8.1. Obtaining Historical Stock Data

Keywords: stock price data

The purpose of this notebook is to download historical trading data for a selected group of the stocks from Alpha Vantage for use with other notebooks. Use of this notebook requires you so enter your personal Alpha Vantage api key into a file data/api_key.txt. The trading data is stored as individual .csv files in a designated directory. Subsequent notebooks read and consolidate that data into a singe file.

You only need to run this notebook if you wish to analyze a different set of stocks, if you wish to update data for the existing set.

8.1.1. Imports

import os
import pandas as pd
import requests
import time

8.1.2. Select Stocks to Download

djia = ['AXP','BA','CAT','CSCO','CVX','DD','DIS','GE', \
        'GS','HD','IBM','INTC','JNJ','JPM','KO','MCD', \
        'MMM','MRK','MSFT','NKE','PFE','PG','T','TRV', \
        'UNH','UTX','V','VZ','WMT','XOM']

favs = ['AAPL']

stocks = favs + djia

data_dir = os.path.join('data', 'stocks')
os.makedirs(data_dir, exist_ok=True)

8.1.3. Alpha Vantage

The following cells retrieve a history of daily trading data for a specified set of stock ticker symbols. These functions use the free Alpha Vantage data service. The free service tier provides up to 5 queries per minute.

The service requires an personal api key which can be claimed here in just a few seconds. Place the key as a string in a file data/api_key.txt in the data directory as this notebook (note: api_key.txt is not distributed with the github repository). The function api_key() returns the key stored in api_key.txt.

def api_key():
    "Read api_key.txt and return api_key"
    try:
        with open('data/api_key.txt') as fp:
            line = fp.readline()
    except:
        raise RuntimeError('Error while attempting to read data/api_key.txt')
    return line.strip()

The function alphavantage(s) returns a pandas dataframe holding historical trading data for a stocker ticker symbol specified by s.

import os
import requests
import pandas as pd

def alphavantage(symbol=None):
    if symbol is None: 
        raise ValueError("No symbol has been provided")
    payload = {
        "function": "TIME_SERIES_DAILY_ADJUSTED",
        "symbol": symbol,
        "outputsize": "full",
        "datatype": "json",
        "apikey": api_key(), 
    }
    api_url = "https://www.alphavantage.co/query"
    try:
        response = requests.get(api_url, params=payload)
    except:
        raise ValueError("No response using api key: " + api_key)
    data = response.json()
    k = list(data.keys())
    metadata = data[k[0]]
    timeseries = data[k[1]]
    S = pd.DataFrame.from_dict(timeseries).T
    S = S.apply(pd.to_numeric)
    S.columns = [h.lstrip('12345678. ') for h in S.columns]
    return S

alphavantage('AAPL').head()

	open	high	low	close	adjusted close	volume	dividend amount	split coefficient
2022-11-07	137.110	139.145	135.671	138.92	138.920000	83374628	0.00	1.0
2022-11-04	142.090	142.670	134.380	138.38	138.380000	140814796	0.23	1.0
2022-11-03	142.060	142.800	138.750	138.88	138.649552	97918516	0.00	1.0
2022-11-02	148.945	152.170	145.000	145.03	144.789347	93604623	0.00	1.0
2022-11-01	155.080	155.450	149.130	150.65	150.400022	80379345	0.00	1.0

get_stock_data(symbols) retrieves trading data for a list of symbols and stores each in seperate file in the data directory. The file name is the ticker symbol with a .csv suffix.

def get_stock_data(symbols, service=alphavantage):
    if isinstance(symbols, str):
        symbols = [symbols]
    assert all(isinstance(s, str) for s in symbols)
    for s in symbols:
        print('downloading', s, end='')
        k = 5
        while k > 0:
            try:
                k -= 1
                S = service(s)
                S.to_csv(os.path.join(data_dir, s + '.csv'))
                print(' success')
                break
            except:
                print('.', end='')
                time.sleep(12)
        if k < 0: print('fail')
            
get_stock_data(['AAPL'])

downloading AAPL success

8.1.4. Download selected ticker Symbols

get_stock_data(stocks)

downloading AAPL success
downloading AXP success
downloading BA success
downloading CAT.. success
downloading CSCO success
downloading CVX success
downloading DD success
downloading DIS success
downloading GE.... success
downloading GS success
downloading HD success
downloading IBM success
downloading INTC success
downloading JNJ.....downloading JPM success
downloading KO success
downloading MCD success
downloading MMM success
downloading MRK success
downloading MSFT.... success
downloading NKE success
downloading PFE success
downloading PG success
downloading T success
downloading TRV.....downloading UNH success
downloading UTX success
downloading V success
downloading VZ success
downloading WMT success
downloading XOM.... success