If you are interested in historical financial data, you often come across the task to get the data and prepare it for you process pipeline. You may have a backtesting system running or various scanners, so you don’t want to spend a decent amount of time in preprocessing your data to fit your pipeline.
A Small Python Helper
This is a small helper I use fairly often to e.g. download historical bitcoin prices with Python.
All you need are the libraries pandas and yfinance, which you can install to your virtual environment with the commands pip install yfinance pandas.
I wrote a small helper, which converts the data from yahoo finance (which are already given as a pandas.DataFrame) to my needs. Baisically it just sets a column as DateTime and eventually renames the column to fit my data pipeline.
You can pass different tickers like BTC-EUR, BTC-USD, ETH-EUR etc. and get (dependent on the asset) data in various resolution, e.g. 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo. For the big crypto currencies, historical data is for sure available down to 60m, which I use mostly in my processes.
No git repo is needed for this simple script. Have a look and adapt to your needs respectively!
Example Code
import pandas as pd
import yfinance as yf
def convert_yf_data(df: pd.DataFrame) -> pd.DataFrame:
"""
Converts a yahoo finance OHLC DataFrame to column name(s) used in this project
old_names = ['Date', 'Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']
new_names = ['Date', 'Open', 'High', 'Low', 'Close']
:param df:
:return:
"""
df_output = pd.DataFrame()
df_output['Date'] = list(df.index)
df_output['Date'] = pd.to_datetime(df_output['Date'], format="%Y-%m-%d %H:%M:%S")
df_output['Open'] = df['Open'].to_list()
df_output['High'] = df['High'].to_list()
df_output['Low'] = df['Low'].to_list()
df_output['Close'] = df['Close'].to_list()
return df_output
df = yf.download(tickers='ETH-USD',
interval="1d",
start="2021-02-28")
convert_yf_data(df).to_csv('data\eth-usd_1d.csv', sep=",", index=False)
Thats it. It will save a .csv file to the given folder and filename, containing the data.
Date,Open,High,Low,Close
2021-02-28,1459.8604736328125,1468.3914794921875,1300.47216796875,1416.0489501953125
2021-03-01,1417.151123046875,1567.694580078125,1416.4161376953125,1564.7076416015625
2021-03-02,1564.0634765625,1597.610107421875,1461.325439453125,1492.6087646484375
2021-03-03,1491.451171875,1650.360595703125,1481.90576171875,1575.8531494140625
2021-03-04,1574.623779296875,1622.953857421875,1511.1033935546875,1541.914306640625
2021-03-05,1541.541748046875,1547.878173828125,1450.891357421875,1533.2750244140625
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