Python合并数据框和groupby

【问题标题】：Python merge dataframes and groupbyPython合并数据框和groupby
【发布时间】：2022-01-14 08:59:12
【问题描述】：

我有四个数据框 vom yfinance：

dataVIX = yf.download('^VIX', '2008-01-01', date.today(), auto_adjust=True)
dataGOLD = yf.download('GLD', '2008-01-01', date.today(), auto_adjust=True)
dataBOND = yf.download('^TNX', '2008-01-01', date.today(), auto_adjust=True)
datasp500 = yf.download('^GSPC', '2008-01-01', date.today(), auto_adjust=True)

现在我想将这四个数据框合并为一个并按日期分组。像这样：

date          Vix                 Gold
2008-01-01    Closing Value X     Closing Value Y ...
...

我尝试的一切都以 bs 的形式出现。有什么建议吗？

【问题讨论】：

标签： python pandas merge

【解决方案1】：

您可以下载tickers的列表：

tickers = ['^VIX', 'GLD', '^TNX', '^GSPC']
df = yf.download(tickers, '2008-01-01', date.today(), auto_adjust=True)['Close']
print(df)

# Output:
                   GLD        ^GSPC   ^TNX       ^VIX
Date                                                 
2007-12-31   82.459999  1468.359985  4.035  22.500000
2008-01-02   84.860001  1447.160034  3.901  23.170000
2008-01-03   85.570000  1447.160034  3.901  22.490000
2008-01-04   85.129997  1411.630005  3.854  23.940001
2008-01-07   84.769997  1416.180054  3.839  23.790001
...                ...          ...    ...        ...
2021-12-02  165.240005  4577.100098  1.448  27.950001
2021-12-03  166.630005  4538.430176  1.343  30.670000
2021-12-06  166.220001  4591.669922  1.434  27.180000
2021-12-07  166.809998  4686.750000  1.480  21.889999
2021-12-08  166.899994  4701.209961  1.509  19.900000

[3511 rows x 4 columns]

【讨论】：