{"id":103538,"date":"2021-09-17T13:35:30","date_gmt":"2021-09-17T17:35:30","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=103538"},"modified":"2022-11-21T09:48:03","modified_gmt":"2022-11-21T14:48:03","slug":"stock-market-data-and-analysis-in-python-part-v","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/stock-market-data-and-analysis-in-python-part-v\/","title":{"rendered":"Stock Market Data And Analysis In Python \u2013 Part V"},"content":{"rendered":"\n

See Part I<\/a> for instructions on how to get pandas_datareader<\/code> or yfinance<\/code> module to retrieve the data, and Part II<\/a> to learn how to get stock market data for different geographies. In Part III<\/a> and Part IV<\/a>, review the tutorial on how to analyse the stock market data for all the stocks which make up the S&P 500.<\/em><\/p>\n\n\n\n

Using Quandl to get Stock Market Data (Optional)<\/strong><\/p>\n\n\n\n

Quandl has many data sources to get different types of stock market data. However, some are free and some are paid. Wiki<\/strong> is the free data source of Quandl to get the data of the end of the day prices of 3000+ US equities<\/strong>. It is curated by Quandl community and also provides information about the dividends and split.<\/p>\n\n\n\n

Quandl also provides paid data source of minute and lower frequencies.

To get the stock market data, you need to first install the quandl module if it is not already installed using the pip command<\/strong> as shown below.<\/p>\n\n\n\n

!pip install quandl<\/code><\/pre>\n\n\n\n
Install quandl.py<\/a> hosted with \u2764 by GitHub<\/a><\/code><\/pre>\n\n\n\n
You need to get your own API Key from quandl to get the stock market data using the below code. <\/p>\n\n\n\n
After you get your key, assign the variable QUANDL_API_KEY with that key. Then set the start date, end date and the ticker of the asset whose stock market data you want to fetch.

The quandl get<\/code> method takes this stock market data as input and returns the open, high, low, close, volume, adjusted values and other information.<\/p>\n\n\n\n
# Import quandl package\nimport quandl\n\n# To get your API key, sign up for a free Quandl account.\n# Then, you can find your API key on Quandl account settings page.\nQUANDL_API_KEY = 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY'\n\n# This is to prompt you to change the Quandl Key\nif QUANDL_API_KEY == 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY':\n    raise Exception(\"Please provide a valid Quandl API key!\")\n \n# Set the start and end date\nstart_date = '1990-01-01'\nend_date = '2018-03-01'\n\n# Set the ticker name\nticker = 'AMZN'\n\n# Feth the data\ndata = quandl.get('WIKI\/'+ticker, \n                  start_date=start_date, \n                  end_date=end_date, \n                  api_key=QUANDL_API_KEY)\n\n# Print the first 5 rows of the dataframe\ndata.head()<\/code><\/pre>\n\n\n\n
get_data_quandl.py<\/a> hosted with \u2764 by GitHub<\/a><\/code><\/pre>\n\n\n\n
Date<\/th>Open<\/th>High<\/th>Low<\/th>Close<\/th>Volume<\/th>Ex-Dividend<\/th>Split Ratio<\/th>Adj. Open<\/th>Adj. High<\/th>Adj. Low<\/th>Adj. Close<\/th>Adj. Volume<\/th><\/tr><\/thead>
1997-05-16<\/th>22.38<\/td>23.75<\/td>20.50<\/td>20.75<\/td>1225000.0<\/td>0.0<\/td>1.0<\/td>1.865000<\/td>1.979167<\/td>1.708333<\/td>1.729167<\/td>14700000.0<\/td><\/tr>
1997-05-19<\/th>20.50<\/td>21.25<\/td>19.50<\/td>20.50<\/td>508900.0<\/td>0.0<\/td>1.0<\/td>1.708333<\/td>1.770833<\/td>1.625000<\/td>1.708333<\/td>6106800.0<\/td><\/tr>
1997-05-20<\/th>20.75<\/td>21.00<\/td>19.63<\/td>19.63<\/td>455600.0<\/td>0.0<\/td>1.0<\/td>1.729167<\/td>1.750000<\/td>1.635833<\/td>1.635833<\/td>5467200.0<\/td><\/tr>
1997-05-21<\/th>19.25<\/td>19.75<\/td>16.50<\/td>17.13<\/td>1571100.0<\/td>0.0<\/td>1.0<\/td>1.604167<\/td>1.645833<\/td>1.375000<\/td>1.427500<\/td>18853200.0<\/td><\/tr>
1997-05-22<\/th>17.25<\/td>17.38<\/td>15.75<\/td>16.75<\/td>981400.0<\/td>0.0<\/td>1.0<\/td>1.437500<\/td>1.448333<\/td>1.312500<\/td>1.395833<\/td>11776800.0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
To learn more about how you can use Quandl, check out this article:<\/p>\n\n\n\n