附加两个具有相同列、不同顺序的数据框 [英] Appending two dataframes with same columns, different order

问题描述

我有两个 pandas 数据框.

I have two pandas dataframes.

noclickDF = DataFrame([[0, 123, 321], [0, 1543, 432]],
                      columns=['click', 'id', 'location'])
clickDF = DataFrame([[1, 123, 421], [1, 1543, 436]],
                      columns=['click', 'location','id'])

我只是想加入这样最终的 DF 看起来像:

I simply want to join such that the final DF will look like:

click  |  id   |   location
0         123        321
0         1543       432
1         421        123
1         436       1543

如您所见，两个原始 DF 的列名相同，但顺序不同.列中也没有连接.

As you can see the column names of both original DF's are the same, but not in the same order. Also there is no join in a column.

推荐答案

你也可以使用 pd.concat:

In [36]: pd.concat([noclickDF, clickDF], ignore_index=True)
Out[36]: 
   click    id  location
0      0   123       321
1      0  1543       432
2      1   421       123
3      1   436      1543

在底层，DataFrame.append 调用 pd.concat.DataFrame.append 包含处理各种类型输入的代码，例如系列、元组、列表和字典.如果你给它传递一个DataFrame，它会直接传递给pd.concat，所以使用pd.concat会更直接一些.

Under the hood, DataFrame.append calls pd.concat. DataFrame.append has code for handling various types of input, such as Series, tuples, lists and dicts. If you pass it a DataFrame, it passes straight through to pd.concat, so using pd.concat is a bit more direct.

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