在超过2个 pandas 数据框中合并 [英] Union in more than 2 pandas dataframe

问题描述

我正在尝试将sql查询转换为python。 sql语句如下：

I am trying to convert a sql query to python. The sql statement is as follows:

select * from table 1 
union
select * from table 2
union 
select * from table 3
union
select * from table 4

现在我在4个数据帧中有这些表 df1，df2，df3，df4 ，我想合并4个与结果匹配的熊猫数据帧与sql查询相同。
我对要使用的等效于SQL Union的操作感到困惑？
预先感谢！

Now I have those tables in 4 dataframe df1, df2, df3, df4 and I would like to union 4 pandas dataframe which would match the result as the same as sql query. I am confused of what operation to be used which is equivalent to sql union? Thanks in advance!!

注意：
所有数据框的列名都相同。

Note: The column name for all the dataframes are the same.

推荐答案

如果我对问题很了解，那么您正在寻找 concat 函数。

If I understand well the issue, you are looking for the concat function.

pandas.concat（[df1，df2，df3，df4]）如果列名称为两个数据框都一样。

pandas.concat([df1, df2, df3, df4]) should work correctly if the column names are the same for both dataframes.

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