├── requirements.txt
├── README.md
├── data
    ├── yahoo.py
    ├── iexcloud.py
    └── alpaca.py
└── chart.py


/requirements.txt:
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1 | plotly
2 | pandas
3 | requests
4 | yfinance


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/README.md:
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 1 | # Stock Historical Data Examples
 2 | 
 3 | * IEXCloud
 4 | * Yahoo
 5 | * Alpaca / Polygon
 6 | 
 7 | # Charting
 8 | 
 9 | * Plotly Candlestick Chart
10 | 


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/data/yahoo.py:
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 1 | import yfinance as yf
 2 | 
 3 | work = yf.Ticker("WORK")
 4 | 
 5 | # get historical market data
 6 | history = work.history(period="max")
 7 | 
 8 | # show pandas dataframe
 9 | print(history)
10 | 
11 | # show csv
12 | print(history.to_csv())


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/data/iexcloud.py:
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 1 | import requests, json, csv
 2 | 
 3 | TOKEN  = "YOUR IEX CLOUD KEY"
 4 | SYMBOL = "PTON"
 5 | 
 6 | r = requests.get("https://sandbox.iexapis.com/stable/stock/{}/chart/max?token={}".format(SYMBOL, TOKEN))
 7 | 
 8 | items = json.loads(r.content)
 9 | 
10 | csv_file = open('stock.csv', 'w')
11 | csv_writer = csv.writer(csv_file)
12 | 
13 | csv_writer.writerow(['date', 'open', 'high', 'low', 'close'])
14 | 
15 | for item in items:
16 |     csv_writer.writerow([item['date'], item['open'], item['high'], item['low'], item['close']])
17 | 
18 | csv_file.close()


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/data/alpaca.py:
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 1 | import requests, json, csv
 2 | from datetime import datetime
 3 | 
 4 | ALPACA_API_KEY = "YOUR APLACA KEY"
 5 | TICKER = 'AAPL'
 6 | START_DATE = '2019-01-01'
 7 | END_DATE = '2019-12-27'
 8 | POLYGON_URL = 'https://api.polygon.io/v2/aggs/ticker/{}/range/1/day/{}/{}?apiKey={}'
 9 | 
10 | r = requests.get(POLYGON_URL.format(TICKER, START_DATE, END_DATE, ALPACA_API_KEY))
11 | 
12 | data = json.loads(r.content)
13 | 
14 | print("date,open,high,low,close")
15 | 
16 | for item in data['results']:
17 |     formatted_date = datetime.fromtimestamp(item['t'] / 1000)
18 |     date_only = formatted_date.strftime('%Y-%m-%d')
19 | 
20 |     print("{},{},{},{},{}".format(date_only, item['o'], item['h'], item['l'], item['c']))


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/chart.py:
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 1 | import plotly.graph_objects as go
 2 | import pandas
 3 | from datetime import datetime
 4 | 
 5 | df = pandas.read_csv('aapl.csv')
 6 | 
 7 | candlestick = go.Candlestick(x=df['date'], 
 8 |                 open=df['open'],
 9 |                 high=df['high'],
10 |                 low=df['low'],
11 |                 close=df['close'])
12 | 
13 | fig = go.Figure(data=[candlestick])
14 | 
15 | # ignore weekends
16 | fig.layout.xaxis.type = 'category'
17 | 
18 | shapes = [
19 |     dict(x0='2019-01-02', x1='2019-01-02', y0=0, y1=1, xref='x', yref='paper'),
20 |     dict(x0='2019-05-05', x1='2019-05-05', y0=0, y1=1, xref='x', yref='paper'),
21 |     dict(x0='2019-07-30', x1='2019-07-30', y0=0, y1=1, xref='x', yref='paper'),
22 |     dict(x0='2019-10-30', x1='2019-10-30', y0=0, y1=1, xref='x', yref='paper'),
23 | ]
24 | 
25 | annotations=[
26 |     dict(x='2019-01-03', y=0.01, xref='x', yref='paper', showarrow=False, xanchor='left', text='Apple Cuts Guidance'),
27 |     dict(x='2019-05-05', y=0.5, xref='x', yref='paper', showarrow=False, xanchor='left', text='Trump Tariff Tweet'),
28 |     dict(x='2019-07-30', y=0.3, xref='x', yref='paper', showarrow=False, xanchor='left', text='Trump Tweets "China is doing very badly"'),
29 |     dict(x='2019-10-30', y=0.3, xref='x', yref='paper', showarrow=False, xanchor='left', text='Apple Q4 Earnings'),
30 | ]
31 | 
32 | fig.update_layout(title='AAPL', annotations=annotations, shapes=shapes)
33 | 
34 | fig.show()
35 | 
36 | fig.write_html('aapl.html', auto_open=False)
37 | 


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