{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"}],"enrichment":{"capability":"Fetches historical and current financial data\u2014stock prices, indices, exchange rates, and cryptocurrency\u2014from multiple global exchanges and returns it as pandas DataFrames.","skillfed_tags":["financial-data","market-data","web-scraper"],"use_cases":["Backtest trading strategies by fetching historical stock prices for multiple symbols and date ranges.","Build financial dashboards that display real-time or recent index values (KOSPI, NASDAQ, S&P 500) and exchange rates.","Analyze cryptocurrency price trends by retrieving BTC/KRW, ETH/USD, and other crypto pairs over time.","Screen Korean stocks by listing all KRX symbols and fetching their price history for fundamental analysis.","Monitor delisted or administratively suspended Korean stocks via KRX-DELISTING and KRX-ADMIN listings."],"what_it_does":"FinanceDataReader is a financial data crawler that retrieves stock prices, market indices, exchange rates, and cryptocurrency data from global exchanges\u2014KRX (Korean), NASDAQ, NYSE, S&P 500, Shanghai, Shenzhen, Hong Kong, Tokyo, and Ho Chi Minh exchanges. It wraps web scraping and API calls behind a simple pandas-centric interface, returning time-series data as DataFrames. The package includes both a Python library (via `fdr.DataReader()`) and a CLI tool (`fdr` command) for terminal-based queries.\n\nIt depends on beautifulsoup4, lxml, pandas, requests, and plotly to parse HTML, fetch data, and structure results. The library handles symbol resolution across markets (e.g., 'AAPL' for US stocks, '005930' for Samsung, 'KS11' for KOSPI index) and supports date-range filtering. It is production-stable, actively maintained, and requires Python 3.9 or later.","worth_installing":"Yes. Low install friction, no security vulnerabilities, active maintenance, and permissive MIT license. Install if you need to fetch financial time-series data from multiple global exchanges into pandas DataFrames. Caveat: reliability depends on upstream data sources (web scraping); verify data accuracy for production use."},"id":"finance-datareader","links":{"html":"https://skillfed.io/packages/finance-datareader","md":"https://skillfed.io/packages/finance-datareader.md","pypi":"https://pypi.org/project/finance-datareader/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-13","license_spdx":null,"license_treatment":"permissive","name":"finance-datareader","python_support":"supports_current","summary":"Financial data reader (price, stock list of markets)"},"popularity":{"monthly_downloads":265271,"position":8327,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.9.202"}