如何合并for循环中产生的dataframe的结果？

发布于 2025-01-14 20:58:23 字数 756 浏览 2 评论 0原文

我正在尝试提取股票收盘价并将它们连接到同一个数据帧（在Python中）并使用for循环。例如：

url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=AAPL&apikey={api}'
r = requests.get(url)
    data = r.json()
    Hist = data['Time Series (Daily)']
    Hist = pd.DataFrame(Hist)
    Hist = pd.DataFrame.transpose(Hist)
    stock_list1= Hist.iloc[:, 3]

url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=BX&apikey={api}'
r = requests.get(url)
    data = r.json()
    Hist = data['Time Series (Daily)']
    Hist = pd.DataFrame(Hist)
    Hist = pd.DataFrame.transpose(Hist)
    stock_list2= Hist.iloc[:, 3]
    
    stock_list = pd.concat([stock_list1,stock_list2], axis = 1)

有什么办法可以在 for 循环中做到这一点吗？谢谢。

原文

I am trying to extract stock closing price and concatenate them into the same dataframe (in python) and using a for loop. For excample :

url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=AAPL&apikey={api}'
r = requests.get(url)
    data = r.json()
    Hist = data['Time Series (Daily)']
    Hist = pd.DataFrame(Hist)
    Hist = pd.DataFrame.transpose(Hist)
    stock_list1= Hist.iloc[:, 3]

url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=BX&apikey={api}'
r = requests.get(url)
    data = r.json()
    Hist = data['Time Series (Daily)']
    Hist = pd.DataFrame(Hist)
    Hist = pd.DataFrame.transpose(Hist)
    stock_list2= Hist.iloc[:, 3]
    
    stock_list = pd.concat([stock_list1,stock_list2], axis = 1)

is there any way I could do this in a for loop ?
Thanks.

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薄情伤 2025-01-21 20:58:23

您的代码示例似乎没有正确的缩进（Python 中的空格很重要）。

你想要的是将你的迷你数据帧存储在一个列表中，最后将它们连接到你的最终数据帧中；不建议附加到现有数据框。

urlfmt = f"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol={{ticker}}&apikey={api}"
tickers = "BX AAPL".split()
lodf = []
for ticker in tickers:
    data = requests.get(urlfmt.format(ticker=ticker)).json()
    Hist = pd.DataFrame(data['Time Series (Daily)']).T
    lodf.append(Hist.iloc[:, 3])

stock_list = pd.concat(lodf, axis=1)

Your code example doesn't seem to have correct indentation (white space matters in Python).

What you want is to store your mini dataframes in a list, and in the end concatenate them into your final dataframe; appending to an existing dataframe isn't recommended.

urlfmt = f"https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol={{ticker}}&apikey={api}"
tickers = "BX AAPL".split()
lodf = []
for ticker in tickers:
    data = requests.get(urlfmt.format(ticker=ticker)).json()
    Hist = pd.DataFrame(data['Time Series (Daily)']).T
    lodf.append(Hist.iloc[:, 3])

stock_list = pd.concat(lodf, axis=1)

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