如果您知道要按特定顺序排列几列,只需在所有列和预先排序的列之间设置差异,然后调用reindex
:
In [13]: cols = list('xacybz')
In [14]: df = DataFrame(randn(10, len(cols)), columns=cols)
In [15]: preordered = list('xyz')
In [16]: new_order = preordered + list(df.columns - preordered)
In [17]: new_order
Out[17]: ['x', 'y', 'z', 'a', 'b', 'c']
In [18]: df.reindex(columns=new_order)
Out[18]:
x y z a b c
0 -0.012 0.949 -0.276 -0.074 -0.054 0.541
1 0.994 1.059 -0.158 0.267 -0.590 0.263
2 -0.632 -0.015 -0.097 -1.904 -1.351 -1.105
3 -0.730 -0.684 -0.226 2.664 -0.385 1.727
4 0.891 -0.602 3.426 1.529 0.853 -0.451
5 -0.471 0.689 1.170 -0.635 -0.663 0.180
6 1.536 0.793 1.461 0.723 -0.795 -1.094
7 0.417 0.787 1.676 1.563 1.412 0.398
8 0.378 1.436 -0.024 0.293 0.655 -0.113
9 -0.159 -0.416 -1.526 0.633 -0.780 -0.613
preorder
元素的出现顺序无关紧要:
In [25]: shuffle(df.columns.values)
In [26]: df
Out[26]:
b a z c x y
0 -0.054 -0.074 -0.276 0.541 -0.012 0.949
1 -0.590 0.267 -0.158 0.263 0.994 1.059
2 -1.351 -1.904 -0.097 -1.105 -0.632 -0.015
3 -0.385 2.664 -0.226 1.727 -0.730 -0.684
4 0.853 1.529 3.426 -0.451 0.891 -0.602
5 -0.663 -0.635 1.170 0.180 -0.471 0.689
6 -0.795 0.723 1.461 -1.094 1.536 0.793
7 1.412 1.563 1.676 0.398 0.417 0.787
8 0.655 0.293 -0.024 -0.113 0.378 1.436
9 -0.780 0.633 -1.526 -0.613 -0.159 -0.416
In [27]: new_order = preordered + list(df.columns - preordered)
In [28]: new_order
Out[28]: ['x', 'y', 'z', 'a', 'b', 'c']