问：how to get company name and sector for a stock using yfinance
答：
To get the company name and sector for a stock using the yfinance library in Python, you can follow these steps:
1. Install yfinance if you haven't already: pip install yfinance 2. Use the following Python code to get the company name and sector:
import yfinance as yf def get_company_info(ticker_symbol): # Create a Ticker object for the given stock symbol ticker = yf.Ticker(ticker_symbol) try: # Get the info dictionary for the stock info = ticker.info # Extract company name and sector from the info dictionary company_name = info['longName'] sector = info['sector'] return company_name, sector except Exception as e: print(f"Error: Unable to retrieve information for {ticker_symbol}.") print(f"Error details: {e}") return None, None # Example: Get information for Apple Inc. (AAPL) ticker_symbol = 'AAPL' company_name, sector = get_company_info(ticker_symbol) if company_name and sector: print(f"Company Name: {company_name}") print(f"Sector: {sector}")
你如果真想弄些有用的 搞一个程序 monitor 每天的 New Highs New Lows, stock above 200, 50 dma, stocks below 209, 50 dma. 看这些数据和市场表现的关系。懂些股市的人都会明白。难的是 quantify 这种关系 down to a number reading.
历史 back tested, 这个模型可以 catch the near market lows within 5% range. 也就是说 downside is mitigated, 对市场頂 不大行。原因在我以前的贴子有解释过数次 the why (市场心理学哈）
这几天工作不忙闲着玩ChatGPT，请教怎么下载股票信息。
问：how to get company name and sector for a stock using yfinance
答：
To get the company name and sector for a stock using the yfinance library in Python, you can follow these steps:
1. Install yfinance if you haven't already: pip install yfinance 2. Use the following Python code to get the company name and sector:
import yfinance as yf def get_company_info(ticker_symbol): # Create a Ticker object for the given stock symbol ticker = yf.Ticker(ticker_symbol) try: # Get the info dictionary for the stock info = ticker.info # Extract company name and sector from the info dictionary company_name = info['longName'] sector = info['sector'] return company_name, sector except Exception as e: print(f"Error: Unable to retrieve information for {ticker_symbol}.") print(f"Error details: {e}") return None, None # Example: Get information for Apple Inc. (AAPL) ticker_symbol = 'AAPL' company_name, sector = get_company_info(ticker_symbol) if company_name and sector: print(f"Company Name: {company_name}") print(f"Sector: {sector}")https://bbs.wenxuecity.com/bbs/computer/257550.html
"行业"是 Yahoo Finance "Industry" 数据，我也可以直接 Copy 你的
我还在学习，哪天退休了用不起Bloomberg就用Yahoo Finance
如果谁要程序我也可以传上来，就是好玩而已
所有历史数据 Yahoo finance 都有。每天的 Open 和 Close.
你如果真想弄些有用的 搞一个程序 monitor 每天的 New Highs New Lows, stock above 200, 50 dma, stocks below 209, 50 dma. 看这些数据和市场表现的关系。懂些股市的人都会明白。难的是 quantify 这种关系 down to a number reading.
历史 back tested, 这个模型可以 catch the near market lows within 5% range. 也就是说 downside is mitigated, 对市场頂 不大行。原因在我以前的贴子有解释过数次 the why (市场心理学哈）