.257389      NaN   \n",
      "12  Operating Margin    PEP  0.100840  0.325741  0.096218  0.149925      NaN   \n",
      "9   Operating Margin   PRMW  0.038610  0.028517  0.012259  0.076923      NaN   \n",
      "10  Operating Margin   SBUX       NaN  0.146335  0.124280  0.159018      NaN   \n",
      "\n",
      "     Q2 2021   Q4 2022   Q1 2023   Q2 2023  \n",
      "14       NaN       NaN       NaN       NaN  \n",
      "5   0.087868       NaN       NaN       NaN  \n",
      "4        NaN       NaN       NaN       NaN  \n",
      "6        NaN  0.159282  0.146103  0.156602  \n",
      "14       NaN       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN       NaN  \n",
      "13       NaN       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN       NaN  \n",
      "10       NaN  0.142144       NaN       NaN  \n",
      "['CMG', 'DPZ', 'JACK', 'PZZA', 'QSR', 'SBUX', 'SHAK', 'WEN', 'YUM', 'YUMC']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "11  Operating Margin    MCD  0.398902  0.319979  0.292935  0.470708       NaN\n",
      "7   Operating Margin    CMG  0.080571  0.094013  0.152734  0.151351       NaN\n",
      "6   Operating Margin    DPZ  0.166046  0.163205  0.167136  0.164640       NaN\n",
      "14  Operating Margin   JACK       NaN  0.213918  0.118662  0.130219  0.209594\n",
      "10  Operating Margin   PZZA  0.071834  0.025783  0.074570  0.037182       NaN\n",
      "16  Operating Margin    QSR  0.269082  0.310131  0.330079  0.325029       NaN\n",
      "10  Operating Margin   SBUX       NaN  0.146335  0.124280  0.159018  0.142144\n",
      "11  Operating Margin   SHAK -0.031945 -0.073430 -0.003549 -0.021184       NaN\n",
      "18  Operating Margin    WEN  0.162791  0.153374  0.178439  0.183865       NaN\n",
      "9   Operating Margin    YUM  0.265608  0.329024  0.338631  0.332927       NaN\n",
      "11  Operating Margin   YUMC  0.282409  0.081334  0.049342  0.126629       NaN\n",
      "['DD', 'GE', 'HON', 'ITW', 'JNJ']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "10  Operating Margin    MMM  0.187645  0.185865  0.012641  0.482191\n",
      "11  Operating Margin     DD  0.110279  0.113012  0.169476  0.178776\n",
      "10  Operating Margin     GE -0.219097 -0.041082  0.045642 -0.017816\n",
      "14  Operating Margin    HON  0.207116  0.179680  0.190327  0.221316\n",
      "5   Operating Margin    ITW  0.226692  0.227215  0.230865  0.245076\n",
      "16  Operating Margin    JNJ  0.194969  0.250235  0.243131  0.244714\n",
      "['ABT', 'BMY', 'GSK', 'JNJ', 'LLY', 'NOVN', 'PFE', 'SAN', 'ZTS']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               items ticker    Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q3 2021\n",
      "8   Operating Margin    MRK   0.264404  0.350230  0.337491  0.268200       NaN\n",
      "9   Operating Margin    ABT   0.207360  0.244809  0.211069  0.170029       NaN\n",
      "15  Operating Margin    BMY   0.220526  0.228194  0.217885  0.220449       NaN\n",
      "11  Operating Margin    GSK   0.093944  0.318915  0.156011  0.152127       NaN\n",
      "16  Operating Margin    JNJ   0.194969  0.250235  0.243131  0.244714       NaN\n",
      "10  Operating Margin    LLY   0.239625  0.307810  0.186498  0.241573       NaN\n",
      "14  Operating Margin   NOVN -12.354198 -6.859959 -1.345567       NaN -8.796472\n",
      "12  Operating Margin    PFE   0.193611  0.384747  0.436234  0.415761       NaN\n",
      "20  Operating Margin    ZTS   0.257245  0.366062  0.326511  0.333167       NaN\n",
      "['AAPL', 'AVGO', 'CRM', 'CSCO', 'GOOG', 'GOOGL', 'IBM', 'ORCL', 'SAP']\n",
      "               items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q1 2022  \\\n",
      "6   Operating Margin   MSFT  0.429980  0.411548  0.395083  0.428814       NaN   \n",
      "5   Operating Margin   AAPL  0.308179  0.278162  0.276152       NaN  0.334729   \n",
      "9   Operating Margin   AVGO  0.418857  0.441517  0.446361       NaN  0.403322   \n",
      "11  Operating Margin    CRM       NaN       NaN -0.024843  0.001214       NaN   \n",
      "11  Operating Margin   CSCO  0.274135  0.281262  0.262097  0.259683       NaN   \n",
      "6   Operating Margin   GOOG  0.279156  0.248003       NaN       NaN  0.295452   \n",
      "6   Operating Margin  GOOGL  0.279156  0.248003       NaN       NaN  0.295452   \n",
      "18  Operating Margin    IBM  0.110846 -0.319061       NaN       NaN  0.043883   \n",
      "11  Operating Margin   ORCL       NaN  0.363550  0.380236  0.229183       NaN   \n",
      "13  Operating Margin    SAP  0.089530  0.158016       NaN       NaN  0.148792   \n",
      "\n",
      "     Q2 2023   Q3 2023   Q4 2021  \n",
      "6        NaN       NaN       NaN  \n",
      "5        NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN  \n",
      "11  0.019560  0.050019       NaN  \n",
      "11       NaN       NaN       NaN  \n",
      "6        NaN       NaN  0.290541  \n",
      "6        NaN       NaN  0.290541  \n",
      "18       NaN       NaN  0.171788  \n",
      "11  0.250183       NaN       NaN  \n",
      "13       NaN       NaN  0.183310  \n",
      "['ADS', 'CROX', 'SKX', 'UA', 'UAA', 'VFC']\n",
      "               items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023   Q4 2021  \\\n",
      "6   Operating Margin    NKE  0.149848  0.119993  0.133601  0.119189       NaN   \n",
      "11  Operating Margin    ADS  0.169964       NaN       NaN       NaN  0.285636   \n",
      "7   Operating Margin   CROX  0.268020       NaN       NaN       NaN  0.272572   \n",
      "5   Operating Margin    SKX  0.069223       NaN       NaN       NaN  0.056432   \n",
      "9   Operating Margin     UA       NaN -0.035357  0.025204  0.075604  0.056246   \n",
      "9   Operating Margin    UAA       NaN -0.035357  0.025204  0.075604  0.056246   \n",
      "8   Operating Margin    VFC  0.186258  0.067965  0.027851 -0.029536       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022  \n",
      "6        NaN       NaN  \n",
      "11  0.302000  0.016194  \n",
      "7   0.180303  0.256995  \n",
      "5   0.096703  0.082441  \n",
      "9        NaN       NaN  \n",
      "9        NaN       NaN  \n",
      "8        NaN       NaN  \n",
      "['CL', 'EL', 'JNJ', 'OR']\n",
      "               items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "4   Operating Margin     PG  0.246647  0.207626  0.184371  0.239618       NaN   \n",
      "8   Operating Margin     CL  0.198260  0.212795       NaN       NaN  0.082898   \n",
      "7   Operating Margin     EL  0.256003  0.173852  0.022185  0.168193       NaN   \n",
      "16  Operating Margin    JNJ  0.243131  0.244714       NaN       NaN  0.194969   \n",
      "9   Operating Margin     OR -0.010538  0.529770       NaN       NaN -0.754781   \n",
      "\n",
      "     Q1 2022  \n",
      "4        NaN  \n",
      "8   0.191180  \n",
      "7        NaN  \n",
      "16  0.250235  \n",
      "9   0.105374  \n",
      "['AIG', 'AIZ', 'ALL', 'CB', 'CINF', 'HIG', 'L', 'PGR', 'WRB']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "11  Operating Margin    TRV  0.192854  0.144041  0.081367  0.067082\n",
      "11  Operating Margin    AIG  0.379428  0.385754  0.317637  0.282769\n",
      "13  Operating Margin    AIZ  0.073398  0.081386  0.038676  0.013736\n",
      "15  Operating Margin    ALL  0.107063  0.064602 -0.107610 -0.069655\n",
      "15  Operating Margin     CB  0.222455  0.222050  0.174832  0.116158\n",
      "12  Operating Margin   CINF  0.559735 -0.285597 -1.253659 -0.401278\n",
      "14  Operating Margin    HIG  0.165406  0.112182  0.112228  0.086201\n",
      "11  Operating Margin      L  0.156884  0.172754  0.120472  0.081422\n",
      "14  Operating Margin    PGR  0.100601  0.037597 -0.049770  0.016127\n",
      "14  Operating Margin    WRB  0.149341  0.261750  0.085157  0.101689\n",
      "['CI', 'CVS', 'ELV', 'HUM']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "10  Operating Margin    UNH  0.075139  0.086713  0.088782  0.092244\n",
      "14  Operating Margin     CI  0.035077  0.042302  0.050369  0.083962\n",
      "11  Operating Margin    CVS  0.027936  0.045427  0.056662 -0.048436\n",
      "15  Operating Margin    ELV  0.043739  0.066334  0.060856  0.059065\n",
      "12  Operating Margin    HUM  0.002897  0.053776  0.051348  0.061933\n",
      "['AXP', 'BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'WFC']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "8   Operating Margin      V  0.676583  0.667965  0.570172  0.653268       NaN\n",
      "10  Operating Margin    AXP  0.228726  0.187233  0.175693       NaN  0.188291\n",
      "11  Operating Margin     MA  0.570931  0.549027  0.540653       NaN  0.541986\n",
      "10  Operating Margin   PYPL  0.109671  0.112254  0.163307       NaN  0.151778\n",
      "['AAPL', 'T', 'TBB', 'TBC', 'TDS', 'TMUS', 'USM']\n",
      "               items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "10  Operating Margin     VZ  0.187219  0.232342  0.223505  0.230542       NaN\n",
      "5   Operating Margin   AAPL       NaN  0.334729  0.308179  0.278162  0.276152\n",
      "8   Operating Margin      T  0.129596  0.186356  0.167190  0.200113       NaN\n",
      "8   Operating Margin    TBB  0.129596  0.186356  0.167190  0.200113       NaN\n",
      "8   Operating Margin    TBC  0.129596  0.186356  0.167190  0.200113       NaN\n",
      "9   Operating Margin    TDS  0.017493  0.072243  0.046701 -0.007902       NaN\n",
      "9   Operating Margin   TMUS  0.051143  0.089761  0.035988  0.065770       NaN\n",
      "9   Operating Margin    USM  0.004677  0.070297  0.038948 -0.013850       NaN\n",
      "['ABC', 'AMZN', 'CVS', 'MCK', 'RAD']\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "14  Operating Margin    WBA  0.037845  0.030158  0.002976 -0.020833       NaN   \n",
      "12  Operating Margin    ABC  0.010800  0.013514  0.009007  0.007274       NaN   \n",
      "8   Operating Margin   AMZN  0.031509  0.027360  0.019866       NaN  0.025180   \n",
      "11  Operating Margin    CVS  0.045427  0.056662 -0.048436       NaN  0.027936   \n",
      "9   Operating Margin    MCK       NaN       NaN  0.004343  0.009576       NaN   \n",
      "8   Operating Margin    RAD       NaN       NaN       NaN -0.056719       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "14       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "11       NaN       NaN       NaN  \n",
      "9   0.015427  0.016021       NaN  \n",
      "8  -0.014630 -0.050161 -0.002137  \n",
      "['AMZN', 'COST', 'CVS', 'DG', 'JD', 'PDD', 'TGT', 'TJX', 'WBA']\n",
      "               items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023   Q4 2021  \\\n",
      "5   Operating Margin    WMT  0.043743  0.034739  0.046147  0.017636       NaN   \n",
      "8   Operating Margin   AMZN       NaN       NaN       NaN       NaN  0.025180   \n",
      "5   Operating Margin   COST  0.034637  0.032166       NaN       NaN       NaN   \n",
      "11  Operating Margin    CVS       NaN       NaN       NaN       NaN  0.027936   \n",
      "4   Operating Margin     DG  0.092128  0.085247  0.096860  0.077760       NaN   \n",
      "9   Operating Margin     JD       NaN       NaN       NaN       NaN -0.001421   \n",
      "7   Operating Margin    PDD       NaN       NaN       NaN       NaN  0.253645   \n",
      "9   Operating Margin    TGT  0.067589  0.053476  0.012329  0.038540       NaN   \n",
      "7   Operating Margin    TJX  0.091237  0.076363  0.092629  0.111705       NaN   \n",
      "14  Operating Margin    WBA -0.020833       NaN       NaN       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2022  \n",
      "5        NaN       NaN       NaN  \n",
      "8   0.031509  0.027360  0.019866  \n",
      "5        NaN  0.034911  0.034052  \n",
      "11  0.045427  0.056662 -0.048436  \n",
      "4        NaN       NaN       NaN  \n",
      "9  -0.004757  0.014159  0.035950  \n",
      "7   0.090527  0.276622  0.293967  \n",
      "9        NaN       NaN       NaN  \n",
      "7        NaN       NaN       NaN  \n",
      "14  0.037845  0.030158  0.002976  \n"
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = operating_margin(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "    print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = operating_margin(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "37d03347",
   "metadata": {},
   "outputs": [],
   "source": [
    "def net_income_margin(df, symbol=\"\"):\n",
    "#     df = pd.DataFrame()\n",
    "    # for i in my_list:\n",
    "#     i= 'AAPL'\n",
    "#     i_csv = DATA_DIR + 'my_resources/'+ i + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "#     i_df = pd.read_csv(i_csv)\n",
    "    try:\n",
    "        for j in df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            df[j] = pd.to_numeric(df[j])\n",
    "\n",
    "        df_columns = []\n",
    "\n",
    "        for col in df.columns:\n",
    "            df_columns.append(col)\n",
    "\n",
    "        df_columns.insert(1, df_columns[-1])\n",
    "        del df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "\n",
    "        first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Net Income'), df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Revenue'), df_columns[2:]]\n",
    "#         print(first_row)\n",
    "#         print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Net Income Margin\"\n",
    "        third_row = third_row[df_columns]\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Net Income Margin\"\n",
    "        third_row = third_row[df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5f177d53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'DELL', 'GOOG', 'GOOGL', 'HPQ', 'META', 'MSFT']\n",
      "                items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023  \\\n",
      "14  Net Income Margin   AAPL  0.257098  0.234357  0.229860  0.256056   \n",
      "20  Net Income Margin   AMZN -0.016728  0.022596       NaN       NaN   \n",
      "23  Net Income Margin   DELL       NaN       NaN  0.000090  0.041048   \n",
      "19  Net Income Margin   GOOG  0.229633  0.201326       NaN       NaN   \n",
      "19  Net Income Margin  GOOGL  0.229633  0.201326       NaN       NaN   \n",
      "18  Net Income Margin    HPQ  0.060643  0.076309 -0.000135       NaN   \n",
      "17  Net Income Margin   META  0.232010  0.158584       NaN       NaN   \n",
      "15  Net Income Margin   MSFT  0.362763  0.338898  0.322761  0.350265   \n",
      "\n",
      "     Q4 2021   Q1 2022   Q2 2023   Q3 2023  \n",
      "14       NaN       NaN       NaN       NaN  \n",
      "20  0.104234 -0.033012       NaN       NaN  \n",
      "23       NaN       NaN  0.019338  0.009911  \n",
      "19  0.274039  0.241667       NaN       NaN  \n",
      "19  0.274039  0.241667       NaN       NaN  \n",
      "18       NaN  0.063777       NaN       NaN  \n",
      "17  0.305456  0.267486       NaN       NaN  \n",
      "15       NaN       NaN       NaN       NaN  \n",
      "['ABBV', 'AZN', 'GILD', 'JNJ', 'MRNA', 'PFE', 'REGN']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "15  Net Income Margin   AMGN  0.236614  0.199727  0.322159  0.236292       NaN\n",
      "24  Net Income Margin   ABBV  0.331659  0.063361  0.266608       NaN  0.271665\n",
      "21  Net Income Margin    AZN  0.033889  0.033423  0.149335       NaN -0.028890\n",
      "16  Net Income Margin   GILD  0.002883  0.182748  0.254047       NaN  0.052733\n",
      "21  Net Income Margin    JNJ  0.219799  0.200416  0.187382       NaN  0.190937\n",
      "18  Net Income Margin   MRNA  0.602868  0.462624  0.310048       NaN  0.675080\n",
      "26  Net Income Margin    PFE  0.306418  0.357040  0.380290       NaN  0.143558\n",
      "18  Net Income Margin   REGN  0.328499  0.298215  0.448229       NaN  0.450121\n",
      "['BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'V']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "15  Net Income Margin    AXP  0.177026  0.144603  0.134253  0.105122       NaN\n",
      "25  Net Income Margin    BAC       NaN       NaN       NaN       NaN       NaN\n",
      "34  Net Income Margin      C       NaN       NaN       NaN       NaN       NaN\n",
      "26  Net Income Margin    COF       NaN       NaN       NaN       NaN       NaN\n",
      "21  Net Income Margin    DFS       NaN       NaN       NaN       NaN       NaN\n",
      "31  Net Income Margin    JPM       NaN       NaN       NaN       NaN       NaN\n",
      "20  Net Income Margin     MA  0.509193  0.413862  0.434156       NaN  0.456097\n",
      "21  Net Income Margin   PYPL  0.078513 -0.050103  0.194274       NaN  0.115785\n",
      "19  Net Income Margin    SYF       NaN       NaN       NaN       NaN       NaN\n",
      "15  Net Income Margin      V  0.560844  0.507303  0.468866  0.505971       NaN\n",
      "['AM', 'HXL', 'RTX', 'TDG', 'TXT', 'WWD']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "17  Net Income Margin     BA -0.087127  0.011570 -0.205252 -0.031732       NaN\n",
      "19  Net Income Margin     AM  0.366331  0.346844  0.363643       NaN  0.363185\n",
      "17  Net Income Margin    HXL  0.045571  0.113740  0.073485       NaN  0.052456\n",
      "24  Net Income Margin    RTX  0.068974  0.079931  0.081824       NaN  0.040249\n",
      "19  Net Income Margin    TDG  0.136516  0.149962  0.170243  0.176159       NaN\n",
      "17  Net Income Margin    TXT  0.064312  0.068802  0.073099       NaN  0.062312\n",
      "19  Net Income Margin    WWD  0.055351  0.081772  0.063518  0.084375       NaN\n",
      "['DE', 'TEX', 'TTC']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "21  Net Income Margin    CAT  0.113106  0.117428  0.136121  0.087606       NaN\n",
      "20  Net Income Margin     DE  0.094367  0.160840  0.133598  0.144567       NaN\n",
      "15  Net Income Margin    TEX  0.051844  0.068709  0.073149       NaN  0.059596\n",
      "13  Net Income Margin    TTC  0.075027  0.104884  0.107666  0.100683       NaN\n",
      "['ADBE', 'CSCO', 'GOOG', 'GOOGL', 'INTU', 'MSFT', 'ORCL', 'SAP']\n",
      "                items ticker   Q1 2023   Q2 2023   Q3 2023   Q4 2023  \\\n",
      "20  Net Income Margin    CRM  0.003778  0.008808  0.026796 -0.011689   \n",
      "17  Net Income Margin   ADBE       NaN       NaN       NaN       NaN   \n",
      "22  Net Income Margin   CSCO  0.195863       NaN       NaN       NaN   \n",
      "19  Net Income Margin   GOOG       NaN       NaN       NaN       NaN   \n",
      "19  Net Income Margin  GOOGL       NaN       NaN       NaN       NaN   \n",
      "19  Net Income Margin   INTU  0.015402       NaN       NaN       NaN   \n",
      "15  Net Income Margin   MSFT  0.350265       NaN       NaN       NaN   \n",
      "22  Net Income Margin   ORCL  0.135256  0.141833       NaN       NaN   \n",
      "22  Net Income Margin    SAP       NaN       NaN       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "20       NaN       NaN       NaN       NaN       NaN  \n",
      "17  0.297044  0.268582  0.256260  0.259890       NaN  \n",
      "22       NaN  0.233726  0.237164  0.214853       NaN  \n",
      "19  0.241667  0.229633  0.201326       NaN  0.274039  \n",
      "19  0.241667  0.229633  0.201326       NaN  0.274039  \n",
      "19       NaN  0.037411  0.318537 -0.023198       NaN  \n",
      "15       NaN  0.362763  0.338898  0.322761       NaN  \n",
      "22       NaN       NaN  0.220584  0.269341       NaN  \n",
      "22  0.104564  0.044433  0.085321       NaN  0.182057  \n",
      "['AMZN', 'AVGO', 'DELL', 'FTNT', 'MSFT', 'PANW', 'RNG', 'VMW', 'ZM', 'ZS']\n",
      "                items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023  \\\n",
      "22  Net Income Margin   CSCO  0.237164  0.214853  0.195863  0.204017   \n",
      "20  Net Income Margin   AMZN  0.022596       NaN       NaN       NaN   \n",
      "18  Net Income Margin   AVGO  0.363185  0.376148       NaN       NaN   \n",
      "23  Net Income Margin   DELL       NaN  0.000090  0.041048  0.019338   \n",
      "20  Net Income Margin   FTNT  0.201739       NaN       NaN       NaN   \n",
      "15  Net Income Margin   MSFT  0.338898  0.322761  0.350265       NaN   \n",
      "19  Net Income Margin   PANW -0.052632  0.001934  0.012796       NaN   \n",
      "18  Net Income Margin    RNG -0.559921       NaN       NaN       NaN   \n",
      "21  Net Income Margin    VMW       NaN  0.165959  0.078368  0.104017   \n",
      "15  Net Income Margin     ZM       NaN  0.458450  0.106145  0.041856   \n",
      "20  Net Income Margin     ZS -0.353565 -0.307025 -0.191710       NaN   \n",
      "\n",
      "     Q4 2021   Q1 2022   Q2 2022   Q3 2023  \n",
      "22       NaN       NaN       NaN       NaN  \n",
      "20  0.104234 -0.033012 -0.016728       NaN  \n",
      "18       NaN  0.320789  0.319635       NaN  \n",
      "23       NaN       NaN       NaN  0.009911  \n",
      "20  0.206432  0.144503  0.168932       NaN  \n",
      "15       NaN       NaN  0.362763       NaN  \n",
      "19       NaN       NaN -0.071374       NaN  \n",
      "18 -0.263393 -0.322650 -0.328542       NaN  \n",
      "21       NaN       NaN       NaN  0.071940  \n",
      "15       NaN       NaN       NaN  0.043557  \n",
      "20       NaN       NaN -0.392936       NaN  \n",
      "['BP', 'COP', 'ROSN', 'SHEL', 'XOM']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q2 2014  \\\n",
      "17  Net Income Margin    CVX  0.110224  0.119643  0.177783  0.176844      NaN   \n",
      "20  Net Income Margin     BP  0.046010 -0.413821  0.136401 -0.039319      NaN   \n",
      "21  Net Income Margin    COP  0.173743  0.324232  0.243136  0.215438      NaN   \n",
      "15  Net Income Margin   ROSN       NaN       NaN       NaN       NaN     -inf   \n",
      "24  Net Income Margin   SHEL  0.134393  0.084509  0.180294  0.070434      NaN   \n",
      "19  Net Income Margin    XOM  0.109095  0.062462  0.160428  0.184580      NaN   \n",
      "\n",
      "    Q3 2014  Q4 2014  Q1 2015  \n",
      "17      NaN      NaN      NaN  \n",
      "20      NaN      NaN      NaN  \n",
      "21      NaN      NaN      NaN  \n",
      "15     -inf     -inf     -inf  \n",
      "24      NaN      NaN      NaN  \n",
      "19      NaN      NaN      NaN  \n",
      "['AAPL', 'CHTR', 'CMCSA', 'DISH', 'FOX', 'FOXA', 'NFLX', 'PARA', 'PARAA']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022  Q4 2022   Q4 2021  \\\n",
      "24  Net Income Margin    DIS  0.050598  0.024417  0.065523  0.00804       NaN   \n",
      "14  Net Income Margin   AAPL  0.279398  0.257098  0.234357  0.22986       NaN   \n",
      "20  Net Income Margin   CHTR  0.091136  0.108178  0.087454      NaN  0.121859   \n",
      "25  Net Income Margin  CMCSA  0.114447  0.113140 -0.154042      NaN  0.100738   \n",
      "26  Net Income Margin   DISH  0.099977  0.124228  0.100611      NaN  0.124129   \n",
      "21  Net Income Margin    FOX       NaN -0.019140  0.081910  0.10089       NaN   \n",
      "21  Net Income Margin   FOXA       NaN -0.019140  0.081910  0.10089       NaN   \n",
      "16  Net Income Margin   NFLX  0.202974  0.180803  0.176382      NaN  0.078739   \n",
      "25  Net Income Margin   PARA  0.059088  0.053863  0.033401      NaN  0.257250   \n",
      "25  Net Income Margin  PARAA  0.059088  0.053863  0.033401      NaN  0.257250   \n",
      "\n",
      "     Q1 2023  \n",
      "24       NaN  \n",
      "14       NaN  \n",
      "20       NaN  \n",
      "25       NaN  \n",
      "26       NaN  \n",
      "21  0.189536  \n",
      "21  0.189536  \n",
      "16       NaN  \n",
      "25       NaN  \n",
      "25       NaN  \n",
      "['APD', 'DD', 'EMN', 'HUN', 'LIN']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "23  Net Income Margin    DOW  0.120858  0.102791  0.106039  0.052356       NaN\n",
      "22  Net Income Margin    APD       NaN  0.187041  0.180306  0.182502  0.163305\n",
      "24  Net Income Margin     DD  0.047764  0.149053  0.236905  0.110642       NaN\n",
      "25  Net Income Margin    EMN  0.140312  0.086588  0.091954  0.111111       NaN\n",
      "22  Net Income Margin    HUN  0.258778  0.093344  0.096528  0.049727       NaN\n",
      "18  Net Income Margin    LIN  0.123644  0.142979  0.043987  0.144708       NaN\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['BAC', 'BK', 'BLK', 'C', 'MS', 'SCHW', 'UBS', 'WFC']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "15  Net Income Margin     GS  0.284033  0.275108  0.195381  0.166053\n",
      "25  Net Income Margin    BAC       NaN       NaN       NaN       NaN\n",
      "30  Net Income Margin     BK       NaN       NaN       NaN       NaN\n",
      "19  Net Income Margin    BLK  0.321778  0.305597  0.237958  0.326142\n",
      "34  Net Income Margin      C       NaN       NaN       NaN       NaN\n",
      "13  Net Income Margin     MS  0.248956  0.240630  0.172521  0.158774\n",
      "17  Net Income Margin   SCHW  0.326716  0.291597  0.340939  0.340583\n",
      "27  Net Income Margin    UBS       NaN       NaN       NaN       NaN\n",
      "25  Net Income Margin    WFC       NaN       NaN       NaN       NaN\n",
      "['AMZN', 'FAST', 'GWW', 'LOW', 'SHW', 'TGT', 'TSCO', 'WMT']\n",
      "                items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023  \\\n",
      "13  Net Income Margin     HD  0.093844  0.108744  0.118127  0.111623   \n",
      "20  Net Income Margin   AMZN       NaN       NaN       NaN       NaN   \n",
      "11  Net Income Margin   FAST       NaN       NaN       NaN       NaN   \n",
      "16  Net Income Margin    GWW       NaN       NaN       NaN       NaN   \n",
      "17  Net Income Margin    LOW  0.056563  0.098609  0.108895  0.006559   \n",
      "20  Net Income Margin    SHW       NaN       NaN       NaN       NaN   \n",
      "17  Net Income Margin    TGT  0.049813  0.040087  0.007028  0.026850   \n",
      "12  Net Income Margin   TSCO       NaN       NaN       NaN       NaN   \n",
      "17  Net Income Margin    WMT  0.023301  0.014509  0.033685 -0.011766   \n",
      "\n",
      "     Q4 2021   Q1 2022   Q2 2022   Q3 2022  \n",
      "13       NaN       NaN       NaN       NaN  \n",
      "20  0.104234 -0.033012 -0.016728  0.022596  \n",
      "11  0.150783  0.158451  0.161327  0.158158  \n",
      "16  0.084251  0.100356  0.096690  0.108067  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "20  0.063839  0.074215  0.098433  0.113279  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "12  0.066586  0.061839  0.101460  0.071538  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "['GE', 'GRMN', 'JCI', 'MMM']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q4 2022\n",
      "20  Net Income Margin    HON  0.164953  0.135387  0.140847  0.173388      NaN\n",
      "24  Net Income Margin     GE -0.188660 -0.061213 -0.042371 -0.008646      NaN\n",
      "17  Net Income Margin   GRMN  0.205460  0.180733  0.207897  0.185088      NaN\n",
      "21  Net Income Margin    JCI       NaN  0.064995  0.001804  0.057303  0.11316\n",
      "21  Net Income Margin    MMM  0.155481  0.147129  0.008963  0.447732      NaN\n",
      "['ACN', 'ADBE', 'CSCO', 'DELL', 'GOOG', 'GOOGL', 'HPE', 'MSFT', 'ORCL', 'SAP']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "28  Net Income Margin    IBM  0.139742  0.051631  0.089604 -0.226554   \n",
      "15  Net Income Margin    ACN       NaN       NaN  0.108660  0.110527   \n",
      "17  Net Income Margin   ADBE       NaN  0.297044  0.268582  0.256260   \n",
      "22  Net Income Margin   CSCO       NaN       NaN  0.233726  0.237164   \n",
      "23  Net Income Margin   DELL       NaN       NaN       NaN       NaN   \n",
      "19  Net Income Margin   GOOG  0.274039  0.241667  0.229633  0.201326   \n",
      "19  Net Income Margin  GOOGL  0.274039  0.241667  0.229633  0.201326   \n",
      "21  Net Income Margin    HPE       NaN  0.073696  0.037241  0.058840   \n",
      "15  Net Income Margin   MSFT       NaN       NaN  0.362763  0.338898   \n",
      "22  Net Income Margin   ORCL       NaN       NaN       NaN  0.220584   \n",
      "22  Net Income Margin    SAP  0.182057  0.104564  0.044433  0.085321   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2023  \n",
      "28       NaN       NaN       NaN       NaN  \n",
      "15  0.107949  0.124778       NaN       NaN  \n",
      "17  0.259890       NaN       NaN       NaN  \n",
      "22  0.214853  0.195863       NaN       NaN  \n",
      "23  0.000090  0.041048  0.019338  0.009911  \n",
      "19       NaN       NaN       NaN       NaN  \n",
      "19       NaN       NaN       NaN       NaN  \n",
      "21 -0.038623       NaN       NaN       NaN  \n",
      "15  0.322761  0.350265       NaN       NaN  \n",
      "22  0.269341  0.135256  0.141833       NaN  \n",
      "22       NaN       NaN       NaN       NaN  \n",
      "['AMAT', 'AMD', 'AVGO', 'MU', 'NVDA', 'QCOM', 'TXN']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "23  Net Income Margin   INTC  0.225205  0.442053 -0.029633  0.066436   \n",
      "21  Net Income Margin   AMAT       NaN  0.285760  0.245957  0.246319   \n",
      "19  Net Income Margin    AMD  0.201823  0.133515  0.068244  0.011860   \n",
      "18  Net Income Margin   AVGO       NaN  0.320789  0.319635  0.363185   \n",
      "25  Net Income Margin     MU       NaN       NaN  0.290650  0.303865   \n",
      "19  Net Income Margin   NVDA       NaN       NaN       NaN       NaN   \n",
      "16  Net Income Margin   QCOM       NaN  0.317515  0.262809  0.341075   \n",
      "15  Net Income Margin    TXN  0.442467  0.448726  0.439563  0.437894   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2023  \n",
      "23       NaN       NaN       NaN       NaN  \n",
      "21  0.235739       NaN       NaN       NaN  \n",
      "19       NaN       NaN       NaN       NaN  \n",
      "18  0.376148       NaN       NaN       NaN  \n",
      "25  0.224597 -0.047736       NaN       NaN  \n",
      "19  0.392909  0.195222  0.097852  0.114652  \n",
      "16  0.252128       NaN       NaN       NaN  \n",
      "15       NaN       NaN       NaN       NaN  \n",
      "['ABT', 'AZN', 'MDT', 'MRK', 'NOVN', 'PFE', 'PG', 'ROG']\n",
      "                items ticker    Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "21  Net Income Margin    JNJ   0.190937  0.219799  0.200416  0.187382   \n",
      "21  Net Income Margin    ABT   0.173439  0.205717  0.179266  0.137848   \n",
      "21  Net Income Margin    AZN  -0.028890  0.033889  0.033423  0.149335   \n",
      "27  Net Income Margin    MDT        NaN       NaN       NaN  0.190519   \n",
      "21  Net Income Margin    MRK   0.277938  0.271052  0.270267  0.217127   \n",
      "22  Net Income Margin   NOVN -12.569466 -6.939834 -1.441702       NaN   \n",
      "26  Net Income Margin    PFE   0.143558  0.306418  0.357040  0.380290   \n",
      "14  Net Income Margin     PG        NaN       NaN  0.201546  0.173108   \n",
      "23  Net Income Margin    ROG   0.100372  0.066864  0.070973  0.060017   \n",
      "\n",
      "     Q4 2022   Q1 2023   Q2 2023   Q3 2021  \n",
      "21       NaN       NaN       NaN       NaN  \n",
      "21       NaN       NaN       NaN       NaN  \n",
      "21       NaN       NaN       NaN       NaN  \n",
      "27  0.183706  0.126170  0.056427       NaN  \n",
      "21       NaN       NaN       NaN       NaN  \n",
      "22       NaN       NaN       NaN -8.797829  \n",
      "26       NaN       NaN       NaN       NaN  \n",
      "14  0.156393  0.191102       NaN       NaN  \n",
      "23       NaN       NaN       NaN       NaN  \n",
      "['BAC', 'BMO', 'C', 'RY', 'TD', 'WFC']\n",
      "                items ticker  Q4 2021  Q1 2022  Q2 2022  Q3 2022  Q4 2022\n",
      "31  Net Income Margin    JPM      NaN      NaN      NaN      NaN      NaN\n",
      "25  Net Income Margin    BAC      NaN      NaN      NaN      NaN      NaN\n",
      "28  Net Income Margin    BMO      NaN      NaN      NaN      NaN      NaN\n",
      "34  Net Income Margin      C      NaN      NaN      NaN      NaN      NaN\n",
      "30  Net Income Margin     RY      NaN      NaN      NaN      NaN      NaN\n",
      "26  Net Income Margin     TD      NaN      NaN      NaN      NaN      NaN\n",
      "25  Net Income Margin    WFC      NaN      NaN      NaN      NaN      NaN\n",
      "['CCEP', 'COKE', 'FIZZ', 'KDP', 'KHC', 'MDLZ', 'MNST', 'PEP', 'PRMW', 'SBUX']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "26  Net Income Margin     KO  0.255072  0.265084  0.168212  0.255356   \n",
      "16  Net Income Margin   CCEP  0.094073       NaN  0.080556       NaN   \n",
      "13  Net Income Margin   COKE  0.013552  0.066239  0.062696  0.073051   \n",
      "15  Net Income Margin   FIZZ       NaN       NaN       NaN  0.119989   \n",
      "25  Net Income Margin    KDP  0.248599  0.190058  0.061339  0.049696   \n",
      "21  Net Income Margin    KHC -0.038307  0.128371  0.040433  0.066410   \n",
      "19  Net Income Margin   MDLZ  0.130974  0.110124  0.102695  0.068530   \n",
      "23  Net Income Margin   MNST  0.225263  0.193548  0.164955  0.198276   \n",
      "22  Net Income Margin    PEP  0.052361  0.263025  0.070655  0.122980   \n",
      "17  Net Income Margin   PRMW -0.005792 -0.013308 -0.040280  0.001709   \n",
      "19  Net Income Margin   SBUX       NaN  0.101366  0.088397  0.112025   \n",
      "\n",
      "     Q4 2020  Q2 2021   Q4 2022  Q1 2023   Q2 2023  \n",
      "26       NaN      NaN       NaN      NaN       NaN  \n",
      "16  0.064483  0.04123       NaN      NaN       NaN  \n",
      "13       NaN      NaN       NaN      NaN       NaN  \n",
      "15       NaN      NaN  0.120836  0.11145  0.120301  \n",
      "25       NaN      NaN       NaN      NaN       NaN  \n",
      "21       NaN      NaN       NaN      NaN       NaN  \n",
      "19       NaN      NaN       NaN      NaN       NaN  \n",
      "23       NaN      NaN       NaN      NaN       NaN  \n",
      "22       NaN      NaN       NaN      NaN       NaN  \n",
      "17       NaN      NaN       NaN      NaN       NaN  \n",
      "19       NaN      NaN  0.104350      NaN       NaN  \n",
      "['CMG', 'DPZ', 'JACK', 'PZZA', 'QSR', 'SBUX', 'SHAK', 'WEN', 'YUM', 'YUMC']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "22  Net Income Margin    MCD  0.272758  0.194846  0.207765  0.337534       NaN\n",
      "13  Net Income Margin    CMG  0.067823  0.078179  0.117488  0.115766       NaN\n",
      "15  Net Income Margin    DPZ  0.116158  0.090010  0.095775  0.094481       NaN\n",
      "23  Net Income Margin   JACK       NaN  0.113922  0.024189  0.057386  0.113856\n",
      "18  Net Income Margin   PZZA  0.047259  0.018416  0.047801  0.015656       NaN\n",
      "26  Net Income Margin    QSR  0.115783  0.126120  0.143990  0.208575       NaN\n",
      "19  Net Income Margin   SBUX       NaN  0.101366  0.088397  0.112025  0.104350\n",
      "21  Net Income Margin   SHAK -0.047871 -0.049963 -0.005148 -0.008884       NaN\n",
      "27  Net Income Margin    WEN  0.109937  0.075665  0.089219  0.095685       NaN\n",
      "16  Net Income Margin    YUM  0.174603  0.257919  0.136919  0.201829       NaN\n",
      "22  Net Income Margin   YUMC  0.207333  0.037481  0.039004  0.076723       NaN\n",
      "['DD', 'GE', 'HON', 'ITW', 'JNJ']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "21  Net Income Margin    MMM  0.155481  0.147129  0.008963  0.447732\n",
      "24  Net Income Margin     DD  0.047764  0.149053  0.236905  0.110642\n",
      "24  Net Income Margin     GE -0.188660 -0.061213 -0.042371 -0.008646\n",
      "20  Net Income Margin    HON  0.164953  0.135387  0.140847  0.173388\n",
      "13  Net Income Margin    ITW  0.165534  0.168063  0.183994  0.181252\n",
      "21  Net Income Margin    JNJ  0.190937  0.219799  0.200416  0.187382\n",
      "['ABT', 'BMY', 'GSK', 'JNJ', 'LLY', 'NOVN', 'PFE', 'SAN', 'ZTS']\n",
      "                items ticker    Q4 2021   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "21  Net Income Margin    MRK   0.277938  0.271052  0.270267  0.217127   \n",
      "21  Net Income Margin    ABT   0.173439  0.205717  0.179266  0.137848   \n",
      "25  Net Income Margin    BMY   0.197914  0.109718  0.119542  0.143163   \n",
      "19  Net Income Margin    GSK   0.078619  0.250626  0.120941  1.317537   \n",
      "21  Net Income Margin    JNJ   0.190937  0.219799  0.200416  0.187382   \n",
      "22  Net Income Margin    LLY   0.215750  0.243662  0.146887  0.209162   \n",
      "22  Net Income Margin   NOVN -12.569466 -6.939834 -1.441702       NaN   \n",
      "26  Net Income Margin    PFE   0.143558  0.306418  0.357040  0.380290   \n",
      "29  Net Income Margin    SAN        NaN       NaN       NaN       NaN   \n",
      "26  Net Income Margin    ZTS   0.210473  0.299597  0.257797  0.264236   \n",
      "\n",
      "     Q3 2021  \n",
      "21       NaN  \n",
      "21       NaN  \n",
      "25       NaN  \n",
      "19       NaN  \n",
      "21       NaN  \n",
      "22       NaN  \n",
      "22 -8.797829  \n",
      "26       NaN  \n",
      "29       NaN  \n",
      "26       NaN  \n",
      "['AAPL', 'AVGO', 'CRM', 'CSCO', 'GOOG', 'GOOGL', 'IBM', 'ORCL', 'SAP']\n",
      "                items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023  \\\n",
      "15  Net Income Margin   MSFT  0.362763  0.338898  0.322761  0.350265   \n",
      "14  Net Income Margin   AAPL  0.257098  0.234357  0.229860       NaN   \n",
      "18  Net Income Margin   AVGO  0.319635  0.363185  0.376148       NaN   \n",
      "21  Net Income Margin    CRM       NaN       NaN -0.003822  0.003778   \n",
      "22  Net Income Margin   CSCO  0.233726  0.237164  0.214853  0.195863   \n",
      "19  Net Income Margin   GOOG  0.229633  0.201326       NaN       NaN   \n",
      "19  Net Income Margin  GOOGL  0.229633  0.201326       NaN       NaN   \n",
      "28  Net Income Margin    IBM  0.089604 -0.226554       NaN       NaN   \n",
      "22  Net Income Margin   ORCL       NaN  0.220584  0.269341  0.135256   \n",
      "22  Net Income Margin    SAP  0.044433  0.085321       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2023   Q3 2023   Q4 2021  \n",
      "15       NaN       NaN       NaN       NaN  \n",
      "14  0.279398       NaN       NaN       NaN  \n",
      "18  0.320789       NaN       NaN       NaN  \n",
      "21       NaN  0.008808  0.026796       NaN  \n",
      "22       NaN       NaN       NaN       NaN  \n",
      "19  0.241667       NaN       NaN  0.274039  \n",
      "19  0.241667       NaN       NaN  0.274039  \n",
      "28  0.051631       NaN       NaN  0.139742  \n",
      "22       NaN  0.141833       NaN       NaN  \n",
      "22  0.104564       NaN       NaN  0.182057  \n",
      "['ADS', 'CROX', 'SKX', 'UA', 'UAA', 'VFC']\n",
      "                items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023  \\\n",
      "15  Net Income Margin    NKE  0.128415  0.117623  0.115709  0.099962   \n",
      "20  Net Income Margin    ADS  0.120504       NaN       NaN       NaN   \n",
      "18  Net Income Margin   CROX  0.171574       NaN       NaN       NaN   \n",
      "15  Net Income Margin    SKX  0.045793       NaN       NaN       NaN   \n",
      "18  Net Income Margin     UA       NaN -0.046118  0.005930  0.055273   \n",
      "18  Net Income Margin    UAA       NaN -0.046118  0.005930  0.055273   \n",
      "20  Net Income Margin    VFC  0.142936  0.028673 -0.024757 -0.038299   \n",
      "\n",
      "     Q4 2021   Q1 2022   Q2 2022  \n",
      "15       NaN       NaN       NaN  \n",
      "20  0.219152  0.210000  0.012146  \n",
      "18  0.264055  0.110606  0.165803  \n",
      "15  0.243932  0.066484  0.048180  \n",
      "18  0.071942       NaN       NaN  \n",
      "18  0.071942       NaN       NaN  \n",
      "20       NaN       NaN       NaN  \n",
      "['CL', 'EL', 'JNJ', 'OR']\n",
      "                items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023  \\\n",
      "14  Net Income Margin     PG  0.201546  0.173108  0.156393  0.191102   \n",
      "16  Net Income Margin     CL  0.134478  0.138721       NaN       NaN   \n",
      "17  Net Income Margin     EL  0.196425  0.131449  0.014603  0.124427   \n",
      "21  Net Income Margin    JNJ  0.200416  0.187382       NaN       NaN   \n",
      "21  Net Income Margin     OR  0.268281 -2.956467       NaN       NaN   \n",
      "\n",
      "     Q4 2021   Q1 2022  \n",
      "14       NaN       NaN  \n",
      "16  0.033613  0.127074  \n",
      "17       NaN       NaN  \n",
      "21  0.190937  0.219799  \n",
      "21 -0.418053  0.005488  \n",
      "['AIG', 'AIZ', 'ALL', 'CB', 'CINF', 'HIG', 'L', 'PGR', 'WRB']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "17  Net Income Margin    TRV  0.147914  0.115551  0.060179  0.048728\n",
      "19  Net Income Margin    AIG  0.265919  0.269484  0.210235  0.185523\n",
      "24  Net Income Margin    AIZ  0.048155  0.060032  0.020734  0.002747\n",
      "24  Net Income Margin    ALL  0.062793  0.053173 -0.083061 -0.050575\n",
      "24  Net Income Margin     CB  0.204235  0.204158  0.122221  0.066941\n",
      "18  Net Income Margin   CINF  0.442371 -0.224691 -0.985366 -0.296875\n",
      "20  Net Income Margin    HIG  0.125344  0.082514  0.082263  0.060753\n",
      "19  Net Income Margin      L  0.092778  0.097971  0.051754  0.037271\n",
      "21  Net Income Margin    PGR  0.077052  0.026529 -0.047164  0.009707\n",
      "22  Net Income Margin    WRB  0.114042  0.202744  0.071230  0.084068\n",
      "['CI', 'CVS', 'ELV', 'HUM']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "17  Net Income Margin    UNH  0.055205  0.062721  0.063113  0.065048\n",
      "21  Net Income Margin     CI  0.024390  0.027080  0.034351  0.060997\n",
      "21  Net Income Margin    CVS  0.017049  0.030094  0.036597 -0.042090\n",
      "22  Net Income Margin    ELV  0.031082  0.047382  0.042788  0.040512\n",
      "22  Net Income Margin    HUM -0.000665  0.038798  0.029414  0.052415\n",
      "['AXP', 'BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'WFC']\n",
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "15  Net Income Margin      V  0.560844  0.507303  0.468866  0.505971       NaN\n",
      "15  Net Income Margin    AXP  0.177026  0.144603  0.134253       NaN  0.140361\n",
      "25  Net Income Margin    BAC       NaN       NaN       NaN       NaN       NaN\n",
      "34  Net Income Margin      C       NaN       NaN       NaN       NaN       NaN\n",
      "26  Net Income Margin    COF       NaN       NaN       NaN       NaN       NaN\n",
      "21  Net Income Margin    DFS       NaN       NaN       NaN       NaN       NaN\n",
      "31  Net Income Margin    JPM       NaN       NaN       NaN       NaN       NaN\n",
      "20  Net Income Margin     MA  0.509193  0.413862  0.434156       NaN  0.456097\n",
      "21  Net Income Margin   PYPL  0.078513 -0.050103  0.194274       NaN  0.115785\n",
      "19  Net Income Margin    SYF       NaN       NaN       NaN       NaN       NaN\n",
      "25  Net Income Margin    WFC       NaN       NaN       NaN       NaN       NaN\n",
      "['AAPL', 'T', 'TBB', 'TBC', 'TDS', 'TMUS', 'USM']\n",
      "                items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022  Q4 2022\n",
      "24  Net Income Margin     VZ  0.135410  0.136496  0.153867  0.143103      NaN\n",
      "14  Net Income Margin   AAPL       NaN  0.279398  0.257098  0.234357  0.22986\n",
      "19  Net Income Margin      T  0.123126  0.161887  0.140235  0.200579      NaN\n",
      "19  Net Income Margin    TBB  0.123126  0.161887  0.140235  0.200579      NaN\n",
      "19  Net Income Margin    TBC  0.123126  0.161887  0.140235  0.200579      NaN\n",
      "21  Net Income Margin    TDS  0.021866  0.046388  0.025945 -0.005747      NaN\n",
      "19  Net Income Margin   TMUS  0.020303  0.035437 -0.005482  0.026082      NaN\n",
      "19  Net Income Margin    USM  0.025257  0.048515  0.020448 -0.011080      NaN\n",
      "['ABC', 'AMZN', 'CVS', 'MCK', 'RAD']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "26  Net Income Margin    WBA  0.105602  0.026188  0.008866 -0.012851   \n",
      "24  Net Income Margin    ABC  0.007530  0.009494  0.006776  0.004822   \n",
      "20  Net Income Margin   AMZN -0.033012 -0.016728  0.022596       NaN   \n",
      "21  Net Income Margin    CVS  0.030094  0.036597 -0.042090       NaN   \n",
      "20  Net Income Margin    MCK       NaN       NaN -0.000102  0.005567   \n",
      "15  Net Income Margin    RAD       NaN       NaN       NaN -0.064138   \n",
      "\n",
      "     Q4 2021   Q1 2023   Q2 2023   Q3 2023  \n",
      "26       NaN       NaN       NaN       NaN  \n",
      "24       NaN       NaN       NaN       NaN  \n",
      "20  0.104234       NaN       NaN       NaN  \n",
      "21  0.017049       NaN       NaN       NaN  \n",
      "20       NaN  0.011436  0.013199       NaN  \n",
      "15       NaN -0.018288 -0.056092 -0.011014  \n",
      "['AMZN', 'COST', 'CVS', 'DG', 'JD', 'PDD', 'TGT', 'TJX', 'WBA']\n",
      "                items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023  \\\n",
      "17  Net Income Margin    WMT  0.023301  0.014509  0.033685 -0.011766   \n",
      "20  Net Income Margin   AMZN       NaN       NaN       NaN       NaN   \n",
      "17  Net Income Margin   COST  0.025912  0.025056       NaN       NaN   \n",
      "21  Net Income Margin    CVS       NaN       NaN       NaN       NaN   \n",
      "12  Net Income Margin     DG  0.069009  0.063193  0.071929  0.055573   \n",
      "19  Net Income Margin     JD       NaN       NaN       NaN       NaN   \n",
      "18  Net Income Margin    PDD       NaN       NaN       NaN       NaN   \n",
      "17  Net Income Margin    TGT  0.049813  0.040087  0.007028  0.026850   \n",
      "17  Net Income Margin    TJX  0.067850  0.051464  0.068310  0.087375   \n",
      "26  Net Income Margin    WBA -0.012851       NaN       NaN       NaN   \n",
      "\n",
      "     Q4 2021   Q1 2022   Q2 2022   Q3 2022  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "20  0.104234 -0.033012 -0.016728  0.022596  \n",
      "17       NaN       NaN  0.025027  0.025724  \n",
      "21  0.017049  0.030094  0.036597 -0.042090  \n",
      "12       NaN       NaN       NaN       NaN  \n",
      "19 -0.018720 -0.012480  0.016353  0.024485  \n",
      "18  0.243105  0.109229  0.282952  0.298248  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "17       NaN       NaN       NaN       NaN  \n",
      "26       NaN  0.105602  0.026188  0.008866  \n"
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = net_income_margin(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "    print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = net_income_margin(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "87cc6fa6",
   "metadata": {},
   "outputs": [],
   "source": [
    "def acounts_receivables_turnover(i_df, j_df, symbol=\"\"):\n",
    "    \"\"\"\n",
    "    A high ratio may indicate that corporate collection practices are efficient with quality customers \n",
    "    who pay their debts quickly.\n",
    "    \n",
    "    A low ratio could be the result of inefficient collection processes, inadequate credit policies, \n",
    "    or customers who are not financially viable or creditworthy.\n",
    "    \"\"\"\n",
    "    try:\n",
    "\n",
    "        for j in i_df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            i_df[j] = i_df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            i_df[j] = pd.to_numeric(i_df[j])\n",
    "\n",
    "        for k in j_df:\n",
    "            if k == 'ticker' or k == 'items':\n",
    "                continue\n",
    "            j_df[k] = j_df[k].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            j_df[k] = pd.to_numeric(j_df[k])\n",
    "\n",
    "        i_df_columns = []\n",
    "\n",
    "        for col in i_df.columns:\n",
    "            i_df_columns.append(col)\n",
    "\n",
    "        i_df_columns.insert(1, i_df_columns[-1])\n",
    "        del i_df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "        \n",
    "        j_df_columns = []\n",
    "\n",
    "        for col in j_df.columns:\n",
    "            j_df_columns.append(col)\n",
    "\n",
    "        j_df_columns.insert(1, j_df_columns[-1])\n",
    "        del j_df_columns[-1]\n",
    "\n",
    "#         df_columns = [i for i in i_df_columns if i not in j_df_columns]\n",
    "        \n",
    "        first_row = i_df.loc[(i_df['ticker'] == symbol) & (i_df['items'] == 'Total Revenue'), i_df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = j_df.loc[(j_df['ticker'] == symbol) & (j_df['items'] == 'Total Receivables, Net'), j_df_columns[2:]]\n",
    "        # print(first_row)\n",
    "        # print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Accounts Receivable Turnover\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Accounts Receivable Turnover\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b32807e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          items ticker   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "0  Accounts Receivable Turnover   AAPL  2.142687  1.963898  1.479453   \n",
      "0  Accounts Receivable Turnover   AMZN  3.504177  3.537462       NaN   \n",
      "0  Accounts Receivable Turnover   DELL       NaN       NaN  1.232932   \n",
      "0  Accounts Receivable Turnover   GOOG  1.879670  1.909885       NaN   \n",
      "0  Accounts Receivable Turnover  GOOGL  1.879670  1.909885       NaN   \n",
      "0  Accounts Receivable Turnover    HPQ  1.997577  1.944054  2.147874   \n",
      "0  Accounts Receivable Turnover   META  2.500824  2.468513       NaN   \n",
      "0  Accounts Receivable Turnover   MSFT  1.543198  1.513507  1.171799   \n",
      "\n",
      "    Q1 2023   Q4 2021   Q1 2022  Q2 2023   Q3 2023  \n",
      "0  2.162311       NaN       NaN      NaN       NaN  \n",
      "0       NaN  4.177799  3.603627      NaN       NaN  \n",
      "0  1.570132       NaN       NaN   1.4447  1.512358  \n",
      "0       NaN  1.870499  1.909241      NaN       NaN  \n",
      "0       NaN  1.870499  1.909241      NaN       NaN  \n",
      "0       NaN       NaN  1.962882      NaN       NaN  \n",
      "0       NaN  2.398390  2.450219      NaN       NaN  \n",
      "0  1.602417       NaN       NaN      NaN       NaN  \n",
      "                          items ticker   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "0  Accounts Receivable Turnover   AMGN  1.228678  1.237845  1.248967   \n",
      "0  Accounts Receivable Turnover   ABBV  1.261344  1.297766  1.378758   \n",
      "0  Accounts Receivable Turnover    AZN  1.258564  1.120578  1.091542   \n",
      "0  Accounts Receivable Turnover   GILD  1.740164  1.520155  1.617363   \n",
      "0  Accounts Receivable Turnover    JNJ  1.502244  1.488320  1.497231   \n",
      "0  Accounts Receivable Turnover   MRNA  1.803210  1.669831  1.192485   \n",
      "0  Accounts Receivable Turnover    PFE  1.940340  1.830551  1.408186   \n",
      "0  Accounts Receivable Turnover   REGN  0.612730  0.553575  0.529200   \n",
      "\n",
      "    Q4 2022   Q4 2021  \n",
      "0  1.229373       NaN  \n",
      "0       NaN  1.492032  \n",
      "0       NaN  1.165325  \n",
      "0       NaN  1.612286  \n",
      "0       NaN  1.622980  \n",
      "0       NaN  2.187803  \n",
      "0       NaN  2.058977  \n",
      "0       NaN  0.820275  \n",
      "                          items ticker   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "0  Accounts Receivable Turnover    AXP  0.223346  0.242970  0.253937   \n",
      "0  Accounts Receivable Turnover     MA  1.248671  1.273928  1.349906   \n",
      "0  Accounts Receivable Turnover   PYPL  0.150351  0.155257  0.164114   \n",
      "0  Accounts Receivable Turnover      V  1.784378  1.908415  1.874517   \n",
      "\n",
      "    Q4 2022   Q4 2021  \n",
      "0  0.260595       NaN  \n",
      "0       NaN  1.169769  \n",
      "0       NaN  0.165554  \n",
      "0  1.970395       NaN  \n",
      "                          items ticker      Q1 2022      Q2 2022      Q3 2022  \\\n",
      "0  Accounts Receivable Turnover     BA     1.210818     1.329269     1.313900   \n",
      "0  Accounts Receivable Turnover     AM  2765.708861  3011.934211  2887.925000   \n",
      "0  Accounts Receivable Turnover    HXL  1594.285714  1488.636364  1545.338983   \n",
      "0  Accounts Receivable Turnover    RTX     0.761360     0.733873     0.787320   \n",
      "0  Accounts Receivable Turnover    TDG     1.589880     1.491011     1.412121   \n",
      "0  Accounts Receivable Turnover    TXT     3.751250     3.600457     3.681818   \n",
      "0  Accounts Receivable Turnover    WWD     1.052427     0.989882     1.021631   \n",
      "\n",
      "    Q4 2022      Q4 2021  \n",
      "0  1.767360          NaN  \n",
      "0       NaN  2608.313253  \n",
      "0       NaN  1886.387435  \n",
      "0       NaN     0.810770  \n",
      "0  1.390424          NaN  \n",
      "0       NaN     3.964200  \n",
      "0  1.040650          NaN  \n",
      "                          items ticker   Q1 2022   Q2 2022   Q3 2022  \\\n",
      "0  Accounts Receivable Turnover    CAT  0.749201  0.822813  0.878074   \n",
      "0  Accounts Receivable Turnover     DE  0.928398  1.032207  1.019225   \n",
      "0  Accounts Receivable Turnover    TEX  1.906844  1.926655  2.111111   \n",
      "0  Accounts Receivable Turnover    TTC  2.549180  2.845103  3.307692   \n",
      "\n",
      "    Q4 2022   Q4 2021  \n",
      "0  0.928815       NaN  \n",
      "0  1.047041       NaN  \n",
      "0       NaN  1.948819  \n",
      "0  3.519520       NaN  \n",
      "                          items ticker   Q1 2023   Q2 2023   Q3 2023  \\\n",
      "0  Accounts Receivable Turnover    CRM  1.364825  1.230083  1.345639   \n",
      "0  Accounts Receivable Turnover   ADBE       NaN       NaN       NaN   \n",
      "0  Accounts Receivable Turnover   CSCO  1.494409       NaN       NaN   \n",
      "0  Accounts Receivable Turnover   GOOG       NaN       NaN       NaN   \n",
      "0  Accounts Receivable Turnover  GOOGL       NaN       NaN       NaN   \n",
      "0  Accounts Receivable Turnover   INTU  2.501927       NaN       NaN   \n",
      "0  Accounts Receivable Turnover   MSFT  1.602417       NaN       NaN   \n",
      "0  Accounts Receivable Turnover   ORCL  1.927741  1.980797       NaN   \n",
      "0  Accounts Receivable Turnover    SAP       NaN       NaN       NaN   \n",
      "\n",
      "    Q4 2023   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "0  0.669061       NaN       NaN       NaN       NaN       NaN  \n",
      "0       NaN  2.529377  2.761965  2.572838  2.191283       NaN  \n",
      "0       NaN       NaN  1.115789  1.178929  1.107804       NaN  \n",
      "0       NaN  1.909241  1.879670  1.909885       NaN  1.870499  \n",
      "0       NaN  1.909241  1.879670  1.909885       NaN  1.870499  \n",
      "0       NaN       NaN  2.365487  7.569892  2.303435       NaN  \n",
      "0       NaN       NaN  1.543198  1.513507  1.171799       NaN  \n",
      "0       NaN       NaN       NaN  2.291412  1.988913       NaN  \n",
      "0       NaN  0.708196  0.788772  0.801574       NaN  1.181495  \n",
      "                          items ticker      Q3 2022     Q4 2022      Q1 2023  \\\n",
      "0  Accounts Receivable Turnover   CSCO     1.178929    1.107804     1.308002   \n",
      "0  Accounts Receivable Turnover   AMZN     3.537462         NaN          NaN   \n",
      "0  Accounts Receivable Turnover   AVGO     3.125554    3.018932          NaN   \n",
      "0  Accounts Receivable Turnover   DELL          NaN    1.232932     1.570132   \n",
      "0  Accounts Receivable Turnover   FTNT     1.194185         NaN          NaN   \n",
      "0  Accounts Receivable Turnover   MSFT     1.513507    1.171799     1.602417   \n",
      "0  Accounts Receivable Turnover   PANW     1.117647    0.723752     1.262520   \n",
      "0  Accounts Receivable Turnover    RNG     1.913534         NaN          NaN   \n",
      "0  Accounts Receivable Turnover    VMW          NaN    0.936356     1.343193   \n",
      "0  Accounts Receivable Turnover     ZM          NaN    2.550000     2.219008   \n",
      "0  Accounts Receivable Turnover     ZS  1054.437500  793.164589  1321.739777   \n",
      "\n",
      "    Q2 2023   Q4 2021   Q1 2022     Q2 2022   Q3 2023  \n",
      "0  1.333333       NaN       NaN         NaN       NaN  \n",
      "0       NaN  4.177799  3.603627    3.504177       NaN  \n",
      "0       NaN       NaN  3.035053    2.628284       NaN  \n",
      "0  1.444700       NaN       NaN         NaN  1.512358  \n",
      "0       NaN  1.193069  1.208861    1.119565       NaN  \n",
      "0       NaN       NaN       NaN    1.543198       NaN  \n",
      "0       NaN       NaN       NaN    1.383403       NaN  \n",
      "0       NaN  1.922747  1.821012    1.917323       NaN  \n",
      "0  0.986690       NaN       NaN         NaN  1.159206  \n",
      "0  2.085389       NaN       NaN         NaN  1.815486  \n",
      "0       NaN       NaN       NaN  950.048327       NaN  \n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "\"['Q4 2022'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/2397406747.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     11\u001b[0m     \u001b[0mi_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[0mj_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m     \u001b[0mi_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0macounts_receivables_turnover\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mj_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m     \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_row\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/1976052681.py\u001b[0m in \u001b[0;36macounts_receivables_turnover\u001b[1;34m(i_df, j_df, symbol)\u001b[0m\n\u001b[0;32m     49\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ticker'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     50\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'items'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"Accounts Receivable Turnover\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 51\u001b[1;33m         \u001b[0mthird_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj_df_columns\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     52\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     53\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3462\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3463\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3464\u001b[1;33m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3466\u001b[0m         \u001b[1;31m# take() does not accept boolean indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1312\u001b[0m             \u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1314\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1315\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1316\u001b[0m         if needs_i8_conversion(ax.dtype) or isinstance(\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[1;34m(self, key, indexer, axis)\u001b[0m\n\u001b[0;32m   1375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1376\u001b[0m             \u001b[0mnot_found\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1377\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{not_found} not in index\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1378\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1379\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Q4 2022'] not in index\""
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    j_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    j_df = pd.read_csv(j_csv)\n",
    "    i_row = acounts_receivables_turnover(i_df, j_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "#     print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        i_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "        j_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        i_competitor_df = pd.read_csv(i_competitor_csv)\n",
    "        j_competitor_df = pd.read_csv(j_competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = acounts_receivables_turnover(i_competitor_df, j_competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9c5e1d7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def inventory_turnover_ratio(i_df, j_df, symbol=\"\"):\n",
    "    try:\n",
    "\n",
    "        for j in i_df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            i_df[j] = i_df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            i_df[j] = pd.to_numeric(i_df[j])\n",
    "\n",
    "        for k in j_df:\n",
    "            if k == 'ticker' or k == 'items':\n",
    "                continue\n",
    "            j_df[k] = j_df[k].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            j_df[k] = pd.to_numeric(j_df[k])\n",
    "\n",
    "        i_df_columns = []\n",
    "\n",
    "        for col in i_df.columns:\n",
    "            i_df_columns.append(col)\n",
    "\n",
    "        i_df_columns.insert(1, i_df_columns[-1])\n",
    "        del i_df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "        \n",
    "        j_df_columns = []\n",
    "\n",
    "        for col in j_df.columns:\n",
    "            j_df_columns.append(col)\n",
    "\n",
    "        j_df_columns.insert(1, j_df_columns[-1])\n",
    "        del j_df_columns[-1]\n",
    "\n",
    "#         df_columns = [i for i in i_df_columns if i not in j_df_columns]\n",
    "        \n",
    "        first_row = i_df.loc[(i_df['ticker'] == symbol) & (i_df['items'] == 'Cost of Revenue, Total'), i_df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = j_df.loc[(j_df['ticker'] == symbol) & (j_df['items'] == 'Total Inventory'), j_df_columns[2:]]\n",
    "        # print(first_row)\n",
    "        # print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Inventory Turnover Ratio\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Inventory Turnover Ratio\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7dbabdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      items ticker    Q2 2022   Q3 2022    Q4 2022   Q1 2023  \\\n",
      "1  Inventory Turnover Ratio   AAPL  10.021795  8.664458  10.523858  9.797947   \n",
      "1  Inventory Turnover Ratio   AMZN   1.740990  1.917428        NaN       NaN   \n",
      "1  Inventory Turnover Ratio   DELL        NaN       NaN   4.070024  3.239127   \n",
      "1  Inventory Turnover Ratio   GOOG  15.204040  9.872624        NaN       NaN   \n",
      "1  Inventory Turnover Ratio  GOOGL  15.204040  9.872624        NaN       NaN   \n",
      "1  Inventory Turnover Ratio    HPQ   1.471042  1.436035   1.591047       NaN   \n",
      "1  Inventory Turnover Ratio   META        NaN       NaN        NaN       NaN   \n",
      "1  Inventory Turnover Ratio   MSFT   5.617754  4.737561   4.390433  3.620431   \n",
      "\n",
      "     Q4 2021    Q1 2022   Q2 2023   Q3 2023  \n",
      "1        NaN        NaN       NaN       NaN  \n",
      "1   2.537837   1.900677       NaN       NaN  \n",
      "1        NaN        NaN  3.567228  3.080687  \n",
      "1  28.194872  21.620891       NaN       NaN  \n",
      "1  28.194872  21.620891       NaN       NaN  \n",
      "1        NaN   1.512863       NaN       NaN  \n",
      "1        NaN        NaN       NaN       NaN  \n",
      "1        NaN        NaN       NaN       NaN  \n",
      "                      items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "1  Inventory Turnover Ratio   AMGN  0.353888  0.331577  0.333824  0.354361   \n",
      "1  Inventory Turnover Ratio   ABBV  1.154465  1.220259  1.332913       NaN   \n",
      "1  Inventory Turnover Ratio    AZN  0.298924  0.306109  0.417093       NaN   \n",
      "1  Inventory Turnover Ratio   GILD  0.960864  0.965194  0.953520       NaN   \n",
      "1  Inventory Turnover Ratio    JNJ  0.689900  0.690915  0.667580       NaN   \n",
      "1  Inventory Turnover Ratio   MRNA  0.523687  0.718896  0.529610       NaN   \n",
      "1  Inventory Turnover Ratio    PFE  1.003107  0.829443  0.639966       NaN   \n",
      "1  Inventory Turnover Ratio   REGN  0.203313  0.133844  0.131841       NaN   \n",
      "\n",
      "    Q4 2021  \n",
      "1       NaN  \n",
      "1  1.368286  \n",
      "1  0.341645  \n",
      "1  1.623609  \n",
      "1  0.765861  \n",
      "1  0.660652  \n",
      "1  1.060934  \n",
      "1  0.503844  \n",
      "                      items ticker  Q1 2022  Q2 2022  Q3 2022  Q4 2022  \\\n",
      "1  Inventory Turnover Ratio    AXP      NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   PYPL      NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio      V      NaN      NaN      NaN      NaN   \n",
      "\n",
      "   Q4 2021  \n",
      "1      NaN  \n",
      "1      NaN  \n",
      "1      NaN  \n",
      "                      items ticker      Q1 2022      Q2 2022     Q3 2022  \\\n",
      "1  Inventory Turnover Ratio     BA     0.170949     0.182177    0.210311   \n",
      "1  Inventory Turnover Ratio    HXL  1142.481203  1115.808824  933.663366   \n",
      "1  Inventory Turnover Ratio    RTX     1.288337     1.267600    1.289285   \n",
      "1  Inventory Turnover Ratio    TDG     0.438683     0.475040    0.438636   \n",
      "1  Inventory Turnover Ratio    TXT     0.680317     0.706339    0.676971   \n",
      "1  Inventory Turnover Ratio    WWD     0.926991     0.934021    0.952381   \n",
      "\n",
      "    Q4 2022      Q4 2021  \n",
      "1  0.231910          NaN  \n",
      "1       NaN  1183.739837  \n",
      "1       NaN     1.482567  \n",
      "1  0.465465          NaN  \n",
      "1       NaN     0.793253  \n",
      "1  0.982490          NaN  \n",
      "                      items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "1  Inventory Turnover Ratio    CAT  0.635124  0.627794  0.604330  0.702213   \n",
      "1  Inventory Turnover Ratio     DE  0.832388  0.979070  1.042210  1.201295   \n",
      "1  Inventory Turnover Ratio    TEX  0.887079  0.897196  0.900102       NaN   \n",
      "1  Inventory Turnover Ratio    TTC  0.759615  0.946188  0.810437  0.735490   \n",
      "\n",
      "    Q4 2021  \n",
      "1       NaN  \n",
      "1       NaN  \n",
      "1  1.004914  \n",
      "1       NaN  \n",
      "                      items ticker   Q1 2023  Q2 2023  Q3 2023  Q4 2023  \\\n",
      "1  Inventory Turnover Ratio    CRM       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   ADBE       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   CSCO  1.984234      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   GOOG       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio  GOOGL       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   INTU       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   MSFT  3.620431      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio   ORCL       NaN      NaN      NaN      NaN   \n",
      "1  Inventory Turnover Ratio    SAP       NaN      NaN      NaN      NaN   \n",
      "\n",
      "     Q1 2022    Q2 2022   Q3 2022   Q4 2022    Q4 2021  \n",
      "1        NaN        NaN       NaN       NaN        NaN  \n",
      "1        NaN        NaN       NaN       NaN        NaN  \n",
      "1        NaN   2.268577  2.112954  1.977025        NaN  \n",
      "1  21.620891  15.204040  9.872624       NaN  28.194872  \n",
      "1  21.620891  15.204040  9.872624       NaN  28.194872  \n",
      "1        NaN        NaN       NaN       NaN        NaN  \n",
      "1        NaN   5.617754  4.737561  4.390433        NaN  \n",
      "1        NaN        NaN       NaN       NaN        NaN  \n",
      "1        NaN        NaN       NaN       NaN        NaN  \n",
      "                      items ticker     Q3 2022   Q4 2022   Q1 2023   Q2 2023  \\\n",
      "1  Inventory Turnover Ratio   CSCO    2.112954  1.977025  1.984234  1.644904   \n",
      "1  Inventory Turnover Ratio   AMZN    1.917428       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio   AVGO    1.513602  1.560000       NaN       NaN   \n",
      "1  Inventory Turnover Ratio   DELL         NaN  4.070024  3.239127  3.567228   \n",
      "1  Inventory Turnover Ratio   FTNT    1.310185       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio   MSFT    4.737561  4.390433  3.620431       NaN   \n",
      "1  Inventory Turnover Ratio   PANW         NaN       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio    RNG  167.000000       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio    VMW         NaN       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio     ZM         NaN       NaN       NaN       NaN   \n",
      "1  Inventory Turnover Ratio     ZS         NaN       NaN       NaN       NaN   \n",
      "\n",
      "     Q4 2021    Q1 2022    Q2 2022   Q3 2023  \n",
      "1        NaN        NaN        NaN       NaN  \n",
      "1   2.537837   1.900677   1.740990       NaN  \n",
      "1        NaN   1.746711   1.596523       NaN  \n",
      "1        NaN        NaN        NaN  3.080687  \n",
      "1   1.295455   1.372973   1.287179       NaN  \n",
      "1        NaN        NaN   5.617754       NaN  \n",
      "1        NaN        NaN        NaN       NaN  \n",
      "1  22.666667  25.833333  31.600000       NaN  \n",
      "1        NaN        NaN        NaN       NaN  \n",
      "1        NaN        NaN        NaN       NaN  \n",
      "1        NaN        NaN        NaN       NaN  \n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "\"['Q4 2022'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/2742613373.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     11\u001b[0m     \u001b[0mi_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[0mj_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m     \u001b[0mi_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minventory_turnover_ratio\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mj_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m     \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_row\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/1604186101.py\u001b[0m in \u001b[0;36minventory_turnover_ratio\u001b[1;34m(i_df, j_df, symbol)\u001b[0m\n\u001b[0;32m     42\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ticker'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     43\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'items'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"Inventory Turnover Ratio\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 44\u001b[1;33m         \u001b[0mthird_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj_df_columns\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     45\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     46\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3462\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3463\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3464\u001b[1;33m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3466\u001b[0m         \u001b[1;31m# take() does not accept boolean indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1312\u001b[0m             \u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1314\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1315\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1316\u001b[0m         if needs_i8_conversion(ax.dtype) or isinstance(\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[1;34m(self, key, indexer, axis)\u001b[0m\n\u001b[0;32m   1375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1376\u001b[0m             \u001b[0mnot_found\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1377\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{not_found} not in index\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1378\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1379\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Q4 2022'] not in index\""
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    j_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    j_df = pd.read_csv(j_csv)\n",
    "    i_row = inventory_turnover_ratio(i_df, j_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "#     print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        i_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "        j_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        i_competitor_df = pd.read_csv(i_competitor_csv)\n",
    "        j_competitor_df = pd.read_csv(j_competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = inventory_turnover_ratio(i_competitor_df, j_competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f608e48c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def current_ratio(df, symbol=\"\"):\n",
    "    \"\"\"\n",
    "    A ratio under 1.00 indicates that the company’s debts due in a year or less \n",
    "    are greater than its assets—cash or other short-term assets expected to be converted to cash within a year or less. \n",
    "    \n",
    "    A current ratio of less than 1.00 may seem alarming, although different situations \n",
    "    can negatively affect the current ratio in a solid company.\n",
    "    \"\"\"\n",
    "    \n",
    "    try:\n",
    "        for j in df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            df[j] = pd.to_numeric(df[j])\n",
    "\n",
    "        df_columns = []\n",
    "\n",
    "        for col in df.columns:\n",
    "            df_columns.append(col)\n",
    "\n",
    "        df_columns.insert(1, df_columns[-1])\n",
    "        del df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "\n",
    "        first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Current Assets'), df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Current Liabilities'), df_columns[2:]]\n",
    "#         print(first_row)\n",
    "#         print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Current Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Current Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e950f94e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'DELL', 'GOOG', 'GOOGL', 'HPQ', 'META', 'MSFT']\n",
      "            items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "11  Current Ratio   AAPL  0.926844  0.864629  0.879356  0.938020       NaN   \n",
      "8   Current Ratio   AMZN  0.952784  0.936593       NaN       NaN  1.135760   \n",
      "14  Current Ratio   DELL       NaN       NaN  0.801028  0.779811       NaN   \n",
      "10  Current Ratio   GOOG  2.809450  2.517604       NaN       NaN  2.928113   \n",
      "10  Current Ratio  GOOGL  2.809450  2.517604       NaN       NaN  2.928113   \n",
      "12  Current Ratio    HPQ  0.813499  0.857772  0.757122       NaN       NaN   \n",
      "7   Current Ratio   META  2.520007  2.570415       NaN       NaN  3.154294   \n",
      "11  Current Ratio   MSFT  2.247297  1.987655  1.784607  1.840186       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2023   Q3 2023  \n",
      "11       NaN       NaN       NaN  \n",
      "8   0.959630       NaN       NaN  \n",
      "14       NaN  0.771359  0.745803  \n",
      "10  2.871005       NaN       NaN  \n",
      "10  2.871005       NaN       NaN  \n",
      "12  0.742806       NaN       NaN  \n",
      "7   2.810633       NaN       NaN  \n",
      "11       NaN       NaN       NaN  \n",
      "['ABBV', 'AZN', 'GILD', 'JNJ', 'MRNA', 'PFE', 'REGN']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "9   Current Ratio   AMGN  1.437219  1.531304  1.679018  1.414292       NaN\n",
      "9   Current Ratio   ABBV  0.815135  0.844139  0.928222       NaN  0.793544\n",
      "10  Current Ratio    AZN  0.995910  0.958836  0.813843       NaN  1.161547\n",
      "8   Current Ratio   GILD  1.475695  1.428959  1.300393       NaN  1.272351\n",
      "12  Current Ratio    JNJ  1.392579  1.424489  1.432405       NaN  1.348317\n",
      "12  Current Ratio   MRNA  1.769864  1.991045  2.100338       NaN  1.760627\n",
      "14  Current Ratio    PFE  1.385861  1.423033  1.588730       NaN  1.398913\n",
      "10  Current Ratio   REGN  4.755984  5.118655  5.359152       NaN  3.563438\n",
      "['BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'V']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "6   Current Ratio    AXP       NaN       NaN       NaN       NaN       NaN\n",
      "8   Current Ratio     MA  1.337441  1.258668  1.248367       NaN  1.287722\n",
      "8   Current Ratio   PYPL  1.191394  1.225236  1.274752       NaN  1.221827\n",
      "10  Current Ratio      V  1.395196  1.288151  1.426510  1.448473       NaN\n",
      "['AM', 'HXL', 'RTX', 'TDG', 'TXT', 'WWD']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Current Ratio     BA  1.297704  1.250015  1.219074  1.216220       NaN\n",
      "5   Current Ratio     AM  0.575540  0.620968  0.764151       NaN  0.736842\n",
      "8   Current Ratio    HXL  2.769231  2.553506  2.411972       NaN  2.483871\n",
      "9   Current Ratio    RTX  1.162107  1.097227  1.089855       NaN  1.186211\n",
      "8   Current Ratio    TDG  5.058781  5.045350  4.693452  3.961431       NaN\n",
      "9   Current Ratio    TXT  2.290680  2.138169  2.062310       NaN  2.372768\n",
      "14  Current Ratio    WWD  4.384848  3.607046  2.957547  2.434137       NaN\n",
      "['DE', 'TEX', 'TTC']\n",
      "           items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "9  Current Ratio    CAT  1.441487  1.449505  1.409741  1.388633       NaN\n",
      "9  Current Ratio     DE       NaN       NaN       NaN       NaN       NaN\n",
      "9  Current Ratio    TEX  1.994565  1.998953  1.959077       NaN  1.942857\n",
      "9  Current Ratio    TTC  1.457404  1.497750  1.586548  1.574248       NaN\n",
      "['ADBE', 'CSCO', 'GOOG', 'GOOGL', 'INTU', 'MSFT', 'ORCL', 'SAP']\n",
      "            items ticker   Q1 2023   Q2 2023   Q3 2023   Q4 2023   Q1 2022  \\\n",
      "5   Current Ratio    CRM  1.025730  1.058068  1.053876  1.019466       NaN   \n",
      "8   Current Ratio   ADBE       NaN       NaN       NaN       NaN  1.038766   \n",
      "14  Current Ratio   CSCO  1.451679       NaN       NaN       NaN       NaN   \n",
      "10  Current Ratio   GOOG       NaN       NaN       NaN       NaN  2.871005   \n",
      "10  Current Ratio  GOOGL       NaN       NaN       NaN       NaN  2.871005   \n",
      "9   Current Ratio   INTU  1.369624       NaN       NaN       NaN       NaN   \n",
      "11  Current Ratio   MSFT  1.840186       NaN       NaN       NaN       NaN   \n",
      "7   Current Ratio   ORCL  0.603234  0.647864       NaN       NaN       NaN   \n",
      "7   Current Ratio    SAP       NaN       NaN       NaN       NaN  1.111285   \n",
      "\n",
      "     Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "5        NaN       NaN       NaN       NaN  \n",
      "8   1.070819  1.141301  1.106791       NaN  \n",
      "14  1.419988  1.489896  1.432020       NaN  \n",
      "10  2.809450  2.517604       NaN  2.928113  \n",
      "10  2.809450  2.517604       NaN  2.928113  \n",
      "9   1.175876  1.631300  1.390358       NaN  \n",
      "11  2.247297  1.987655  1.784607       NaN  \n",
      "7        NaN  1.520424  1.621291       NaN  \n",
      "7   0.963004  1.029951       NaN  1.242191  \n",
      "['AMZN', 'AVGO', 'DELL', 'FTNT', 'MSFT', 'PANW', 'RNG', 'VMW', 'ZM', 'ZS']\n",
      "            items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023   Q4 2021  \\\n",
      "16  Current Ratio   CSCO  1.489896  1.432020  1.451679  1.413291       NaN   \n",
      "8   Current Ratio   AMZN  0.936593       NaN       NaN       NaN  1.135760   \n",
      "8   Current Ratio   AVGO  2.321844  2.623936       NaN       NaN       NaN   \n",
      "14  Current Ratio   DELL       NaN  0.801028  0.779811  0.771359       NaN   \n",
      "11  Current Ratio   FTNT  1.072662       NaN       NaN       NaN  1.553494   \n",
      "11  Current Ratio   MSFT  1.987655  1.784607  1.840186       NaN       NaN   \n",
      "10  Current Ratio   PANW  0.742217  0.772333  0.699695       NaN       NaN   \n",
      "9   Current Ratio    RNG  1.212833       NaN       NaN       NaN  1.237643   \n",
      "11  Current Ratio    VMW       NaN  0.825407  0.747076  0.761312       NaN   \n",
      "12  Current Ratio     ZM       NaN  3.913924  3.628524  3.435458       NaN   \n",
      "8   Current Ratio     ZS  2.242059  1.990300  2.009901       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2023  \n",
      "16       NaN       NaN       NaN  \n",
      "8   0.959630  0.952784       NaN  \n",
      "8   2.440115  2.143271       NaN  \n",
      "14       NaN       NaN  0.745803  \n",
      "11  1.277579  1.120683       NaN  \n",
      "11       NaN  2.247297       NaN  \n",
      "10       NaN  0.657440       NaN  \n",
      "9   1.251736  1.188103       NaN  \n",
      "11       NaN       NaN  0.703451  \n",
      "12       NaN       NaN  3.239451  \n",
      "8        NaN  2.379187       NaN  \n",
      "['BP', 'COP', 'ROSN', 'SHEL', 'XOM']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "11  Current Ratio    CVX  1.432843  1.308453  1.396389  1.471673       NaN   \n",
      "12  Current Ratio     BP  1.187241  1.157917  1.041271       NaN  1.153238   \n",
      "13  Current Ratio    COP  1.512904  1.543877  1.461242       NaN  1.335163   \n",
      "0   Current Ratio   ROSN       NaN       NaN       NaN       NaN       NaN   \n",
      "6   Current Ratio   SHEL  1.341780  1.392204  1.376213       NaN  1.347661   \n",
      "10  Current Ratio    XOM  1.072108  1.162938  1.340711       NaN  1.044330   \n",
      "\n",
      "     Q2 2014   Q3 2014   Q4 2014  Q1 2015  \n",
      "11       NaN       NaN       NaN      NaN  \n",
      "12       NaN       NaN       NaN      NaN  \n",
      "13       NaN       NaN       NaN      NaN  \n",
      "0   0.042105  0.682051  0.257485      0.0  \n",
      "6        NaN       NaN       NaN      NaN  \n",
      "10       NaN       NaN       NaN      NaN  \n",
      "['AAPL', 'CHTR', 'CMCSA', 'DISH', 'FOX', 'FOXA', 'NFLX', 'PARA', 'PARAA']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "6   Current Ratio    DIS  1.095749  1.061687  1.023385  1.000860       NaN   \n",
      "9   Current Ratio   AAPL  1.037812  0.926844  0.864629  0.879356       NaN   \n",
      "5   Current Ratio   CHTR  0.396008  0.328039  0.323760       NaN  0.286242   \n",
      "7   Current Ratio  CMCSA  0.855818  0.876998  0.836316       NaN  0.845271   \n",
      "11  Current Ratio   DISH  0.657927  0.635171  0.495286       NaN  1.154543   \n",
      "4   Current Ratio    FOX       NaN  2.966551  3.732202  3.606707       NaN   \n",
      "4   Current Ratio   FOXA       NaN  2.966551  3.732202  3.606707       NaN   \n",
      "6   Current Ratio   NFLX  1.046253  1.045467  1.135334       NaN  0.950642   \n",
      "7   Current Ratio   PARA  1.579142  1.471773  1.309704       NaN  1.759257   \n",
      "7   Current Ratio  PARAA  1.579142  1.471773  1.309704       NaN  1.759257   \n",
      "\n",
      "     Q1 2023  \n",
      "6        NaN  \n",
      "9        NaN  \n",
      "5        NaN  \n",
      "7        NaN  \n",
      "11       NaN  \n",
      "4   3.596528  \n",
      "4   3.596528  \n",
      "6        NaN  \n",
      "7        NaN  \n",
      "7        NaN  \n",
      "['APD', 'DD', 'EMN', 'HUN', 'LIN']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "12  Current Ratio    DOW  1.576289  1.697947  1.635660  1.605928       NaN\n",
      "10  Current Ratio    APD       NaN  2.465399  1.949766  1.868800  1.812752\n",
      "13  Current Ratio     DD  2.900629  2.819797  2.549327  2.386099       NaN\n",
      "12  Current Ratio    EMN  1.563783  1.571747  1.271601  1.280012       NaN\n",
      "14  Current Ratio    HUN  1.915163  1.882908  2.118989  2.003762       NaN\n",
      "8   Current Ratio    LIN  0.744631  0.844961  0.736973  0.743842       NaN\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['BAC', 'BK', 'BLK', 'C', 'MS', 'SCHW', 'UBS', 'WFC']\n",
      "           items ticker  Q4 2021  Q1 2022  Q2 2022  Q3 2022\n",
      "6  Current Ratio     GS      NaN      NaN      NaN      NaN\n",
      "2  Current Ratio    BLK      NaN      NaN      NaN      NaN\n",
      "4  Current Ratio     MS      NaN      NaN      NaN      NaN\n",
      "2  Current Ratio   SCHW      NaN      NaN      NaN      NaN\n",
      "['AMZN', 'FAST', 'GWW', 'LOW', 'SHW', 'TGT', 'TSCO', 'WMT']\n",
      "           items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023   Q4 2021  \\\n",
      "4  Current Ratio     HD  1.012616  1.114523  1.183481  1.387191       NaN   \n",
      "8  Current Ratio   AMZN       NaN       NaN       NaN       NaN  1.135760   \n",
      "7  Current Ratio   FAST       NaN       NaN       NaN       NaN  4.189150   \n",
      "6  Current Ratio    GWW       NaN       NaN       NaN       NaN  2.625000   \n",
      "5  Current Ratio    LOW  1.019931  1.173148  1.112982  1.197116       NaN   \n",
      "8  Current Ratio    SHW       NaN       NaN       NaN       NaN  0.883566   \n",
      "5  Current Ratio    TGT  0.991999  0.866290  0.822143  0.857461       NaN   \n",
      "4  Current Ratio   TSCO       NaN       NaN       NaN       NaN  1.573850   \n",
      "4  Current Ratio    WMT  0.927797  0.862115  0.842491  0.864626       NaN   \n",
      "\n",
      "    Q1 2022   Q2 2022   Q3 2022  \n",
      "4       NaN       NaN       NaN  \n",
      "8  0.959630  0.952784  0.936593  \n",
      "7  4.067024  3.713781  3.980075  \n",
      "6  2.548220  2.578857  2.625210  \n",
      "5       NaN       NaN       NaN  \n",
      "8  0.875306  0.869686  1.003445  \n",
      "5       NaN       NaN       NaN  \n",
      "4  1.440000  1.440678  1.484487  \n",
      "4       NaN       NaN       NaN  \n",
      "['GE', 'GRMN', 'JCI', 'MMM']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "13  Current Ratio    HON  1.300595  1.212413  1.195518  1.243857       NaN\n",
      "13  Current Ratio     GE  1.277077  1.186619  1.125735  1.099255       NaN\n",
      "10  Current Ratio   GRMN  2.943370  3.540330  2.538793  2.749827       NaN\n",
      "12  Current Ratio    JCI       NaN  1.036648  0.996396  0.972734  1.039683\n",
      "12  Current Ratio    MMM  1.704815  1.579108  1.466653  1.560830       NaN\n",
      "['ACN', 'ADBE', 'CSCO', 'DELL', 'GOOG', 'GOOGL', 'HPE', 'MSFT', 'ORCL', 'SAP']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "17  Current Ratio    IBM  0.878640  0.919955  0.876021  0.951848       NaN   \n",
      "5   Current Ratio    ACN       NaN       NaN  1.234556  1.268369  1.233293   \n",
      "8   Current Ratio   ADBE       NaN  1.038766  1.070819  1.141301  1.106791   \n",
      "14  Current Ratio   CSCO       NaN       NaN  1.419988  1.489896  1.432020   \n",
      "14  Current Ratio   DELL       NaN       NaN       NaN       NaN  0.801028   \n",
      "10  Current Ratio   GOOG  2.928113  2.871005  2.809450  2.517604       NaN   \n",
      "10  Current Ratio  GOOGL  2.928113  2.871005  2.809450  2.517604       NaN   \n",
      "12  Current Ratio    HPE       NaN  0.944757  0.900050  0.916522  0.884871   \n",
      "11  Current Ratio   MSFT       NaN       NaN  2.247297  1.987655  1.784607   \n",
      "7   Current Ratio   ORCL       NaN       NaN       NaN  1.520424  1.621291   \n",
      "7   Current Ratio    SAP  1.242191  1.111285  0.963004  1.029951       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "17       NaN       NaN       NaN  \n",
      "5   1.255893       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "14  1.451679       NaN       NaN  \n",
      "14  0.779811  0.771359  0.745803  \n",
      "10       NaN       NaN       NaN  \n",
      "10       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "11  1.840186       NaN       NaN  \n",
      "7   0.603234  0.647864       NaN  \n",
      "7        NaN       NaN       NaN  \n",
      "['AMAT', 'AMD', 'AVGO', 'MU', 'NVDA', 'QCOM', 'TXN']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "11  Current Ratio   INTC  2.132328  2.133824  1.858623  1.771222       NaN   \n",
      "14  Current Ratio   AMAT       NaN  2.507503  2.292331  2.258744  2.158152   \n",
      "12  Current Ratio    AMD  2.024292  2.395449  2.437443  2.155134       NaN   \n",
      "8   Current Ratio   AVGO       NaN  2.440115  2.143271  2.321844  2.623936   \n",
      "13  Current Ratio     MU       NaN       NaN  3.108124  3.239834  2.889110   \n",
      "9   Current Ratio   NVDA       NaN       NaN       NaN       NaN  6.650288   \n",
      "11  Current Ratio   QCOM       NaN  1.647682  1.608845  1.606137  1.746503   \n",
      "12  Current Ratio    TXN  5.326975  5.541930  5.094922  4.922087       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "11       NaN       NaN       NaN  \n",
      "14       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "13  3.512797       NaN       NaN  \n",
      "9   5.317332  3.620494  3.387746  \n",
      "11       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "['ABT', 'AZN', 'MDT', 'MRK', 'NOVN', 'PFE', 'PG', 'ROG']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022  \\\n",
      "12  Current Ratio    JNJ  1.348317  1.392579  1.424489  1.432405       NaN   \n",
      "11  Current Ratio    ABT  1.849599  1.852534  2.013880  1.858960       NaN   \n",
      "10  Current Ratio    AZN  1.161547  0.995910  0.958836  0.813843       NaN   \n",
      "12  Current Ratio    MDT       NaN       NaN       NaN  2.610395  1.860497   \n",
      "12  Current Ratio    MRK  1.267845  1.397383  1.386222  1.459301       NaN   \n",
      "9   Current Ratio   NOVN  4.854709  1.249218  1.402151       NaN       NaN   \n",
      "14  Current Ratio    PFE  1.398913  1.385861  1.423033  1.588730       NaN   \n",
      "7   Current Ratio     PG       NaN       NaN  0.671760  0.680678  0.654545   \n",
      "12  Current Ratio    ROG  3.560976  3.583851  4.103226  4.623188       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2021  \n",
      "12       NaN       NaN       NaN  \n",
      "11       NaN       NaN       NaN  \n",
      "10       NaN       NaN       NaN  \n",
      "12  1.575557  1.755824       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "9        NaN       NaN  4.856624  \n",
      "14       NaN       NaN       NaN  \n",
      "7   0.615025       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "['BAC', 'BMO', 'C', 'RY', 'TD', 'WFC']\n",
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022, Q4 2022]\n",
      "Index: []\n",
      "['CCEP', 'COKE', 'FIZZ', 'KDP', 'KHC', 'MDLZ', 'MNST', 'PEP', 'PRMW', 'SBUX']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2020  \\\n",
      "12  Current Ratio     KO  1.130075  1.179326  1.127125  1.125939       NaN   \n",
      "10  Current Ratio   CCEP  0.945347       NaN  0.940939       NaN  0.984541   \n",
      "12  Current Ratio   COKE  1.289820  1.175615  1.241556  1.402509       NaN   \n",
      "7   Current Ratio   FIZZ       NaN       NaN       NaN  1.991597       NaN   \n",
      "16  Current Ratio    KDP  0.471396  0.541253  0.557758  0.597954       NaN   \n",
      "12  Current Ratio    KHC  0.992277  1.023279  0.892422  0.904904       NaN   \n",
      "13  Current Ratio   MDLZ  0.738292  0.682053  0.678303  0.691991       NaN   \n",
      "9   Current Ratio   MNST  4.851813  4.544061  4.293419  4.186275       NaN   \n",
      "12  Current Ratio    PEP  0.830778  0.865164  0.831393  0.917748       NaN   \n",
      "11  Current Ratio   PRMW  0.718310  0.720399  0.776224  0.755556       NaN   \n",
      "11  Current Ratio   SBUX       NaN  0.813250  0.828317  0.841228       NaN   \n",
      "\n",
      "     Q2 2021   Q4 2022   Q1 2023  Q2 2023  \n",
      "12       NaN       NaN       NaN      NaN  \n",
      "10  0.907718       NaN       NaN      NaN  \n",
      "12       NaN       NaN       NaN      NaN  \n",
      "7        NaN  1.896552  1.924242  2.02027  \n",
      "16       NaN       NaN       NaN      NaN  \n",
      "12       NaN       NaN       NaN      NaN  \n",
      "13       NaN       NaN       NaN      NaN  \n",
      "9        NaN       NaN       NaN      NaN  \n",
      "12       NaN       NaN       NaN      NaN  \n",
      "11       NaN       NaN       NaN      NaN  \n",
      "11       NaN  0.766936       NaN      NaN  \n",
      "['CMG', 'DPZ', 'JACK', 'PZZA', 'QSR', 'SBUX', 'SHAK', 'WEN', 'YUM', 'YUMC']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "4   Current Ratio    MCD  1.778358  1.099410  1.413506  1.646873       NaN\n",
      "8   Current Ratio    CMG  1.581236  1.314149  1.257212  1.316626       NaN\n",
      "5   Current Ratio    DPZ  1.456853  1.447059  1.471304  1.426598       NaN\n",
      "13  Current Ratio   JACK       NaN  0.586331  0.410501  0.438034  0.542146\n",
      "10  Current Ratio   PZZA  0.888502  1.025090  0.960000  0.909091       NaN\n",
      "7   Current Ratio    QSR  0.966986  0.922319  0.889393  1.002083       NaN\n",
      "11  Current Ratio   SBUX       NaN  0.813250  0.828317  0.841228  0.766936\n",
      "6   Current Ratio   SHAK  3.388430  3.071429  2.895522  2.531034       NaN\n",
      "11  Current Ratio    WEN  1.388759  2.647059  2.616541  2.619617       NaN\n",
      "6   Current Ratio    YUM  1.082686  1.041475  1.207946  1.282154       NaN\n",
      "10  Current Ratio   YUMC  1.979018  2.046043  2.125406  2.238593       NaN\n",
      "['DD', 'GE', 'HON', 'ITW', 'JNJ']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "12  Current Ratio    MMM  1.704815  1.579108  1.466653  1.560830\n",
      "13  Current Ratio     DD  2.900629  2.819797  2.549327  2.386099\n",
      "13  Current Ratio     GE  1.277077  1.186619  1.125735  1.099255\n",
      "13  Current Ratio    HON  1.300595  1.212413  1.195518  1.243857\n",
      "9   Current Ratio    ITW  1.836888  1.731985  1.483698  1.410747\n",
      "12  Current Ratio    JNJ  1.348317  1.392579  1.424489  1.432405\n",
      "['ABT', 'BMY', 'GSK', 'JNJ', 'LLY', 'NOVN', 'PFE', 'SAN', 'ZTS']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q3 2021\n",
      "12  Current Ratio    MRK  1.267845  1.397383  1.386222  1.459301       NaN\n",
      "11  Current Ratio    ABT  1.849599  1.852534  2.013880  1.858960       NaN\n",
      "16  Current Ratio    BMY  1.521035  1.319881  1.443270  1.415531       NaN\n",
      "10  Current Ratio    GSK  0.788931  1.194003  1.432219  0.966401       NaN\n",
      "12  Current Ratio    JNJ  1.348317  1.392579  1.424489  1.432405       NaN\n",
      "10  Current Ratio    LLY  1.225802  1.267369  1.095640  1.126941       NaN\n",
      "9   Current Ratio   NOVN  4.854709  1.249218  1.402151       NaN  4.856624\n",
      "14  Current Ratio    PFE  1.398913  1.385861  1.423033  1.588730       NaN\n",
      "11  Current Ratio    ZTS  3.856427  2.253461  2.179941  2.274653       NaN\n",
      "['AAPL', 'AVGO', 'CRM', 'CSCO', 'GOOG', 'GOOGL', 'IBM', 'ORCL', 'SAP']\n",
      "            items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q1 2022  \\\n",
      "11  Current Ratio   MSFT  2.247297  1.987655  1.784607  1.840186       NaN   \n",
      "9   Current Ratio   AAPL  0.926844  0.864629  0.879356       NaN  1.037812   \n",
      "8   Current Ratio   AVGO  2.143271  2.321844  2.623936       NaN  2.440115   \n",
      "5   Current Ratio    CRM       NaN       NaN  1.048742  1.025730       NaN   \n",
      "14  Current Ratio   CSCO  1.419988  1.489896  1.432020  1.451679       NaN   \n",
      "10  Current Ratio   GOOG  2.809450  2.517604       NaN       NaN  2.871005   \n",
      "10  Current Ratio  GOOGL  2.809450  2.517604       NaN       NaN  2.871005   \n",
      "17  Current Ratio    IBM  0.876021  0.951848       NaN       NaN  0.919955   \n",
      "7   Current Ratio   ORCL       NaN  1.520424  1.621291  0.603234       NaN   \n",
      "7   Current Ratio    SAP  0.963004  1.029951       NaN       NaN  1.111285   \n",
      "\n",
      "     Q2 2023   Q3 2023   Q4 2021  \n",
      "11       NaN       NaN       NaN  \n",
      "9        NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "5   1.058068  1.053876       NaN  \n",
      "14       NaN       NaN       NaN  \n",
      "10       NaN       NaN  2.928113  \n",
      "10       NaN       NaN  2.928113  \n",
      "17       NaN       NaN  0.878640  \n",
      "7   0.647864       NaN       NaN  \n",
      "7        NaN       NaN  1.242191  \n",
      "['ADS', 'CROX', 'SKX', 'UA', 'UAA', 'VFC']\n",
      "            items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023   Q4 2021  \\\n",
      "8   Current Ratio    NKE  3.057609  2.629357  2.644656  2.691146       NaN   \n",
      "4   Current Ratio    ADS       NaN       NaN       NaN       NaN       NaN   \n",
      "9   Current Ratio   CROX  1.966725       NaN       NaN       NaN  1.719072   \n",
      "10  Current Ratio    SKX  2.271401       NaN       NaN       NaN  2.331950   \n",
      "6   Current Ratio     UA       NaN  2.180908  2.056203  2.090292  2.300690   \n",
      "6   Current Ratio    UAA       NaN  2.180908  2.056203  2.090292  2.300690   \n",
      "13  Current Ratio    VFC  1.427109  1.384012  1.331409  1.063973       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022  \n",
      "8        NaN       NaN  \n",
      "4        NaN       NaN  \n",
      "9   1.956685  1.940199  \n",
      "10  2.436700  2.336387  \n",
      "6        NaN       NaN  \n",
      "6        NaN       NaN  \n",
      "13       NaN       NaN  \n",
      "['CL', 'EL', 'JNJ', 'OR']\n",
      "            items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "7   Current Ratio     PG  0.671760  0.680678  0.654545  0.615025       NaN   \n",
      "12  Current Ratio     CL  1.174061  1.174978       NaN       NaN  1.085411   \n",
      "10  Current Ratio     EL  1.727699  1.754710  1.598968  1.682034       NaN   \n",
      "12  Current Ratio    JNJ  1.424489  1.432405       NaN       NaN  1.348317   \n",
      "11  Current Ratio     OR  1.428571  0.981132       NaN       NaN  0.442197   \n",
      "\n",
      "     Q1 2022  \n",
      "7        NaN  \n",
      "12  1.092641  \n",
      "10       NaN  \n",
      "12  1.392579  \n",
      "11  1.246914  \n",
      "['AIG', 'AIZ', 'ALL', 'CB', 'CINF', 'HIG', 'L', 'PGR', 'WRB']\n",
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022]\n",
      "Index: []\n",
      "['CI', 'CVS', 'ELV', 'HUM']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "13  Current Ratio    CVS  0.884982  0.881098  0.907752  0.943819\n",
      "['AXP', 'BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'WFC']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "10  Current Ratio      V  1.395196  1.288151  1.426510  1.448473       NaN\n",
      "6   Current Ratio    AXP       NaN       NaN       NaN       NaN       NaN\n",
      "8   Current Ratio     MA  1.337441  1.258668  1.248367       NaN  1.287722\n",
      "8   Current Ratio   PYPL  1.191394  1.225236  1.274752       NaN  1.221827\n",
      "['AAPL', 'T', 'TBB', 'TBC', 'TDS', 'TMUS', 'USM']\n",
      "            items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "9   Current Ratio     VZ  0.778796  0.763765  0.761803  0.747935       NaN\n",
      "9   Current Ratio   AAPL       NaN  1.037812  0.926844  0.864629  0.879356\n",
      "11  Current Ratio      T  1.607531  0.931656  0.701071  0.618003       NaN\n",
      "11  Current Ratio    TBB  1.607531  0.931656  0.701071  0.618003       NaN\n",
      "11  Current Ratio    TBC  1.607531  0.931656  0.701071  0.618003       NaN\n",
      "13  Current Ratio    TDS  1.732203  1.869955  1.662075  1.480483       NaN\n",
      "9   Current Ratio   TMUS  0.889017  0.814779  0.847444  0.812799       NaN\n",
      "11  Current Ratio    USM  1.777409  1.845361  1.703666  1.524113       NaN\n",
      "['ABC', 'AMZN', 'CVS', 'MCK', 'RAD']\n",
      "            items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "8   Current Ratio    WBA  0.830940  0.741178  0.784144  0.748439       NaN   \n",
      "10  Current Ratio    ABC  0.946292  0.920837  0.921004  0.910575       NaN   \n",
      "8   Current Ratio   AMZN  0.959630  0.952784  0.936593       NaN  1.135760   \n",
      "13  Current Ratio    CVS  0.881098  0.907752  0.943819       NaN  0.884982   \n",
      "7   Current Ratio    MCK       NaN       NaN  0.979895  0.953885       NaN   \n",
      "6   Current Ratio    RAD       NaN       NaN       NaN  1.175929       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "8        NaN       NaN       NaN  \n",
      "10       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "13       NaN       NaN       NaN  \n",
      "7   0.961484  0.960523       NaN  \n",
      "6   1.262023  1.327066  1.302408  \n",
      "['AMZN', 'COST', 'CVS', 'DG', 'JD', 'PDD', 'TGT', 'TJX', 'WBA']\n",
      "            items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023   Q4 2021  \\\n",
      "4   Current Ratio    WMT  0.927797  0.862115  0.842491  0.864626       NaN   \n",
      "8   Current Ratio   AMZN       NaN       NaN       NaN       NaN  1.135760   \n",
      "6   Current Ratio   COST  1.021814  1.032752       NaN       NaN       NaN   \n",
      "13  Current Ratio    CVS       NaN       NaN       NaN       NaN  0.884982   \n",
      "4   Current Ratio     DG  1.054357  0.969074  1.015330  1.232816       NaN   \n",
      "9   Current Ratio     JD       NaN       NaN       NaN       NaN  1.352091   \n",
      "11  Current Ratio    PDD       NaN       NaN       NaN       NaN  1.716729   \n",
      "5   Current Ratio    TGT  0.991999  0.866290  0.822143  0.857461       NaN   \n",
      "6   Current Ratio    TJX  1.266622  1.245633  1.166355  1.156222       NaN   \n",
      "8   Current Ratio    WBA  0.748439       NaN       NaN       NaN       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2022  \n",
      "4        NaN       NaN       NaN  \n",
      "8   0.959630  0.952784  0.936593  \n",
      "6        NaN  1.032335  1.036521  \n",
      "13  0.881098  0.907752  0.943819  \n",
      "4        NaN       NaN       NaN  \n",
      "9   1.320644  1.268136  1.304546  \n",
      "11  1.885465  2.046877  2.265779  \n",
      "5        NaN       NaN       NaN  \n",
      "6        NaN       NaN       NaN  \n",
      "8   0.830940  0.741178  0.784144  \n"
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = current_ratio(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "    print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = current_ratio(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7aebf880",
   "metadata": {},
   "outputs": [],
   "source": [
    "def quick_ratio(df, symbol=\"\"):\n",
    "    \"\"\"\n",
    "    The higher the ratio result, the better a company's liquidity and financial health; \n",
    "    the lower the ratio, the more likely the company will struggle with paying debts.\n",
    "    \"\"\"\n",
    "    try:\n",
    "        for j in df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            df[j] = df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            df[j] = pd.to_numeric(df[j])\n",
    "\n",
    "        df_columns = []\n",
    "\n",
    "        for col in df.columns:\n",
    "            df_columns.append(col)\n",
    "\n",
    "        df_columns.insert(1, df_columns[-1])\n",
    "        del df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "\n",
    "        first_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Current Assets'), df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = df.loc[(df['ticker'] == symbol) & (df['items'] == 'Total Inventory'), df_columns[2:]]\n",
    "#         print(first_row)\n",
    "#         print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Quick Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Quick Ratio\"\n",
    "        third_row = third_row[df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c4b83a92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AMZN', 'DELL', 'GOOG', 'GOOGL', 'HPQ', 'META', 'MSFT']\n",
      "          items ticker    Q2 2022    Q3 2022    Q4 2022    Q1 2023  \\\n",
      "11  Quick Ratio   AAPL  21.644689  20.668507  27.376668  18.882258   \n",
      "8   Quick Ratio   AMZN   3.503447   3.587279        NaN        NaN   \n",
      "14  Quick Ratio   DELL        NaN        NaN   7.635300   6.591684   \n",
      "10  Quick Ratio   GOOG  87.056061  52.632763        NaN        NaN   \n",
      "10  Quick Ratio  GOOGL  87.056061  52.632763        NaN        NaN   \n",
      "12  Quick Ratio    HPQ   2.629137   2.807129   2.607110        NaN   \n",
      "7   Quick Ratio   META        NaN        NaN        NaN        NaN   \n",
      "11  Quick Ratio   MSFT  57.697251  46.699636  45.345804  37.678538   \n",
      "\n",
      "       Q4 2021     Q1 2022  Q2 2023   Q3 2023  \n",
      "11         NaN         NaN      NaN       NaN  \n",
      "8     4.950368    3.826450      NaN       NaN  \n",
      "14         NaN         NaN  7.18375  6.284349  \n",
      "10  160.805983  129.914536      NaN       NaN  \n",
      "10  160.805983  129.914536      NaN       NaN  \n",
      "12         NaN    2.487470      NaN       NaN  \n",
      "7          NaN         NaN      NaN       NaN  \n",
      "11         NaN         NaN      NaN       NaN  \n",
      "['ABBV', 'AZN', 'GILD', 'JNJ', 'MRNA', 'PFE', 'REGN']\n",
      "          items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022    Q4 2021\n",
      "9   Quick Ratio   AMGN  4.198594  4.242863  5.058230  4.500203        NaN\n",
      "9   Quick Ratio   ABBV  7.610968  8.568905  9.572509       NaN   8.928389\n",
      "10  Quick Ratio    AZN  2.970488  3.362862  3.982670       NaN   2.921518\n",
      "8   Quick Ratio   GILD  8.521592  8.818608  9.264525       NaN   9.129790\n",
      "12  Quick Ratio    JNJ  5.498089  5.582495  5.587666       NaN   5.870704\n",
      "12  Quick Ratio   MRNA  8.419156  7.060385  6.883486       NaN  11.152672\n",
      "14  Quick Ratio    PFE  5.453452  6.453606  7.400715       NaN   6.589359\n",
      "10  Quick Ratio   REGN  7.181727  6.998648  6.396766       NaN   7.183496\n",
      "['BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'V']\n",
      "          items ticker  Q1 2022  Q2 2022  Q3 2022  Q4 2022  Q4 2021\n",
      "6   Quick Ratio    AXP      NaN      NaN      NaN      NaN      NaN\n",
      "8   Quick Ratio     MA      NaN      NaN      NaN      NaN      NaN\n",
      "8   Quick Ratio   PYPL      NaN      NaN      NaN      NaN      NaN\n",
      "10  Quick Ratio      V      NaN      NaN      NaN      NaN      NaN\n",
      "['AM', 'HXL', 'RTX', 'TDG', 'TXT', 'WWD']\n",
      "          items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Quick Ratio     BA  1.328155  1.326376  1.369455  1.401428       NaN\n",
      "5   Quick Ratio     AM       NaN       NaN       NaN       NaN       NaN\n",
      "8   Quick Ratio    HXL  2.571429  2.544118  2.260726       NaN  2.504065\n",
      "9   Quick Ratio    RTX  4.178890  4.088148  4.004692       NaN  4.581608\n",
      "8   Quick Ratio    TDG  5.737449  5.285024  4.778788  4.240991       NaN\n",
      "9   Quick Ratio    TXT  2.086814  1.986627  1.959654       NaN  2.145617\n",
      "14  Quick Ratio    WWD  3.201327  2.744330  2.488095  2.552529       NaN\n",
      "['DE', 'TEX', 'TTC']\n",
      "         items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022  Q4 2021\n",
      "9  Quick Ratio    CAT  2.830829  2.643536  2.525326  2.691149      NaN\n",
      "9  Quick Ratio     DE       NaN       NaN       NaN       NaN      NaN\n",
      "9  Quick Ratio    TEX  1.992400  1.982347  1.903160       NaN  2.17199\n",
      "9  Quick Ratio    TTC  1.727163  1.865471  1.708200  1.593720      NaN\n",
      "['ADBE', 'CSCO', 'GOOG', 'GOOGL', 'INTU', 'MSFT', 'ORCL', 'SAP']\n",
      "          items ticker    Q1 2023  Q2 2023  Q3 2023  Q4 2023     Q1 2022  \\\n",
      "5   Quick Ratio    CRM        NaN      NaN      NaN      NaN         NaN   \n",
      "8   Quick Ratio   ADBE        NaN      NaN      NaN      NaN         NaN   \n",
      "14  Quick Ratio   CSCO  13.566441      NaN      NaN      NaN         NaN   \n",
      "10  Quick Ratio   GOOG        NaN      NaN      NaN      NaN  129.914536   \n",
      "10  Quick Ratio  GOOGL        NaN      NaN      NaN      NaN  129.914536   \n",
      "9   Quick Ratio   INTU        NaN      NaN      NaN      NaN         NaN   \n",
      "11  Quick Ratio   MSFT  37.678538      NaN      NaN      NaN         NaN   \n",
      "7   Quick Ratio   ORCL        NaN      NaN      NaN      NaN         NaN   \n",
      "7   Quick Ratio    SAP        NaN      NaN      NaN      NaN         NaN   \n",
      "\n",
      "      Q2 2022    Q3 2022    Q4 2022     Q4 2021  \n",
      "5         NaN        NaN        NaN         NaN  \n",
      "8         NaN        NaN        NaN         NaN  \n",
      "14  17.872268  16.127745  14.297897         NaN  \n",
      "10  87.056061  52.632763        NaN  160.805983  \n",
      "10  87.056061  52.632763        NaN  160.805983  \n",
      "9         NaN        NaN        NaN         NaN  \n",
      "11  57.697251  46.699636  45.345804         NaN  \n",
      "7         NaN        NaN        NaN         NaN  \n",
      "7         NaN        NaN        NaN         NaN  \n",
      "['AMZN', 'AVGO', 'DELL', 'FTNT', 'MSFT', 'PANW', 'RNG', 'VMW', 'ZM', 'ZS']\n",
      "          items ticker     Q3 2022    Q4 2022    Q1 2023    Q2 2023  \\\n",
      "16  Quick Ratio   CSCO   16.127745  14.297897  13.566441  12.265924   \n",
      "8   Quick Ratio   AMZN    3.587279        NaN        NaN        NaN   \n",
      "8   Quick Ratio   AVGO    8.466268   9.612468        NaN        NaN   \n",
      "14  Quick Ratio   DELL         NaN   7.635300   6.591684   7.183750   \n",
      "11  Quick Ratio   FTNT   13.805556        NaN        NaN        NaN   \n",
      "11  Quick Ratio   MSFT   46.699636  45.345804  37.678538        NaN   \n",
      "10  Quick Ratio   PANW         NaN        NaN        NaN        NaN   \n",
      "9   Quick Ratio    RNG  775.000000        NaN        NaN        NaN   \n",
      "11  Quick Ratio    VMW         NaN        NaN        NaN        NaN   \n",
      "12  Quick Ratio     ZM         NaN        NaN        NaN        NaN   \n",
      "8   Quick Ratio     ZS         NaN        NaN        NaN        NaN   \n",
      "\n",
      "       Q4 2021     Q1 2022     Q2 2022   Q3 2023  \n",
      "16         NaN         NaN         NaN       NaN  \n",
      "8     4.950368    3.826450    3.503447       NaN  \n",
      "8          NaN   10.092763    8.878897       NaN  \n",
      "14         NaN         NaN         NaN  6.284349  \n",
      "11   20.460227   17.340541   15.143590       NaN  \n",
      "11         NaN         NaN   57.697251       NaN  \n",
      "10         NaN         NaN         NaN       NaN  \n",
      "9   108.500000  120.166667  147.800000       NaN  \n",
      "11         NaN         NaN         NaN       NaN  \n",
      "12         NaN         NaN         NaN       NaN  \n",
      "8          NaN         NaN         NaN       NaN  \n",
      "['BP', 'COP', 'ROSN', 'SHEL', 'XOM']\n",
      "          items ticker    Q1 2022    Q2 2022    Q3 2022   Q4 2022    Q4 2021  \\\n",
      "11  Quick Ratio    CVX   6.851954   6.634867   5.721284  6.104402        NaN   \n",
      "12  Quick Ratio     BP   3.989870   3.701433   3.676929       NaN   3.904939   \n",
      "13  Quick Ratio    COP  14.979557  15.283630  16.682708       NaN  13.286424   \n",
      "0   Quick Ratio   ROSN        NaN        NaN        NaN       NaN        NaN   \n",
      "6   Quick Ratio   SHEL   5.066016   4.578491   4.703724       NaN   5.097989   \n",
      "10  Quick Ratio    XOM   3.483564   3.950095   4.120559       NaN   3.149840   \n",
      "\n",
      "    Q2 2014  Q3 2014  Q4 2014  Q1 2015  \n",
      "11      NaN      NaN      NaN      NaN  \n",
      "12      NaN      NaN      NaN      NaN  \n",
      "13      NaN      NaN      NaN      NaN  \n",
      "0       NaN      NaN      NaN      NaN  \n",
      "6       NaN      NaN      NaN      NaN  \n",
      "10      NaN      NaN      NaN      NaN  \n",
      "['AAPL', 'CHTR', 'CMCSA', 'DISH', 'FOX', 'FOXA', 'NFLX', 'PARA', 'PARAA']\n",
      "          items ticker    Q1 2022    Q2 2022    Q3 2022    Q4 2022    Q4 2021  \\\n",
      "6   Quick Ratio    DIS  24.470632  22.007703  19.762264  16.703789        NaN   \n",
      "9   Quick Ratio   AAPL  26.064329  21.644689  20.668507  27.376668        NaN   \n",
      "5   Quick Ratio   CHTR        NaN        NaN        NaN        NaN        NaN   \n",
      "7   Quick Ratio  CMCSA        NaN        NaN        NaN        NaN        NaN   \n",
      "11  Quick Ratio   DISH   9.860335   8.259386   5.152364        NaN  14.061682   \n",
      "4   Quick Ratio    FOX        NaN   7.416376  10.071247  10.469027        NaN   \n",
      "4   Quick Ratio   FOXA        NaN   7.416376  10.071247  10.469027        NaN   \n",
      "6   Quick Ratio   NFLX        NaN        NaN        NaN        NaN        NaN   \n",
      "7   Quick Ratio   PARA  16.162105  10.528582   9.064343        NaN  11.087766   \n",
      "7   Quick Ratio  PARAA  16.162105  10.528582   9.064343        NaN  11.087766   \n",
      "\n",
      "     Q1 2023  \n",
      "6        NaN  \n",
      "9        NaN  \n",
      "5        NaN  \n",
      "7        NaN  \n",
      "11       NaN  \n",
      "4   8.328431  \n",
      "4   8.328431  \n",
      "6        NaN  \n",
      "7        NaN  \n",
      "7        NaN  \n",
      "['APD', 'DD', 'EMN', 'HUN', 'LIN']\n",
      "          items ticker   Q4 2021    Q1 2022    Q2 2022    Q3 2022    Q4 2022\n",
      "12  Quick Ratio    DOW  2.827998   2.856314   2.646687   2.612204        NaN\n",
      "10  Quick Ratio    APD       NaN  13.314168  12.301181  12.387160  12.223735\n",
      "13  Quick Ratio     DD  6.856663   6.453530   5.944822   6.083086        NaN\n",
      "12  Quick Ratio    EMN  3.089096   2.949731   2.192223   2.078481        NaN\n",
      "14  Quick Ratio    HUN  3.270608   2.885673   2.453248   2.962002        NaN\n",
      "8   Quick Ratio    LIN  5.862089   6.940544   6.311310   6.039353        NaN\n",
      "['BAC', 'BK', 'BLK', 'C', 'MS', 'SCHW', 'UBS', 'WFC']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         items ticker  Q4 2021  Q1 2022  Q2 2022  Q3 2022\n",
      "6  Quick Ratio     GS      NaN      NaN      NaN      NaN\n",
      "2  Quick Ratio    BLK      NaN      NaN      NaN      NaN\n",
      "4  Quick Ratio     MS      NaN      NaN      NaN      NaN\n",
      "2  Quick Ratio   SCHW      NaN      NaN      NaN      NaN\n",
      "['AMZN', 'FAST', 'GWW', 'LOW', 'SHW', 'TGT', 'TSCO', 'WMT']\n",
      "         items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023   Q4 2021  \\\n",
      "4  Quick Ratio     HD  1.316612  1.338775  1.262688  1.309577       NaN   \n",
      "8  Quick Ratio   AMZN       NaN       NaN       NaN       NaN  4.950368   \n",
      "7  Quick Ratio   FAST       NaN       NaN       NaN       NaN  1.874672   \n",
      "6  Quick Ratio    GWW       NaN       NaN       NaN       NaN  2.144920   \n",
      "5  Quick Ratio    LOW  1.139449  1.265428  1.172694  1.261089       NaN   \n",
      "8  Quick Ratio    SHW       NaN       NaN       NaN       NaN  2.622730   \n",
      "5  Quick Ratio    TGT  1.551791  1.190280  1.204504  1.191389       NaN   \n",
      "4  Quick Ratio   TSCO       NaN       NaN       NaN       NaN  1.483341   \n",
      "4  Quick Ratio    WMT  1.434588  1.359160  1.404583  1.355052       NaN   \n",
      "\n",
      "    Q1 2022   Q2 2022   Q3 2022  \n",
      "4       NaN       NaN       NaN  \n",
      "8  3.826450  3.503447  3.587279  \n",
      "7  1.895066  1.893694  1.904648  \n",
      "6  2.301192  2.267839  2.262675  \n",
      "5       NaN       NaN       NaN  \n",
      "8  2.613139  2.595357  2.400706  \n",
      "5       NaN       NaN       NaN  \n",
      "4  1.233645  1.299799  1.161314  \n",
      "4       NaN       NaN       NaN  \n",
      "['GE', 'GRMN', 'JCI', 'MMM']\n",
      "          items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2022\n",
      "13  Quick Ratio    HON  4.938108  4.437317  4.276722  4.094710       NaN\n",
      "13  Quick Ratio     GE  4.186786  3.820097  3.455706  3.426209       NaN\n",
      "10  Quick Ratio   GRMN  3.470684  3.046269  2.833677  2.588389       NaN\n",
      "12  Quick Ratio    JCI       NaN  4.269278  4.617097  4.490676  4.655378\n",
      "12  Quick Ratio    MMM  3.089870  2.731947  2.571125  2.652716       NaN\n",
      "['ACN', 'ADBE', 'CSCO', 'DELL', 'GOOG', 'GOOGL', 'HPE', 'MSFT', 'ORCL', 'SAP']\n",
      "          items ticker     Q4 2021     Q1 2022    Q2 2022    Q3 2022  \\\n",
      "17  Quick Ratio    IBM   17.913281   17.640766  16.565321  16.164437   \n",
      "5   Quick Ratio    ACN         NaN         NaN        NaN        NaN   \n",
      "8   Quick Ratio   ADBE         NaN         NaN        NaN        NaN   \n",
      "14  Quick Ratio   CSCO         NaN         NaN  17.872268  16.127745   \n",
      "14  Quick Ratio   DELL         NaN         NaN        NaN        NaN   \n",
      "10  Quick Ratio   GOOG  160.805983  129.914536  87.056061  52.632763   \n",
      "10  Quick Ratio  GOOGL  160.805983  129.914536  87.056061  52.632763   \n",
      "12  Quick Ratio    HPE         NaN    3.635031   3.414506   3.514764   \n",
      "11  Quick Ratio   MSFT         NaN         NaN  57.697251  46.699636   \n",
      "7   Quick Ratio   ORCL         NaN         NaN        NaN        NaN   \n",
      "7   Quick Ratio    SAP         NaN         NaN        NaN        NaN   \n",
      "\n",
      "      Q4 2022    Q1 2023  Q2 2023   Q3 2023  \n",
      "17        NaN        NaN      NaN       NaN  \n",
      "5         NaN        NaN      NaN       NaN  \n",
      "8         NaN        NaN      NaN       NaN  \n",
      "14  14.297897  13.566441      NaN       NaN  \n",
      "14   7.635300   6.591684  7.18375  6.284349  \n",
      "10        NaN        NaN      NaN       NaN  \n",
      "10        NaN        NaN      NaN       NaN  \n",
      "12   3.973261        NaN      NaN       NaN  \n",
      "11  45.345804  37.678538      NaN       NaN  \n",
      "7         NaN        NaN      NaN       NaN  \n",
      "7         NaN        NaN      NaN       NaN  \n",
      "['AMAT', 'AMD', 'AVGO', 'MU', 'NVDA', 'QCOM', 'TXN']\n",
      "          items ticker   Q4 2021    Q1 2022   Q2 2022   Q3 2022    Q4 2022  \\\n",
      "11  Quick Ratio   INTC  5.434113   5.242396  4.155413  3.839373        NaN   \n",
      "14  Quick Ratio   AMAT       NaN   3.470393  3.043322  2.803124   2.684592   \n",
      "12  Quick Ratio    AMD  4.390281   5.499383  5.083837  4.280202        NaN   \n",
      "8   Quick Ratio   AVGO       NaN  10.092763  8.878897  8.466268   9.612468   \n",
      "13  Quick Ratio     MU       NaN        NaN  3.994427  4.034109   3.268948   \n",
      "9   Quick Ratio   NVDA       NaN        NaN       NaN       NaN  11.066795   \n",
      "11  Quick Ratio   QCOM       NaN   5.237503  4.744237  3.506645   3.268254   \n",
      "12  Quick Ratio    TXN  7.164921   6.800971  5.931332  5.728785        NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "11       NaN       NaN       NaN  \n",
      "14       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "13  2.742074       NaN       NaN  \n",
      "9   9.350300  7.050141  5.213965  \n",
      "11       NaN       NaN       NaN  \n",
      "12       NaN       NaN       NaN  \n",
      "['ABT', 'AZN', 'MDT', 'MRK', 'NOVN', 'PFE', 'PG', 'ROG']\n",
      "          items ticker   Q4 2021    Q1 2022    Q2 2022   Q3 2022   Q4 2022  \\\n",
      "12  Quick Ratio    JNJ  5.870704   5.498089   5.582495  5.587666       NaN   \n",
      "11  Quick Ratio    ABT  4.700213   4.116851   4.230548  4.332926       NaN   \n",
      "10  Quick Ratio    AZN  2.921518   2.970488   3.362862  3.982670       NaN   \n",
      "12  Quick Ratio    MDT       NaN        NaN        NaN  5.162384  4.995451   \n",
      "12  Quick Ratio    MRK  5.084159   5.400762   5.802349  5.978090       NaN   \n",
      "9   Quick Ratio   NOVN       NaN  39.703654  39.804362       NaN       NaN   \n",
      "14  Quick Ratio    PFE  6.589359   5.453452   6.453606  7.400715       NaN   \n",
      "7   Quick Ratio     PG       NaN        NaN   3.828113  3.297564  3.127239   \n",
      "12  Quick Ratio    ROG  4.390977   3.796053   3.719298  3.666667       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023  Q3 2021  \n",
      "12       NaN       NaN      NaN  \n",
      "11       NaN       NaN      NaN  \n",
      "10       NaN       NaN      NaN  \n",
      "12  4.602828  5.024332      NaN  \n",
      "12       NaN       NaN      NaN  \n",
      "9        NaN       NaN      NaN  \n",
      "14       NaN       NaN      NaN  \n",
      "7   2.967194       NaN      NaN  \n",
      "12       NaN       NaN      NaN  \n",
      "['BAC', 'BMO', 'C', 'RY', 'TD', 'WFC']\n",
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022, Q4 2022]\n",
      "Index: []\n",
      "['CCEP', 'COKE', 'FIZZ', 'KDP', 'KHC', 'MDLZ', 'MNST', 'PEP', 'PRMW', 'SBUX']\n",
      "          items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022   Q4 2020  \\\n",
      "12  Quick Ratio     KO  6.603691  5.922481  6.390776  6.509978       NaN   \n",
      "10  Quick Ratio   CCEP  4.978392       NaN  4.948936       NaN  5.985316   \n",
      "12  Quick Ratio   COKE  3.554455  3.807971  3.990132  3.917197       NaN   \n",
      "7   Quick Ratio   FIZZ       NaN       NaN       NaN  2.662921       NaN   \n",
      "16  Quick Ratio    KDP  3.419463  3.339713  3.043584  3.007650       NaN   \n",
      "12  Quick Ratio    KHC  3.295713  2.998707  2.370521  2.223479       NaN   \n",
      "13  Quick Ratio   MDLZ  3.819055  3.389359  3.031600  2.920719       NaN   \n",
      "9   Quick Ratio   MNST  7.895447  5.778319  5.301354  5.442642       NaN   \n",
      "12  Quick Ratio    PEP  5.011042  4.691726  4.280878  4.690775       NaN   \n",
      "11  Quick Ratio   PRMW  5.368421  4.809524  5.045455  4.771930       NaN   \n",
      "11  Quick Ratio   SBUX       NaN  4.431888  3.927604  3.313643       NaN   \n",
      "\n",
      "    Q2 2021   Q4 2022   Q1 2023   Q2 2023  \n",
      "12      NaN       NaN       NaN       NaN  \n",
      "10  4.86246       NaN       NaN       NaN  \n",
      "12      NaN       NaN       NaN       NaN  \n",
      "7       NaN  2.669903  2.822222  3.397727  \n",
      "16      NaN       NaN       NaN       NaN  \n",
      "12      NaN       NaN       NaN       NaN  \n",
      "13      NaN       NaN       NaN       NaN  \n",
      "9       NaN       NaN       NaN       NaN  \n",
      "12      NaN       NaN       NaN       NaN  \n",
      "11      NaN       NaN       NaN       NaN  \n",
      "11      NaN  3.224162       NaN       NaN  \n",
      "['CMG', 'DPZ', 'JACK', 'PZZA', 'QSR', 'SBUX', 'SHAK', 'WEN', 'YUM', 'YUMC']\n",
      "          items ticker     Q4 2021     Q1 2022     Q2 2022     Q3 2022  \\\n",
      "4   Quick Ratio    MCD  127.660714   93.120000  114.395349  133.511628   \n",
      "8   Quick Ratio    CMG   41.878788   36.533333   36.068966   31.676471   \n",
      "5   Quick Ratio    DPZ   12.661765   11.038462   12.085714   11.315068   \n",
      "13  Quick Ratio   JACK         NaN   54.333333   28.666667   34.166667   \n",
      "10  Quick Ratio   PZZA    7.285714    7.333333    6.315789    5.714286   \n",
      "7   Quick Ratio    QSR   18.916667   15.611111   13.754386   14.914729   \n",
      "11  Quick Ratio   SBUX         NaN    4.431888    3.927604    3.313643   \n",
      "6   Quick Ratio   SHAK  102.500000   96.750000   97.000000   91.750000   \n",
      "11  Quick Ratio    WEN   98.833333  180.000000  174.000000  156.428571   \n",
      "6   Quick Ratio    YUM         NaN         NaN         NaN         NaN   \n",
      "10  Quick Ratio   YUMC   10.916667   12.365217   12.963173   14.672897   \n",
      "\n",
      "      Q4 2022  \n",
      "4         NaN  \n",
      "8         NaN  \n",
      "5         NaN  \n",
      "13  56.600000  \n",
      "10        NaN  \n",
      "7         NaN  \n",
      "11   3.224162  \n",
      "6         NaN  \n",
      "11        NaN  \n",
      "6         NaN  \n",
      "10        NaN  \n",
      "['DD', 'GE', 'HON', 'ITW', 'JNJ']\n",
      "          items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "12  Quick Ratio    MMM  3.089870  2.731947  2.571125  2.652716\n",
      "13  Quick Ratio     DD  6.856663  6.453530  5.944822  6.083086\n",
      "13  Quick Ratio     GE  4.186786  3.820097  3.455706  3.426209\n",
      "13  Quick Ratio    HON  4.938108  4.437317  4.276722  4.094710\n",
      "9   Quick Ratio    ITW  3.762692  3.548593  3.225823  3.087195\n",
      "12  Quick Ratio    JNJ  5.870704  5.498089  5.582495  5.587666\n",
      "['ABT', 'BMY', 'GSK', 'JNJ', 'LLY', 'NOVN', 'PFE', 'SAN', 'ZTS']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022  Q3 2021\n",
      "12  Quick Ratio    MRK   5.084159   5.400762   5.802349   5.978090      NaN\n",
      "11  Quick Ratio    ABT   4.700213   4.116851   4.230548   4.332926      NaN\n",
      "16  Quick Ratio    BMY  15.876850  14.316065  14.092437  12.919961      NaN\n",
      "10  Quick Ratio    GSK   3.229120   4.828919  11.618353   4.346212      NaN\n",
      "12  Quick Ratio    JNJ   5.870704   5.498089   5.582495   5.587666      NaN\n",
      "10  Quick Ratio    LLY   4.748327   4.357822   4.389587   4.604542      NaN\n",
      "9   Quick Ratio   NOVN        NaN  39.703654  39.804362        NaN      NaN\n",
      "14  Quick Ratio    PFE   6.589359   5.453452   6.453606   7.400715      NaN\n",
      "11  Quick Ratio    ZTS   3.603744   3.323772   3.016327   2.844551      NaN\n",
      "['AAPL', 'AVGO', 'CRM', 'CSCO', 'GOOG', 'GOOGL', 'IBM', 'ORCL', 'SAP']\n",
      "          items ticker    Q2 2022    Q3 2022    Q4 2022    Q1 2023  \\\n",
      "11  Quick Ratio   MSFT  57.697251  46.699636  45.345804  37.678538   \n",
      "9   Quick Ratio   AAPL  21.644689  20.668507  27.376668        NaN   \n",
      "8   Quick Ratio   AVGO   8.878897   8.466268   9.612468        NaN   \n",
      "5   Quick Ratio    CRM        NaN        NaN        NaN        NaN   \n",
      "14  Quick Ratio   CSCO  17.872268  16.127745  14.297897  13.566441   \n",
      "10  Quick Ratio   GOOG  87.056061  52.632763        NaN        NaN   \n",
      "10  Quick Ratio  GOOGL  87.056061  52.632763        NaN        NaN   \n",
      "17  Quick Ratio    IBM  16.565321  16.164437        NaN        NaN   \n",
      "7   Quick Ratio   ORCL        NaN        NaN        NaN        NaN   \n",
      "7   Quick Ratio    SAP        NaN        NaN        NaN        NaN   \n",
      "\n",
      "       Q1 2022  Q2 2023  Q3 2023     Q4 2021  \n",
      "11         NaN      NaN      NaN         NaN  \n",
      "9    26.064329      NaN      NaN         NaN  \n",
      "8    10.092763      NaN      NaN         NaN  \n",
      "5          NaN      NaN      NaN         NaN  \n",
      "14         NaN      NaN      NaN         NaN  \n",
      "10  129.914536      NaN      NaN  160.805983  \n",
      "10  129.914536      NaN      NaN  160.805983  \n",
      "17   17.640766      NaN      NaN   17.913281  \n",
      "7          NaN      NaN      NaN         NaN  \n",
      "7          NaN      NaN      NaN         NaN  \n",
      "['ADS', 'CROX', 'SKX', 'UA', 'UAA', 'VFC']\n",
      "          items ticker   Q3 2022   Q4 2022   Q1 2023   Q2 2023   Q4 2021  \\\n",
      "8   Quick Ratio    NKE  3.501558  3.350713  2.988719  2.943062       NaN   \n",
      "4   Quick Ratio    ADS       NaN       NaN       NaN       NaN       NaN   \n",
      "9   Quick Ratio   CROX  2.184825       NaN       NaN       NaN  3.116822   \n",
      "10  Quick Ratio    SKX  2.013491       NaN       NaN       NaN  2.292318   \n",
      "6   Quick Ratio     UA       NaN  3.438107  3.144654  2.850926  4.113440   \n",
      "6   Quick Ratio    UAA       NaN  3.438107  3.144654  2.850926  4.113440   \n",
      "13  Quick Ratio    VFC  3.574981  3.233263  1.970098  2.068364       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022  \n",
      "8        NaN       NaN  \n",
      "4        NaN       NaN  \n",
      "9   2.546569  2.326693  \n",
      "10  2.362759  2.282609  \n",
      "6        NaN       NaN  \n",
      "6        NaN       NaN  \n",
      "13       NaN       NaN  \n",
      "['CL', 'EL', 'JNJ', 'OR']\n",
      "          items ticker    Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "7   Quick Ratio     PG   3.828113  3.297564  3.127239  2.967194       NaN   \n",
      "12  Quick Ratio     CL   2.564612  2.546068       NaN       NaN  2.598700   \n",
      "10  Quick Ratio     EL   3.811256  3.356890  3.184247  2.937707       NaN   \n",
      "12  Quick Ratio    JNJ   5.582495  5.587666       NaN       NaN  5.870704   \n",
      "11  Quick Ratio     OR  19.615385       inf       NaN       NaN  8.052632   \n",
      "\n",
      "      Q1 2022  \n",
      "7         NaN  \n",
      "12   2.593035  \n",
      "10        NaN  \n",
      "12   5.498089  \n",
      "11  28.280000  \n",
      "['AIG', 'AIZ', 'ALL', 'CB', 'CINF', 'HIG', 'L', 'PGR', 'WRB']\n",
      "Empty DataFrame\n",
      "Columns: [items, ticker, Q4 2021, Q1 2022, Q2 2022, Q3 2022]\n",
      "Index: []\n",
      "['CI', 'CVS', 'ELV', 'HUM']\n",
      "          items ticker   Q4 2021   Q1 2022   Q2 2022   Q3 2022\n",
      "13  Quick Ratio    CVS  3.378829  3.385628  3.576518  3.784528\n",
      "['AXP', 'BAC', 'C', 'COF', 'DFS', 'JPM', 'MA', 'PYPL', 'SYF', 'WFC']\n",
      "          items ticker  Q1 2022  Q2 2022  Q3 2022  Q4 2022  Q4 2021\n",
      "10  Quick Ratio      V      NaN      NaN      NaN      NaN      NaN\n",
      "6   Quick Ratio    AXP      NaN      NaN      NaN      NaN      NaN\n",
      "8   Quick Ratio     MA      NaN      NaN      NaN      NaN      NaN\n",
      "8   Quick Ratio   PYPL      NaN      NaN      NaN      NaN      NaN\n",
      "['AAPL', 'T', 'TBB', 'TBC', 'TDS', 'TMUS', 'USM']\n",
      "          items ticker    Q4 2021    Q1 2022    Q2 2022    Q3 2022    Q4 2022\n",
      "9   Quick Ratio     VZ  12.022259   9.723968  10.284970  12.686243        NaN\n",
      "9   Quick Ratio   AAPL        NaN  26.064329  21.644689  20.668507  27.376668\n",
      "11  Quick Ratio      T  51.358797  24.375515  10.640234   8.207116        NaN\n",
      "11  Quick Ratio    TBB  51.358797  24.375515  10.640234   8.207116        NaN\n",
      "11  Quick Ratio    TBC  51.358797  24.375515  10.640234   8.207116        NaN\n",
      "13  Quick Ratio    TDS  11.483146  11.331522   9.629108   8.277778        NaN\n",
      "9   Quick Ratio   TMUS   8.138294   6.429098   7.791351   9.535826        NaN\n",
      "11  Quick Ratio    USM   9.277457   9.101695   8.121359   6.893004        NaN\n",
      "['ABC', 'AMZN', 'CVS', 'MCK', 'RAD']\n",
      "          items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021  \\\n",
      "8   Quick Ratio    WBA  2.143958  1.880407  2.215023  2.023465       NaN   \n",
      "10  Quick Ratio    ABC  2.416779  2.540122  2.511850  2.544999       NaN   \n",
      "8   Quick Ratio   AMZN  3.826450  3.503447  3.587279       NaN  4.950368   \n",
      "13  Quick Ratio    CVS  3.385628  3.576518  3.784528       NaN  3.378829   \n",
      "7   Quick Ratio    MCK       NaN       NaN  2.444176  2.471982       NaN   \n",
      "6   Quick Ratio    RAD       NaN       NaN       NaN  1.760592       NaN   \n",
      "\n",
      "     Q1 2023   Q2 2023   Q3 2023  \n",
      "8        NaN       NaN       NaN  \n",
      "10       NaN       NaN       NaN  \n",
      "8        NaN       NaN       NaN  \n",
      "13       NaN       NaN       NaN  \n",
      "7   2.326737  2.336889       NaN  \n",
      "6   1.807089  1.846496  1.856638  \n",
      "['AMZN', 'COST', 'CVS', 'DG', 'JD', 'PDD', 'TGT', 'TJX', 'WBA']\n",
      "          items ticker   Q4 2022   Q1 2023   Q2 2023   Q3 2023       Q4 2021  \\\n",
      "4   Quick Ratio    WMT  1.434588  1.359160  1.404583  1.355052           NaN   \n",
      "8   Quick Ratio   AMZN       NaN       NaN       NaN       NaN      4.950368   \n",
      "6   Quick Ratio   COST  1.825878  1.838889       NaN       NaN           NaN   \n",
      "13  Quick Ratio    CVS       NaN       NaN       NaN       NaN      3.378829   \n",
      "4   Quick Ratio     DG  1.122907  1.106785  1.107699  1.122043           NaN   \n",
      "9   Quick Ratio     JD       NaN       NaN       NaN       NaN      3.963863   \n",
      "11  Quick Ratio    PDD       NaN       NaN       NaN       NaN  11493.500000   \n",
      "5   Quick Ratio    TGT  1.551791  1.190280  1.204504  1.191389           NaN   \n",
      "6   Quick Ratio    TJX  2.223918  1.785408  1.670902  1.559491           NaN   \n",
      "8   Quick Ratio    WBA  2.023465       NaN       NaN       NaN           NaN   \n",
      "\n",
      "     Q1 2022   Q2 2022   Q3 2022  \n",
      "4        NaN       NaN       NaN  \n",
      "8   3.826450  3.503447  3.587279  \n",
      "6        NaN  1.975432  1.873007  \n",
      "13  3.385628  3.576518  3.784528  \n",
      "4        NaN       NaN       NaN  \n",
      "9   4.204521  4.261413  4.660131  \n",
      "11       NaN       NaN       NaN  \n",
      "5        NaN       NaN       NaN  \n",
      "6        NaN       NaN       NaN  \n",
      "8   2.143958  1.880407  2.215023  \n"
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    i_row = quick_ratio(i_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "    print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        competitor_df = pd.read_csv(competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = quick_ratio(competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b1385991",
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_on_assets(i_df, j_df, symbol=\"\"):\n",
    "    try:\n",
    "\n",
    "        for j in i_df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            i_df[j] = i_df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            i_df[j] = pd.to_numeric(i_df[j])\n",
    "\n",
    "        for k in j_df:\n",
    "            if k == 'ticker' or k == 'items':\n",
    "                continue\n",
    "            j_df[k] = j_df[k].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            j_df[k] = pd.to_numeric(j_df[k])\n",
    "\n",
    "        i_df_columns = []\n",
    "\n",
    "        for col in i_df.columns:\n",
    "            i_df_columns.append(col)\n",
    "\n",
    "        i_df_columns.insert(1, i_df_columns[-1])\n",
    "        del i_df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "        \n",
    "        j_df_columns = []\n",
    "\n",
    "        for col in j_df.columns:\n",
    "            j_df_columns.append(col)\n",
    "\n",
    "        j_df_columns.insert(1, j_df_columns[-1])\n",
    "        del j_df_columns[-1]\n",
    "\n",
    "#         df_columns = [i for i in i_df_columns if i not in j_df_columns]\n",
    "        \n",
    "        first_row = i_df.loc[(i_df['ticker'] == symbol) & (i_df['items'] == 'Income After Tax'), i_df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = j_df.loc[(j_df['ticker'] == symbol) & (j_df['items'] == 'Total Assets'), j_df_columns[2:]]\n",
    "        # print(first_row)\n",
    "        # print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Return on Assets\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Return on Assets\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1364f46f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "12  Return on Assets   AAPL  0.071322  0.057810  0.058740  0.086513       NaN   \n",
      "17  Return on Assets   AMZN -0.004803  0.006712       NaN       NaN  0.034055   \n",
      "19  Return on Assets   DELL       NaN       NaN -0.008239  0.012092       NaN   \n",
      "17  Return on Assets   GOOG  0.045053  0.038827       NaN       NaN  0.057456   \n",
      "17  Return on Assets  GOOGL  0.045053  0.038827       NaN       NaN  0.057456   \n",
      "16  Return on Assets    HPQ  0.025062  0.028512 -0.000052       NaN       NaN   \n",
      "15  Return on Assets   META  0.039386  0.024568       NaN       NaN  0.061963   \n",
      "13  Return on Assets   MSFT  0.055128  0.048542  0.045883  0.048796       NaN   \n",
      "\n",
      "     Q1 2022  Q2 2023  Q3 2023  \n",
      "12       NaN      NaN      NaN  \n",
      "17 -0.009356      NaN      NaN  \n",
      "19       NaN   0.0057  0.00283  \n",
      "17  0.046027      NaN      NaN  \n",
      "17  0.046027      NaN      NaN  \n",
      "16  0.027909      NaN      NaN  \n",
      "15  0.045458      NaN      NaN  \n",
      "13       NaN      NaN      NaN  \n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Return on Assets   AMGN  0.024934  0.022211  0.033642  0.024815       NaN\n",
      "21  Return on Assets   ABBV  0.031373  0.006481  0.027964       NaN  0.027605\n",
      "18  Return on Assets    AZN  0.003869  0.003728  0.017434       NaN -0.003284\n",
      "13  Return on Assets   GILD  0.000190  0.018053  0.028550       NaN  0.005533\n",
      "19  Return on Assets    JNJ  0.028869  0.027087  0.025456       NaN  0.026019\n",
      "16  Return on Assets   MRNA  0.132457  0.084360  0.040029       NaN  0.197333\n",
      "22  Return on Assets    PFE  0.042852  0.050576  0.044254       NaN  0.021209\n",
      "16  Return on Assets   REGN  0.036965  0.031317  0.047547       NaN  0.087635\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Return on Assets    AXP  0.010717  0.009567  0.008743  0.006884       NaN\n",
      "23  Return on Assets    BAC  0.002182  0.002008  0.002305       NaN  0.002213\n",
      "28  Return on Assets      C  0.001807  0.002011  0.001476       NaN  0.001387\n",
      "21  Return on Assets    COF  0.005534  0.004613  0.003813       NaN  0.005611\n",
      "19  Return on Assets    DFS  0.011563  0.009695  0.008254       NaN  0.009679\n",
      "29  Return on Assets    JPM  0.002094  0.002252  0.002580       NaN  0.002778\n",
      "18  Return on Assets     MA  0.070796  0.062792  0.066442       NaN  0.063155\n",
      "19  Return on Assets   PYPL  0.006715 -0.004382  0.017400       NaN  0.010567\n",
      "17  Return on Assets    SYF  0.009783  0.008445  0.006977       NaN  0.008491\n",
      "13  Return on Assets      V  0.048322  0.044580  0.039937  0.046081       NaN\n",
      "               items ticker    Q1 2022    Q2 2022    Q3 2022   Q4 2022  \\\n",
      "13  Return on Assets     BA  -0.009146   0.001181  -0.024048 -0.004872   \n",
      "17  Return on Assets     AM  14.341516  14.213212  15.099569       NaN   \n",
      "13  Return on Assets    HXL   5.711282  15.076268   9.005764       NaN   \n",
      "18  Return on Assets    RTX   0.007065   0.008414   0.008817       NaN   \n",
      "15  Return on Assets    TDG   0.008471   0.010562   0.012700  0.014635   \n",
      "14  Return on Assets    TXT   0.012130   0.013729   0.014101       NaN   \n",
      "17  Return on Assets    WWD   0.007435   0.012336   0.010383  0.014188   \n",
      "\n",
      "      Q4 2021  \n",
      "13        NaN  \n",
      "17  14.182179  \n",
      "13   6.598084  \n",
      "18   0.004777  \n",
      "15        NaN  \n",
      "14   0.013079  \n",
      "17        NaN  \n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "17  Return on Assets    CAT  0.018596  0.020578  0.025103  0.017756       NaN\n",
      "16  Return on Assets     DE  0.011317  0.024864  0.021712  0.024903       NaN\n",
      "12  Return on Assets    TEX  0.017687  0.024716  0.027545       NaN  0.020251\n",
      "11  Return on Assets    TTC  0.021519  0.037654  0.036337  0.033183       NaN\n",
      "               items ticker   Q1 2023   Q2 2023   Q3 2023   Q4 2023   Q1 2022  \\\n",
      "18  Return on Assets    CRM  0.000301  0.000722  0.002285 -0.000991       NaN   \n",
      "15  Return on Assets   ADBE       NaN       NaN       NaN       NaN  0.048737   \n",
      "20  Return on Assets   CSCO  0.028693       NaN       NaN       NaN       NaN   \n",
      "17  Return on Assets   GOOG       NaN       NaN       NaN       NaN  0.046027   \n",
      "17  Return on Assets  GOOGL       NaN       NaN       NaN       NaN  0.046027   \n",
      "17  Return on Assets   INTU  0.001477       NaN       NaN       NaN       NaN   \n",
      "13  Return on Assets   MSFT  0.048796       NaN       NaN       NaN       NaN   \n",
      "20  Return on Assets   ORCL  0.011879  0.013552       NaN       NaN       NaN   \n",
      "19  Return on Assets    SAP       NaN       NaN       NaN       NaN  0.008275   \n",
      "\n",
      "     Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "18       NaN       NaN       NaN       NaN  \n",
      "15  0.044747  0.042477  0.043291       NaN  \n",
      "20  0.031540  0.032803  0.029946       NaN  \n",
      "17  0.045053  0.038827       NaN  0.057456  \n",
      "17  0.045053  0.038827       NaN  0.057456  \n",
      "17  0.003802  0.062916 -0.002019       NaN  \n",
      "13  0.055128  0.048542  0.045883       NaN  \n",
      "20       NaN  0.021345  0.029177       NaN  \n",
      "19  0.002686  0.006979       NaN  0.020234  \n",
      "               items ticker    Q3 2022    Q4 2022    Q1 2023   Q2 2023  \\\n",
      "20  Return on Assets   CSCO   0.032803   0.029946   0.028693  0.028934   \n",
      "17  Return on Assets   AMZN   0.006712        NaN        NaN       NaN   \n",
      "15  Return on Assets   AVGO   0.043098   0.045857        NaN       NaN   \n",
      "19  Return on Assets   DELL        NaN  -0.008239   0.012092  0.005700   \n",
      "16  Return on Assets   FTNT   0.044415        NaN        NaN       NaN   \n",
      "13  Return on Assets   MSFT   0.048542   0.045883   0.048796       NaN   \n",
      "17  Return on Assets   PANW  -0.006577   0.000245   0.001594       NaN   \n",
      "16  Return on Assets    RNG  -0.123057        NaN        NaN       NaN   \n",
      "18  Return on Assets    VMW        NaN   0.020435   0.008821  0.012396   \n",
      "13  Return on Assets     ZM        NaN   0.065025   0.014327  0.005716   \n",
      "18  Return on Assets     ZS -40.160396 -34.469467 -24.034556       NaN   \n",
      "\n",
      "     Q4 2021   Q1 2022    Q2 2022   Q3 2023  \n",
      "20       NaN       NaN        NaN       NaN  \n",
      "17  0.034055 -0.009356  -0.004803       NaN  \n",
      "15       NaN  0.033759   0.036113       NaN  \n",
      "19       NaN       NaN        NaN  0.002830  \n",
      "16  0.034465  0.026013   0.034372       NaN  \n",
      "13       NaN       NaN   0.055128       NaN  \n",
      "17       NaN       NaN  -0.009038       NaN  \n",
      "16 -0.045754 -0.058801  -0.063517       NaN  \n",
      "18       NaN       NaN        NaN  0.008213  \n",
      "13       NaN       NaN        NaN  0.006125  \n",
      "18       NaN       NaN -41.461602       NaN  \n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "\"['Q4 2022'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/3407547461.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     11\u001b[0m     \u001b[0mi_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[0mj_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m     \u001b[0mi_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreturn_on_assets\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mj_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m     \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_row\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/1741590035.py\u001b[0m in \u001b[0;36mreturn_on_assets\u001b[1;34m(i_df, j_df, symbol)\u001b[0m\n\u001b[0;32m     42\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ticker'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     43\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'items'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"Return on Assets\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 44\u001b[1;33m         \u001b[0mthird_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj_df_columns\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     45\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     46\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3462\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3463\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3464\u001b[1;33m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3466\u001b[0m         \u001b[1;31m# take() does not accept boolean indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1312\u001b[0m             \u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1314\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1315\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1316\u001b[0m         if needs_i8_conversion(ax.dtype) or isinstance(\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[1;34m(self, key, indexer, axis)\u001b[0m\n\u001b[0;32m   1375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1376\u001b[0m             \u001b[0mnot_found\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1377\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{not_found} not in index\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1378\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1379\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Q4 2022'] not in index\""
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    j_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    j_df = pd.read_csv(j_csv)\n",
    "    i_row = return_on_assets(i_df, j_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "#     print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        i_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "        j_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        i_competitor_df = pd.read_csv(i_competitor_csv)\n",
    "        j_competitor_df = pd.read_csv(j_competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = return_on_assets(i_competitor_df, j_competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bd7c4f5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_on_equity(i_df, j_df, symbol=\"\"):\n",
    "    try:\n",
    "\n",
    "        for j in i_df:\n",
    "            if j == 'ticker' or j == 'items':\n",
    "                continue\n",
    "            i_df[j] = i_df[j].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            i_df[j] = pd.to_numeric(i_df[j])\n",
    "\n",
    "        for k in j_df:\n",
    "            if k == 'ticker' or k == 'items':\n",
    "                continue\n",
    "            j_df[k] = j_df[k].str.replace(\",\", \"\", regex=True).str.replace(\"(\", \"-\", regex=True).str.replace(\")\", \"\", regex=True).str.replace(\"--\", \"\", regex=True)\n",
    "            j_df[k] = pd.to_numeric(j_df[k])\n",
    "\n",
    "        i_df_columns = []\n",
    "\n",
    "        for col in i_df.columns:\n",
    "            i_df_columns.append(col)\n",
    "\n",
    "        i_df_columns.insert(1, i_df_columns[-1])\n",
    "        del i_df_columns[-1]\n",
    "        # print(i_df_columns)\n",
    "        \n",
    "        j_df_columns = []\n",
    "\n",
    "        for col in j_df.columns:\n",
    "            j_df_columns.append(col)\n",
    "\n",
    "        j_df_columns.insert(1, j_df_columns[-1])\n",
    "        del j_df_columns[-1]\n",
    "\n",
    "#         df_columns = [i for i in i_df_columns if i not in j_df_columns]\n",
    "        \n",
    "        first_row = i_df.loc[(i_df['ticker'] == symbol) & (i_df['items'] == 'Income After Tax'), i_df_columns[2:]]\n",
    "        # gross_margin\n",
    "        second_row = j_df.loc[(j_df['ticker'] == symbol) & (j_df['items'] == 'Total Equity'), j_df_columns[2:]]\n",
    "        # print(first_row)\n",
    "        # print(second_row)\n",
    "        third_row = first_row / second_row.values\n",
    "        # print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Return on Equity\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "\n",
    "    except ValueError:\n",
    "        third_row = first_row / second_row\n",
    "    #     print(third_row)\n",
    "        third_row['ticker'] = symbol\n",
    "        third_row['items'] = \"Return on Equity\"\n",
    "        third_row = third_row[j_df_columns]\n",
    "#         third_row = third_row.reshape(1,4)\n",
    "    return third_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "97e14096",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               items ticker   Q2 2022   Q3 2022   Q4 2022   Q1 2023   Q4 2021  \\\n",
      "12  Return on Equity   AAPL  0.371074  0.334590  0.408924  0.528813       NaN   \n",
      "17  Return on Equity   AMZN -0.015342  0.020911       NaN       NaN  0.103599   \n",
      "19  Return on Equity   DELL       NaN       NaN  0.453412 -0.434200       NaN   \n",
      "17  Return on Equity   GOOG  0.062650  0.054845       NaN       NaN  0.082032   \n",
      "17  Return on Equity  GOOGL  0.062650  0.054845       NaN       NaN  0.082032   \n",
      "16  Return on Equity    HPQ -0.526870 -0.482744  0.000685       NaN       NaN   \n",
      "15  Return on Equity   META  0.053170  0.035417       NaN       NaN  0.082360   \n",
      "13  Return on Equity   MSFT  0.117274  0.102674  0.100515  0.101149       NaN   \n",
      "\n",
      "     Q1 2022   Q2 2023   Q3 2023  \n",
      "12       NaN       NaN       NaN  \n",
      "17 -0.028679       NaN       NaN  \n",
      "19       NaN -0.176923 -0.069472  \n",
      "17  0.064708       NaN       NaN  \n",
      "17  0.064708       NaN       NaN  \n",
      "16 -0.466495       NaN       NaN  \n",
      "15  0.060579       NaN       NaN  \n",
      "13       NaN       NaN       NaN  \n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Return on Equity   AMGN  1.611354  0.544440  0.586641  0.441409       NaN\n",
      "21  Return on Equity   ABBV  0.275932  0.063332  0.247093       NaN  0.262526\n",
      "18  Return on Equity    AZN  0.010677  0.010019  0.046735       NaN -0.008811\n",
      "13  Return on Equity   GILD  0.000602  0.056088  0.084721       NaN  0.017846\n",
      "19  Return on Equity    JNJ  0.068921  0.063046  0.059760       NaN  0.063980\n",
      "16  Return on Equity   MRNA  0.214173  0.122157  0.057970       NaN  0.344150\n",
      "22  Return on Equity    PFE  0.095579  0.113258  0.093326       NaN  0.049858\n",
      "16  Return on Equity   REGN  0.048908  0.041183  0.061383       NaN  0.118760\n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "13  Return on Equity    AXP  0.093777  0.084528  0.078488  0.063615       NaN\n",
      "23  Return on Equity    BAC  0.026506  0.023213  0.026276       NaN  0.025968\n",
      "28  Return on Equity      C  0.021876  0.024064  0.017702       NaN  0.015740\n",
      "21  Return on Equity    COF  0.042648  0.038027  0.033306       NaN  0.039752\n",
      "19  Return on Equity    DFS  0.092459  0.080718  0.070419       NaN  0.079579\n",
      "29  Return on Equity    JPM  0.028968  0.030226  0.033807       NaN  0.035355\n",
      "18  Return on Equity     MA  0.374040  0.368660  0.392863       NaN  0.325356\n",
      "19  Return on Equity   PYPL  0.024705 -0.017251  0.065634       NaN  0.036867\n",
      "17  Return on Equity    SYF  0.069459  0.060031  0.054027       NaN  0.059539\n",
      "13  Return on Equity      V  0.109383  0.101337  0.096131  0.110733       NaN\n",
      "               items ticker    Q1 2022    Q2 2022    Q3 2022   Q4 2022  \\\n",
      "13  Return on Equity     BA   0.080660  -0.010747   0.186903  0.042058   \n",
      "17  Return on Equity     AM  35.415929  35.603139  37.981013       NaN   \n",
      "13  Return on Equity    HXL  10.961668  28.716216  17.301038       NaN   \n",
      "18  Return on Equity    RTX   0.015539   0.018995   0.019875       NaN   \n",
      "15  Return on Equity    TDG  -0.061907  -0.068644  -0.080309 -0.070236   \n",
      "14  Return on Equity    TXT   0.027902   0.032054   0.033274       NaN   \n",
      "17  Return on Equity    WWD   0.013495   0.023392   0.020419  0.028406   \n",
      "\n",
      "      Q4 2021  \n",
      "13        NaN  \n",
      "17  34.379537  \n",
      "13  12.516824  \n",
      "18   0.010552  \n",
      "15        NaN  \n",
      "14   0.030374  \n",
      "17        NaN  \n",
      "               items ticker   Q1 2022   Q2 2022   Q3 2022   Q4 2022   Q4 2021\n",
      "17  Return on Equity    CAT  0.089657  0.106123  0.130267  0.091688       NaN\n",
      "16  Return on Equity     DE  0.050607  0.110612  0.099039  0.110650       NaN\n",
      "12  Return on Equity    TEX  0.046679  0.070543  0.079227       NaN  0.052252\n",
      "11  Return on Equity    TTC  0.062500  0.107026  0.097125  0.087278       NaN\n",
      "               items ticker   Q1 2023   Q2 2023   Q3 2023   Q4 2023   Q1 2022  \\\n",
      "18  Return on Equity    CRM  0.000476  0.001131  0.003538 -0.001679       NaN   \n",
      "15  Return on Equity   ADBE       NaN       NaN       NaN       NaN  0.091906   \n",
      "20  Return on Equity   CSCO  0.066299       NaN       NaN       NaN       NaN   \n",
      "17  Return on Equity   GOOG       NaN       NaN       NaN       NaN  0.064708   \n",
      "17  Return on Equity  GOOGL       NaN       NaN       NaN       NaN  0.064708   \n",
      "17  Return on Equity   INTU  0.002490       NaN       NaN       NaN       NaN   \n",
      "13  Return on Equity   MSFT  0.101149       NaN       NaN       NaN       NaN   \n",
      "20  Return on Equity   ORCL -0.263489 -0.410033       NaN       NaN       NaN   \n",
      "19  Return on Equity    SAP       NaN       NaN       NaN       NaN  0.015859   \n",
      "\n",
      "     Q2 2022   Q3 2022   Q4 2022   Q4 2021  \n",
      "18       NaN       NaN       NaN       NaN  \n",
      "15  0.084233  0.079037  0.083695       NaN  \n",
      "20  0.075273  0.075347  0.070777       NaN  \n",
      "17  0.062650  0.054845       NaN  0.082032  \n",
      "17  0.062650  0.054845       NaN  0.082032  \n",
      "17  0.006412  0.105772 -0.003406       NaN  \n",
      "13  0.117274  0.102674  0.100515       NaN  \n",
      "20       NaN -0.266674 -0.512701       NaN  \n",
      "19  0.005095  0.012712       NaN  0.037063  \n",
      "               items ticker     Q3 2022     Q4 2022     Q1 2023   Q2 2023  \\\n",
      "20  Return on Equity   CSCO    0.075347    0.070777    0.066299  0.066861   \n",
      "17  Return on Equity   AMZN    0.020911         NaN         NaN       NaN   \n",
      "15  Return on Equity   AVGO    0.147250    0.147915         NaN       NaN   \n",
      "19  Return on Equity   DELL         NaN    0.453412   -0.434200 -0.176923   \n",
      "16  Return on Equity   FTNT   -0.373228         NaN         NaN       NaN   \n",
      "13  Return on Equity   MSFT    0.102674    0.100515    0.101149       NaN   \n",
      "17  Return on Equity   PANW   -0.215976    0.014286    0.039370       NaN   \n",
      "16  Return on Equity    RNG    6.333333         NaN         NaN       NaN   \n",
      "18  Return on Equity    VMW         NaN   -0.668950   -0.588808  2.478571   \n",
      "13  Return on Equity     ZM         NaN    0.084948    0.019166  0.007679   \n",
      "18  Return on Equity     ZS -190.610902 -170.422339 -158.148492       NaN   \n",
      "\n",
      "     Q4 2021   Q1 2022     Q2 2022   Q3 2023  \n",
      "20       NaN       NaN         NaN       NaN  \n",
      "17  0.103599 -0.028679   -0.015342       NaN  \n",
      "15       NaN  0.107628    0.123551       NaN  \n",
      "19       NaN       NaN         NaN -0.069472  \n",
      "16  0.260870  0.674312   -0.463104       NaN  \n",
      "13       NaN       NaN    0.117274       NaN  \n",
      "17       NaN       NaN   -0.796610       NaN  \n",
      "16 -0.219331 -0.608871   -0.987654       NaN  \n",
      "18       NaN       NaN         NaN  0.286600  \n",
      "13       NaN       NaN         NaN  0.008339  \n",
      "18       NaN       NaN -186.307978       NaN  \n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "\"['Q4 2022'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/319834707.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     11\u001b[0m     \u001b[0mi_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m     \u001b[0mj_df\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mj_csv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m     \u001b[0mi_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreturn_on_equity\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mj_df\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m     \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi_row\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_29120/3461922719.py\u001b[0m in \u001b[0;36mreturn_on_equity\u001b[1;34m(i_df, j_df, symbol)\u001b[0m\n\u001b[0;32m     42\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'ticker'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msymbol\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     43\u001b[0m         \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'items'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"Return on Equity\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 44\u001b[1;33m         \u001b[0mthird_row\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mthird_row\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mj_df_columns\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     45\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     46\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3462\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mis_iterator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3463\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3464\u001b[1;33m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3466\u001b[0m         \u001b[1;31m# take() does not accept boolean indexers\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[1;34m(self, key, axis)\u001b[0m\n\u001b[0;32m   1312\u001b[0m             \u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_indexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_reindex_non_unique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1313\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1314\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_validate_read_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkeyarr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1315\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1316\u001b[0m         if needs_i8_conversion(ax.dtype) or isinstance(\n",
      "\u001b[1;32m~\\AppData\\Roaming\\Python\\Python37\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[1;34m(self, key, indexer, axis)\u001b[0m\n\u001b[0;32m   1375\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1376\u001b[0m             \u001b[0mnot_found\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmissing_mask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnonzero\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0munique\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1377\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{not_found} not in index\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1378\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1379\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Q4 2022'] not in index\""
     ]
    }
   ],
   "source": [
    "for i in dow_jones_list:\n",
    "    df = pd.DataFrame()\n",
    "    \n",
    "    # assign directories\n",
    "    i_directory = f\"C:/Users/jake_/OneDrive/Desktop/financial_scraping/dow_jones_stocks/{i}\" \n",
    "    competitor_directory = i_directory + \"/competitors\"\n",
    "    \n",
    "    i_csv = i_directory + '/' + i + \"quarterlyincome-statement.csv\"\n",
    "    j_csv = i_directory + '/' + i + \"quarterlybalance-sheet.csv\"\n",
    "\n",
    "    i_df = pd.read_csv(i_csv)\n",
    "    j_df = pd.read_csv(j_csv)\n",
    "    i_row = return_on_equity(i_df, j_df, symbol=i)\n",
    "    df = df.append(i_row)\n",
    "    \n",
    "    \n",
    "    competitor_list =[]\n",
    "    \n",
    "    # iterate over files in\n",
    "    # that directory\n",
    "    for filename in os.listdir(competitor_directory):\n",
    "        if (filename.__contains__(\"ratio.csv\") == False):\n",
    "            f = os.path.join(competitor_directory, filename)\n",
    "            f = f.split(\"\\\\\")[1]\n",
    "            # checking if it is a file\n",
    "        #     if os.path.isfile(f):\n",
    "            competitor_list.append(f)\n",
    "#     print(competitor_list)\n",
    "    for symbol in competitor_list:\n",
    "        i_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlyincome-statement.csv\"\n",
    "        j_competitor_csv = competitor_directory + \"/\" + symbol + '/' + symbol + \"quarterlybalance-sheet.csv\"\n",
    "#         print(competitor_csv)\n",
    "        i_competitor_df = pd.read_csv(i_competitor_csv)\n",
    "        j_competitor_df = pd.read_csv(j_competitor_csv)\n",
    "#             print(competitor_df)\n",
    "        competitor_rows = return_on_equity(i_competitor_df, j_competitor_df, symbol=symbol)\n",
    "        df = df.append(competitor_rows)\n",
    "        \n",
    "    df = pd.DataFrame(df)\n",
    "    print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39802fd1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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