Stock Market Data And Analysis In Python – Part V

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

Using Quandl to get Stock Market Data (Optional)

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

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 as shown below.

!pip install quandl

Install quandl.py hosted with ❤ by GitHub

You need to get your own API Key from quandl to get the stock market data using the below code.

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 method takes this stock market data as input and returns the open, high, low, close, volume, adjusted values and other information.

# Import quandl package
import quandl

# To get your API key, sign up for a free Quandl account.
# Then, you can find your API key on Quandl account settings page.
QUANDL_API_KEY = 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY'

# This is to prompt you to change the Quandl Key
if QUANDL_API_KEY == 'REPLACE-THIS-TEXT-WITH-A-REAL-API-KEY':
    raise Exception("Please provide a valid Quandl API key!")
 
# Set the start and end date
start_date = '1990-01-01'
end_date = '2018-03-01'

# Set the ticker name
ticker = 'AMZN'

# Feth the data
data = quandl.get('WIKI/'+ticker, 
                  start_date=start_date, 
                  end_date=end_date, 
                  api_key=QUANDL_API_KEY)

# Print the first 5 rows of the dataframe
data.head()

get_data_quandl.py hosted with ❤ by GitHub

Date	Open	High	Low	Close	Volume	Ex-Dividend	Split Ratio	Adj. Open	Adj. High	Adj. Low	Adj. Close	Adj. Volume
1997-05-16	22.38	23.75	20.50	20.75	1225000.0	0.0	1.0	1.865000	1.979167	1.708333	1.729167	14700000.0
1997-05-19	20.50	21.25	19.50	20.50	508900.0	0.0	1.0	1.708333	1.770833	1.625000	1.708333	6106800.0
1997-05-20	20.75	21.00	19.63	19.63	455600.0	0.0	1.0	1.729167	1.750000	1.635833	1.635833	5467200.0
1997-05-21	19.25	19.75	16.50	17.13	1571100.0	0.0	1.0	1.604167	1.645833	1.375000	1.427500	18853200.0
1997-05-22	17.25	17.38	15.75	16.75	981400.0	0.0	1.0	1.437500	1.448333	1.312500	1.395833	11776800.0

To learn more about how you can use Quandl, check out this article:

• How to Get Historical Market Data Through Python API

Stay tuned for next installment in which Ishan Shah will demonstrate in details how to use yfinance to get fundamental data.

See https://blog.quantinsti.com/stock-market-data-analysis-python/ for additional insight on this topic.

Past performance is not indicative of future results.

Any stock, options or futures symbols displayed are for illustrative purposes only and are not intended to portray recommendations.