Get_Live_Historical_Data_Fundamentals_of_Stock(s).ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNCfj7is8kE86oSvg17PGXW",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/YigitBCesur/Finance-and-Trading/blob/main/Get_Live_Historical_Data_Fundamentals_of_Stock(s).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "HOW TO GET LIVE STOCK DATA IN PYTHON\n",
        "\n",
        "--- Get Stock Information in Python ---"
      ],
      "metadata": {
        "id": "VCeYBLBj9VJb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install yfinance\n",
        "! pip install --upgrade pandas_datareader\n"
      ],
      "metadata": {
        "id": "po5Bi3EUE0cD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e5058a12-eb9f-4a58-f7ee-728ccd124804"
      },
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.85)\n",
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            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: pandas_datareader in /usr/local/lib/python3.7/dist-packages (0.9.0)\n",
            "Collecting pandas_datareader\n",
            "  Downloading pandas_datareader-0.10.0-py3-none-any.whl (109 kB)\n",
            "\u001b[K     |████████████████████████████████| 109 kB 5.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from pandas_datareader) (2.28.1)\n",
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            "Installing collected packages: pandas-datareader\n",
            "  Attempting uninstall: pandas-datareader\n",
            "    Found existing installation: pandas-datareader 0.9.0\n",
            "    Uninstalling pandas-datareader-0.9.0:\n",
            "      Successfully uninstalled pandas-datareader-0.9.0\n",
            "Successfully installed pandas-datareader-0.10.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "! pip install yahoo-fin"
      ],
      "metadata": {
        "id": "EQtxzDzM8zQJ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "191e9320-205c-4647-a2af-272ac36a7f75"
      },
      "execution_count": 146,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: yahoo-fin in /usr/local/lib/python3.7/dist-packages (0.8.9.1)\n",
            "Requirement already satisfied: requests-html in /usr/local/lib/python3.7/dist-packages (from yahoo-fin) (0.10.0)\n",
            "Requirement already satisfied: feedparser in /usr/local/lib/python3.7/dist-packages (from yahoo-fin) (6.0.10)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from yahoo-fin) (1.3.5)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from yahoo-fin) (2.28.1)\n",
            "Requirement already satisfied: sgmllib3k in /usr/local/lib/python3.7/dist-packages (from feedparser->yahoo-fin) (1.0.0)\n",
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            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->yahoo-fin) (1.25.11)\n",
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            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->yahoo-fin) (2.10)\n",
            "Requirement already satisfied: parse in /usr/local/lib/python3.7/dist-packages (from requests-html->yahoo-fin) (1.19.0)\n",
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            "Requirement already satisfied: pyppeteer>=0.0.14 in /usr/local/lib/python3.7/dist-packages (from requests-html->yahoo-fin) (1.0.2)\n",
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            "Requirement already satisfied: importlib-metadata>=1.4 in /usr/local/lib/python3.7/dist-packages (from pyppeteer>=0.0.14->requests-html->yahoo-fin) (4.13.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=1.4->pyppeteer>=0.0.14->requests-html->yahoo-fin) (4.1.1)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=1.4->pyppeteer>=0.0.14->requests-html->yahoo-fin) (3.10.0)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.7/dist-packages (from bs4->requests-html->yahoo-fin) (4.6.3)\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 147,
      "metadata": {
        "id": "E89lhF1-8BeN"
      },
      "outputs": [],
      "source": [
        "from yahoo_fin.stock_info import *\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Get Live Stock Price**"
      ],
      "metadata": {
        "id": "kkmS2ma__Qep"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(get_live_price('PLTR'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fXiR7riQ9nMU",
        "outputId": "a593e6d0-eff0-4adb-9b8b-9ddb03d287f4"
      },
      "execution_count": 148,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "8.40999984741211\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Quote Table in Stock**"
      ],
      "metadata": {
        "id": "porET2il-z84"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "quote= get_quote_table('PLTR')\n",
        "print(quote)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4qUP8Z-V9nI3",
        "outputId": "71a9f132-ca6a-4164-8852-3b4d34cc2aaa"
      },
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'1y Target Est': 9.44, '52 Week Range': '6.44 - 23.52', 'Ask': '8.37 x 45100', 'Avg. Volume': 35789523.0, 'Beta (5Y Monthly)': 3.09, 'Bid': '8.36 x 1000', \"Day's Range\": '7.38 - 8.42', 'EPS (TTM)': -0.25, 'Earnings Date': 'Nov 07, 2022', 'Ex-Dividend Date': nan, 'Forward Dividend & Yield': 'N/A (N/A)', 'Market Cap': '17.494B', 'Open': 7.48, 'PE Ratio (TTM)': nan, 'Previous Close': 7.64, 'Quote Price': 8.40999984741211, 'Volume': 54867037.0}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.Series(quote)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ApoP2ilTs5fX",
        "outputId": "94002e20-abf1-4383-94e2-6a846f0ae01b"
      },
      "execution_count": 175,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1y Target Est                       9.44\n",
              "52 Week Range               6.44 - 23.52\n",
              "Ask                         8.37 x 45100\n",
              "Avg. Volume                   35789523.0\n",
              "Beta (5Y Monthly)                   3.09\n",
              "Bid                          8.36 x 1000\n",
              "Day's Range                  7.38 - 8.42\n",
              "EPS (TTM)                          -0.25\n",
              "Earnings Date               Nov 07, 2022\n",
              "Ex-Dividend Date                     NaN\n",
              "Forward Dividend & Yield       N/A (N/A)\n",
              "Market Cap                       17.494B\n",
              "Open                                7.48\n",
              "PE Ratio (TTM)                       NaN\n",
              "Previous Close                      7.64\n",
              "Quote Price                         8.41\n",
              "Volume                        54867037.0\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 175
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Companies' Tickers SP 500**"
      ],
      "metadata": {
        "id": "_fS1eyre-oEA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(tickers_sp500())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ybf5IeSh9nHB",
        "outputId": "cb66dd9e-9a82-4e50-f1ef-0ddd9735cfbc"
      },
      "execution_count": 150,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['A', 'AAL', 'AAP', 'AAPL', 'ABBV', 'ABC', 'ABMD', 'ABT', 'ACGL', 'ACN', 'ADBE', 'ADI', 'ADM', 'ADP', 'ADSK', 'AEE', 'AEP', 'AES', 'AFL', 'AIG', 'AIZ', 'AJG', 'AKAM', 'ALB', 'ALGN', 'ALK', 'ALL', 'ALLE', 'AMAT', 'AMCR', 'AMD', 'AME', 'AMGN', 'AMP', 'AMT', 'AMZN', 'ANET', 'ANSS', 'AON', 'AOS', 'APA', 'APD', 'APH', 'APTV', 'ARE', 'ATO', 'ATVI', 'AVB', 'AVGO', 'AVY', 'AWK', 'AXP', 'AZO', 'BA', 'BAC', 'BALL', 'BAX', 'BBWI', 'BBY', 'BDX', 'BEN', 'BF-B', 'BIIB', 'BIO', 'BK', 'BKNG', 'BKR', 'BLK', 'BMY', 'BR', 'BRK-B', 'BRO', 'BSX', 'BWA', 'BXP', 'C', 'CAG', 'CAH', 'CARR', 'CAT', 'CB', 'CBOE', 'CBRE', 'CCI', 'CCL', 'CDAY', 'CDNS', 'CDW', 'CE', 'CEG', 'CF', 'CFG', 'CHD', 'CHRW', 'CHTR', 'CI', 'CINF', 'CL', 'CLX', 'CMA', 'CMCSA', 'CME', 'CMG', 'CMI', 'CMS', 'CNC', 'CNP', 'COF', 'COO', 'COP', 'COST', 'CPB', 'CPRT', 'CPT', 'CRL', 'CRM', 'CSCO', 'CSGP', 'CSX', 'CTAS', 'CTLT', 'CTRA', 'CTSH', 'CTVA', 'CVS', 'CVX', 'CZR', 'D', 'DAL', 'DD', 'DE', 'DFS', 'DG', 'DGX', 'DHI', 'DHR', 'DIS', 'DISH', 'DLR', 'DLTR', 'DOV', 'DOW', 'DPZ', 'DRI', 'DTE', 'DUK', 'DVA', 'DVN', 'DXC', 'DXCM', 'EA', 'EBAY', 'ECL', 'ED', 'EFX', 'EIX', 'EL', 'ELV', 'EMN', 'EMR', 'ENPH', 'EOG', 'EPAM', 'EQIX', 'EQR', 'EQT', 'ES', 'ESS', 'ETN', 'ETR', 'ETSY', 'EVRG', 'EW', 'EXC', 'EXPD', 'EXPE', 'EXR', 'F', 'FANG', 'FAST', 'FBHS', 'FCX', 'FDS', 'FDX', 'FE', 'FFIV', 'FIS', 'FISV', 'FITB', 'FLT', 'FMC', 'FOX', 'FOXA', 'FRC', 'FRT', 'FTNT', 'FTV', 'GD', 'GE', 'GEN', 'GILD', 'GIS', 'GL', 'GLW', 'GM', 'GNRC', 'GOOG', 'GOOGL', 'GPC', 'GPN', 'GRMN', 'GS', 'GWW', 'HAL', 'HAS', 'HBAN', 'HCA', 'HD', 'HES', 'HIG', 'HII', 'HLT', 'HOLX', 'HON', 'HPE', 'HPQ', 'HRL', 'HSIC', 'HST', 'HSY', 'HUM', 'HWM', 'IBM', 'ICE', 'IDXX', 'IEX', 'IFF', 'ILMN', 'INCY', 'INTC', 'INTU', 'INVH', 'IP', 'IPG', 'IQV', 'IR', 'IRM', 'ISRG', 'IT', 'ITW', 'IVZ', 'J', 'JBHT', 'JCI', 'JKHY', 'JNJ', 'JNPR', 'JPM', 'K', 'KDP', 'KEY', 'KEYS', 'KHC', 'KIM', 'KLAC', 'KMB', 'KMI', 'KMX', 'KO', 'KR', 'L', 'LDOS', 'LEN', 'LH', 'LHX', 'LIN', 'LKQ', 'LLY', 'LMT', 'LNC', 'LNT', 'LOW', 'LRCX', 'LUMN', 'LUV', 'LVS', 'LW', 'LYB', 'LYV', 'MA', 'MAA', 'MAR', 'MAS', 'MCD', 'MCHP', 'MCK', 'MCO', 'MDLZ', 'MDT', 'MET', 'META', 'MGM', 'MHK', 'MKC', 'MKTX', 'MLM', 'MMC', 'MMM', 'MNST', 'MO', 'MOH', 'MOS', 'MPC', 'MPWR', 'MRK', 'MRNA', 'MRO', 'MS', 'MSCI', 'MSFT', 'MSI', 'MTB', 'MTCH', 'MTD', 'MU', 'NCLH', 'NDAQ', 'NDSN', 'NEE', 'NEM', 'NFLX', 'NI', 'NKE', 'NOC', 'NOW', 'NRG', 'NSC', 'NTAP', 'NTRS', 'NUE', 'NVDA', 'NVR', 'NWL', 'NWS', 'NWSA', 'NXPI', 'O', 'ODFL', 'OGN', 'OKE', 'OMC', 'ON', 'ORCL', 'ORLY', 'OTIS', 'OXY', 'PARA', 'PAYC', 'PAYX', 'PCAR', 'PCG', 'PEAK', 'PEG', 'PEP', 'PFE', 'PFG', 'PG', 'PGR', 'PH', 'PHM', 'PKG', 'PKI', 'PLD', 'PM', 'PNC', 'PNR', 'PNW', 'POOL', 'PPG', 'PPL', 'PRU', 'PSA', 'PSX', 'PTC', 'PWR', 'PXD', 'PYPL', 'QCOM', 'QRVO', 'RCL', 'RE', 'REG', 'REGN', 'RF', 'RHI', 'RJF', 'RL', 'RMD', 'ROK', 'ROL', 'ROP', 'ROST', 'RSG', 'RTX', 'SBAC', 'SBNY', 'SBUX', 'SCHW', 'SEDG', 'SEE', 'SHW', 'SIVB', 'SJM', 'SLB', 'SNA', 'SNPS', 'SO', 'SPG', 'SPGI', 'SRE', 'STE', 'STT', 'STX', 'STZ', 'SWK', 'SWKS', 'SYF', 'SYK', 'SYY', 'T', 'TAP', 'TDG', 'TDY', 'TECH', 'TEL', 'TER', 'TFC', 'TFX', 'TGT', 'TJX', 'TMO', 'TMUS', 'TPR', 'TRGP', 'TRMB', 'TROW', 'TRV', 'TSCO', 'TSLA', 'TSN', 'TT', 'TTWO', 'TXN', 'TXT', 'TYL', 'UAL', 'UDR', 'UHS', 'ULTA', 'UNH', 'UNP', 'UPS', 'URI', 'USB', 'V', 'VFC', 'VICI', 'VLO', 'VMC', 'VNO', 'VRSK', 'VRSN', 'VRTX', 'VTR', 'VTRS', 'VZ', 'WAB', 'WAT', 'WBA', 'WBD', 'WDC', 'WEC', 'WELL', 'WFC', 'WHR', 'WM', 'WMB', 'WMT', 'WRB', 'WRK', 'WST', 'WTW', 'WY', 'WYNN', 'XEL', 'XOM', 'XRAY', 'XYL', 'YUM', 'ZBH', 'ZBRA', 'ZION', 'ZTS']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stock = input (\"Please enter a ticker symbol  : \")\n",
        "\n",
        "if stock in tickers_sp500():\n",
        "  print ('The Stock is in the SP500 ')\n",
        "else:\n",
        "  print(' not in the SP500 ')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LHoHQsCd-mdA",
        "outputId": "a1fdc76f-72d6-433c-c202-8301390dd09d"
      },
      "execution_count": 151,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Please enter a ticker symbol  : PLTR\n",
            " not in the SP500 \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Importing Stock Prices from Yahoo Finance**"
      ],
      "metadata": {
        "id": "JB9ypXiOElWE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import yfinance as yf"
      ],
      "metadata": {
        "id": "bOG5adYlB3-w"
      },
      "execution_count": 152,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Just One Stock**"
      ],
      "metadata": {
        "id": "9xut5A_IIfGX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ticker= 'PLTR'\n",
        "#PLTR = yf.download(ticker)\n",
        "#PLTR = yf.download(ticker, start= '2021-01-01', end='2022-11-11', rounding=True)    # Adding dates\n",
        "#PLTR = yf.download(ticker, start= '2021-01-01', end='2022-11-11', rounding=True)[\"Adj Close\"]    # Select the column\n",
        "PLTR = yf.download(ticker, start= '2021-01-01', end='2022-11-11', rounding=True)[[\"Adj Close\", 'Volume']]    # Select the columns\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hRz5KkDuFZEt",
        "outputId": "ea6ec1c9-354e-406f-9d1e-ac3140c919c9"
      },
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PLTR"
      ],
      "metadata": {
        "colab": {
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        "id": "O8mGbd61GGVM",
        "outputId": "8d940077-2998-414d-ec26-ebb9057c4d69"
      },
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "execute_result",
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              "            Adj Close    Volume\n",
              "Date                           \n",
              "2021-01-04      23.37  44970400\n",
              "2021-01-05      24.60  29050400\n",
              "2021-01-06      23.54  32732900\n",
              "2021-01-07      25.00  32240000\n",
              "2021-01-08      25.20  41313800\n",
              "...               ...       ...\n",
              "2022-11-04       7.93  64257800\n",
              "2022-11-07       7.02  99332800\n",
              "2022-11-08       7.21  56353900\n",
              "2022-11-09       6.98  42517300\n",
              "2022-11-10       7.64  58579800\n",
              "\n",
              "[469 rows x 2 columns]"
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              "      <td>29050400</td>\n",
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              "      <th>2021-01-06</th>\n",
              "      <td>23.54</td>\n",
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              "      <td>25.20</td>\n",
              "      <td>41313800</td>\n",
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              "      <th>...</th>\n",
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              "      <th>2022-11-04</th>\n",
              "      <td>7.93</td>\n",
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              "      <th>2022-11-07</th>\n",
              "      <td>7.02</td>\n",
              "      <td>99332800</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-08</th>\n",
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              "      <th>2022-11-09</th>\n",
              "      <td>6.98</td>\n",
              "      <td>42517300</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-10</th>\n",
              "      <td>7.64</td>\n",
              "      <td>58579800</td>\n",
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    },
    {
      "cell_type": "markdown",
      "source": [
        "**Several Stocks**"
      ],
      "metadata": {
        "id": "ydXJGGbHIkvV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "tickers= ['PLTR', 'QS', 'APRE', 'NIO']\n",
        "#Stocks = yf.download(tickers)\n",
        "Stocks = yf.download(tickers, start= '2021-01-01', end='2022-11-11', rounding=True)[\"Adj Close\"]\n",
        "#Stocks = yf.download(tickers, start= '2021-01-01', end='2022-11-11', rounding=True)[\"Adj Close\"].T      # Transpose\n",
        "Stocks"
      ],
      "metadata": {
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          "height": 473
        },
        "id": "Nydh8kBXInv0",
        "outputId": "cc8515de-a15c-4af0-d451-d347eb2d6faa"
      },
      "execution_count": 164,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  4 of 4 completed\n"
          ]
        },
        {
          "output_type": "execute_result",
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              "             APRE    NIO   PLTR     QS\n",
              "Date                                  \n",
              "2021-01-04  4.730  53.49  23.37  49.96\n",
              "2021-01-05  4.900  53.20  24.60  59.50\n",
              "2021-01-06  4.900  50.50  23.54  63.03\n",
              "2021-01-07  5.120  54.28  25.00  62.00\n",
              "2021-01-08  5.100  58.92  25.20  56.79\n",
              "...           ...    ...    ...    ...\n",
              "2022-11-04  0.657  11.68   7.93   8.09\n",
              "2022-11-07  0.636  10.98   7.02   7.81\n",
              "2022-11-08  0.610  10.56   7.21   7.93\n",
              "2022-11-09  0.589   9.25   6.98   6.74\n",
              "2022-11-10  0.525  10.34   7.64   7.23\n",
              "\n",
              "[469 rows x 4 columns]"
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              "      <td>0.525</td>\n",
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              "      <td>7.23</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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          "metadata": {},
          "execution_count": 164
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### HISTORY on TICKER with **(+plus)** Dividends - Stock SplitsThe yfinance \n",
        "\n",
        "TICKER object\n",
        "\n",
        "1- start and end dates\n",
        "\n",
        "2- period instead of start/end\n",
        "\n",
        "3- valid periods: 1d, 5d, Imo, 3mo, 6mo, Ty, 2y, Sy, 1Oy, ytd,max\n",
        "\n",
        "4- valid intervals: Im, 2m, 5m, 15m, 30m, 6Om, 9Om, th, 1d, Sd, 1wk, 1mo, 3mo.\n",
        "\n",
        "5- actions = True: Includes info on both dividends and splits. (Optional default is False)\n",
        "\n",
        "6- prepost = True: download pre/post regular market hours data. (Optional default is False) ( FALSE= Market Hours , TRUE = PreMarket, Market , Post-Market Hours  )\n"
      ],
      "metadata": {
        "id": "T8VqQSMuVkvh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **One Stock **"
      ],
      "metadata": {
        "id": "uvhhch0hh4y1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "symbol= 'AAPL'\n",
        "ticker = yf.Ticker(symbol)                               # Aware of First Big Letter"
      ],
      "metadata": {
        "id": "29hhPmcJXNve"
      },
      "execution_count": 156,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**1- start and end dates**"
      ],
      "metadata": {
        "id": "O6lnARLQefA0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = ticker.history ( start='2019-01-01' , end='2020-12-31', rounding=True)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "v7HbbYnUaDpp",
        "outputId": "895b0332-3e7d-4444-e5a2-02ef8c3c7ed7"
      },
      "execution_count": 157,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                             Open    High     Low   Close     Volume  \\\n",
              "Date                                                                   \n",
              "2019-01-02 00:00:00-05:00   37.37   38.33   37.21   38.11  148158800   \n",
              "2019-01-03 00:00:00-05:00   34.74   35.16   34.26   34.31  365248800   \n",
              "2019-01-04 00:00:00-05:00   34.87   35.84   34.70   35.77  234428400   \n",
              "2019-01-07 00:00:00-05:00   35.88   35.91   35.20   35.69  219111200   \n",
              "2019-01-08 00:00:00-05:00   36.09   36.63   35.84   36.38  164101200   \n",
              "...                           ...     ...     ...     ...        ...   \n",
              "2020-12-23 00:00:00-05:00  130.59  130.86  129.23  129.41   88223700   \n",
              "2020-12-24 00:00:00-05:00  129.76  131.88  129.54  130.40   54930100   \n",
              "2020-12-28 00:00:00-05:00  132.40  135.71  131.93  135.07  124486200   \n",
              "2020-12-29 00:00:00-05:00  136.41  137.14  132.75  133.27  121047300   \n",
              "2020-12-30 00:00:00-05:00  133.97  134.38  131.82  132.13   96452100   \n",
              "\n",
              "                           Dividends  Stock Splits  \n",
              "Date                                                \n",
              "2019-01-02 00:00:00-05:00        0.0           0.0  \n",
              "2019-01-03 00:00:00-05:00        0.0           0.0  \n",
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              "2019-01-08 00:00:00-05:00        0.0           0.0  \n",
              "...                              ...           ...  \n",
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              "2020-12-30 00:00:00-05:00        0.0           0.0  \n",
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              "      <th>2019-01-02 00:00:00-05:00</th>\n",
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              "      <td>130.59</td>\n",
              "      <td>130.86</td>\n",
              "      <td>129.23</td>\n",
              "      <td>129.41</td>\n",
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              "      <th>2020-12-24 00:00:00-05:00</th>\n",
              "      <td>129.76</td>\n",
              "      <td>131.88</td>\n",
              "      <td>129.54</td>\n",
              "      <td>130.40</td>\n",
              "      <td>54930100</td>\n",
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              "    <tr>\n",
              "      <th>2020-12-28 00:00:00-05:00</th>\n",
              "      <td>132.40</td>\n",
              "      <td>135.71</td>\n",
              "      <td>131.93</td>\n",
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              "      <th>2020-12-29 00:00:00-05:00</th>\n",
              "      <td>136.41</td>\n",
              "      <td>137.14</td>\n",
              "      <td>132.75</td>\n",
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              "      <th>2020-12-30 00:00:00-05:00</th>\n",
              "      <td>133.97</td>\n",
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              "      <td>131.82</td>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 157
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**2- period instead of start/end**"
      ],
      "metadata": {
        "id": "kn3KvXfleZ40"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = ticker.history ( period='max', rounding=True , actions=False , interval='1m')                       # 1 MINUTE interval\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "uGmIhLo1azFR",
        "outputId": "c675ffcc-ca2c-44c6-ded5-1c51f84228b5"
      },
      "execution_count": 158,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             Open    High     Low   Close     Volume\n",
              "Datetime                                                            \n",
              "2022-11-07 09:30:00-05:00  137.11  138.22  137.09  137.85  5160318.0\n",
              "2022-11-07 09:31:00-05:00  137.88  137.88  136.85  137.02   810692.0\n",
              "2022-11-07 09:32:00-05:00  137.01  137.28  136.78  137.15   453574.0\n",
              "2022-11-07 09:33:00-05:00  136.85  136.86  136.29  136.49   743820.0\n",
              "2022-11-07 09:34:00-05:00  136.49  137.19  136.32  136.98   478466.0\n",
              "...                           ...     ...     ...     ...        ...\n",
              "2022-11-11 15:56:00-05:00  149.65  149.67  149.53  149.63   462355.0\n",
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              "2022-11-11 16:00:00-05:00  149.70  149.70  149.70  149.70        0.0\n",
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              "      <th>2022-11-07 09:30:00-05:00</th>\n",
              "      <td>137.11</td>\n",
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              "      <th>2022-11-07 09:31:00-05:00</th>\n",
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              "      <td>137.01</td>\n",
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              "<p>1949 rows × 5 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2dffb069-767f-4b1d-8e50-ee8827468052')\"\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 158
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = ticker.history ( period='5d', rounding=True , actions=False , interval='1m', prepost=False)                       # Prepost - False ( just market hours)    True( Pre- Market-Post hours 5am-7 pm )\n",
        "df"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
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        "id": "hEYi2xqedWPc",
        "outputId": "d86265e0-b0c6-4055-e2d4-b42a321e6bcb"
      },
      "execution_count": 159,
      "outputs": [
        {
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              "                             Open    High     Low   Close   Volume\n",
              "Datetime                                                          \n",
              "2022-11-07 09:30:00-05:00  137.11  138.22  137.09  137.85  5160318\n",
              "2022-11-07 09:31:00-05:00  137.88  137.88  136.85  137.02   810692\n",
              "2022-11-07 09:32:00-05:00  137.01  137.28  136.78  137.15   453574\n",
              "2022-11-07 09:33:00-05:00  136.85  136.86  136.29  136.49   743820\n",
              "2022-11-07 09:34:00-05:00  136.49  137.19  136.32  136.98   478466\n",
              "...                           ...     ...     ...     ...      ...\n",
              "2022-11-11 15:56:00-05:00  149.65  149.67  149.53  149.63   462355\n",
              "2022-11-11 15:57:00-05:00  149.63  149.64  149.50  149.53   401885\n",
              "2022-11-11 15:58:00-05:00  149.54  149.60  149.53  149.55   416882\n",
              "2022-11-11 15:59:00-05:00  149.56  149.70  149.50  149.66  1289854\n",
              "2022-11-11 16:00:00-05:00  149.70  149.70  149.70  149.70        0\n",
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              "      <th>2022-11-07 09:30:00-05:00</th>\n",
              "      <td>137.11</td>\n",
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              "      <th>2022-11-07 09:32:00-05:00</th>\n",
              "      <td>137.01</td>\n",
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              "      <td>149.56</td>\n",
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              "<p>1949 rows × 5 columns</p>\n",
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              "                                                     [key], {});\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "84TESwC-gxRP",
        "outputId": "891d2a8c-2b2b-4182-eeda-b5334779b4ab"
      },
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 1949 entries, 2022-11-07 09:30:00-05:00 to 2022-11-11 16:00:00-05:00\n",
            "Data columns (total 5 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   Open    1949 non-null   float64\n",
            " 1   High    1949 non-null   float64\n",
            " 2   Low     1949 non-null   float64\n",
            " 3   Close   1949 non-null   float64\n",
            " 4   Volume  1949 non-null   int64  \n",
            "dtypes: float64(4), int64(1)\n",
            "memory usage: 91.4 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Crypto Currencies has no closing , Prepost = True"
      ],
      "metadata": {
        "id": "brefRZ4mhiPi"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Multiple Stocks ** "
      ],
      "metadata": {
        "id": "pVDayIxWiF94"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "symbols= 'AAPL GM GOOG'                         # ' x y z '\n",
        "tickers = yf.Tickers(symbols)                   #  Tickers()"
      ],
      "metadata": {
        "id": "X7IuEP91iR8F"
      },
      "execution_count": 166,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = tickers.history ( start='2020-12-31', rounding=True , interval='1d', actions=False )\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "id": "6eKqPa7qjIlO",
        "outputId": "e98750ac-bf60-435a-8232-072be556b84d"
      },
      "execution_count": 167,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  3 of 3 completed\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Close                  High                   Low                \\\n",
              "              AAPL     GM   GOOG    AAPL     GM   GOOG    AAPL     GM   GOOG   \n",
              "Date                                                                           \n",
              "2020-12-31  131.12  41.55  87.59  133.14  41.70  87.95  130.16  41.11  86.77   \n",
              "2021-01-04  127.87  40.42  86.41  132.03  42.02  88.03  125.26  40.05  85.39   \n",
              "2021-01-05  129.46  41.57  87.05  130.18  41.74  87.38  126.91  39.95  85.90   \n",
              "2021-01-06  125.10  42.88  86.76  129.50  43.75  87.40  124.88  41.76  84.95   \n",
              "2021-01-07  129.37  43.22  89.36  130.07  43.88  89.42  126.34  42.86  86.85   \n",
              "...            ...    ...    ...     ...    ...    ...     ...    ...    ...   \n",
              "2022-11-07  138.92  39.39  88.65  139.15  39.47  88.94  135.67  38.69  86.96   \n",
              "2022-11-08  139.50  39.05  88.91  141.43  39.51  90.40  137.49  38.51  87.65   \n",
              "2022-11-09  134.87  38.06  87.40  138.55  38.87  89.49  134.59  38.03  87.36   \n",
              "2022-11-10  146.87  39.74  94.17  146.87  40.60  94.55  139.50  38.86  91.65   \n",
              "2022-11-11  149.70  41.12  96.73  150.01  41.58  97.36  144.37  39.82  94.16   \n",
              "\n",
              "              Open                   Volume                      \n",
              "              AAPL     GM   GOOG       AAPL        GM      GOOG  \n",
              "Date                                                             \n",
              "2020-12-31  132.49  41.66  86.77   99116600  11101300  20238000  \n",
              "2021-01-04  131.94  41.85  87.88  143301900  15768100  38038000  \n",
              "2021-01-05  127.36  39.97  86.25   97664900  18045800  22906000  \n",
              "2021-01-06  126.21  41.82  85.13  155088000  22694900  52042000  \n",
              "2021-01-07  126.84  43.88  87.00  109578200  13625700  45300000  \n",
              "...            ...    ...    ...        ...       ...       ...  \n",
              "2022-11-07  137.11  39.36  87.34   83374600  11526900  26899900  \n",
              "2022-11-08  140.41  39.47  89.16   89908500  10946400  30172000  \n",
              "2022-11-09  138.50  38.55  88.54   74917800  10526200  26743900  \n",
              "2022-11-10  141.24  39.15  92.34  118854000  20197600  42371200  \n",
              "2022-11-11  145.82  39.86  94.71   93903800  13033000  30190917  \n",
              "\n",
              "[471 rows x 15 columns]"
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              "      <th>AAPL</th>\n",
              "      <th>GM</th>\n",
              "      <th>GOOG</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>GM</th>\n",
              "      <th>GOOG</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>GM</th>\n",
              "      <th>GOOG</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>GM</th>\n",
              "      <th>GOOG</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>GM</th>\n",
              "      <th>GOOG</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-12-31</th>\n",
              "      <td>131.12</td>\n",
              "      <td>41.55</td>\n",
              "      <td>87.59</td>\n",
              "      <td>133.14</td>\n",
              "      <td>41.70</td>\n",
              "      <td>87.95</td>\n",
              "      <td>130.16</td>\n",
              "      <td>41.11</td>\n",
              "      <td>86.77</td>\n",
              "      <td>132.49</td>\n",
              "      <td>41.66</td>\n",
              "      <td>86.77</td>\n",
              "      <td>99116600</td>\n",
              "      <td>11101300</td>\n",
              "      <td>20238000</td>\n",
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              "    <tr>\n",
              "      <th>2021-01-04</th>\n",
              "      <td>127.87</td>\n",
              "      <td>40.42</td>\n",
              "      <td>86.41</td>\n",
              "      <td>132.03</td>\n",
              "      <td>42.02</td>\n",
              "      <td>88.03</td>\n",
              "      <td>125.26</td>\n",
              "      <td>40.05</td>\n",
              "      <td>85.39</td>\n",
              "      <td>131.94</td>\n",
              "      <td>41.85</td>\n",
              "      <td>87.88</td>\n",
              "      <td>143301900</td>\n",
              "      <td>15768100</td>\n",
              "      <td>38038000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-05</th>\n",
              "      <td>129.46</td>\n",
              "      <td>41.57</td>\n",
              "      <td>87.05</td>\n",
              "      <td>130.18</td>\n",
              "      <td>41.74</td>\n",
              "      <td>87.38</td>\n",
              "      <td>126.91</td>\n",
              "      <td>39.95</td>\n",
              "      <td>85.90</td>\n",
              "      <td>127.36</td>\n",
              "      <td>39.97</td>\n",
              "      <td>86.25</td>\n",
              "      <td>97664900</td>\n",
              "      <td>18045800</td>\n",
              "      <td>22906000</td>\n",
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              "    <tr>\n",
              "      <th>2021-01-06</th>\n",
              "      <td>125.10</td>\n",
              "      <td>42.88</td>\n",
              "      <td>86.76</td>\n",
              "      <td>129.50</td>\n",
              "      <td>43.75</td>\n",
              "      <td>87.40</td>\n",
              "      <td>124.88</td>\n",
              "      <td>41.76</td>\n",
              "      <td>84.95</td>\n",
              "      <td>126.21</td>\n",
              "      <td>41.82</td>\n",
              "      <td>85.13</td>\n",
              "      <td>155088000</td>\n",
              "      <td>22694900</td>\n",
              "      <td>52042000</td>\n",
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              "    <tr>\n",
              "      <th>2021-01-07</th>\n",
              "      <td>129.37</td>\n",
              "      <td>43.22</td>\n",
              "      <td>89.36</td>\n",
              "      <td>130.07</td>\n",
              "      <td>43.88</td>\n",
              "      <td>89.42</td>\n",
              "      <td>126.34</td>\n",
              "      <td>42.86</td>\n",
              "      <td>86.85</td>\n",
              "      <td>126.84</td>\n",
              "      <td>43.88</td>\n",
              "      <td>87.00</td>\n",
              "      <td>109578200</td>\n",
              "      <td>13625700</td>\n",
              "      <td>45300000</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-07</th>\n",
              "      <td>138.92</td>\n",
              "      <td>39.39</td>\n",
              "      <td>88.65</td>\n",
              "      <td>139.15</td>\n",
              "      <td>39.47</td>\n",
              "      <td>88.94</td>\n",
              "      <td>135.67</td>\n",
              "      <td>38.69</td>\n",
              "      <td>86.96</td>\n",
              "      <td>137.11</td>\n",
              "      <td>39.36</td>\n",
              "      <td>87.34</td>\n",
              "      <td>83374600</td>\n",
              "      <td>11526900</td>\n",
              "      <td>26899900</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-08</th>\n",
              "      <td>139.50</td>\n",
              "      <td>39.05</td>\n",
              "      <td>88.91</td>\n",
              "      <td>141.43</td>\n",
              "      <td>39.51</td>\n",
              "      <td>90.40</td>\n",
              "      <td>137.49</td>\n",
              "      <td>38.51</td>\n",
              "      <td>87.65</td>\n",
              "      <td>140.41</td>\n",
              "      <td>39.47</td>\n",
              "      <td>89.16</td>\n",
              "      <td>89908500</td>\n",
              "      <td>10946400</td>\n",
              "      <td>30172000</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-09</th>\n",
              "      <td>134.87</td>\n",
              "      <td>38.06</td>\n",
              "      <td>87.40</td>\n",
              "      <td>138.55</td>\n",
              "      <td>38.87</td>\n",
              "      <td>89.49</td>\n",
              "      <td>134.59</td>\n",
              "      <td>38.03</td>\n",
              "      <td>87.36</td>\n",
              "      <td>138.50</td>\n",
              "      <td>38.55</td>\n",
              "      <td>88.54</td>\n",
              "      <td>74917800</td>\n",
              "      <td>10526200</td>\n",
              "      <td>26743900</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-10</th>\n",
              "      <td>146.87</td>\n",
              "      <td>39.74</td>\n",
              "      <td>94.17</td>\n",
              "      <td>146.87</td>\n",
              "      <td>40.60</td>\n",
              "      <td>94.55</td>\n",
              "      <td>139.50</td>\n",
              "      <td>38.86</td>\n",
              "      <td>91.65</td>\n",
              "      <td>141.24</td>\n",
              "      <td>39.15</td>\n",
              "      <td>92.34</td>\n",
              "      <td>118854000</td>\n",
              "      <td>20197600</td>\n",
              "      <td>42371200</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-11</th>\n",
              "      <td>149.70</td>\n",
              "      <td>41.12</td>\n",
              "      <td>96.73</td>\n",
              "      <td>150.01</td>\n",
              "      <td>41.58</td>\n",
              "      <td>97.36</td>\n",
              "      <td>144.37</td>\n",
              "      <td>39.82</td>\n",
              "      <td>94.16</td>\n",
              "      <td>145.82</td>\n",
              "      <td>39.86</td>\n",
              "      <td>94.71</td>\n",
              "      <td>93903800</td>\n",
              "      <td>13033000</td>\n",
              "      <td>30190917</td>\n",
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              "<p>471 rows × 15 columns</p>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**In complex data , lets select the columns we want to work on**"
      ],
      "metadata": {
        "id": "Uqd_4Zlskxsl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "idx = pd.IndexSlice\n",
        "df.loc[:, idx['Close', ['AAPL', 'GM']]]        # All rows, Then 'Close' column ,then 'AAPL and GM' columns in 'CLose '\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486
        },
        "id": "ta4AnYllmUlh",
        "outputId": "2250767d-1b10-4663-efa4-3649f1e156b4"
      },
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Close       \n",
              "              AAPL     GM\n",
              "Date                     \n",
              "2020-12-31  131.12  41.55\n",
              "2021-01-04  127.87  40.42\n",
              "2021-01-05  129.46  41.57\n",
              "2021-01-06  125.10  42.88\n",
              "2021-01-07  129.37  43.22\n",
              "...            ...    ...\n",
              "2022-11-07  138.92  39.39\n",
              "2022-11-08  139.50  39.05\n",
              "2022-11-09  134.87  38.06\n",
              "2022-11-10  146.87  39.74\n",
              "2022-11-11  149.70  41.12\n",
              "\n",
              "[471 rows x 2 columns]"
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              "          document.querySelector('#df-57fbf05e-3d20-4007-8d06-6c710a84d229 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-57fbf05e-3d20-4007-8d06-6c710a84d229');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# HOW TO GROUP BY    #  ( group_by parameters )\n",
        "\n",
        "df = tickers.history ( start='2020-12-31', rounding=True , interval='1d', actions=False , group_by='tickers' )\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "id": "GTH5-wOwrb4X",
        "outputId": "23af2fdb-d304-46e9-9972-6e7c6c3c1fbe"
      },
      "execution_count": 169,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  3 of 3 completed\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               GM                                   AAPL                  \\\n",
              "             Open   High    Low  Close    Volume    Open    High     Low   \n",
              "Date                                                                       \n",
              "2020-12-31  41.66  41.70  41.11  41.55  11101300  132.49  133.14  130.16   \n",
              "2021-01-04  41.85  42.02  40.05  40.42  15768100  131.94  132.03  125.26   \n",
              "2021-01-05  39.97  41.74  39.95  41.57  18045800  127.36  130.18  126.91   \n",
              "2021-01-06  41.82  43.75  41.76  42.88  22694900  126.20  129.50  124.88   \n",
              "2021-01-07  43.88  43.88  42.86  43.22  13625700  126.84  130.07  126.34   \n",
              "...           ...    ...    ...    ...       ...     ...     ...     ...   \n",
              "2022-11-07  39.36  39.47  38.69  39.39  11526900  137.11  139.15  135.67   \n",
              "2022-11-08  39.47  39.51  38.51  39.05  10946400  140.41  141.43  137.49   \n",
              "2022-11-09  38.55  38.87  38.03  38.06  10526200  138.50  138.55  134.59   \n",
              "2022-11-10  39.15  40.60  38.86  39.74  20197600  141.24  146.87  139.50   \n",
              "2022-11-11  39.86  41.58  39.82  41.12  13033000  145.82  150.01  144.37   \n",
              "\n",
              "                                GOOG                                 \n",
              "             Close     Volume   Open   High    Low  Close    Volume  \n",
              "Date                                                                 \n",
              "2020-12-31  131.12   99116600  86.77  87.95  86.77  87.59  20238000  \n",
              "2021-01-04  127.87  143301900  87.88  88.03  85.39  86.41  38038000  \n",
              "2021-01-05  129.46   97664900  86.25  87.38  85.90  87.05  22906000  \n",
              "2021-01-06  125.10  155088000  85.13  87.40  84.95  86.76  52042000  \n",
              "2021-01-07  129.37  109578200  87.00  89.42  86.85  89.36  45300000  \n",
              "...            ...        ...    ...    ...    ...    ...       ...  \n",
              "2022-11-07  138.92   83374600  87.34  88.94  86.96  88.65  26899900  \n",
              "2022-11-08  139.50   89908500  89.16  90.40  87.65  88.91  30172000  \n",
              "2022-11-09  134.87   74917800  88.54  89.49  87.36  87.40  26743900  \n",
              "2022-11-10  146.87  118854000  92.34  94.55  91.65  94.17  42371200  \n",
              "2022-11-11  149.70   93903800  94.71  97.36  94.16  96.73  30190917  \n",
              "\n",
              "[471 rows x 15 columns]"
            ],
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              "      <th colspan=\"5\" halign=\"left\">GM</th>\n",
              "      <th colspan=\"5\" halign=\"left\">AAPL</th>\n",
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              "      <th></th>\n",
              "      <th>Open</th>\n",
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              "      <th>Open</th>\n",
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              "      <th>Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
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              "      <th>Volume</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-12-31</th>\n",
              "      <td>41.66</td>\n",
              "      <td>41.70</td>\n",
              "      <td>41.11</td>\n",
              "      <td>41.55</td>\n",
              "      <td>11101300</td>\n",
              "      <td>132.49</td>\n",
              "      <td>133.14</td>\n",
              "      <td>130.16</td>\n",
              "      <td>131.12</td>\n",
              "      <td>99116600</td>\n",
              "      <td>86.77</td>\n",
              "      <td>87.95</td>\n",
              "      <td>86.77</td>\n",
              "      <td>87.59</td>\n",
              "      <td>20238000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-04</th>\n",
              "      <td>41.85</td>\n",
              "      <td>42.02</td>\n",
              "      <td>40.05</td>\n",
              "      <td>40.42</td>\n",
              "      <td>15768100</td>\n",
              "      <td>131.94</td>\n",
              "      <td>132.03</td>\n",
              "      <td>125.26</td>\n",
              "      <td>127.87</td>\n",
              "      <td>143301900</td>\n",
              "      <td>87.88</td>\n",
              "      <td>88.03</td>\n",
              "      <td>85.39</td>\n",
              "      <td>86.41</td>\n",
              "      <td>38038000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-05</th>\n",
              "      <td>39.97</td>\n",
              "      <td>41.74</td>\n",
              "      <td>39.95</td>\n",
              "      <td>41.57</td>\n",
              "      <td>18045800</td>\n",
              "      <td>127.36</td>\n",
              "      <td>130.18</td>\n",
              "      <td>126.91</td>\n",
              "      <td>129.46</td>\n",
              "      <td>97664900</td>\n",
              "      <td>86.25</td>\n",
              "      <td>87.38</td>\n",
              "      <td>85.90</td>\n",
              "      <td>87.05</td>\n",
              "      <td>22906000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-06</th>\n",
              "      <td>41.82</td>\n",
              "      <td>43.75</td>\n",
              "      <td>41.76</td>\n",
              "      <td>42.88</td>\n",
              "      <td>22694900</td>\n",
              "      <td>126.20</td>\n",
              "      <td>129.50</td>\n",
              "      <td>124.88</td>\n",
              "      <td>125.10</td>\n",
              "      <td>155088000</td>\n",
              "      <td>85.13</td>\n",
              "      <td>87.40</td>\n",
              "      <td>84.95</td>\n",
              "      <td>86.76</td>\n",
              "      <td>52042000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-01-07</th>\n",
              "      <td>43.88</td>\n",
              "      <td>43.88</td>\n",
              "      <td>42.86</td>\n",
              "      <td>43.22</td>\n",
              "      <td>13625700</td>\n",
              "      <td>126.84</td>\n",
              "      <td>130.07</td>\n",
              "      <td>126.34</td>\n",
              "      <td>129.37</td>\n",
              "      <td>109578200</td>\n",
              "      <td>87.00</td>\n",
              "      <td>89.42</td>\n",
              "      <td>86.85</td>\n",
              "      <td>89.36</td>\n",
              "      <td>45300000</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "    <tr>\n",
              "      <th>2022-11-07</th>\n",
              "      <td>39.36</td>\n",
              "      <td>39.47</td>\n",
              "      <td>38.69</td>\n",
              "      <td>39.39</td>\n",
              "      <td>11526900</td>\n",
              "      <td>137.11</td>\n",
              "      <td>139.15</td>\n",
              "      <td>135.67</td>\n",
              "      <td>138.92</td>\n",
              "      <td>83374600</td>\n",
              "      <td>87.34</td>\n",
              "      <td>88.94</td>\n",
              "      <td>86.96</td>\n",
              "      <td>88.65</td>\n",
              "      <td>26899900</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-08</th>\n",
              "      <td>39.47</td>\n",
              "      <td>39.51</td>\n",
              "      <td>38.51</td>\n",
              "      <td>39.05</td>\n",
              "      <td>10946400</td>\n",
              "      <td>140.41</td>\n",
              "      <td>141.43</td>\n",
              "      <td>137.49</td>\n",
              "      <td>139.50</td>\n",
              "      <td>89908500</td>\n",
              "      <td>89.16</td>\n",
              "      <td>90.40</td>\n",
              "      <td>87.65</td>\n",
              "      <td>88.91</td>\n",
              "      <td>30172000</td>\n",
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              "    <tr>\n",
              "      <th>2022-11-09</th>\n",
              "      <td>38.55</td>\n",
              "      <td>38.87</td>\n",
              "      <td>38.03</td>\n",
              "      <td>38.06</td>\n",
              "      <td>10526200</td>\n",
              "      <td>138.50</td>\n",
              "      <td>138.55</td>\n",
              "      <td>134.59</td>\n",
              "      <td>134.87</td>\n",
              "      <td>74917800</td>\n",
              "      <td>88.54</td>\n",
              "      <td>89.49</td>\n",
              "      <td>87.36</td>\n",
              "      <td>87.40</td>\n",
              "      <td>26743900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-10</th>\n",
              "      <td>39.15</td>\n",
              "      <td>40.60</td>\n",
              "      <td>38.86</td>\n",
              "      <td>39.74</td>\n",
              "      <td>20197600</td>\n",
              "      <td>141.24</td>\n",
              "      <td>146.87</td>\n",
              "      <td>139.50</td>\n",
              "      <td>146.87</td>\n",
              "      <td>118854000</td>\n",
              "      <td>92.34</td>\n",
              "      <td>94.55</td>\n",
              "      <td>91.65</td>\n",
              "      <td>94.17</td>\n",
              "      <td>42371200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-11-11</th>\n",
              "      <td>39.86</td>\n",
              "      <td>41.58</td>\n",
              "      <td>39.82</td>\n",
              "      <td>41.12</td>\n",
              "      <td>13033000</td>\n",
              "      <td>145.82</td>\n",
              "      <td>150.01</td>\n",
              "      <td>144.37</td>\n",
              "      <td>149.70</td>\n",
              "      <td>93903800</td>\n",
              "      <td>94.71</td>\n",
              "      <td>97.36</td>\n",
              "      <td>94.16</td>\n",
              "      <td>96.73</td>\n",
              "      <td>30190917</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>471 rows × 15 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-12c194de-a2e4-4485-bdff-9d75f5b596ec')\"\n",
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              "          const element = document.querySelector('#df-12c194de-a2e4-4485-bdff-9d75f5b596ec');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
          "execution_count": 169
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **How to download the FUNDAMENTAL DATA of Stock(s)**"
      ],
      "metadata": {
        "id": "M7vjcFcEr7mQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "symbol= 'AAPL'\n",
        "ticker = yf.Ticker(symbol)       "
      ],
      "metadata": {
        "id": "wJ2FWrQCsCmB"
      },
      "execution_count": 170,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.info"
      ],
      "metadata": {
        "id": "fgDIjjWpsXw7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.info.keys()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5X1IKvFssmFH",
        "outputId": "67671277-2f6e-4834-d98f-f400d0c220e1"
      },
      "execution_count": 172,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "dict_keys(['zip', 'sector', 'fullTimeEmployees', 'longBusinessSummary', 'city', 'phone', 'state', 'country', 'companyOfficers', 'website', 'maxAge', 'address1', 'industry', 'ebitdaMargins', 'profitMargins', 'grossMargins', 'operatingCashflow', 'revenueGrowth', 'operatingMargins', 'ebitda', 'targetLowPrice', 'recommendationKey', 'grossProfits', 'freeCashflow', 'targetMedianPrice', 'currentPrice', 'earningsGrowth', 'currentRatio', 'returnOnAssets', 'numberOfAnalystOpinions', 'targetMeanPrice', 'debtToEquity', 'returnOnEquity', 'targetHighPrice', 'totalCash', 'totalDebt', 'totalRevenue', 'totalCashPerShare', 'financialCurrency', 'revenuePerShare', 'quickRatio', 'recommendationMean', 'exchange', 'shortName', 'longName', 'exchangeTimezoneName', 'exchangeTimezoneShortName', 'isEsgPopulated', 'gmtOffSetMilliseconds', 'quoteType', 'symbol', 'messageBoardId', 'market', 'annualHoldingsTurnover', 'enterpriseToRevenue', 'beta3Year', 'enterpriseToEbitda', '52WeekChange', 'morningStarRiskRating', 'forwardEps', 'revenueQuarterlyGrowth', 'sharesOutstanding', 'fundInceptionDate', 'annualReportExpenseRatio', 'totalAssets', 'bookValue', 'sharesShort', 'sharesPercentSharesOut', 'fundFamily', 'lastFiscalYearEnd', 'heldPercentInstitutions', 'netIncomeToCommon', 'trailingEps', 'lastDividendValue', 'SandP52WeekChange', 'priceToBook', 'heldPercentInsiders', 'nextFiscalYearEnd', 'yield', 'mostRecentQuarter', 'shortRatio', 'sharesShortPreviousMonthDate', 'floatShares', 'beta', 'enterpriseValue', 'priceHint', 'threeYearAverageReturn', 'lastSplitDate', 'lastSplitFactor', 'legalType', 'lastDividendDate', 'morningStarOverallRating', 'earningsQuarterlyGrowth', 'priceToSalesTrailing12Months', 'dateShortInterest', 'pegRatio', 'ytdReturn', 'forwardPE', 'lastCapGain', 'shortPercentOfFloat', 'sharesShortPriorMonth', 'impliedSharesOutstanding', 'category', 'fiveYearAverageReturn', 'previousClose', 'regularMarketOpen', 'twoHundredDayAverage', 'trailingAnnualDividendYield', 'payoutRatio', 'volume24Hr', 'regularMarketDayHigh', 'navPrice', 'averageDailyVolume10Day', 'regularMarketPreviousClose', 'fiftyDayAverage', 'trailingAnnualDividendRate', 'open', 'toCurrency', 'averageVolume10days', 'expireDate', 'algorithm', 'dividendRate', 'exDividendDate', 'circulatingSupply', 'startDate', 'regularMarketDayLow', 'currency', 'trailingPE', 'regularMarketVolume', 'lastMarket', 'maxSupply', 'openInterest', 'marketCap', 'volumeAllCurrencies', 'strikePrice', 'averageVolume', 'dayLow', 'ask', 'askSize', 'volume', 'fiftyTwoWeekHigh', 'fromCurrency', 'fiveYearAvgDividendYield', 'fiftyTwoWeekLow', 'bid', 'tradeable', 'dividendYield', 'bidSize', 'dayHigh', 'coinMarketCapLink', 'regularMarketPrice', 'preMarketPrice', 'logo_url'])"
            ]
          },
          "metadata": {},
          "execution_count": 172
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.Series(ticker.info)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pkz3w7W2suJN",
        "outputId": "4514a53e-ac56-4893-b849-a5e0447ee02d"
      },
      "execution_count": 174,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "zip                                                                95014\n",
              "sector                                                        Technology\n",
              "fullTimeEmployees                                                 164000\n",
              "longBusinessSummary    Apple Inc. designs, manufactures, and markets ...\n",
              "city                                                           Cupertino\n",
              "                                             ...                        \n",
              "dayHigh                                                           150.01\n",
              "coinMarketCapLink                                                   None\n",
              "regularMarketPrice                                                 149.7\n",
              "preMarketPrice                                                    145.86\n",
              "logo_url                             https://logo.clearbit.com/apple.com\n",
              "Length: 153, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 174
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.info['lastDividendValue']                    # Info in Info   "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BlBvGRvZtHdk",
        "outputId": "f416d8d4-06d5-4606-8064-2b395450c54f"
      },
      "execution_count": 176,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.23"
            ]
          },
          "metadata": {},
          "execution_count": 176
        }
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    {
      "cell_type": "code",
      "source": [
        "data=ticker.history(period='5y')\n",
        "data"
      ],
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          "height": 455
        },
        "id": "Wqp3wm0-tik7",
        "outputId": "2d5e2f6f-52fc-46a5-fe34-13e6d16a6175"
      },
      "execution_count": 178,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "2022-11-11 00:00:00-05:00  145.820007  150.009995  144.369995  149.699997   \n",
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        "id": "N-Y2VP5at7nB",
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      "execution_count": 180,
      "outputs": [
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          "data": {
            "text/plain": [
              "                           Dividends  Stock Splits\n",
              "Date                                              \n",
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              "      <th>2019-02-08 00:00:00-05:00</th>\n",
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              "      <td>0.2050</td>\n",
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              "      <td>0.2050</td>\n",
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              "    <tr>\n",
              "      <th>2021-02-05 00:00:00-05:00</th>\n",
              "      <td>0.2050</td>\n",
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              "    <tr>\n",
              "      <th>2021-05-07 00:00:00-04:00</th>\n",
              "      <td>0.2200</td>\n",
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              "      <th>2021-08-06 00:00:00-04:00</th>\n",
              "      <td>0.2200</td>\n",
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              "      <th>2021-11-05 00:00:00-04:00</th>\n",
              "      <td>0.2200</td>\n",
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              "      <th>2022-11-04 00:00:00-04:00</th>\n",
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        "ticker.dividends"
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              "Date\n",
              "2018-02-09 00:00:00-05:00    0.1575\n",
              "2018-05-11 00:00:00-04:00    0.1825\n",
              "2018-08-10 00:00:00-04:00    0.1825\n",
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              "2022-08-05 00:00:00-04:00    0.2300\n",
              "2022-11-04 00:00:00-04:00    0.2300\n",
              "Name: Dividends, dtype: float64"
            ]
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          "metadata": {},
          "execution_count": 181
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            "text/plain": [
              "              Revenue     Earnings\n",
              "Quarter                           \n",
              "4Q2021   123945000000  34630000000\n",
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              "Date\n",
              "2020-08-31 00:00:00-04:00    4.0\n",
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              "                                           2022-09-24     2022-06-25  \\\n",
              "Research Development                     6761000000.0   6797000000.0   \n",
              "Effect Of Accounting Charges                     None           None   \n",
              "Income Before Tax                       24657000000.0  23066000000.0   \n",
              "Minority Interest                                None           None   \n",
              "Net Income                              20721000000.0  19442000000.0   \n",
              "Selling General Administrative           6440000000.0   6012000000.0   \n",
              "Gross Profit                            38095000000.0  35885000000.0   \n",
              "Ebit                                    24894000000.0  23076000000.0   \n",
              "Operating Income                        24894000000.0  23076000000.0   \n",
              "Other Operating Expenses                         None           None   \n",
              "Interest Expense                         -827000000.0   -719000000.0   \n",
              "Extraordinary Items                              None           None   \n",
              "Non Recurring                                    None           None   \n",
              "Other Items                                      None           None   \n",
              "Income Tax Expense                       3936000000.0   3624000000.0   \n",
              "Total Revenue                           90146000000.0  82959000000.0   \n",
              "Total Operating Expenses                65252000000.0  59883000000.0   \n",
              "Cost Of Revenue                         52051000000.0  47074000000.0   \n",
              "Total Other Income Expense Net           -237000000.0    -10000000.0   \n",
              "Discontinued Operations                          None           None   \n",
              "Net Income From Continuing Ops          20721000000.0  19442000000.0   \n",
              "Net Income Applicable To Common Shares  20721000000.0  19442000000.0   \n",
              "\n",
              "                                           2022-03-26      2021-12-25  \n",
              "Research Development                     6387000000.0    6306000000.0  \n",
              "Effect Of Accounting Charges                     None            None  \n",
              "Income Before Tax                       30139000000.0   41241000000.0  \n",
              "Minority Interest                                None            None  \n",
              "Net Income                              25010000000.0   34630000000.0  \n",
              "Selling General Administrative           6193000000.0    6449000000.0  \n",
              "Gross Profit                            42559000000.0   54243000000.0  \n",
              "Ebit                                    29979000000.0   41488000000.0  \n",
              "Operating Income                        29979000000.0   41488000000.0  \n",
              "Other Operating Expenses                         None            None  \n",
              "Interest Expense                         -691000000.0    -694000000.0  \n",
              "Extraordinary Items                              None            None  \n",
              "Non Recurring                                    None            None  \n",
              "Other Items                                      None            None  \n",
              "Income Tax Expense                       5129000000.0    6611000000.0  \n",
              "Total Revenue                           97278000000.0  123945000000.0  \n",
              "Total Operating Expenses                67299000000.0   82457000000.0  \n",
              "Cost Of Revenue                         54719000000.0   69702000000.0  \n",
              "Total Other Income Expense Net            160000000.0    -247000000.0  \n",
              "Discontinued Operations                          None            None  \n",
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              "      <th>2022-06-25</th>\n",
              "      <th>2022-03-26</th>\n",
              "      <th>2021-12-25</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Research Development</th>\n",
              "      <td>6761000000.0</td>\n",
              "      <td>6797000000.0</td>\n",
              "      <td>6387000000.0</td>\n",
              "      <td>6306000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Effect Of Accounting Charges</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Income Before Tax</th>\n",
              "      <td>24657000000.0</td>\n",
              "      <td>23066000000.0</td>\n",
              "      <td>30139000000.0</td>\n",
              "      <td>41241000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Minority Interest</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Income</th>\n",
              "      <td>20721000000.0</td>\n",
              "      <td>19442000000.0</td>\n",
              "      <td>25010000000.0</td>\n",
              "      <td>34630000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Selling General Administrative</th>\n",
              "      <td>6440000000.0</td>\n",
              "      <td>6012000000.0</td>\n",
              "      <td>6193000000.0</td>\n",
              "      <td>6449000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gross Profit</th>\n",
              "      <td>38095000000.0</td>\n",
              "      <td>35885000000.0</td>\n",
              "      <td>42559000000.0</td>\n",
              "      <td>54243000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ebit</th>\n",
              "      <td>24894000000.0</td>\n",
              "      <td>23076000000.0</td>\n",
              "      <td>29979000000.0</td>\n",
              "      <td>41488000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Operating Income</th>\n",
              "      <td>24894000000.0</td>\n",
              "      <td>23076000000.0</td>\n",
              "      <td>29979000000.0</td>\n",
              "      <td>41488000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Operating Expenses</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Interest Expense</th>\n",
              "      <td>-827000000.0</td>\n",
              "      <td>-719000000.0</td>\n",
              "      <td>-691000000.0</td>\n",
              "      <td>-694000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Extraordinary Items</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Non Recurring</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Items</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Income Tax Expense</th>\n",
              "      <td>3936000000.0</td>\n",
              "      <td>3624000000.0</td>\n",
              "      <td>5129000000.0</td>\n",
              "      <td>6611000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Revenue</th>\n",
              "      <td>90146000000.0</td>\n",
              "      <td>82959000000.0</td>\n",
              "      <td>97278000000.0</td>\n",
              "      <td>123945000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Operating Expenses</th>\n",
              "      <td>65252000000.0</td>\n",
              "      <td>59883000000.0</td>\n",
              "      <td>67299000000.0</td>\n",
              "      <td>82457000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cost Of Revenue</th>\n",
              "      <td>52051000000.0</td>\n",
              "      <td>47074000000.0</td>\n",
              "      <td>54719000000.0</td>\n",
              "      <td>69702000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Other Income Expense Net</th>\n",
              "      <td>-237000000.0</td>\n",
              "      <td>-10000000.0</td>\n",
              "      <td>160000000.0</td>\n",
              "      <td>-247000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Discontinued Operations</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Income From Continuing Ops</th>\n",
              "      <td>20721000000.0</td>\n",
              "      <td>19442000000.0</td>\n",
              "      <td>25010000000.0</td>\n",
              "      <td>34630000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Income Applicable To Common Shares</th>\n",
              "      <td>20721000000.0</td>\n",
              "      <td>19442000000.0</td>\n",
              "      <td>25010000000.0</td>\n",
              "      <td>34630000000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0ca6669d-2c78-44ec-beab-5d2cdf6136c4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 192
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.balance_sheet\n",
        "#ticker.quarterly_balance_sheet"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 770
        },
        "id": "fXKy5oPyvWzL",
        "outputId": "04351177-c64a-4c8a-88fb-befa139c0fcf"
      },
      "execution_count": 193,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                2022-09-24    2021-09-25  \\\n",
              "Total Liab                                    3.020830e+11  2.879120e+11   \n",
              "Total Stockholder Equity                      5.067200e+10  6.309000e+10   \n",
              "Other Current Liab                            6.709400e+10  5.357700e+10   \n",
              "Total Assets                                  3.527550e+11  3.510020e+11   \n",
              "Common Stock                                  6.484900e+10  5.736500e+10   \n",
              "Other Current Assets                          2.122300e+10  1.411100e+10   \n",
              "Retained Earnings                            -3.068000e+09  5.562000e+09   \n",
              "Other Liab                                    3.839400e+10  4.305000e+10   \n",
              "Gains Losses Not Affecting Retained Earnings -1.110900e+10  1.630000e+08   \n",
              "Other Assets                                  4.401100e+10  3.876200e+10   \n",
              "Cash                                          2.364600e+10  3.494000e+10   \n",
              "Total Current Liabilities                     1.539820e+11  1.254810e+11   \n",
              "Short Long Term Debt                          1.112800e+10  9.613000e+09   \n",
              "Other Stockholder Equity                     -1.110900e+10  1.630000e+08   \n",
              "Property Plant Equipment                      5.253400e+10  4.952700e+10   \n",
              "Total Current Assets                          1.354050e+11  1.348360e+11   \n",
              "Long Term Investments                         1.208050e+11  1.278770e+11   \n",
              "Net Tangible Assets                           5.067200e+10  6.309000e+10   \n",
              "Short Term Investments                        2.465800e+10  2.769900e+10   \n",
              "Net Receivables                               6.093200e+10  5.150600e+10   \n",
              "Long Term Debt                                9.895900e+10  1.091060e+11   \n",
              "Inventory                                     4.946000e+09  6.580000e+09   \n",
              "Accounts Payable                              6.411500e+10  5.476300e+10   \n",
              "\n",
              "                                                2020-09-26    2019-09-28  \n",
              "Total Liab                                    2.585490e+11  2.480280e+11  \n",
              "Total Stockholder Equity                      6.533900e+10  9.048800e+10  \n",
              "Other Current Liab                            4.786700e+10  4.324200e+10  \n",
              "Total Assets                                  3.238880e+11  3.385160e+11  \n",
              "Common Stock                                  5.077900e+10  4.517400e+10  \n",
              "Other Current Assets                          1.126400e+10  1.235200e+10  \n",
              "Retained Earnings                             1.496600e+10  4.589800e+10  \n",
              "Other Liab                                    4.610800e+10  5.050300e+10  \n",
              "Gains Losses Not Affecting Retained Earnings -4.060000e+08 -5.840000e+08  \n",
              "Other Assets                                  3.395200e+10  3.297800e+10  \n",
              "Cash                                          3.801600e+10  4.884400e+10  \n",
              "Total Current Liabilities                     1.053920e+11  1.057180e+11  \n",
              "Short Long Term Debt                          8.773000e+09  1.026000e+10  \n",
              "Other Stockholder Equity                     -4.060000e+08 -5.840000e+08  \n",
              "Property Plant Equipment                      4.533600e+10  3.737800e+10  \n",
              "Total Current Assets                          1.437130e+11  1.628190e+11  \n",
              "Long Term Investments                         1.008870e+11  1.053410e+11  \n",
              "Net Tangible Assets                           6.533900e+10  9.048800e+10  \n",
              "Short Term Investments                        5.292700e+10  5.171300e+10  \n",
              "Net Receivables                               3.744500e+10  4.580400e+10  \n",
              "Long Term Debt                                9.866700e+10  9.180700e+10  \n",
              "Inventory                                     4.061000e+09  4.106000e+09  \n",
              "Accounts Payable                              4.229600e+10  4.623600e+10  "
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>2022-09-24</th>\n",
              "      <th>2021-09-25</th>\n",
              "      <th>2020-09-26</th>\n",
              "      <th>2019-09-28</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Total Liab</th>\n",
              "      <td>3.020830e+11</td>\n",
              "      <td>2.879120e+11</td>\n",
              "      <td>2.585490e+11</td>\n",
              "      <td>2.480280e+11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Stockholder Equity</th>\n",
              "      <td>5.067200e+10</td>\n",
              "      <td>6.309000e+10</td>\n",
              "      <td>6.533900e+10</td>\n",
              "      <td>9.048800e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Current Liab</th>\n",
              "      <td>6.709400e+10</td>\n",
              "      <td>5.357700e+10</td>\n",
              "      <td>4.786700e+10</td>\n",
              "      <td>4.324200e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Assets</th>\n",
              "      <td>3.527550e+11</td>\n",
              "      <td>3.510020e+11</td>\n",
              "      <td>3.238880e+11</td>\n",
              "      <td>3.385160e+11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Common Stock</th>\n",
              "      <td>6.484900e+10</td>\n",
              "      <td>5.736500e+10</td>\n",
              "      <td>5.077900e+10</td>\n",
              "      <td>4.517400e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Current Assets</th>\n",
              "      <td>2.122300e+10</td>\n",
              "      <td>1.411100e+10</td>\n",
              "      <td>1.126400e+10</td>\n",
              "      <td>1.235200e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Retained Earnings</th>\n",
              "      <td>-3.068000e+09</td>\n",
              "      <td>5.562000e+09</td>\n",
              "      <td>1.496600e+10</td>\n",
              "      <td>4.589800e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Liab</th>\n",
              "      <td>3.839400e+10</td>\n",
              "      <td>4.305000e+10</td>\n",
              "      <td>4.610800e+10</td>\n",
              "      <td>5.050300e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gains Losses Not Affecting Retained Earnings</th>\n",
              "      <td>-1.110900e+10</td>\n",
              "      <td>1.630000e+08</td>\n",
              "      <td>-4.060000e+08</td>\n",
              "      <td>-5.840000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Assets</th>\n",
              "      <td>4.401100e+10</td>\n",
              "      <td>3.876200e+10</td>\n",
              "      <td>3.395200e+10</td>\n",
              "      <td>3.297800e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cash</th>\n",
              "      <td>2.364600e+10</td>\n",
              "      <td>3.494000e+10</td>\n",
              "      <td>3.801600e+10</td>\n",
              "      <td>4.884400e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Current Liabilities</th>\n",
              "      <td>1.539820e+11</td>\n",
              "      <td>1.254810e+11</td>\n",
              "      <td>1.053920e+11</td>\n",
              "      <td>1.057180e+11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Short Long Term Debt</th>\n",
              "      <td>1.112800e+10</td>\n",
              "      <td>9.613000e+09</td>\n",
              "      <td>8.773000e+09</td>\n",
              "      <td>1.026000e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Stockholder Equity</th>\n",
              "      <td>-1.110900e+10</td>\n",
              "      <td>1.630000e+08</td>\n",
              "      <td>-4.060000e+08</td>\n",
              "      <td>-5.840000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Property Plant Equipment</th>\n",
              "      <td>5.253400e+10</td>\n",
              "      <td>4.952700e+10</td>\n",
              "      <td>4.533600e+10</td>\n",
              "      <td>3.737800e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Current Assets</th>\n",
              "      <td>1.354050e+11</td>\n",
              "      <td>1.348360e+11</td>\n",
              "      <td>1.437130e+11</td>\n",
              "      <td>1.628190e+11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Long Term Investments</th>\n",
              "      <td>1.208050e+11</td>\n",
              "      <td>1.278770e+11</td>\n",
              "      <td>1.008870e+11</td>\n",
              "      <td>1.053410e+11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Tangible Assets</th>\n",
              "      <td>5.067200e+10</td>\n",
              "      <td>6.309000e+10</td>\n",
              "      <td>6.533900e+10</td>\n",
              "      <td>9.048800e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Short Term Investments</th>\n",
              "      <td>2.465800e+10</td>\n",
              "      <td>2.769900e+10</td>\n",
              "      <td>5.292700e+10</td>\n",
              "      <td>5.171300e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Receivables</th>\n",
              "      <td>6.093200e+10</td>\n",
              "      <td>5.150600e+10</td>\n",
              "      <td>3.744500e+10</td>\n",
              "      <td>4.580400e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Long Term Debt</th>\n",
              "      <td>9.895900e+10</td>\n",
              "      <td>1.091060e+11</td>\n",
              "      <td>9.866700e+10</td>\n",
              "      <td>9.180700e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Inventory</th>\n",
              "      <td>4.946000e+09</td>\n",
              "      <td>6.580000e+09</td>\n",
              "      <td>4.061000e+09</td>\n",
              "      <td>4.106000e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Accounts Payable</th>\n",
              "      <td>6.411500e+10</td>\n",
              "      <td>5.476300e+10</td>\n",
              "      <td>4.229600e+10</td>\n",
              "      <td>4.623600e+10</td>\n",
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              "                                                     [key], {});\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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    {
      "cell_type": "code",
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        "ticker.cashflow"
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      "execution_count": 194,
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        {
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          "data": {
            "text/plain": [
              "                                             2022-09-24    2021-09-25  \\\n",
              "Investments                               -9.560000e+09 -3.075000e+09   \n",
              "Change To Liabilities                      9.926000e+09  1.400200e+10   \n",
              "Total Cashflows From Investing Activities -2.235400e+10 -1.454500e+10   \n",
              "Net Borrowings                            -1.230000e+08  1.266500e+10   \n",
              "Total Cash From Financing Activities      -1.107490e+11 -9.335300e+10   \n",
              "Change To Operating Activities            -8.387000e+09 -6.146000e+09   \n",
              "Net Income                                 9.980300e+10  9.468000e+10   \n",
              "Change In Cash                            -1.095200e+10 -3.860000e+09   \n",
              "Repurchase Of Stock                       -9.562500e+10 -9.252700e+10   \n",
              "Total Cash From Operating Activities       1.221510e+11  1.040380e+11   \n",
              "Depreciation                               1.110400e+10  1.128400e+10   \n",
              "Other Cashflows From Investing Activities -1.780000e+09 -3.520000e+08   \n",
              "Dividends Paid                            -1.484100e+10 -1.446700e+10   \n",
              "Change To Inventory                        1.484000e+09 -2.642000e+09   \n",
              "Change To Account Receivables             -1.823000e+09 -1.012500e+10   \n",
              "Other Cashflows From Financing Activities -1.600000e+08  9.760000e+08   \n",
              "Change To Netincome                        1.004400e+10  2.985000e+09   \n",
              "Capital Expenditures                      -1.070800e+10 -1.108500e+10   \n",
              "Issuance Of Stock                                   NaN           NaN   \n",
              "\n",
              "                                             2020-09-26    2019-09-28  \n",
              "Investments                                5.453000e+09  5.809300e+10  \n",
              "Change To Liabilities                     -1.981000e+09 -2.548000e+09  \n",
              "Total Cashflows From Investing Activities -4.289000e+09  4.589600e+10  \n",
              "Net Borrowings                             2.499000e+09 -7.819000e+09  \n",
              "Total Cash From Financing Activities      -8.682000e+10 -9.097600e+10  \n",
              "Change To Operating Activities             8.810000e+08 -8.960000e+08  \n",
              "Net Income                                 5.741100e+10  5.525600e+10  \n",
              "Change In Cash                            -1.043500e+10  2.431100e+10  \n",
              "Repurchase Of Stock                       -7.599200e+10 -6.971400e+10  \n",
              "Total Cash From Operating Activities       8.067400e+10  6.939100e+10  \n",
              "Depreciation                               1.105600e+10  1.254700e+10  \n",
              "Other Cashflows From Investing Activities -9.090000e+08 -1.078000e+09  \n",
              "Dividends Paid                            -1.408100e+10 -1.411900e+10  \n",
              "Change To Inventory                       -1.270000e+08 -2.890000e+08  \n",
              "Change To Account Receivables              6.917000e+09  2.450000e+08  \n",
              "Other Cashflows From Financing Activities  7.540000e+08 -1.050000e+08  \n",
              "Change To Netincome                        6.517000e+09  5.076000e+09  \n",
              "Capital Expenditures                      -7.309000e+09 -1.049500e+10  \n",
              "Issuance Of Stock                                   NaN  7.810000e+08  "
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              "      <th></th>\n",
              "      <th>2022-09-24</th>\n",
              "      <th>2021-09-25</th>\n",
              "      <th>2020-09-26</th>\n",
              "      <th>2019-09-28</th>\n",
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              "      <th>Investments</th>\n",
              "      <td>-9.560000e+09</td>\n",
              "      <td>-3.075000e+09</td>\n",
              "      <td>5.453000e+09</td>\n",
              "      <td>5.809300e+10</td>\n",
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              "      <td>-2.548000e+09</td>\n",
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              "      <th>Total Cashflows From Investing Activities</th>\n",
              "      <td>-2.235400e+10</td>\n",
              "      <td>-1.454500e+10</td>\n",
              "      <td>-4.289000e+09</td>\n",
              "      <td>4.589600e+10</td>\n",
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              "      <th>Net Borrowings</th>\n",
              "      <td>-1.230000e+08</td>\n",
              "      <td>1.266500e+10</td>\n",
              "      <td>2.499000e+09</td>\n",
              "      <td>-7.819000e+09</td>\n",
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              "    <tr>\n",
              "      <th>Total Cash From Financing Activities</th>\n",
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              "      <td>-9.335300e+10</td>\n",
              "      <td>-8.682000e+10</td>\n",
              "      <td>-9.097600e+10</td>\n",
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              "      <th>Change To Operating Activities</th>\n",
              "      <td>-8.387000e+09</td>\n",
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              "      <td>8.810000e+08</td>\n",
              "      <td>-8.960000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Income</th>\n",
              "      <td>9.980300e+10</td>\n",
              "      <td>9.468000e+10</td>\n",
              "      <td>5.741100e+10</td>\n",
              "      <td>5.525600e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Change In Cash</th>\n",
              "      <td>-1.095200e+10</td>\n",
              "      <td>-3.860000e+09</td>\n",
              "      <td>-1.043500e+10</td>\n",
              "      <td>2.431100e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Repurchase Of Stock</th>\n",
              "      <td>-9.562500e+10</td>\n",
              "      <td>-9.252700e+10</td>\n",
              "      <td>-7.599200e+10</td>\n",
              "      <td>-6.971400e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Cash From Operating Activities</th>\n",
              "      <td>1.221510e+11</td>\n",
              "      <td>1.040380e+11</td>\n",
              "      <td>8.067400e+10</td>\n",
              "      <td>6.939100e+10</td>\n",
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              "    <tr>\n",
              "      <th>Depreciation</th>\n",
              "      <td>1.110400e+10</td>\n",
              "      <td>1.128400e+10</td>\n",
              "      <td>1.105600e+10</td>\n",
              "      <td>1.254700e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Cashflows From Investing Activities</th>\n",
              "      <td>-1.780000e+09</td>\n",
              "      <td>-3.520000e+08</td>\n",
              "      <td>-9.090000e+08</td>\n",
              "      <td>-1.078000e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividends Paid</th>\n",
              "      <td>-1.484100e+10</td>\n",
              "      <td>-1.446700e+10</td>\n",
              "      <td>-1.408100e+10</td>\n",
              "      <td>-1.411900e+10</td>\n",
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              "    <tr>\n",
              "      <th>Change To Inventory</th>\n",
              "      <td>1.484000e+09</td>\n",
              "      <td>-2.642000e+09</td>\n",
              "      <td>-1.270000e+08</td>\n",
              "      <td>-2.890000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Change To Account Receivables</th>\n",
              "      <td>-1.823000e+09</td>\n",
              "      <td>-1.012500e+10</td>\n",
              "      <td>6.917000e+09</td>\n",
              "      <td>2.450000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Other Cashflows From Financing Activities</th>\n",
              "      <td>-1.600000e+08</td>\n",
              "      <td>9.760000e+08</td>\n",
              "      <td>7.540000e+08</td>\n",
              "      <td>-1.050000e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Change To Netincome</th>\n",
              "      <td>1.004400e+10</td>\n",
              "      <td>2.985000e+09</td>\n",
              "      <td>6.517000e+09</td>\n",
              "      <td>5.076000e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Capital Expenditures</th>\n",
              "      <td>-1.070800e+10</td>\n",
              "      <td>-1.108500e+10</td>\n",
              "      <td>-7.309000e+09</td>\n",
              "      <td>-1.049500e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Issuance Of Stock</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.810000e+08</td>\n",
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              "  </tbody>\n",
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  "
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          },
          "metadata": {},
          "execution_count": 194
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.sustainability"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 927
        },
        "id": "65ZMtlsDvvV7",
        "outputId": "0486b794-1687-43ba-cf9c-792a027ceeb3"
      },
      "execution_count": 195,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                     Value\n",
              "2022-8                                    \n",
              "palmOil                              False\n",
              "controversialWeapons                 False\n",
              "gambling                             False\n",
              "socialScore                           6.86\n",
              "nuclear                              False\n",
              "furLeather                           False\n",
              "alcoholic                            False\n",
              "gmo                                  False\n",
              "catholic                             False\n",
              "socialPercentile                      None\n",
              "peerCount                               55\n",
              "governanceScore                       9.18\n",
              "environmentPercentile                 None\n",
              "animalTesting                        False\n",
              "tobacco                              False\n",
              "totalEsg                             16.68\n",
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              "                                  Firm      To Grade From Grade Action\n",
              "Date                                                                  \n",
              "2012-02-09 08:17:00  Canaccord Genuity           Buy              main\n",
              "2012-03-08 07:33:00     FBN Securities    Outperform              main\n",
              "2012-03-13 06:08:00          Jefferies           Buy              main\n",
              "2012-03-14 06:13:00     Morgan Stanley    Overweight              main\n",
              "2012-03-14 08:21:00  Canaccord Genuity           Buy              main\n",
              "...                                ...           ...        ...    ...\n",
              "2022-10-28 13:19:17            Wedbush    Outperform              main\n",
              "2022-11-07 12:39:27           Barclays  Equal-Weight              main\n",
              "2022-11-07 13:08:30  B of A Securities       Neutral              main\n",
              "2022-11-08 12:14:23     Morgan Stanley    Overweight              main\n",
              "2022-11-08 12:17:03                UBS           Buy              main\n",
              "\n",
              "[871 rows x 4 columns]"
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              "<p>871 rows × 4 columns</p>\n",
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          "data": {
            "text/plain": [
              "                                    0                    1\n",
              "Earnings Date     2023-01-25 10:59:00  2023-01-30 12:00:00\n",
              "Earnings Average                 2.05                 2.05\n",
              "Earnings Low                     1.89                 1.89\n",
              "Earnings High                     2.2                  2.2\n",
              "Revenue Average          126360000000         126360000000\n",
              "Revenue Low              117857000000         117857000000\n",
              "Revenue High             132365000000         132365000000"
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              "      <th>Earnings High</th>\n",
              "      <td>2.2</td>\n",
              "      <td>2.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Revenue Average</th>\n",
              "      <td>126360000000</td>\n",
              "      <td>126360000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Revenue Low</th>\n",
              "      <td>117857000000</td>\n",
              "      <td>117857000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Revenue High</th>\n",
              "      <td>132365000000</td>\n",
              "      <td>132365000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "        buttonEl.style.display =\n",
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              "\n",
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              "          const element = document.querySelector('#df-72b1c9c3-b472-4f2d-b248-bcb5cd6f0982');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 197
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Option Data**"
      ],
      "metadata": {
        "id": "i9vHpSVpv_P3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ticker.options     # calling   "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b30spTrGwHKf",
        "outputId": "8a0db9ad-ff5a-4b22-c681-aa9411c51848"
      },
      "execution_count": 200,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('2022-11-18',\n",
              " '2022-11-25',\n",
              " '2022-12-02',\n",
              " '2022-12-09',\n",
              " '2022-12-16',\n",
              " '2022-12-23',\n",
              " '2023-01-20',\n",
              " '2023-02-17',\n",
              " '2023-03-17',\n",
              " '2023-04-21',\n",
              " '2023-05-19',\n",
              " '2023-06-16',\n",
              " '2023-07-21',\n",
              " '2023-09-15',\n",
              " '2024-01-19',\n",
              " '2024-03-15',\n",
              " '2024-06-21',\n",
              " '2025-01-17')"
            ]
          },
          "metadata": {},
          "execution_count": 200
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Expiration date in Calling Options\n",
        "\n",
        "expiration_date= ticker.options[0]\n",
        "expiration_date"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "u09EVHPLwiwZ",
        "outputId": "13f475aa-1e6c-4e6a-e298-a34cbf3a6eb4"
      },
      "execution_count": 204,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2022-11-18'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 204
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from requests.api import options\n",
        "options= ticker.option_chain(expiration_date)"
      ],
      "metadata": {
        "id": "pTkCbBwYxF87"
      },
      "execution_count": 203,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "options.calls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "3LwlecOdxVKQ",
        "outputId": "44be1dca-d50e-441b-c3ef-4155e360acee"
      },
      "execution_count": 206,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         contractSymbol             lastTradeDate  strike  lastPrice    bid  \\\n",
              "0   AAPL221118C00050000 2022-11-04 18:43:38+00:00    50.0      86.65  99.30   \n",
              "1   AAPL221118C00055000 2022-11-03 18:17:55+00:00    55.0      84.45  94.25   \n",
              "2   AAPL221118C00060000 2022-11-11 16:16:03+00:00    60.0      87.45  89.30   \n",
              "3   AAPL221118C00065000 2022-11-03 19:33:52+00:00    65.0      74.95  84.40   \n",
              "4   AAPL221118C00070000 2022-11-09 15:00:53+00:00    70.0      67.50  79.30   \n",
              "..                  ...                       ...     ...        ...    ...   \n",
              "70  AAPL221118C00260000 2022-11-03 13:30:00+00:00   260.0       0.01   0.00   \n",
              "71  AAPL221118C00270000 2022-11-03 19:45:17+00:00   270.0       0.01   0.00   \n",
              "72  AAPL221118C00280000 2022-11-08 15:22:05+00:00   280.0       0.01   0.00   \n",
              "73  AAPL221118C00290000 2022-11-08 18:19:30+00:00   290.0       0.01   0.00   \n",
              "74  AAPL221118C00300000 2022-11-11 20:45:37+00:00   300.0       0.01   0.00   \n",
              "\n",
              "      ask    change  percentChange  volume  openInterest  impliedVolatility  \\\n",
              "0   99.95  0.000000       0.000000     4.0           9.0           3.699220   \n",
              "1   94.90  0.000000       0.000000    80.0           0.0           3.292971   \n",
              "2   90.00  4.489998       5.412244     2.0           3.0           3.207033   \n",
              "3   85.05  0.000000       0.000000    40.0           0.0           2.171880   \n",
              "4   79.90  0.000000       0.000000     3.0           3.0           2.550785   \n",
              "..    ...       ...            ...     ...           ...                ...   \n",
              "70   0.01  0.000000       0.000000     1.0        1391.0           1.218754   \n",
              "71   0.01  0.000000       0.000000     1.0        2624.0           1.312503   \n",
              "72   0.01  0.000000       0.000000     1.0        1983.0           1.375003   \n",
              "73   0.01  0.000000       0.000000     2.0         880.0           1.437503   \n",
              "74   0.01  0.000000       0.000000     2.0       10889.0           1.500002   \n",
              "\n",
              "    inTheMoney contractSize currency  \n",
              "0         True      REGULAR      USD  \n",
              "1         True      REGULAR      USD  \n",
              "2         True      REGULAR      USD  \n",
              "3         True      REGULAR      USD  \n",
              "4         True      REGULAR      USD  \n",
              "..         ...          ...      ...  \n",
              "70       False      REGULAR      USD  \n",
              "71       False      REGULAR      USD  \n",
              "72       False      REGULAR      USD  \n",
              "73       False      REGULAR      USD  \n",
              "74       False      REGULAR      USD  \n",
              "\n",
              "[75 rows x 14 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-42ee1e19-d653-4a75-825d-971a51f053fc\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>contractSymbol</th>\n",
              "      <th>lastTradeDate</th>\n",
              "      <th>strike</th>\n",
              "      <th>lastPrice</th>\n",
              "      <th>bid</th>\n",
              "      <th>ask</th>\n",
              "      <th>change</th>\n",
              "      <th>percentChange</th>\n",
              "      <th>volume</th>\n",
              "      <th>openInterest</th>\n",
              "      <th>impliedVolatility</th>\n",
              "      <th>inTheMoney</th>\n",
              "      <th>contractSize</th>\n",
              "      <th>currency</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AAPL221118C00050000</td>\n",
              "      <td>2022-11-04 18:43:38+00:00</td>\n",
              "      <td>50.0</td>\n",
              "      <td>86.65</td>\n",
              "      <td>99.30</td>\n",
              "      <td>99.95</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.699220</td>\n",
              "      <td>True</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AAPL221118C00055000</td>\n",
              "      <td>2022-11-03 18:17:55+00:00</td>\n",
              "      <td>55.0</td>\n",
              "      <td>84.45</td>\n",
              "      <td>94.25</td>\n",
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              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>80.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.292971</td>\n",
              "      <td>True</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AAPL221118C00060000</td>\n",
              "      <td>2022-11-11 16:16:03+00:00</td>\n",
              "      <td>60.0</td>\n",
              "      <td>87.45</td>\n",
              "      <td>89.30</td>\n",
              "      <td>90.00</td>\n",
              "      <td>4.489998</td>\n",
              "      <td>5.412244</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.207033</td>\n",
              "      <td>True</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AAPL221118C00065000</td>\n",
              "      <td>2022-11-03 19:33:52+00:00</td>\n",
              "      <td>65.0</td>\n",
              "      <td>74.95</td>\n",
              "      <td>84.40</td>\n",
              "      <td>85.05</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>40.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.171880</td>\n",
              "      <td>True</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AAPL221118C00070000</td>\n",
              "      <td>2022-11-09 15:00:53+00:00</td>\n",
              "      <td>70.0</td>\n",
              "      <td>67.50</td>\n",
              "      <td>79.30</td>\n",
              "      <td>79.90</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.550785</td>\n",
              "      <td>True</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>AAPL221118C00260000</td>\n",
              "      <td>2022-11-03 13:30:00+00:00</td>\n",
              "      <td>260.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1391.0</td>\n",
              "      <td>1.218754</td>\n",
              "      <td>False</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>AAPL221118C00270000</td>\n",
              "      <td>2022-11-03 19:45:17+00:00</td>\n",
              "      <td>270.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2624.0</td>\n",
              "      <td>1.312503</td>\n",
              "      <td>False</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>AAPL221118C00280000</td>\n",
              "      <td>2022-11-08 15:22:05+00:00</td>\n",
              "      <td>280.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1983.0</td>\n",
              "      <td>1.375003</td>\n",
              "      <td>False</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>AAPL221118C00290000</td>\n",
              "      <td>2022-11-08 18:19:30+00:00</td>\n",
              "      <td>290.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.0</td>\n",
              "      <td>880.0</td>\n",
              "      <td>1.437503</td>\n",
              "      <td>False</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>AAPL221118C00300000</td>\n",
              "      <td>2022-11-11 20:45:37+00:00</td>\n",
              "      <td>300.0</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.0</td>\n",
              "      <td>10889.0</td>\n",
              "      <td>1.500002</td>\n",
              "      <td>False</td>\n",
              "      <td>REGULAR</td>\n",
              "      <td>USD</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>75 rows × 14 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-42ee1e19-d653-4a75-825d-971a51f053fc')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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      "execution_count": 207,
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 75 entries, 0 to 74\n",
            "Data columns (total 14 columns):\n",
            " #   Column             Non-Null Count  Dtype              \n",
            "---  ------             --------------  -----              \n",
            " 0   contractSymbol     75 non-null     object             \n",
            " 1   lastTradeDate      75 non-null     datetime64[ns, UTC]\n",
            " 2   strike             75 non-null     float64            \n",
            " 3   lastPrice          75 non-null     float64            \n",
            " 4   bid                75 non-null     float64            \n",
            " 5   ask                75 non-null     float64            \n",
            " 6   change             75 non-null     float64            \n",
            " 7   percentChange      75 non-null     float64            \n",
            " 8   volume             72 non-null     float64            \n",
            " 9   openInterest       72 non-null     float64            \n",
            " 10  impliedVolatility  75 non-null     float64            \n",
            " 11  inTheMoney         75 non-null     bool               \n",
            " 12  contractSize       75 non-null     object             \n",
            " 13  currency           75 non-null     object             \n",
            "dtypes: bool(1), datetime64[ns, UTC](1), float64(9), object(3)\n",
            "memory usage: 7.8+ KB\n"
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      "execution_count": 208,
      "outputs": [
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              "         contractSymbol             lastTradeDate  strike  lastPrice     bid  \\\n",
              "0   AAPL221118P00050000 2022-11-08 18:20:05+00:00    50.0       0.01    0.00   \n",
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              "..                  ...                       ...     ...        ...     ...   \n",
              "71  AAPL221118P00260000 2022-11-09 15:16:40+00:00   260.0     122.25  110.15   \n",
              "72  AAPL221118P00270000 2022-11-09 15:16:40+00:00   270.0     132.25  120.15   \n",
              "73  AAPL221118P00280000 2022-11-09 15:05:08+00:00   280.0     142.60  130.15   \n",
              "74  AAPL221118P00290000 2022-11-10 20:53:08+00:00   290.0     143.85  140.15   \n",
              "75  AAPL221118P00300000 2022-11-10 20:55:05+00:00   300.0     153.25  150.15   \n",
              "\n",
              "       ask  change  percentChange  volume  openInterest  impliedVolatility  \\\n",
              "0     0.01     0.0            0.0     2.0        3061.0           2.437504   \n",
              "1     0.01     0.0            0.0  1044.0        2062.0           2.250004   \n",
              "2     0.01     0.0            0.0     3.0        7105.0           2.062505   \n",
              "3     0.01     0.0            0.0    49.0       11599.0           1.875001   \n",
              "4     0.01     0.0            0.0     1.0        4889.0           1.750001   \n",
              "..     ...     ...            ...     ...           ...                ...   \n",
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              "73  130.75     0.0            0.0    11.0           0.0           1.894532   \n",
              "74  140.65     0.0            0.0     6.0           6.0           1.890626   \n",
              "75  150.65     0.0            0.0     7.0           7.0           1.972656   \n",
              "\n",
              "    inTheMoney contractSize currency  \n",
              "0        False      REGULAR      USD  \n",
              "1        False      REGULAR      USD  \n",
              "2        False      REGULAR      USD  \n",
              "3        False      REGULAR      USD  \n",
              "4        False      REGULAR      USD  \n",
              "..         ...          ...      ...  \n",
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              "72        True      REGULAR      USD  \n",
              "73        True      REGULAR      USD  \n",
              "74        True      REGULAR      USD  \n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 208
        }
      ]
    }
  ]
}