Loading...
This is a short tutorial article that explains and gives example for how to use Python to download historical OHLC (Open, High, Low, Close) data with the Coinbase API. (*Please note that the Coinbase API is intended
to be used for personal usage - refer to their market data terms). In the below Python script, we will use Pandas, requests, and json libraries to create a simple function that will ultimately write a CSV file
with the filename "Coinbase_PAIR_dailydata.csv".. So if we want BTC/USD, the resulting filename will be: Coinbase_BTCUSD_dailydata.csv - Go ahead and give it a try!
This script is extremely simple, and can be greatly enhanced or fitted to meet your personal needs. It can easily be modified to save the data into a database, or pull different time frames or pairs... If you have a custom data need and would like help setting up the proper code, feel free to reach out to us
Notice: Information contained herein is not and should not be construed as an offer, solicitation, or recommendation to buy or sell securities. The information has been obtained from sources we believe to be reliable; however no guarantee is made or implied with respect to its accuracy, timeliness, or completeness. Author does not own the any crypto currency discussed. The information and content are subject to change without notice. CryptoDataDownload and its affiliates do not provide investment, tax, legal or accounting advice.
This material has been prepared for informational purposes only and is the opinion of the author, and is not intended to provide, and should not be relied on for, investment, tax, legal, accounting advice. You should consult your own investment, tax, legal and accounting advisors before engaging in any transaction. All content published by CryptoDataDownload is not an endorsement whatsoever. CryptoDataDownload was not compensated to submit this article. Please also visit our Privacy policy; disclaimer; and terms and conditions page for further information.How to Convert the Unix Timestamp From UTC To Your Local Timezone
Basic Overview of the Commitment of Traders (COT) Report by the CFTC
Humans vs Bot Investors: Identifiable Behavioral Differences
Implementation of the Tail Ratio Forecasting Model to Estimate Next Day Return
Research Shows Google Search Trends Can Forecast Bitcoin Price Increases
Major Cryptocurrency Risk Adjusted Return Comparisons with Sharpe Ratios
Finding the US Treasury Risk Free Rate (RFR) Via Par Yield Curve
Examining Correlations using Principal Component Analysis (PCA)
How to Combine Two Timeseries Together Into Single Pandas DataFrame in Python
Identifying Causal Relationships Between NFT and Cryptocurrency Markets
How to Query SEC Litigation API and Save Results into Pandas Dataframe: Python
DragonChain (DRGN) Foundation Sued by SEC for Unregistered Securities Violations
Comparing a Variety of Bitcoin Volatility Models & Discussing Results
Bitcoin Asymmetric Volatility Estimation: Improving GARCH Forecasts