使用 Quandl 谷歌金融数据集代码标签将 Quandl 数据下载到熊猫

Question

我想专门使用Quandl的Google Finance数据库来下载股票价格以回测策略。原因是谷歌财经的数据与Quandl的WIKI和雅虎数据库相比，针对拆分等调整的股票数据是干净的。如此处所示，最后一个链接将显示针对以下各项调整的股票分割：

https://www.quandl.com/WIKI/AAPL-Apple-Inc-AAPL

https://www.quandl.com/YAHOO/AAPL-AAPL-Apple-Inc

https://www.quandl.com/GOOG/NASDAQ_AAPL-Apple-Inc-AAPL

然而，Quandl的谷歌数据库标签是GOOG/NYSE_IBM或GOOG/NASDAQ_AAPL的形式，它们与WIKI/IBM、YAHOO/IBM等标签不同。

由于手动添加纽约证券交易所或纳斯达克标签是不可行的，在这些交易所上市的股票数量，是否有一种有效的方法可以从Quandl下载股票数据，给定csv或熊猫数据框中的股票列表？

这是我的代码 FWIW：

nyseList = pd.read_csv('dowjonesIA.csv')  # read csv
masterList = pd.DataFrame(nyseList.Ticker)  # save symbols only into another df
 for index, rows in masterList.iterrows():
     ticker = masterList.loc[index]  # this will not work for passing element
     stock = Quandl.get(ticker, trim_start="2000-01-01", trim_end="2015-01-01")
#stock = Quandl.get("GOOG/NASDAQ_AAPL", trim_start="2000-01-01", trim_end="2015-01-01")  #this is the actual format that works
 # lags data for signal
 stock['diff'] = (stock.Open - stock.Close.shift(1))/stock.Close.shift(1)
 lowerBound = -0.08
 upperBound = 0.08
#generate signal based on 8% rule
stock['signal'] = np.where(stock['diff'] >= upperBound, 1.0, np.where (stock['diff'] <= lowerBound, -1.0, 0.0))
initialCapital = 100000.0
accountLimit = 0.05
#calculate size based on account risk and price
stock['position'] = (stock.signal*initialCapital*accountLimit)/stock.Open
#shows if there is a position open
stock['open trade'] = np.where(stock['position'] > 0, 1.0, np.where(stock['position'] < 0, -1.0, 0.0))
#determine profit/loss
stock['pnl'] = (stock.position*stock.Close) - (stock.position*stock.Open)
#sums up results to starting acct capital
stock['equity curve'] = initialCapital + stock.pnl.cumsum()
print(stock.head(20))  # is dataframe
# plots test results
stock['equity curve'].plot()
plt.show()

我尝试使用内置于远程数据访问中的 pandas，并且在将字符串作为 args 的股票符号传递时也会出现问题。此外，任何以矢量化方式执行循环的建议都值得赞赏，而不是迭代执行，并且对于一般逻辑流。提前谢谢。

Answer 1

没

关系，我只是将标签作为字符串附加到股票代码字符串中。此格式将起作用：

masterList = pd.Dataframe('GOOG/NYSE_' + nyseList['Ticker'].astype(str))

归功于此线程：将字符串附加到 pandas 数据帧所述列中每个值的开头（优雅地）