作者: 周末视频平台自动推荐了 Yahoo Finance 的一个视频,说 FX 和 NYT 拍了一个关于$特斯拉(TSLA)$Autopilot 的纪录片叫 Elon Musk's Crash Course。 片长1小时15分钟,记录了几起 Autopilot 导致的交通事故以及马斯克和特斯拉是如何应对的。准确来说,Elon Musk's Crash Course 是一部纪录片剧集的第二季第一...
$特斯拉(TSLA)$NvidiaCEO Jensen Huang told Yahoo Finance today: "@Teslais far ahead in self-driving cars; Every single car, someday we will have to have autonomous capability." Nvidia 首席执行官黄仁勋今天对雅虎财经表示:“@Tesla在自动驾驶汽车领域遥遥领先;未来有一天,我们的每一辆汽车都必须具备自动...
df.to_csv('TSLA.csv') 除了利用Yahoo财经的API来将数据导入为DataFrame,也可以将数据从CSV文件读取到DataFrame中: 代码语言:javascript 复制 df=pd.read_csv('tsla.csv',parse_dates=True,index_col=0) 下面,可以制图: 代码语言:javascript 复制 df.plot()plt.show() COOL,但是这里真正能看到的唯一的东西就...
FxQuoteusdeur=YahooFinance.getFx(FxSymbols.USDEUR);FxQuoteusdgbp=YahooFinance.getFx("USDGBP=X");System.out.println(usdeur);System.out.println(usdgbp); Output: Single stock, include historical quotes (1) Stocktesla=YahooFinance.get("TSLA",true);System.out.println(tesla.getHistory()); ...
Stock tesla = YahooFinance.get("TSLA",true); System.out.println(tesla.getHistory()); Output [Symbol@Date: low-high, open->close (adjusted close), ... ] [TSLA@2014-10-01: 217.32-265.54, 242.2->229.7 (229.7), TSLA@2014-09-02: 240.12-291.42, 275.5->242.68 (242.68), ...] ...
from financetoolkit import Toolkit toolkit = Toolkit(["AAPL", "TSLA"], api_key="FINANCIAL_MODELING_PREP_KEY") # Collect all Ratios toolkit.ratios.collect_liquidity_ratios() # Get an Individual Ratio toolkit.ratios.get_current_ratio() Current Ratio The current ratio is calculated by dividing...
我可以通过下面的代码将其下载到多个csv,但我找不到一种方法将它们存储在不同的数据文件中(只需将它们下载到csv中) import yfinance stocks = ['TSLA','MSFT','NIO','AAPL','AMD','ADBE','ALGN','AMZN','AMGN','AEP', 浏览1提问于2021-09-12得票数 1 回答已采纳...
tsla tesla, inc. 260.46 +6.24 (+2.45%) plug plug power inc. 2.2800 +0.2200 (+10.68%) trending tickers tsla tesla, inc. 260.46 +6.24 (+2.45%) nio nio inc. 6.52 +0.74 (+12.80%) ionq ionq, inc. 9.71 +1.65 (+20.47%) ^dji dow jones industrial average 42,313.00 +137.89 (+0.33%)...
A common alternative is to download it fromYahoo Finance. It is convenient to access by search stock symbols, like “TSLA” for Tesla. If you want to search for other stock markets, just add the market name after the symbol. For example, you can get 0050 in Taiwan by querying “0050....
import matplotlib.pyplot as plt import mplfinance as mpf import yfinance as yf tickers = ['AAPL','GOOG','TSLA'] data = yf.download(tickers, start="2021-01-01", end="2021-03-01", group_by='ticker') aapl = data[('AAPL',)] goog = data[('GOOG',)] tsla = data[('TSLA',)] ...