text: import pandas as pd
  
  df1 = pd.DataFrame({
      'HPI': [80, 85, 88, 85],
      'Int_rate': [2, 3, 4, 4],
      'US_GDP_Thousands': [50, 55, 65, 55]},
      index=[2001, 2002, 2003, 2004])
  df2 = pd.DataFrame({
      'HPI': [80, 85, 88, 85],
      'Int_rate': [2, 3, 4, 4],
      'US_GDP_Thousands': [50, 55, 65, 55]},
      index=[2005, 2006, 2007, 2008]
  )
  df3 = pd.DataFrame({
      'HPI': [80, 85, 88, 85],
      'Unemployment': [2, 3, 4, 4],
      'LOW_GDP_Thousands': [50, 55, 65, 55], },
      index=[2009, 2010, 2011, 2012]
  )
  # concat = pd.concat([df1, df2])
  # print(concat)
  
  # print('-'*50)
  #
  # df4 = df1.append(df3)
  # print(df4)
  
  # 使用pd.merge 能合并相同类型的列表
  print(pd.merge(df1, df2, on=['HPI', 'Int_rate']))
  