Pandas-06-数据合并

1. pd.concat实现数据合并

• pd.concat([data1, data2], axis=1)

  • 按照行或列进行合并，axis=0为列索引，axis=1为行索引

  比如将刚才处理好的one-hot编码与原数据合并

  # 按照行索引进行合并
  pd.concat([data, dummies], axis=1)
  

  

2. pd.merge

• pd.merge(left, right, how='inner', on=None)

  • 可以指定按照两组共同的数据的共同键值对合并或者左右各自
  • left：DataFrame
  • right：另一个DataFrame
  • on：指定的共同键
  • how：按照什么方式进行连接

  Merge method	SQL Jion Name	Description
  left	LEFT OUTER JION	左连接
  right	RIGHT OUTER JION	右连接
  inner	INNER JION	内连接
  outer	FULL OUTER JION	外连接

  left = pd.DataFrame({
      "A": ["A0", "A1", "A2", "A3"],
      "B": ["B0", "B1", "B2", "B3"],
      "key1": ["K0", "K0", "K1", "K2"],
      "key2": ["K0", "K1", "K0", "K1"]
  })
  right = pd.DataFrame({
      "C": ["C0", "C1", "C2", "C3"],
      "D": ["D0", "D1", "D2", "D3"],
      "key1": ["K0", "K1", "K1", "K2"],
      "key2": ["K0", "K0", "K0", "K0"]
  })
  

• 默认为内连接：

  # 默认内连接
  result = pd.merge(left, right, on=["key1", "key2"])
  

  

• 左连接

  # 左连接
  result = pd.merge(left, right, how="left", on=["key1", "key2"])
  

  

• 右连接

  # 右连接
  result = pd.merge(left, right, how="right", on=["key1", "key2"])
  

  

• 外连接

  # 外连接
  result = pd.merge(left, right, how="outer", on=["key1", "key2"])
  

  

3. 总结

• pd.concat(["数据1", "数据2"], axis=)
• pd.merge(left, right, how=, on=)
  • how -- 以何种方式连接
  • on -- 连接的键的依据是哪些