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| Deletions are marked like this. | Additions are marked like this. |
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| from pandas._libs.tslibs.timestamps import Timestamp | |
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| for k in d['Close'].iterkeys(): print (k) | # for k in d['Close'].iterkeys(): print (k) d['Close'][Timestamp('2019-11-22 00:00:00')] d['Close'][Timestamp('2020-02-10 00:00:00')] |
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== MSFT example == {{{#!highlight sh cd ~/Documents/ mkdir yfinance-test cd yfinance-test/ sudo apt install python3-venv python3 -m venv testVenv source testVenv/bin/activate pip install yfinance python3 test-msft.py }}} {{{#!highlight python import yfinance as yf msft = yf.Ticker("MSFT") historyDataFrame = msft.history(period="5d") print("Available columns") for colname in historyDataFrame: print(" "+colname) print("Available indexes") for row in historyDataFrame.index: print(" "+str(row)) columnClose = historyDataFrame['Close'] rowidx = 0 print("Symbol:"+msft.info['symbol']) for closeValue in columnClose.values: print(historyDataFrame.index[rowidx], closeValue) rowidx += 1 }}} |
yfinance
yfinance aimes to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance.
- pip install yfinance --user
1 import yfinance
2 from pandas._libs.tslibs.timestamps import Timestamp
3 data = yfinance.download("AMZN",start="2019-01-01",end="2020-02-12")
4 d = data.to_dict()
5 d['Close'].key
6 # for k in d['Close'].iterkeys(): print (k)
7 d['Close'][Timestamp('2019-11-22 00:00:00')]
8 d['Close'][Timestamp('2020-02-10 00:00:00')]
MSFT example
1 import yfinance as yf
2 msft = yf.Ticker("MSFT")
3
4 historyDataFrame = msft.history(period="5d")
5 print("Available columns")
6 for colname in historyDataFrame:
7 print(" "+colname)
8
9 print("Available indexes")
10 for row in historyDataFrame.index:
11 print(" "+str(row))
12
13 columnClose = historyDataFrame['Close']
14 rowidx = 0
15 print("Symbol:"+msft.info['symbol'])
16 for closeValue in columnClose.values:
17 print(historyDataFrame.index[rowidx], closeValue)
18 rowidx += 1