Finhub.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": "### Finhub API - News Data",
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    "execution_start": 1641153523575,
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   },
   "source": "import os\nimport requests\nfrom datetime import datetime\nfrom dateutil.relativedelta import relativedelta\nfrom pathlib import Path\nimport json\nfrom decouple import config\nfrom langdetect import detect\nimport time\nimport sqlite3\nimport bs4 as bs",
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
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    "cell_id": "00001-80816cea-e5b6-4e4b-bfdd-221d83dcbb60",
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    "execution_millis": 7,
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   },
   "source": "import os\n# os.environ[\"FINHUB_KEY\"]",
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00004-3d473d2c-57db-4308-bb75-ddb0047b9d73",
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    "execution_start": 1641143262784,
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   "source": "def delta_date(start_date,end_date):\n    \"\"\"Function that returns the number of days between 2 dates \"\"\"\n\n    return abs((datetime.strptime(start_date, \"%Y-%m-%d\") - datetime.strptime(end_date, \"%Y-%m-%d\")).days)\n\ndef get_tickers():\n    \"\"\"Method that gets the stock symbols from companies listed in the S&P 500\n    Return\n    ------\n    `tickers` : list\n        S&P 500 company symbols\n    \"\"\"\n    resp = requests.get('http://en.wikipedia.org/wiki/List_of_S%26P_500_companies')\n    soup = bs.BeautifulSoup(resp.text, 'lxml')\n    table = soup.find_all('table')[0]  # Grab the first table\n\n    tickers = []\n    for row in table.findAll('tr')[1:]:\n        ticker = row.findAll('td')[0].text.strip('\\n')\n        tickers.append(ticker)\n\n    return tickers\n\nclass Init():\n    \"\"\"Class that initializes global value for the module. It also use general method to initialize value.\n     \"\"\"\n\n    def __init__(self):\n        \"\"\"Built-in method to inialize the global values for the module\n        Attributes\n        -----------\n        `self.start.date` : str\n            start date of the training period. Must be within the last year for the free version of FinHub. Format\n            must be \"YYYY-mm-dd\"\n        `self.end_date` : str\n            end date of the training period. Format must be \"YYYY-mm-dd\"\n        `self.ticker` : list\n            tickers on which we want to perform the test. Can be one ticker in form of a list as well as a list\n            of tickers like the s&p 500.\n        `self.db_name` : str\n            name of the sqlite3 database\n        `self.dir_path` : str\n            directory where the data are saved. It takes into account the `self.start_date` and `self.end_date`\n        `self.start_date_` : datetime object\n            same thing as `start_date` but as a datetime object\n        `self.end_date_` : datetime object\n            same thing as `start_date` but as a datetime object\n        \"\"\"\n\n        #initialize value here\n        self.start_date = \"2021-12-01\"\n        self.end_date = \"2021-12-31\"\n        self.tickers = ['AMZN','MSFT','GS','JPM','MS']\n\n        self.db_name = 'financial_data_test'\n        self.dir_path = os.path.dirname(os.path.realpath('/work/NewsData')) + '/output/' + self.start_date + '_' + \\\n                        self.end_date + '/'\n        Path(self.dir_path).mkdir(parents=True, exist_ok=True) #create new path if it doesn't exist\n        self.start_date_ = datetime.strptime(self.start_date, \"%Y-%m-%d\")  #datetime object\n        self.end_date_ = datetime.strptime(self.end_date, \"%Y-%m-%d\")    #datetime object\n        self.delta_date = abs((self.end_date_ - self.start_date_).days) #number of days between 2 dates\n\n\n        try:\n            self.start_date_ > self.end_date_\n        except:\n            print(\"'start_date' is after 'end_date'\")\n\n        t = (datetime.now()- relativedelta(years=1))\n        d= datetime.strptime(self.start_date, \"%Y-%m-%d\")\n\n        if (datetime.strptime(self.start_date, \"%Y-%m-%d\") <= (datetime.now()- relativedelta(years=1))) :\n            raise Exception(\"'start_date' is older than 1 year. It doesn't work with the free version of FinHub\")\n\nclass FinnHub():\n    \"\"\"Class to make API calls to FinnHub\"\"\"\n\n    def __init__(self,start_date,end_date,start_date_,end_date_,tickers,dir_path,db_name):\n        \"\"\" Class constructor\n        Parameters\n        ----------\n        `start_date` : str\n            Start date of the request. Must be within 1 year from now for must request\n            with the free version of FinHub\n        `end_date` : str\n            End date of the request.\n        `start_date_` : datetime object\n            Same thing as `start_date` but as a datetime object\n        `end_date_` : datetime object\n             Same thing as `start_date` but as a datetime object\n        `ticker` : str\n            Ticker symbol\n        `db_name` : str\n            Name of the sqlite database\n        `dir_path` : str\n            Directory  where our data will be stored\n        Attributes\n        ----------\n        `self.max_call` : int\n            maximum api calls per minute for the finhub API\n        `self.time_sleep` : int\n            seconds to sleep before making a new API call. Default is 60 seconds as the maximum number of API calls is\n            per minute\n        `self.nb_request` : int\n            nb of request made so far. Set to 0 in constructor `__init__` as we may loop through ticker\n            and want to avoid the variable to reset to 0 when exiting the wrapper `iterate_day()` (which could generate\n            an error)\n        `self.finhub_key` : str\n            finhub unique API key. Get yours here : https://finnhub.io/\n        `self.db_name : str\n            default file name for the sql database\n        \"\"\"\n\n        #Initialize attributes values here\n        self.max_call = 60\n        self.time_sleep = 60\n        self.nb_request = 0\n        self.finhub_key = config('FINHUB_KEY')\n        self.news_header = ['category', 'datetime','headline','id','image','related','source','summary','url']\n        self.start_date = start_date\n        self.end_date = end_date\n        self.tickers = tickers\n        self.ticker_request = tickers #different value because ticker like 'ALL' (All State) can generate error in SQLite\n                                    #database\n        self.dir_path = dir_path\n        self.db_name = db_name\n        self.js_data = []\n\n        self.start_date_ = start_date_ #datetime object\n        self.end_date_ = end_date_ #datetime object\n\n        #call the methods to access historical financial headlines\n        #tickers = get_tickers() #get_tickers is to get tickers from all the companies listedin the s&p 500\n\n        for ticker_ in self.tickers:\n            self.js_data.clear()\n            self.ticker = ticker_ + '_'\n            self.ticker_request = ticker_\n            self.req_new()\n            self.create_table()\n            self.clean_table()\n            self.lang_review()\n\n    def init_sql(func):\n        \"\"\" Decorator that open the sql database, save it and close it. The operation are between the opening and\n        saving of the file\"\"\"\n\n        def wrapper_(self):\n            conn_ = sqlite3.connect(self.dir_path + self.db_name + '.db')\n            c = conn_.cursor()\n            func(self,conn_,c)\n            conn_.commit()\n            conn_.close()\n        return wrapper_\n\n    @init_sql\n    def clean_table(self,conn_,c):\n        \"\"\"Method that clean the database using sqlite3\n        Parameters\n        ----------\n        `conn_` : database object\n            Connection object that represents the database\n        `c` : database object\n            Cursor object\n        \"\"\"\n\n        #remove NULL entry (row) from headline column\n        c.execute(f\" DELETE FROM {self.ticker} WHERE {self.news_header[2]} IS NULL OR \"\n                  f\"trim({self.news_header[2]}) = '';\")\n        # remove NULL value from datetime\n        c.execute(f\" DELETE FROM {self.ticker} WHERE {self.news_header[1]} IS NULL OR \"\n                  f\"trim({self.news_header[1]}) = '';\")\n\n        #removes duplicate entries (row)\n        c.execute(f\" DELETE FROM {self.ticker} WHERE rowid NOT IN (select MIN(rowid)\"\n                  f\"FROM {self.ticker} GROUP BY {self.news_header[2]})\")\n\n    @init_sql\n    def create_table(self,conn_,c):\n        \"\"\" Method that creates a table in SQLite database. It creates the table  in `self.dir_path` and write\n        the data in it\n        Parameters\n        ----------\n        `conn_` : database object\n            Connection object that represents the database\n        `c` : database object\n            Cursor object\n        \"\"\"\n\n        #create table if it does not exist\n        c.execute(f'drop table if exists {self.ticker}')\n        conn_.commit()\n        c.execute(f\"CREATE TABLE IF NOT EXISTS {self.ticker} ({self.news_header[0]})\")\n        conn_.commit()\n\n        #add columns to the table if the columns don't exist\n        for header_ in range(len(self.news_header)-1):\n            c.execute(f\"alter table {self.ticker} add column '%s' \" % self.news_header[header_+1])\n            conn_.commit()\n\n        iteration = 0\n        for data_ in self.js_data:\n            iteration +=1\n            try :\n                c.execute(f'insert into {self.ticker} values (?,?,?,?,?,?,?,?,?)',[data_[self.news_header[0]],\n                          data_[self.news_header[1]],data_[self.news_header[2]],data_[self.news_header[3]],\n                        data_[self.news_header[4]],data_[self.news_header[5]],data_[self.news_header[6]],\n                          data_[self.news_header[7]],data_[self.news_header[8]]])\n            except:\n                print(f\"Error at the {iteration}th ieration\")\n\n            conn_.commit()\n\n    def iterate_day(func):\n        \"\"\" Decorator that makes the API call on FinHub each days between the `self.start_date`\n        and `self.end_date` \"\"\"\n\n        def wrapper_(self):\n            delta_date_ = delta_date(self.start_date,self.end_date)\n            date_ = self.start_date\n            date_obj = self.start_date_\n\n            for item in range(delta_date_ + 1):\n                self.nb_request +=1\n                func(self,date_)\n                date_obj = date_obj + relativedelta(days=1)\n                date_  = date_obj.strftime(\"%Y-%m-%d\")\n                if self.nb_request == (self.max_call-1):\n                    time.sleep(self.time_sleep)\n                    self.nb_request=0\n        return wrapper_\n\n    @init_sql\n    def lang_review(self,conn_,c):\n        \"\"\" Methods that delete non-english entries based on the 'headline' column in a SQLlite3 db\n        Parameters\n        ----------\n        `conn_` : database object\n            Connection object that represents the database\n        `c` : database object\n            Cursor object\n        \"\"\"\n\n        list_ = []\n        c.execute(f\" SELECT {self.news_header[2]} FROM {self.ticker}\")\n\n        #check for non-english headlines\n        for item_ in c:\n            if detect(item_[0]) != 'en':\n                list_.append(item_[0])\n\n        #delete non-english entries (rows)\n            query = f\"DELETE FROM {self.ticker} where {self.news_header[2]} in ({','.join(['?']*len(list_))})\"\n            c.execute(query, list_)\n\n    @iterate_day\n    def req_new(self,date_):\n        \"\"\" Method that makes news request(s) to the Finnhub API\"\"\"\n\n        request_ = requests.get('https://finnhub.io/api/v1/company-news?symbol=' + self.ticker_request + '&from=' +\n                                date_ + '&to=' + date_ + '&token=' + self.finhub_key)\n        self.js_data += request_.json()\n\n\ninit_ = Init()\n\nfinhub = FinnHub(start_date=init_.start_date, end_date=init_.end_date,start_date_=init_.start_date_ ,\n                end_date_ =init_.end_date_, tickers=init_.tickers, dir_path =init_.dir_path,db_name=init_.db_name)",
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": "Finhub API gives a database file(.db) :: we convert news data for every stock to csv file in NEWS_Finhub file.",
   "metadata": {
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    "is_collapsed": false,
    "cell_id": "00004-613ca9e2-6fcb-46e4-aeb8-438242494776",
    "deepnote_cell_type": "text-cell-p"
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  {
   "cell_type": "code",
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    "source_hash": "7a6a0348",
    "execution_start": 1641143496750,
    "execution_millis": 20,
    "deepnote_cell_type": "code"
   },
   "source": "import sqlite3\n\n# creating file path\ndbfile = '/work/output/2021-12-01_2021-12-31/financial_data_test.db'\n# Create a SQL connection to our SQLite database\ncon = sqlite3.connect(dbfile)\n\n# creating cursor\ncur = con.cursor()\n\n# reading all table names\ntable_list = [a for a in cur.execute(\"SELECT name FROM sqlite_master WHERE type = 'table'\")]\n# here is you table list\nprint(table_list)\n\n# Be sure to close the connection\ncon.close()",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "[('AMZN_',), ('MSFT_',), ('GS_',), ('JPM_',), ('MS_',)]\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00006-3764fde1-3cbf-44f9-8a09-eaeedd60e806",
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    "source_hash": "77f00651",
    "execution_start": 1641143519202,
    "execution_millis": 13,
    "deepnote_output_heights": [
     21.1875
    ],
    "deepnote_cell_type": "code"
   },
   "source": "c.execute('SELECT * FROM GS_')\nresults = c.fetchall()\nprint(len(results))",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "327\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00007-214f2ab0-2d92-4c65-82a0-24572fe7b23b",
    "deepnote_to_be_reexecuted": false,
    "source_hash": "6e12bf8a",
    "execution_start": 1641143520921,
    "execution_millis": 15,
    "deepnote_cell_type": "code"
   },
   "source": "c.execute('SELECT * FROM JPM_')\nresults = c.fetchall()\nprint(len(results))",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "382\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00008-d018133f-149a-4653-8ffa-c20b45da7e21",
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    "source_hash": "77126961",
    "execution_start": 1641143522235,
    "execution_millis": 8,
    "deepnote_cell_type": "code"
   },
   "source": "c.execute('SELECT * FROM MS_')\nresults = c.fetchall()\nprint(len(results))",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "242\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00009-8b2745c2-1f16-48e4-958b-6895f909f1c9",
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    "source_hash": "e052423a",
    "execution_start": 1641143524229,
    "execution_millis": 20,
    "deepnote_cell_type": "code"
   },
   "source": "c.execute('SELECT * FROM MSFT_')\nresults = c.fetchall()\nprint(len(results))",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "976\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
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    "source_hash": "47f5ba92",
    "execution_start": 1641143525949,
    "execution_millis": 18,
    "deepnote_cell_type": "code"
   },
   "source": "c.execute('SELECT * FROM AMZN_')\nresults = c.fetchall()\nprint(len(results))",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "1283\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
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    "execution_start": 1641143529519,
    "execution_millis": 2,
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   "source": "c.close()",
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    "cell_id": "00012-57937b27-aeff-4411-a3f3-cd1b6b0b4cc1",
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   "source": "import sqlite3\nfrom sqlite3 import Error\n\nimport pandas as pd\ndataPath = '/work/output/2021-12-01_2021-12-31/financial_data_test.db'\n# create database connection\nconn = sqlite3.connect(dataPath)\n\ndef create_connection(db_file):\n              try:\n                   conn = sqlite3.connect(db_file)\n                   return conn\n              except Error as e:\n                    print(e)\n\n              return None\n# create a function for reading & writing the Wifi table\n\ndef read_write_wifi_tbl_to_csv(conn):\n            cur = conn.cursor()\n            query='select * from JPM_'\n            data=pd.read_sql(query,conn)\n            data.to_csv('news_jpmT.csv')\n\ndef main():\n    # create a database connection\n    conn = create_connection(dataPath)\n    with conn:\n      print(\"1. Query and writing to table\")\n      read_write_wifi_tbl_to_csv(conn)\n\nif __name__ == '__main__':\n                main()",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "text": "1. Query and writing to table\n",
     "output_type": "stream",
     "data": {}
    }
   ]
  },
  {
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    "source_hash": "a1d833fc",
    "execution_start": 1641143690989,
    "execution_millis": 3,
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   },
   "source": "conn.close()",
   "execution_count": null,
   "outputs": []
  },
  {
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    "source_hash": "9bebda8f",
    "execution_start": 1641143696710,
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    "deepnote_cell_type": "code"
   },
   "source": "df1 = pd.read_csv('news_gsT.csv')\ndf1.tail()",
   "execution_count": null,
   "outputs": [
    {
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         "summary": "ESG investing is on the rise. Goldman Sachs names the buy-rated \"under-owned\" stocks where ESG perf…",
         "url": "https://finnhub.io/api/news?id=056baaac1143097af91956935674ace195afb05503218b7cf4215881bc701b65",
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        {
         "Unnamed: 0": 1,
         "category": "company",
         "datetime": 1638377820,
         "headline": "Goldman Sachs Group Inc. stock underperforms Wednesday when compared to competitors",
         "id": 76744264,
         "image": "https://images.mktw.net/im-220105/social",
         "related": "GS",
         "source": "MarketWatch",
         "summary": "Shares of Goldman Sachs Group Inc. slid 0.66% to $376.48 Wednesday, on what proved to be an all-aro…",
         "url": "https://finnhub.io/api/news?id=586234ba29c97d06ec5a72cb8b5182949a01d16a7c40e19b0d5cdc83ba2abfa2",
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         "category": "company",
         "datetime": 1638374700,
         "headline": "Why BioXcel Therapeutics Stock Is Slumping Today",
         "id": 75747160,
         "image": "https://www.nasdaq.com/sites/acquia.prod/files/2019-05/0902-Q19%20Total%20Markets%20photos%20and%20…",
         "related": "GS",
         "source": "Nasdaq",
         "summary": "What happened\nShares of BioXcel Therapeutics (NASDAQ: BTAI) were down by 11.6% as of 3:08 p.m. ET W…",
         "url": "https://finnhub.io/api/news?id=f9224a0592a3ab2cf1f10e89cf95e4a9a3de2c0e60659cd29624d9b8d2c535ff",
         "_deepnote_index_column": 2
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         "headline": "Is the Options Market Predicting a Spike in Goldman Sachs (GS) Stock?",
         "id": 75922377,
         "image": "https://s.yimg.com/uu/api/res/1.2/05k8WdMbUDL7ljYuvfGHiw--~B/aD00MDA7dz02MzU7YXBwaWQ9eXRhY2h5b24-/h…",
         "related": "GS",
         "source": "Yahoo",
         "summary": "Investors need to pay close attention to Goldman Sachs (GS) stock based on the movements in the opt…",
         "url": "https://finnhub.io/api/news?id=389388c1fda3b60699194713499e90c3276f04ae9e88bf4f66629160efa774a4",
         "_deepnote_index_column": 3
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         "Unnamed: 0": 4,
         "category": "company",
         "datetime": 1638354660,
         "headline": "Dow's nearly 400-point rally highlighted by gains for American Express, Goldman Sachs stocks",
         "id": 76715075,
         "image": "https://mw3.wsj.net/mw5/content/logos/mw_logo_social.png",
         "related": "GS",
         "source": "MarketWatch",
         "summary": "Buoyed by positive gains for shares of American Express and Goldman Sachs, the Dow Jones Industrial…",
         "url": "https://finnhub.io/api/news?id=99b0e4af4bb16b6e2b9770d187b8e432fd3cb47da490f7454cb341e46958a09a",
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      "text/plain": "   Unnamed: 0 category    datetime  \\\n0           0  company  1638389603   \n1           1  company  1638377820   \n2           2  company  1638374700   \n3           3  company  1638366001   \n4           4  company  1638354660   \n\n                                            headline        id  \\\n0  Goldman Sachs picks its favorite under-the-rad...  75844602   \n1  Goldman Sachs Group Inc. stock underperforms W...  76744264   \n2   Why BioXcel Therapeutics Stock Is Slumping Today  75747160   \n3  Is the Options Market Predicting a Spike in Go...  75922377   \n4  Dow's nearly 400-point rally highlighted by ga...  76715075   \n\n                                               image related       source  \\\n0  https://image.cnbcfm.com/api/v1/image/10388143...      GS         CNBC   \n1           https://images.mktw.net/im-220105/social      GS  MarketWatch   \n2  https://www.nasdaq.com/sites/acquia.prod/files...      GS       Nasdaq   \n3  https://s.yimg.com/uu/api/res/1.2/05k8WdMbUDL7...      GS        Yahoo   \n4  https://mw3.wsj.net/mw5/content/logos/mw_logo_...      GS  MarketWatch   \n\n                                             summary  \\\n0  ESG investing is on the rise. Goldman Sachs na...   \n1  Shares of Goldman Sachs Group Inc. slid 0.66% ...   \n2  What happened\\nShares of BioXcel Therapeutics ...   \n3  Investors need to pay close attention to Goldm...   \n4  Buoyed by positive gains for shares of America...   \n\n                                                 url  \n0  https://finnhub.io/api/news?id=056baaac1143097...  \n1  https://finnhub.io/api/news?id=586234ba29c97d0...  \n2  https://finnhub.io/api/news?id=f9224a0592a3ab2...  \n3  https://finnhub.io/api/news?id=389388c1fda3b60...  \n4  https://finnhub.io/api/news?id=99b0e4af4bb16b6...  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unnamed: 0</th>\n      <th>category</th>\n      <th>datetime</th>\n      <th>headline</th>\n      <th>id</th>\n      <th>image</th>\n      <th>related</th>\n      <th>source</th>\n      <th>summary</th>\n      <th>url</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>company</td>\n      <td>1638389603</td>\n      <td>Goldman Sachs picks its favorite under-the-rad...</td>\n      <td>75844602</td>\n      <td>https://image.cnbcfm.com/api/v1/image/10388143...</td>\n      <td>GS</td>\n      <td>CNBC</td>\n      <td>ESG investing is on the rise. Goldman Sachs na...</td>\n      <td>https://finnhub.io/api/news?id=056baaac1143097...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>company</td>\n      <td>1638377820</td>\n      <td>Goldman Sachs Group Inc. stock underperforms W...</td>\n      <td>76744264</td>\n      <td>https://images.mktw.net/im-220105/social</td>\n      <td>GS</td>\n      <td>MarketWatch</td>\n      <td>Shares of Goldman Sachs Group Inc. slid 0.66% ...</td>\n      <td>https://finnhub.io/api/news?id=586234ba29c97d0...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>company</td>\n      <td>1638374700</td>\n      <td>Why BioXcel Therapeutics Stock Is Slumping Today</td>\n      <td>75747160</td>\n      <td>https://www.nasdaq.com/sites/acquia.prod/files...</td>\n      <td>GS</td>\n      <td>Nasdaq</td>\n      <td>What happened\\nShares of BioXcel Therapeutics ...</td>\n      <td>https://finnhub.io/api/news?id=f9224a0592a3ab2...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>company</td>\n      <td>1638366001</td>\n      <td>Is the Options Market Predicting a Spike in Go...</td>\n      <td>75922377</td>\n      <td>https://s.yimg.com/uu/api/res/1.2/05k8WdMbUDL7...</td>\n      <td>GS</td>\n      <td>Yahoo</td>\n      <td>Investors need to pay close attention to Goldm...</td>\n      <td>https://finnhub.io/api/news?id=389388c1fda3b60...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>company</td>\n      <td>1638354660</td>\n      <td>Dow's nearly 400-point rally highlighted by ga...</td>\n      <td>76715075</td>\n      <td>https://mw3.wsj.net/mw5/content/logos/mw_logo_...</td>\n      <td>GS</td>\n      <td>MarketWatch</td>\n      <td>Buoyed by positive gains for shares of America...</td>\n      <td>https://finnhub.io/api/news?id=99b0e4af4bb16b6...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
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