How To Get Stocks Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to get stocks data with Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Start by installing the yfinance library\n",
    "\n",
    "Documentation: https://pypi.org/project/yfinance/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "!pip install yfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "tesla = yf.Ticker('TSLA')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'zip': '94304',\n",
       " 'sector': 'Consumer Cyclical',\n",
       " 'fullTimeEmployees': 70757,\n",
       " 'longBusinessSummary': 'Tesla, Inc. designs, develops, manufactures, leases, and sells electric vehicles, and energy generation and storage systems in the United States, China, and internationally. The company operates in two segments, Automotive, and Energy Generation and Storage. The Automotive segment offers electric vehicles, as well as sells automotive regulatory credits. It provides sedans and sport utility vehicles through direct and used vehicle sales, a network of Tesla Superchargers, and in-app upgrades; and purchase financing and leasing services. This segment is also involved in the provision of non-warranty after-sales vehicle services, sale of used vehicles, retail merchandise, and vehicle insurance, as well as sale of products through its subsidiaries to third party customers; services for electric vehicles through its company-owned service locations, and Tesla mobile service technicians; and vehicle limited warranties and extended service plans. The Energy Generation and Storage segment engages in the design, manufacture, installation, sale, and leasing of solar energy generation and energy storage products, and related services to residential, commercial, and industrial customers and utilities through its website, stores, and galleries, as well as through a network of channel partners. This segment also offers service and repairs to its energy product customers, including under warranty; and various financing options to its solar customers. The company was formerly known as Tesla Motors, Inc. and changed its name to Tesla, Inc. in February 2017. Tesla, Inc. was founded in 2003 and is headquartered in Palo Alto, California.',\n",
       " 'city': 'Palo Alto',\n",
       " 'phone': '650-681-5000',\n",
       " 'state': 'CA',\n",
       " 'country': 'United States',\n",
       " 'companyOfficers': [],\n",
       " 'website': 'http://www.tesla.com',\n",
       " 'maxAge': 1,\n",
       " 'address1': '3500 Deer Creek Road',\n",
       " 'industry': 'Auto Manufacturers',\n",
       " 'previousClose': 673.58,\n",
       " 'regularMarketOpen': 700.3,\n",
       " 'twoHundredDayAverage': 584.02264,\n",
       " 'trailingAnnualDividendYield': None,\n",
       " 'payoutRatio': 0,\n",
       " 'volume24Hr': None,\n",
       " 'regularMarketDayHigh': 717.85,\n",
       " 'navPrice': None,\n",
       " 'averageDailyVolume10Day': 50551185,\n",
       " 'totalAssets': None,\n",
       " 'regularMarketPreviousClose': 673.58,\n",
       " 'fiftyDayAverage': 778.5372,\n",
       " 'trailingAnnualDividendRate': None,\n",
       " 'open': 700.3,\n",
       " 'toCurrency': None,\n",
       " 'averageVolume10days': 50551185,\n",
       " 'expireDate': None,\n",
       " 'yield': None,\n",
       " 'algorithm': None,\n",
       " 'dividendRate': None,\n",
       " 'exDividendDate': None,\n",
       " 'beta': 2.06013,\n",
       " 'circulatingSupply': None,\n",
       " 'startDate': None,\n",
       " 'regularMarketDayLow': 655.06,\n",
       " 'priceHint': 2,\n",
       " 'currency': 'USD',\n",
       " 'trailingPE': 1037.9376,\n",
       " 'regularMarketVolume': 48166712,\n",
       " 'lastMarket': None,\n",
       " 'maxSupply': None,\n",
       " 'openInterest': None,\n",
       " 'marketCap': 637611933696,\n",
       " 'volumeAllCurrencies': None,\n",
       " 'strikePrice': None,\n",
       " 'averageVolume': 40455196,\n",
       " 'priceToSalesTrailing12Months': 20.21854,\n",
       " 'dayLow': 655.06,\n",
       " 'ask': 664.25,\n",
       " 'ytdReturn': None,\n",
       " 'askSize': 800,\n",
       " 'volume': 48166712,\n",
       " 'fiftyTwoWeekHigh': 900.4,\n",
       " 'forwardPE': 120.7782,\n",
       " 'fromCurrency': None,\n",
       " 'fiveYearAvgDividendYield': None,\n",
       " 'fiftyTwoWeekLow': 70.102,\n",
       " 'bid': 662.41,\n",
       " 'tradeable': False,\n",
       " 'dividendYield': None,\n",
       " 'bidSize': 1400,\n",
       " 'dayHigh': 717.85,\n",
       " 'exchange': 'NMS',\n",
       " 'shortName': 'Tesla, Inc.',\n",
       " 'longName': 'Tesla, Inc.',\n",
       " 'exchangeTimezoneName': 'America/New_York',\n",
       " 'exchangeTimezoneShortName': 'EST',\n",
       " 'isEsgPopulated': False,\n",
       " 'gmtOffSetMilliseconds': '-18000000',\n",
       " 'quoteType': 'EQUITY',\n",
       " 'symbol': 'TSLA',\n",
       " 'messageBoardId': 'finmb_27444752',\n",
       " 'market': 'us_market',\n",
       " 'annualHoldingsTurnover': None,\n",
       " 'enterpriseToRevenue': 20.356,\n",
       " 'beta3Year': None,\n",
       " 'profitMargins': 0.02286,\n",
       " 'enterpriseToEbitda': 150.233,\n",
       " '52WeekChange': 4.310219,\n",
       " 'morningStarRiskRating': None,\n",
       " 'forwardEps': 5.5,\n",
       " 'revenueQuarterlyGrowth': None,\n",
       " 'sharesOutstanding': 959854016,\n",
       " 'fundInceptionDate': None,\n",
       " 'annualReportExpenseRatio': None,\n",
       " 'bookValue': 23.151,\n",
       " 'sharesShort': 44000524,\n",
       " 'sharesPercentSharesOut': 0.0458,\n",
       " 'fundFamily': None,\n",
       " 'lastFiscalYearEnd': 1609372800,\n",
       " 'heldPercentInstitutions': 0.42529,\n",
       " 'netIncomeToCommon': 690000000,\n",
       " 'trailingEps': 0.64,\n",
       " 'lastDividendValue': None,\n",
       " 'SandP52WeekChange': 0.4136821,\n",
       " 'priceToBook': 28.693365,\n",
       " 'heldPercentInsiders': 0.19985001,\n",
       " 'nextFiscalYearEnd': 1672444800,\n",
       " 'mostRecentQuarter': 1609372800,\n",
       " 'shortRatio': 1.59,\n",
       " 'sharesShortPreviousMonthDate': 1611878400,\n",
       " 'floatShares': 771319079,\n",
       " 'enterpriseValue': 641945108480,\n",
       " 'threeYearAverageReturn': None,\n",
       " 'lastSplitDate': 1598832000,\n",
       " 'lastSplitFactor': '5:1',\n",
       " 'legalType': None,\n",
       " 'lastDividendDate': None,\n",
       " 'morningStarOverallRating': None,\n",
       " 'earningsQuarterlyGrowth': 1.571,\n",
       " 'dateShortInterest': 1614297600,\n",
       " 'pegRatio': 6.45,\n",
       " 'lastCapGain': None,\n",
       " 'shortPercentOfFloat': 0.056999996,\n",
       " 'sharesShortPriorMonth': 52379526,\n",
       " 'impliedSharesOutstanding': None,\n",
       " 'category': None,\n",
       " 'fiveYearAverageReturn': None,\n",
       " 'regularMarketPrice': 700.3,\n",
       " 'logo_url': 'https://logo.clearbit.com/tesla.com'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesla.info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Price to Book: 28.693365\n",
      "Peg Ratio: 6.45\n",
      "Book Value: 23.151\n",
      "Short Ratio: 1.59\n"
     ]
    }
   ],
   "source": [
    "print('Price to Book:', tesla.info['priceToBook'])\n",
    "print('Peg Ratio:', tesla.info['pegRatio'])\n",
    "print('Book Value:', tesla.info['bookValue'])\n",
    "print('Short Ratio:', tesla.info['shortRatio'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "tesladf = tesla.history(period='1y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Dividends</th>\n",
       "      <th>Stock Splits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-02-25</th>\n",
       "      <td>726.15</td>\n",
       "      <td>737.21</td>\n",
       "      <td>670.58</td>\n",
       "      <td>682.22</td>\n",
       "      <td>39023900</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-02-26</th>\n",
       "      <td>700.00</td>\n",
       "      <td>706.70</td>\n",
       "      <td>659.51</td>\n",
       "      <td>675.50</td>\n",
       "      <td>41011300</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-01</th>\n",
       "      <td>690.11</td>\n",
       "      <td>719.00</td>\n",
       "      <td>685.05</td>\n",
       "      <td>718.43</td>\n",
       "      <td>27009700</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-02</th>\n",
       "      <td>718.28</td>\n",
       "      <td>721.11</td>\n",
       "      <td>685.00</td>\n",
       "      <td>686.44</td>\n",
       "      <td>23617600</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-03</th>\n",
       "      <td>687.99</td>\n",
       "      <td>700.70</td>\n",
       "      <td>651.71</td>\n",
       "      <td>653.20</td>\n",
       "      <td>29957200</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-04</th>\n",
       "      <td>655.80</td>\n",
       "      <td>873.94</td>\n",
       "      <td>600.00</td>\n",
       "      <td>621.44</td>\n",
       "      <td>65448500</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-05</th>\n",
       "      <td>626.06</td>\n",
       "      <td>627.84</td>\n",
       "      <td>539.49</td>\n",
       "      <td>597.95</td>\n",
       "      <td>89300300</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-08</th>\n",
       "      <td>600.55</td>\n",
       "      <td>620.13</td>\n",
       "      <td>558.79</td>\n",
       "      <td>563.00</td>\n",
       "      <td>51497000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-09</th>\n",
       "      <td>608.18</td>\n",
       "      <td>678.09</td>\n",
       "      <td>595.21</td>\n",
       "      <td>673.58</td>\n",
       "      <td>67028000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-10</th>\n",
       "      <td>700.30</td>\n",
       "      <td>717.85</td>\n",
       "      <td>655.06</td>\n",
       "      <td>664.79</td>\n",
       "      <td>48441696</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open    High     Low   Close    Volume  Dividends  Stock Splits\n",
       "Date                                                                         \n",
       "2021-02-25  726.15  737.21  670.58  682.22  39023900          0           0.0\n",
       "2021-02-26  700.00  706.70  659.51  675.50  41011300          0           0.0\n",
       "2021-03-01  690.11  719.00  685.05  718.43  27009700          0           0.0\n",
       "2021-03-02  718.28  721.11  685.00  686.44  23617600          0           0.0\n",
       "2021-03-03  687.99  700.70  651.71  653.20  29957200          0           0.0\n",
       "2021-03-04  655.80  873.94  600.00  621.44  65448500          0           0.0\n",
       "2021-03-05  626.06  627.84  539.49  597.95  89300300          0           0.0\n",
       "2021-03-08  600.55  620.13  558.79  563.00  51497000          0           0.0\n",
       "2021-03-09  608.18  678.09  595.21  673.58  67028000          0           0.0\n",
       "2021-03-10  700.30  717.85  655.06  664.79  48441696          0           0.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesladf.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Dividends</th>\n",
       "      <th>Stock Splits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>253.000000</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>253.000000</td>\n",
       "      <td>2.530000e+02</td>\n",
       "      <td>253.0</td>\n",
       "      <td>253.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>408.004901</td>\n",
       "      <td>419.245020</td>\n",
       "      <td>396.065138</td>\n",
       "      <td>408.222885</td>\n",
       "      <td>6.237002e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.019763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>235.505547</td>\n",
       "      <td>241.247398</td>\n",
       "      <td>229.742609</td>\n",
       "      <td>235.557768</td>\n",
       "      <td>3.309301e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.314347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>74.940000</td>\n",
       "      <td>80.970000</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>72.240000</td>\n",
       "      <td>1.515770e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.800000</td>\n",
       "      <td>190.890000</td>\n",
       "      <td>181.830000</td>\n",
       "      <td>188.130000</td>\n",
       "      <td>3.676700e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>406.900000</td>\n",
       "      <td>412.530000</td>\n",
       "      <td>392.300000</td>\n",
       "      <td>407.000000</td>\n",
       "      <td>5.630970e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>600.550000</td>\n",
       "      <td>620.130000</td>\n",
       "      <td>578.450000</td>\n",
       "      <td>597.950000</td>\n",
       "      <td>8.183900e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.380000</td>\n",
       "      <td>900.400000</td>\n",
       "      <td>871.600000</td>\n",
       "      <td>883.090000</td>\n",
       "      <td>2.221262e+08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open        High         Low       Close        Volume  \\\n",
       "count  253.000000  253.000000  253.000000  253.000000  2.530000e+02   \n",
       "mean   408.004901  419.245020  396.065138  408.222885  6.237002e+07   \n",
       "std    235.505547  241.247398  229.742609  235.557768  3.309301e+07   \n",
       "min     74.940000   80.970000   70.100000   72.240000  1.515770e+07   \n",
       "25%    183.800000  190.890000  181.830000  188.130000  3.676700e+07   \n",
       "50%    406.900000  412.530000  392.300000  407.000000  5.630970e+07   \n",
       "75%    600.550000  620.130000  578.450000  597.950000  8.183900e+07   \n",
       "max    891.380000  900.400000  871.600000  883.090000  2.221262e+08   \n",
       "\n",
       "       Dividends  Stock Splits  \n",
       "count      253.0    253.000000  \n",
       "mean         0.0      0.019763  \n",
       "std          0.0      0.314347  \n",
       "min          0.0      0.000000  \n",
       "25%          0.0      0.000000  \n",
       "50%          0.0      0.000000  \n",
       "75%          0.0      0.000000  \n",
       "max          0.0      5.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tesladf.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,10))\n",
    "plt.plot(tesladf.index, tesladf.Close, c='navy')\n",
    "plt.legend(['Tesla'], loc='upper left')\n",
    "plt.title('Tesla Stock Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
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  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
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   "window_display": false
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 },
 "nbformat": 4,
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}