Introduction to cryptoQuotes
The {cryptoQuotes} package provides a streamlined API for accessing high-quality cryptocurrency market data from major exchanges. This powerful R tool eliminates the need for web crawlers or API keys, offering researchers, traders, and students reliable access to:
- OHLC-V (Open, High, Low, Close, Volume) data
- Various sentiment indicators
- Market data across timeframes (seconds to months)
👉 Explore cryptoQuotes documentation for detailed feature explanations.
Key Features
- Exchange Support: Works with Binance and other major exchanges
- Futures Market Data: Includes derivatives trading information
- Flexible Intervals: From 30-second to monthly candles
- Clean Data Output: Returns tidy data frames ready for analysis
Getting Started with OHLC-V Data
Retrieving Bitcoin Market Data
# Get OHLC-V data in 30-minute intervals
# for BTC/USDT from Binance futures
BTC <- cryptoQuotes::get_quote(
ticker = 'BTCUSDT',
source = 'binance',
futures = TRUE,
interval = '30m',
from = Sys.Date() - 1
)
# Display latest values
tail(BTC)Expected Output Structure
open high low close volume
57667.8 57718.6 57318.3 57663.1 5587.568
57663.0 57780.0 57422.4 57580.2 3122.371
57582.0 57631.6 57344.7 57497.1 2389.315
57497.0 57950.0 57418.9 57699.9 4807.539
57700.0 58290.6 57679.0 57888.0 12973.359
57888.0 57912.2 57716.0 57812.5 1562.662👉 Learn advanced trading strategies with cryptocurrency market data.
Installation Guide
Stable Release (CRAN)
install.packages(
pkgs = 'cryptoQuotes',
dependencies = TRUE
)Development Version (GitHub)
devtools::install_github(
repo = 'https://github.com/serkor1/cryptoQuotes/',
ref = 'development'
)FAQ Section
What exchanges does cryptoQuotes support?
Currently supports Binance with planned expansion to other major exchanges. The package architecture allows for easy addition of new exchange APIs.
How frequently is the data updated?
Data reflects real-time exchange information, with update frequency matching your selected interval (from 30 seconds to 1 month).
Is there rate limiting?
The package implements intelligent request throttling to prevent API abuse while maximizing data access.
Can I use this for algorithmic trading?
Absolutely! The clean data output integrates seamlessly with popular R quantitative finance packages like quantmod and TTR.
Does it work with RStudio?
Yes, cryptoQuotes functions work perfectly in both base R and RStudio environments.
How do I handle missing data?
The package includes built-in NA handling with options for linear interpolation or last-observation-carried-forward imputation.
Advanced Usage Tips
- Combine with ggplot2 for professional cryptocurrency charts
- Use with forecast package for time series predictions
- Integrate with shiny to build trading dashboards
Remember to always verify your analysis with multiple data sources when making financial decisions.