如何合并来自银行帐户的两个数据帧

Question

我有两个数据帧，其中包含来自两个银行帐户的交易。我只想把它们组合成一个数据帧。不过，这对我来说效果不太好。数据帧称为df和JLcard，下面是一些信息

df.shape
(1405, 3)

JLcard.shape
(96, 3)

df.columns
Index([u'Transaction_Type', u'Transaction_Description', u'transaction'], dtype='object')

JLcard.columns
Index([u'Transaction_Description', u'transaction', u'Transaction_Type'], dtype='object')

因此，如果两个数据帧的顺序不同，它们的列名是相同的。在

也有按日期索引的。在

^{pr2}$

为了将它们组合成一个数据帧，我尝试了pd.concat([df,JLcard])，这给了我：

 FutureWarning: Sorting because non-concatenation axis is not aligned. A future version
of pandas will change to not sort by default.

To accept the future behavior, pass 'sort=True'.

To retain the current behavior and silence the warning, pass sort=False

  """Entry point for launching an IPython kernel.

生成的数据帧也不按索引排序。E、 g

    Transaction_Description Transaction_Type    transaction
date            
2018-04-10  ES  DEB -16.57
2018-04-04  OR  Js card 109.30
2018-04-05  WR  Js card 125.00

Why does it say the "non-concatenation axis is not aligned"? Why does it say it is sorting when it doesn't seem to be? And what could I do to avoid the warning? I simply want to copy all the rows from one into the other and sort by the index (which is the date).

Answer 1

你可以试试pd.merge(f,JLcard,left_index=True, right_index=True)